publications | PATCH|Lab

2026

EOAD-Signature Atrophy Predicts Dementia in Early-Onset MCI due to Alzheimer Disease: An MRI-Based Prognostic Biomarker.

T. Paranhos, Yuta Katsumi, M. Brickhouse, A. Eloyan, Ryan Eckbo, Alexander Zaitsev, Anna Du, R. La Joie, M. Thangarajah, Alexander Taurone, P. Vemuri, C. Jack, D. Hammers, P. Aisen, Laurel Beckett, R. Koeppe, W. Kukull, Arthur W. Toga, A. Atri, David Clark, Gregory S. Day, R. Duara, N. Graff-Radford, Ian M. Grant, Lawrence S. Honig, E. Johnson, David T. Jones, Joseph C. Masdeu, Mario F. Mendez, Erik S. Musiek, C. Onyike, Meghan Riddle, E. Rogalski, S. Salloway, S. Sha, R. Turner, Thomas S Wingo, David A. Wolk, Kyle B. Womack, M. Carrillo, G. Rabinovici, L. Apostolova, B. Dickerson, Mark C. Eldaief, and Alexandra Touroutoglou

Neurology, Oct 2026

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BACKGROUND AND OBJECTIVES Early-onset Alzheimer disease (EOAD) is associated with substantial variability in clinical progression, and reliable biomarkers to predict the transition from mild cognitive impairment (MCI) to dementia remain limited. Structural MRI measures have demonstrated prognostic value in late-onset Alzheimer disease, but their utility for predicting progression in EOAD is less well understood. The goal was to examine whether baseline cortical atrophy predicts progression to dementia in patients with MCI because of EOAD. METHODS This study included a well-characterized cohort of patients with EOAD enrolled in the large multisite natural history Longitudinal Early-Onset Alzheimer’s Disease Study. Participants underwent standardized clinical assessments and structural MRI at baseline. Participants were aged between 40 and 64 years with biomarker-supported sporadic EOAD at the MCI stage. Cortical atrophy was measured within the EOAD-signature, a set of predominantly parieto-temporal regions showing greater atrophy in EOAD than in controls. Clinical severity was measured with the global Clinical Dementia Rating. Cox proportional hazards models estimated the association between baseline EOAD-signature atrophy burden and the hazard of progression to dementia over time. We evaluated whether EOAD-signature atrophy improved prognostic performance beyond baseline clinical severity using likelihood ratio tests, Akaike Information Criterion (AIC), and Harrell concordance index. RESULTS A total of 130 patients with MCI due to EOAD (mean age 59.6 ± 4.1 years; 49% female) and 97 cognitively normal controls (mean age 56.9 ± 6.0 years; 64% female) were included. Greater baseline atrophy within the EOAD-signature predicted faster progression to dementia (hazard ratio [HR] = 1.24 per 1-SD increase in atrophy; 95% CI 1.13-1.37; p < 0.002). Adding EOAD-signature atrophy burden to a model including baseline clinical severity significantly improved model fit (ΔAIC = -4.5; likelihood ratio test p = 0.011). DISCUSSION Baseline cortical atrophy within the EOAD-signature predicts progression from MCI to dementia in EOAD and provides prognostic information beyond baseline clinical severity. These findings support the potential value of EOAD-signature atrophy as an MRI-based biomarker for individualized prognostication and clinical trial stratification.
Mild Amyloid Burden in the Brains of Cognitively Unimpaired Individuals is Associated with Long-Term Cognitive Impairment.

Cheng-Jie Xiong, Jing-Qin Luo, Sarah M. Hartz, S. Schindler, Walter W. Kukull, Jason J. Hassenstab, D. Wolk, C. Gleason, Sterling C. Johnson, R. Sperling, K. Johnson, E. Roberson, K. Moulder, Emily N. Gremminger, Folasade Agboola, Elizabeth A. Grant, Russ C. Hornbeck, Parinaz Massoumzadeh, S. Keefe, Donna L. Dierker, David M. Holtzman, and J. C. Morris

Annals of neurology, Oct 2026

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OBJECTIVE We aimed to identify the minimal amount of amyloid burden measured by positron emission tomography (PET) in amyloid-negative cognitively unimpaired individuals that predicts the development of cognitive impairment. METHODS A total of 1,896 cognitively unimpaired participants underwent longitudinal clinical/cognitive assessments for up to 20.3 years after amyloid PET imaging. Cox proportional hazards models were used to assess how the risk of cognitive impairment was associated with subthresholds of amyloid PET Centiloid. Linear mixed effects models were used to associate the longitudinal cognitive decline and amyloid accumulation with baseline amyloid burden. RESULTS Amyloid-positive participants (Centiloid >20; n = 421) were 154% (hazard ratio 2.54, p < 0.0001) more likely to develop cognitive impairment than amyloid-negative participants. Approximately 48.7% of the amyloid-negative participants had mild amyloid burden (defined by Centiloid from 0.93 to 20) and were 43% more likely to develop cognitive impairment (hazard ratio 1.43, p = 0.008) than the lowest amyloid group (Centiloid <0.93) approximately 10 years post baseline. Longitudinal changes in amyloid PET Centiloid and cognition followed a similar pattern: amyloid-positive participants were the fastest, followed by the mild amyloid burden group and finally the lowest amyloid group, and the cognitive trajectories for the latter 2 started to separate only approximately 10 years post baseline (p = 0.003). INTERPRETATION Almost half of amyloid-negative cognitively unimpaired individuals were at an elevated long-term risk of cognitive impairment, when compared with those with the lowest amyloid levels. These findings suggest that the current threshold for amyloid positivity may be overly restrictive, potentially excluding a large portion of high-risk participants from prevention trials. ANN NEUROL 2026.
Normative Modeling of Brain Volume in Multiple Sclerosis Using Healthy Controls

Max Korbmacher, I. Lie, K. Wesnes, E. Westman, T. Espeseth, O. A. Andreassen, L. Westlye, S. Wergeland, H. Harbo, G. Nygaard, K. Myhr, E. Høgestøl, Ø. Torkildsen, Michael W. Weiner, P. Aisen, Ronald Petersen, C. Jack, William J. Jagust, S. Landau, M. Rivera-Mindt, Ozioma C. Okonkwo, Leslie M. Shaw, Edward B. Lee, A. Toga, Laurel Beckett, Danielle J. Harvey, Robert C. Green, A. Saykin, K. Nho, R. Perrin, D. Tosun, P. Sachdev, Erin Drake, T. Montine, Cat Conti, M. Weiner, R. Nosheny, D. T. Sacrey, J. Fockler, Melanie J. Miller, Cat Conti, Winnie Kwang, Cheng-Shi Jin, Adam Diaz, Miriam Ashford, D. Flenniken, Adrienne Kormos, M. Rafii, Rema Raman, G. Jimenez, and 450 more authors

Neurology Open Access, Sep 2026

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Operationalizing Alzheimer’s disease trials in the era of targeted therapies

Jagan A. Pillai, S. Alladi, Brian S. Appleby, J. Brosch, K. Frederiksen, D. Galasko, O. Lopez, J. Leverenz, Andrew J. Saykin, Jonathan M. Schott, Sudha Seshadri, Babak Tousi, and D. Wolk

Alzheimer’s & Dementia, Sep 2026

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The therapeutic landscape of Alzheimer’s disease (AD) is rapidly evolving with the clinical adoption of anti‐amyloid monoclonal antibodies (mAbs) despite an incomplete understanding of disease mechanisms, progression, and heterogeneity. Designing both observational longitudinal cohorts and clinical trials with novel mAbs in mind is imperative. These studies should capture mAb type, dosing, duration, degree of amyloid clearance, and downstream effects on neurodegeneration to interpret outcomes. Observational cohorts can compare treated and untreated populations, track biomarker trajectories, assess co‐pathologies, and evaluate social determinants of health. Future trials must address variability in treatment response, identify resistant subgroups, and include long‐term follow‐up to assess durability and post‐treatment effects. Combination therapy trials should be stage specific, pairing novel agents with mAbs and incorporating broader stratification beyond traditional biomarkers to reflect clinical and pathological heterogeneity. Integrating biological and clinical outcomes, with digital biomarkers and responder‐enrichment strategies will enable more precise, mechanism‐driven, and individualized therapeutic approaches in AD.
Progress towards a biotypic biomarker profile for amyotrophic lateral sclerosis-frontotemporal spectrum disorders.

Michael J. Strong, Neil S. Donison, A. Al-Chalabi, B. Boeve, E. Finger, H. Holstege, E. Huey, Edward B. Lee, Sarah J. Marzi, Caroline A. McHutchison, C. Mcmillan, M. Otto, L. Petrucelli, M. Prudencio, T. Simuni, M. Tartaglia, Martin R. Turner, P. Damme, and D. Wolk

Brain : a journal of neurology, Sep 2026

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Determining the optimal timing of disease-modifying therapies for neurodegenerative disorders will necessitate identification of when the underlying pathobiological process becomes active, well in advance of the point at which clinical manifestions appear. Phenoconversion, the emergence of clinically manifest syndomes, may be preceded by years to decades of silent pathobiological activity that can only be mapped by an array of biomarkers. ALS and FTD, traditionally identified as distinct clinical syndromes, are increasingly recognized to exist along a spectrum of clinical syndromes with shared genetic risk and shared underlying pathology. This clinicopathological spectrum is underpinned by cytoplasmic aggregation of TAR DNA-binding protein 43 (TDP-43) as the common neuropathological hallmark. In contrast, the majority of neuropathologically-defined frontotemporal lobar degeneration (FTLD) is associated with alterations in either TDP-43 metabolism (FTLD-TDP) or of the microtubule associated protein tau (FTLD-tau), with a smaller percentage associated with either autosomal dominant genetic mutations or impairments in the ubiquitin proteasome system. As the field of neurodegenerative disorders increasingly shifts towards the frameworks of a pathobiological definition of disease, there is a growing imperative to develop biomarkers that reflect the varied pathobiologies that underly these disorders, and to determine the sensitivity of such biomarkers to detect the presence of these pathobiologies before phenoconversion. To that end, an international workshop was convened in London, Canada in 2025 to review the evidence for existing or evolving biomarkers suitable for (1) the detection of either ALS or FTD pathobiology prior to phenoconversion and/or (2) predict phenoconversion in at risk individuals. Such biomarkers might be conceptualized as "biotypic biomarkers", capturing their ability to describe an underlying pathophysiology whilst being agnostic to the emergent clinical manifestations. Whereas no single biotypic marker is yet able to predict the emergence of ALS, FTD or their intersection, a multimodal approach to developing a biotypic biomarker profile holds promise for the detection of relevant pathobiological processes. The strength of such an approach would be augmented by also addressing issues of resiliency/susceptibility both in terms of genetic risk susceptibility profiles and developing sensitive biomarkers of genomic and cellular aging. By including such nontraditional markers of disease, a more robust picture of not only the degenerative process but also of those factors that might potentially mitigate or drive a heightened probability of disease can be derived.
Discovering repurposable drugs for Alzheimer’s disease and related dementias: target trial emulation using decentralised real-world data

Qiong Wu, Lu Li, Yu-Qing Lei, Ting Zhou, Hui-Lin Tang, Bing-Yu Zhang, Yi-Wen Lu, Maxwell Salvatore, Da-Zheng Zhang, Jia-Yi Tong, Ting-Yin Wang, Si-Qi Chen, Hao-Yang Li, Zhenxing Xu, Yu Huang, Yu Hu, N. Hong, Yu-Jia Zhou, Fong-Ci Lin, K. O’Brien, Yong Chen, Ruo-Wang Li, Hua Xu, Fei Wang, Jiang Bian, D. Wolk, and Yong Chen

eBioMedicine, Sep 2026

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Summary Background Alzheimer’s disease and related dementias (ADRD) affect nearly 6.9 million Americans, with the number expected to triple by 2050, while disease-modifying therapies remain unavailable. Drug repurposing, which identifies new indications for already approved medications, offers a more efficient and cost-effective pathway to accelerate development of effective therapies for ADRD. The aim of this study is to identify potential drug repurposing signals by systematically screening routinely prescribed drugs for associations with progression from mild cognitive impairment (MCI) to ADRD. Methods We conducted a multi-site target trial emulation using electronic health record (EHR) data from four decentralised databases: INSIGHT Clinical Research Network, OneFlorida + Clinical Research Consortium, the University of Pennsylvania Health System, and Yale New Haven Health System. We performed an independent validation using EHR data from the TriNetX Research Network and a genetic risk-stratified sensitivity analysis in the Penn Medicine BioBank (PMBB) database. Eligible participants were adults aged 50 years or older at the time of MCI diagnosis, with no prior diagnosis of ADRD and no prior use of the trial drugs. Initiation of each of 181 routinely prescribed drugs was compared with two active control groups defined by initiation of supplements or cardiovascular medications. Risk ratios (RRs) and 95% CIs were estimated using a federated target trial emulation framework (LATTE) with stabilised inverse probability of treatment weighting and Poisson regression. Findings A total of 122,972 eligible patients were identified from the four decentralised databases, 335,506 patients identified from the TriNetX network for validation and 898 from PMBB database. Federated, multi-site target trial emulation identified 20 drug repurposing hypotheses with statistically significant protective effects, including anti-inflammatory and pain-modulating agents (celecoxib: RR 0.43; 95% CI: 0.23–0.81; dexamethasone RR 0.46; 95% CI: 0.29–0.73; gabapentin: RR 0.55; 95% CI: 0.36–0.83; ketorolac: RR 0.50; 95% CI: 0.31–0.80; methylprednisolone: RR 0.43; 95% CI: 0.24–0.76; prednisone: RR 0.48; 95% CI: 0.28–0.83; pregabalin: RR 0.53; 95% CI: 0.35–0.79), antimicrobial and microbiome-associated agents (cefazolin: RR 0.62; 95% CI: 0.45–0.84; clavulanate: RR 0.56; 95% CI: 0.44–0.71; fluconazole: RR 0.36; 95% CI: 0.23–0.58), neuromodulators and adrenergic agents (epinephrine: RR 0.42; 95% CI: 0.31–0.56; propranolol: RR 0.56; 95% CI: 0.37–0.85; salmeterol: RR 0.49; 95% CI: 0.32–0.74; tizanidine: RR 0.29; 95% CI: 0.14–0.57), vascular, metabolic, and hormonal modulators (empagliflozin: RR 0.29; 95% CI: 0.17–0.50; oestradiol: RR 0.47; 95% CI: 0.28–0.81; ezetimibe: RR 0.69; 95% CI: 0.52–0.91; sodium bicarbonate: RR 0.49; 95% CI: 0.29–0.84; spironolactone: RR 0.43; 95% CI: 0.31–0.60), and histamine-related and gastrointestinal agents (famotidine: RR 0.64; 95% CI: 0.55–0.74). Results were consistent in the independent validation using TriNetX network and sensitivity analysis in PMBB database. Interpretation 20 widely used medications may be associated with reduced progression from MCI to ADRD and represent promising candidates for clinical evaluation as repurposed therapies for dementia. Funding National Institutes of Health.
Sample size determination for a prospective bridging study to harmonize retrospective data from multiple studies—Application to a biofluid biomarker study of Alzheimer’s disease

Cheng-Jie Xiong, Yu-Zheng Nie, Jing-Qin Luo, Rui-Jin Lu, D. Wolk, Leslie Shaw, C. Gleason, Sterling C. Johnson, Folasade Agboola, J. C. Morris, and S. Schindler

Statistical Methods in Medical Research, Sep 2026

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Biomarkers measured from biofluid samples and imaging scans are important to aid diagnosis of diseases and track their progression over time, especially in neurodegenerative diseases such as Alzheimer’s disease (AD). Combining retrospectively obtained biomarker data across multiple studies can increase statistical power, but existing biomarker data may be generated using different assay platforms, scanner types, or processing protocols by different studies, which may significantly affect the measurements of biomarkers and hence render it necessary to harmonize the data across the studies. An optimal way of biomarker data harmonization is to re-analyze all the biofluid samples or imaging scans together on a single platform in a central reference lab, but this is often not practical because of the substantial cost involved as well as the limited amount of biofluid samples available. A more practical solution is to prospectively design a bridging study by re-measuring a subset of biofluid samples or imaging scans from the studies in a reference lab to evaluate how biomarker values may be harmonized across studies. An important design question for such a bridging study is the size of the retrospectively collected biofluid samples or imaging scans that will be re-measured. We aim to address this question by conceptualizing a latent but true biomarker that underlies the observed versions of the biomarker measured across retrospective studies and proposing methods to determine the sample size of a bridging study for estimating the biological correlation of the true biomarker with a standard and validated clinical outcome. We also report bridging data of several analytes from cerebrospinal fluid (CSF) in a multi-center biomarker study of AD and demonstrate that a small proportion of the CSF samples may be sufficient to design a future bridging study for estimating the correlations of CSF biomarkers with a cognitive and functional outcome.
Does FLAIR super-resolution erase or hallucinate small white-matter lesions?

Zahra Khodakarami, Yue Li, Pulkit Khandelwal, John A. Detre, Sandhitsu R. Das, Christopher A. Brown, David Wolk, and Paul Yushkevich

Aug 2026

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White matter hyperintensities (WMH), bright regions on Fluid-attenuated Inversion Recovery (FLAIR) scans are associated with cerebrovascular pathology and neurodegeneration. FLAIR is usually acquired with thick slices in clinical settings, giving it poor through-plane resolution. Super-resolution (SR) is a widely used method for recovering an isotropic volume from an anisotropic scan. Yet whether applying it prior to WMH segmentation preserves lesion content remains unknown: a model may erase small real lesions or hallucinate absent ones. We used 1-mm isotropic high-resolution (HR) FLAIR scans from 29 individuals in the ADNI cohort, each manually segmented for WMH by an expert. Then, we degraded each to simulated 3 and 5 mm through-plane acquisitions. Multi-contrast implicit neural representation (INR), a single-contrast self-supervised model (ECLARE), and cubic interpolation were used to upsample them onto the HR grid. WMH segmentation from a simulated thick slice and the original HR FLAIR set the floor and ceiling, respectively, for the per-lesion analysis. Of four WMH segmentation methods (WMH-SynthSeg, segcsvd, MARS-WMH, TrUE-Net), we ran the analysis under the most sensitive one to small lesions on HR (MARS-WMH) with the evaluation metrics of detection sensitivity, erasure rate (HR-detected lesions lost after reconstruction), and hallucination rate (predicted components absent from both the manual and HR segmentation). The dominant effect of SR was erasure of small real lesions, not hallucination, and it increased with slice thickness, though every reconstruction still improved lesion detection over the raw thick slice. ECLARE recovered small lesion signal best at both thicknesses, while the INR was no better than cubic interpolation.
Association Between Postmortem Pathologic Burden and the Rate of Clinical Progression in Patients With Frontotemporal Lobar Degeneration.

R. Magee, Sharon X. Xie, DT Ohm, E. Rhodes, L. Massimo, V. Van Deerlin, D. Wolk, Edward B. Lee, C. Mcmillan, and D. Irwin

Neurology, Aug 2026

Cited by 1

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BACKGROUND AND OBJECTIVES Histopathologic staging of Alzheimer disease has led to validation of imaging techniques that guide diagnosis and treatment. We previously constructed preliminary phases of the sequential progression of TDP-43 and tau to guide similar efforts in behavioral-variant frontotemporal dementia (bvFTD). In this article, we expand this work using digital pathology and longitudinal clinical data to more comprehensively model the relationship between clinical progression and the distribution and severity of postmortem frontotemporal lobar degeneration (FTLD) pathology. METHODS In this retrospective cohort study, 101 patients (42% female, median age at symptom onset = 63 years) were selected from the Penn Integrated Neurodegenerative Disease Database and had both longitudinal assessments and primary neuropathologic diagnosis of FTLD-Tau or FTLD-TDP. We used validated methods to quantify the burden of primary pathology from up to 6 cortical regions across hemispheres. FTLD-TDP pathologic phase was constructed from diagnostic pathology data based on published criteria. We tested the association between pathologic metrics and (1) disease duration or (2) the rate of clinic progression measured by 2 independent global measures (Clinical Dementia Rating Scale-Sum of Boxes [CDR-SB] and Mini-Mental State Examination [MMSE]). Linear regression and linear mixed-effects models were adjusted for hemisphere sampled, sex, age at onset, pathogenic variant status, and pathologic subtype. RESULTS Disease duration did not associate with pathologic burden in multiple regression (FTLD-TDP β = 0.01 [-0.06, 0.09]; p = 0.7; FTLD-Tau β = 0.1 [-0.4, 0.7]; p = 0.7). By contrast, mean TDP-43 burden, but not FTLD-Tau burden, was associated with both worse relative CDR-SB (β = 0.1 [0.06, 0.2]; p = 0.0001) and MMSE (β = -0.1 [-0.2, -0.03]; p = 0.009) among all FTLD-TDP patients. TDP-43 phase also associated with worse CDR-SB (β = 0.07 [0.02, 0.1]; p = 0.005) and MMSE (β = -0.2 [-0.3, -0.1]; p = 0.000005). TDP-43 burden (CDR-SB (β = 0.1 [0.03, 0.2]; p = 0.005 and MMSE (β = -0.2 [-0.4, -0.05]; p = 0.009)), but not phase (CDR-SB (β = 0.02 [-0.03, 0.08]; p = 0.4 and MMSE (β = -0.04 [-1, 0.07]; p = 0.5)), associated with relative decline in sensitivity analyses limited to bvFTD. DISCUSSION Greater TDP-43 burden was most closely associated with antemortem clinical decline rather than cumulative aggregation through the disease course. These human data suggest that the temporal dynamics of protein aggregation may differ among FTLD proteinopathies, with implications for the interpretation of FTLD-Tau and FTLD-TDP‑specific biomarkers as these are developed.
EOAD-Signature Atrophy Predicts Dementia in Early-Onset MCI due to Alzheimer Disease

T. Paranhos, Yuta Katsumi, M. Brickhouse, A. Eloyan, Ryan Eckbo, Alexander Zaitsev, Anna Du, R. La Joie, M. Thangarajah, Alexander Taurone, P. Vemuri, C. Jack, Dustin B. Hammers, P. Aisen, Laurel Beckett, R. Koeppe, W. Kukull, A. Toga, A. Atri, David Clark, Gregory S. Day, R. Duara, N. Graff-Radford, Ian M. Grant, Lawrence S. Honig, Erik C. B. Johnson, David T. Jones, Joseph C. Masdeu, Mario F. Mendez, Erik S. Musiek, C. Onyike, Meghan Riddle, E. Rogalski, S. Salloway, S. Sha, R. Turner, Thomas S. Wingo, D. Wolk, Kyle B. Womack, M. Carrillo, G. Rabinovici, Liana G. Apostolova, B. Dickerson, Mark C. Eldaief, and Alexandra Touroutoglou

Neurology, Aug 2026

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Background and Objectives Early-onset Alzheimer disease (EOAD) is associated with substantial variability in clinical progression, and reliable biomarkers to predict the transition from mild cognitive impairment (MCI) to dementia remain limited. Structural MRI measures have demonstrated prognostic value in late-onset Alzheimer disease, but their utility for predicting progression in EOAD is less well understood. The goal was to examine whether baseline cortical atrophy predicts progression to dementia in patients with MCI because of EOAD. Methods This study included a well-characterized cohort of patients with EOAD enrolled in the large multisite natural history Longitudinal Early-Onset Alzheimer’s Disease Study. Participants underwent standardized clinical assessments and structural MRI at baseline. Participants were aged between 40 and 64 years with biomarker-supported sporadic EOAD at the MCI stage. Cortical atrophy was measured within the EOAD-signature, a set of predominantly parieto-temporal regions showing greater atrophy in EOAD than in controls. Clinical severity was measured with the global Clinical Dementia Rating. Cox proportional hazards models estimated the association between baseline EOAD-signature atrophy burden and the hazard of progression to dementia over time. We evaluated whether EOAD-signature atrophy improved prognostic performance beyond baseline clinical severity using likelihood ratio tests, Akaike Information Criterion (AIC), and Harrell concordance index. Results A total of 130 patients with MCI due to EOAD (mean age 59.6 ± 4.1 years; 49% female) and 97 cognitively normal controls (mean age 56.9 ± 6.0 years; 64% female) were included. Greater baseline atrophy within the EOAD-signature predicted faster progression to dementia (hazard ratio [HR] = 1.24 per 1-SD increase in atrophy; 95% CI 1.13–1.37; p < 0.002). Adding EOAD-signature atrophy burden to a model including baseline clinical severity significantly improved model fit (ΔAIC = −4.5; likelihood ratio test p = 0.011). Discussion Baseline cortical atrophy within the EOAD-signature predicts progression from MCI to dementia in EOAD and provides prognostic information beyond baseline clinical severity. These findings support the potential value of EOAD-signature atrophy as an MRI-based biomarker for individualized prognostication and clinical trial stratification.
Clinicopathologic Evaluation of Amyloid Clearance in Alzheimer Disease

Christopher A. Brown, John L. Robinson, Sandhitsu R. Das, Emily McGrew, Eunran Suh, Viviana M. Van Deerlin, David J. Irwin, I. Nasrallah, Dawn Mechanic-Hamilton, Paul A. Yushkevich, D. Wolk, and Edward B. Lee

JAMA, Jul 2026

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Importance: The long-term efficacy of amyloid targeting therapies hinge on their ability to slow downstream neuropathologic change, but little is known about the influence of amyloid clearance on tau pathology and neurodegeneration. Objective: To determine the post-mortem and in vivo association between post-treatment amyloid levels and downstream neuropathology in a patient with patchy areas showing minimal residual amyloid following aducanumab therapy. Design, Setting, and Participants: Clinicopathologic case report from a single academic memory center. A p.R47H TREM2 (a variant associated with higher Alzheimer disease risk) male carrier in his 50s with mild cognitive impairment who received aducanumab in the EMERGE/EMBARK trials and 14 age- or TREM2-matched untreated controls from the Penn Center for Neurodegenerative Disease Research. Exposures: 30 doses of aducanumab (cumulative dose 280mg/kg) over 4.5 years. Main Outcomes and Measures: Neuropathologic evaluation of amyloid, tau, and neuroinflammation; Amyloid PET and Tau PET standardized uptake value ratio, longitudinal change in cortical thickness. Results: Four years after receiving his final dose of aducanumab, the patient died and autopsy demonstrated variable levels of amyloid pathology, including regions with very low amyloid juxtaposed with regions showing typical high amyloid burden in deep cortical layers with only low amyloid burden in superficial layers. Regions showing low post-treatment amyloid were preferentially found in gyral crests and were associated with less tau pathology than untreated controls on autopsy and slower longitudinal atrophy on in vivo MRI (β = −0.50, [−0.62, −0.37], t = −7.96, p < .001). In contrast, regions with high amyloid burden were preferentially found in sulcal depths and had similar levels of tau pathology as seen in untreated controls on autopsy. Conclusion and Relevance: In this case report, areas of extensive amyloid clearance following amyloid targeting therapy were associated with less downstream neuropathological change and appear to preferentially occur in gyral crests. Future studies should evaluate the differential mechanisms involved in amyloid clearance from superficial and deep cortical layers and in gyri and sulci, as extensive amyloid clearance may be necessary to achieve downstream neuropathologic benefit following amyloid removal.
Volumetric postmortem MRI of the medial temporal lobe in Alzheimer’s disease and related disorders: methodological advances and implications for in vivo biomarker development

Y. Salman, Amanda E. Denning, J. Schaeverbeke, Sandra O. Tomé, N. Joudiou, Pulkit Khandelwal, Paul Yushkevich, R. Vandenberghe, Bernard Gallez, L. Wisse, and Bernard J. Hanseeuw

NeuroImage, Jul 2026

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Magnetic resonance imaging (MRI) is central to the study and diagnosis of neurodegenerative diseases. Yet, no MRI biomarker is currently specific to a given neurodegenerative disease. This may result from the limited resolution of conventional MRI, which restricts detailed investigation of medial temporal lobe (MTL) subregions, a crucial hub for many neuropathologies. Moreover, in vivo MRI cannot be directly compared with neuropathological data, the gold standard for disease definition. Even when antemortem MRI and postmortem analyses are combined, the time gap between imaging and neuropathological examination allows pathogenic processes to progress, reducing the accuracy of these correlations. Over the past two decades, postmortem MRI has gained increasing interest because it enables long, motion-free acquisitions and the use of specialized coils and preclinical scanners, providing ultra-high spatial resolution. Additionally, it allows direct correspondence between imaging and neuropathological measures. Consequently, volumetric postmortem MRI, particularly investigations of the MTL, has become an increasingly common approach in Alzheimer’s disease and related disorders (ADRD). This narrative review specifically focuses on volumetric postmortem MRI of the MTL and summarizes the main methodologies for anatomical postmortem MTL imaging in ADRD and recent advances in the characterization of neurodegenerative changes, from brain preparation to MRI acquisition. It also highlights the translational potential of volumetric postmortem MRI for developing in vivo biomarkers, optimizing imaging protocols and segmentation methods, and assessing the impact of proteinopathies. Finally, it outlines current limitations, technical challenges, and perspectives for future research.
Predicting Risk of Cognitive Impairment With Alzheimer Disease Blood Biomarkers.

Suzanne E. Schindler, and D. Wolk

JAMA, Jul 2026

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Regional juxtacortical microstructural changes and gene expression provide insights into neurodegeneration in Alzheimer’s disease

Junfang Zhang, Lipeng Sun, Xinyuan Yang, Lin Kang, Yingting Zheng, Qi Huang, Wei Dong Xu, Y. Guan, Jun Liu, Yulei Deng, Fang Xie, Xiaomeng Xu, Binyin Li, Michael W. Weiner, P. Aisen, Ronald Petersen, C. Jack, William J Jagust, J. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, A. Saykin, John C. Morris, R. Perrin, Leslie M. Shaw, Maria C. Carrillo, W. Potter, L. Barnes, M. Bernard, Hector González, Carole Ho, John K. Hsiao, Jonathan Jackson, Eliezer Masliah, Donna Masterman, Ozioma C. Okonkwo, R. Perrin, Laurie Ryan, N. Silverberg, A. Fleisher, J. Fockler, Cat Conti, D. Veitch, J. Neuhaus, Chengshi Jin, R. Nosheny, Miriam Ashford, D. Flenniken, A. Kormos, and 384 more authors

Translational Psychiatry, Jul 2026

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Reply: Cerebrovascular contributions to the ’vulnerable’ medial temporal lobe T-N phenotype.

Sandhitsu R. Das, Xueying Lyu, and D. Wolk

Brain : a journal of neurology, Jun 2026

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Clinicoanatomic localization of iron-rich gliosis in aphasic presentations of globular glial tauopathy

D. Irwin, Sheina Emrani, Daniel T. Ohm, W. Trotman, A. Bahena, Eric Teunissen-Bermeo, Philip Sabatini, Sandhitsu R. Das, G. Mizsei, K. Prabhakaran, R. Ittyerah, H. B. Coslett, L. Massimo, D. Wolk, John A. Detre, James C. Gee, Edward B. Lee, Paul Yushkevich, Corey T. McMillan, and M. Tisdall

Brain Communications, Jun 2026

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Abstract Globular glial tauopathy is a 4-repeat tauopathy associated with heterogenous clinical syndromes, including primary progressive aphasia. Iron-reactive gliosis in mid-to-deep cortical layers has previously been reported in this disorder, but detailed anatomic localization and its relationship to clinical symptoms is understudied, particularly within the anatomic framework of primary progressive aphasia. In a series of five autopsy-confirmed patients with globular glial tauopathy and one healthy control, we utilize ultra-high-resolution whole-hemisphere ex vivo 7 Telsa MRI and digital pathology to study whole-hemisphere and local laminar/cellular patterns of pathology within affected cortex. We find signature laminar patterns of iron-rich gliosis localized to brain regions implicated in distinct clinical aphasia syndromes between patients: patients who presented with non-fluent aphasia had iron-rich gliosis pathology localized to inferior and superior frontal and motor regions while iron-rich pathology was largely localized to the anterior temporal lobe in a patient with the semantic variant. Moreover, in one patient with non-fluent aphasia and additional iron-sensitive 7 Telsa MRI during life, we find evidence of antemortem iron-rich pathology in the same frontal regions observed post-mortem. These data suggest that focal neuroinflammation and iron dysregulation may contribute to the clinical expression of tauopathies and be detectable during life to improve diagnosis.
Cortical thickness in perirhinal area BA35 predicts adaptive episodic memory-guided decision making in older adults

Karolina M. Lempert, Michael S. Cohen, Kameron A MacNear, Frances M. Reckers, Laura Zaneski, Long Xie, Sandhitsu R. Das, Paul Yushkevich, D. Wolk, and Joseph W. Kable

The journals of gerontology. Series B, Psychological sciences and social sciences, Jun 2026

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Objectives: To make adaptive decisions, it is often necessary to retrieve episodic memories, for example, about whether an item was previously associated with reward. Compared to young adults, older adults are impaired at making adaptive episodic memory-based choices. There are substantial individual differences across older adults, however. In this study, we examined whether hippocampal volume or extrahippocampal cortical thickness in the medial temporal lobe (MTL) is associated with better episodic memory-based decision making in cognitively unimpaired older adults. Methods: Older adults (n = 87; aged 61–88) completed a decision-making task and a T1-weighted anatomical MRI scan. In the task, they studied images of houses paired with arbitrary reward values (5 or 0). Later, they made incentivized approach/avoid decisions about these items. Finally, their memory for the items and their values was assessed. MTL structural data were segmented with the ASHS-T1 pipeline to obtain volume measures for anterior and posterior hippocampus, and cortical thickness measures in entorhinal cortex, parahippocampal cortex, and perirhinal cortex Brodmann areas (BAs) 35 and 36. Results: BA35 cortical thickness was associated with better performance in the decision-making task. This effect persisted after adjusting for memory performance, suggesting that BA35 thickness is specifically linked to the retrieval and use of episodic memories at the time of choice. Discussion: Although this study is cross-sectional, it suggests that atrophy in BA35 may contribute to subtle changes in the ability to use memory to make reward-maximizing choices, even in individuals who do not yet show evident cognitive impairment.
Assessing subcortical, brainstem and cerebellar metabolic patterns using [18F]FDG PET-CT imaging in dementia with Lewy bodies

Daniël S. L. Loewenstein, Max Grinsven, C. Pont, Anne I. J. Arens, Paul L. J. Dautzenberg, Astrid M. Strien, O. Sabri, S. Hesse, M. Rullmann, D. Henssen, Michael W. Weiner, P. Aisen, Ronald Petersen, C. Jack, W. Jagust, S. Landau, M. Rivera-Mindt, O. Okonkwo, Leslie M. Shaw, Edward B. Lee, A. Toga, Laurel A. Beckett, Danielle J. Harvey, Robert C. Green, A. Saykin, K. Nho, Richard J. Perrin, D. Tosun, P. Sachdev, Erin Drake, T. Montine, R. Nosheny, D. T. Sacrey, J. Fockler, Melanie J. Miller, Cat Conti, Winnie Kwang, Cheng-Shi Jin, Adam Diaz, Miriam Ashford, D. Flenniken, Adrienne Kormos, M. Rafii, Rema Raman, Gustavo Jimenez, M. Donohue, Jennifer Salazar, Andrea Fidell, Virginia Boatwright, Justin Robison, and 450 more authors

European Journal of Nuclear Medicine and Molecular Imaging, Jun 2026

Cited by 1

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Numerous clinical features of Dementia with Lewy Bodies (DLB) are attributed to dysfunction in subcortical anatomy. Despite this, [18F]FDG PET imaging as a diagnostic tool for DLB largely relies on the metabolic signature of the occipital lobe, precuneus, and posterior cingulate cortex. This study aimed to assess subcortical brain metabolism in patients with DLB using [18F]FDG PET imaging. Patients diagnosed with probable DLB were included from both a prospectively maintained regional database (n = 33), and the ADNI database (n = 43). Using statistical parametric mapping (SPM) analysis, metabolic activity was compared with a cohort of subjects exhibiting normal brain metabolism (n = 19). A sub-analysis was conducted with disease progression included as a covariate. Hypermetabolism was observed in various subcortical regions, notably in the dentate nucleus, anterolateral thalamus, and regions of the superior cerebellar peduncle. Increased metabolism was also detected in the mesencephalic tectum, likely representing heightened activity in the superior colliculus. All findings were reproduced in the ADNI cohort and were found to be dependent on the DLB disease stage. Additionally, the well-established cortical hypometabolic signature of DLB pathology was evident, validating our methods and findings. Increased metabolic activity is evident in a variety of brainstem, cerebellar, and subcortical regions in patients with DLB. The dentatorubrothalamic tract, in particular, emerges as a structure of interest that connects these structures and potentially helps in understanding DLB pathophysiology. Correction for disease stage eliminated this pattern, suggesting a driver associated with disease progression.
Vulnerability of anterior medial temporal lobe subregions to early tau‐related neurodegeneration in Alzheimer’s disease: Converging evidence from tau‐PET and plasma p‐tau217

N. S. Mundada, Niyousha Sadeghpour, Emily McGrew, Hannah L. Tucker, I. Nasrallah, Sandhitsu R. Das, D. Wolk, Paul Yushkevich, Christopher A. Brown, and L. Wisse

Alzheimer’s & Dementia, Jun 2026

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The anterior medial temporal lobe (MTL), including the entorhinal cortex (ERC) and Brodmann area 35 (BA35), is among the earliest cortical sites of tau pathology in Alzheimer’s disease (AD), yet conventional image segmentation methods poorly capture these regions.
Characterizing the MRI signature of hippocampal sclerosis of aging

G. Rådman, Amanda E. Denning, S. Ravikumar, Nicola Spotorno, R. Ittyerah, Lisa Levorse, John L. Robinson, T. Schuck, Sydney A. Lim, E. Chung, M. Bedard, W. Trotman, A. Bahena, M. Mar Arroyo-Jiménez, Alicia Vela, Esther Buendia, Maria Mercedes Iñiguez Onzoño Martin, M. Rabal, Mónica Muñoz-López, R. Olsen, John A. Detre, Edward B. Lee, David A. Wolk, Daniel T. Ohm, Corey T. McMillan, R. Insausti, David J. Irwin, Paul Yushkevich, and L. Wisse

Alzheimer’s Research & Therapy, Jun 2026

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Hippocampal sclerosis of aging (HS-A), a common cause of dementia, can currently only be diagnosed at autopsy. We aimed to identify and evaluate MRI metrics to distinguish HS-A from Alzheimer’s Disease neuropathologic change (ADNC) and cases with limited/no pathology. HS-A (N = 5), ADNC (N = 10), and limited/no pathology (N = 12) cases were compared on postmortem MRI signatures: manually measured cornu ammonis (CA)1/subiculum thickness, grey matter signal intensity, and automated hippocampal subfield thickness metrics. Similar metrics were obtained in T1-weighted antemortem MRI in an initial dataset (HS-A = 4, ADNC = 7, limited/no pathology = 25) for group differences and discrimination (HS-A vs ADNC). T1-weighted metrics were then evaluated in a second dataset (HS-A = 6, ADNC = 18) and in a pooled post-hoc analysis combining HS-A and ADNC cases from both datasets (NHS-A = 10, NADNC = 25). Postmortem MRI showed hippocampal thinning and grey matter hypointensity in HS-A at the CA1-subiculum junction more severe than in ADNC and limited/no pathology cases. In antemortem MRI, differentiating HS-A and ADNC based on anterior/posterior manual measures of CA1/subiculum thickness and hippocampal volumes displayed good discrimination in dataset 1, but lower discriminative performance in dataset 2. In complementary analyses pooling both datasets and adjusting for age, manual thickness achieved good performance (area under the curve (AUC) = 0.80–0.87), while anterior, posterior, and whole hippocampal volumes showed excellent discrimination (AUC = 0.94–0.98). The study included a relatively small and neuropathologically heterogeneous sample. The final antemortem analyses were exploratory, reflecting challenges in replicating findings across independent datasets. Classification was limited to HS-A and ADNC, leaving it uncertain how the metrics perform when comparing HS-A with other diagnostic groups. HS-A diagnoses were determined postmortem, often several years after MRI, and most measures relied on standard imaging sequences with limited resolution to assess fine-grained hippocampal subfields. HS-A displays distinct changes in the hippocampus that are detectable through structural MRI. Associated quantifiable MRI metrics may serve as promising tools in aiding antemortem HS-A diagnosis but require further validation in larger cohorts and against other dementia-related diseases.
Depression and Anxiety Modify Cognitive Concerns Associated with Amyloid and Early Clinical Impairment

S. Stites, Rosalie Schumann, Yidan Shi, Dawn Mechanic-Hamilton, and D. Wolk

Neuropsychology, Jun 2026

Cited by 1

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Objective: Cognitive concerns (CCs) are common for patients with Alzheimer’s disease (AD) dementia. We explore anxiety, depression, and clinical impairment as moderators of CCs in early AD. Understanding these associations may help inform efforts to advance early identification of disease progression in AD. Methods: Data sources, selected based on requirements for availability of biomarker data and clinical assessment data, generated a pooled sample of adults ages 65+ with known amyloid status and cognitive function ranging from unimpaired (Clinical Dementia Rating global score (CDR-GS=0, n=5,498) to early impairment (CDR-GS=0.5, n=504). Measures of CCs, anxiety, and depression were standardized to cognitively unimpaired groups. To model the difference in effects for different levels of anxiety and depression, we used mixed-effects quantile regression for median adjusted for age, sex, race, and educational years. All reported findings are p<0.05. Results: Higher CCs were associated with early clinical impairment (estimated change in median (β) =15.5). CCs were higher with higher versus lower anxiety, except in unimpaired persons with elevated amyloid. In this latter group of unimpaired persons with elevated amyloid, CCs were higher with higher versus lower depression. Conclusion: In combination elevated amyloid, anxiety, and depression may offer data to guide clinical interpretation of CCs in early clinical impairment. The findings advance understanding of mood effects in early AD and inform specific measurement considerations. Future longitudinal studies are needed.
Automated Optical Density Normalization for Myelin Quantification: Cross-Modal Validation with 7T Ex Vivo MRI

Zahra Khodakarami, Sheina Emrani, Pulkit Khandelwal, Chinmayee Athalye, Amanda E. Denning, W. Trotman, Lisa Levorse, Eric Teunissen-Bermeo, Hamsanandini Radhakrishnan, Daniel T. Ohm, Christopher A. Olm, N. Capp, R. Ittyerah, K. Prabhakaran, John A. Detre, Sandhitsu R. Das, D. Wolk, Corey T. McMillan, G. Mizsei, M. Tisdall, David J. Irwin, John L. Robinson, Edward B. Lee, and Paul Yushkevich

May 2026

Abs arXiv

White matter hyperintensities (WMH) are bright regions on T2-weighted magnetic resonance imaging (MRI) scans and are associated with cerebrovascular pathology and neurodegeneration, including myelin loss. While Luxol Fast Blue histopathology provides visualization of myelin integrity, quantitative analysis requires measuring Optical Density as a proxy for myelin concentration. However, differences in laboratory protocols and tissue processing introduce staining variability that acts as systematic noise, obscuring the biological signal and preventing consistent comparison across histology runs. To address this, we developed an automated pipeline that identifies reference (non-pathologic) regions in whole-slide images to compute normalized Optical Density heatmaps. We validated this approach through two complementary evaluations: (1) comparison against expert ratings of myelin loss severity, and (2) cross-modal spatial comparison with co-registered 7T ex vivo MRI for voxel-wise evaluation within white matter regions. The pipeline’s reference selection showed strong concordance with expert-identified reference regions, and normalized Optical Density demonstrated a substantially stronger correlation with MRI signal intensity than raw measurements. This correlation persisted within WMH, confirming that the pipeline captures continuous myelin pathology rather than merely the presence or absence of myelin loss contrast. By mitigating staining artifacts, this pipeline provides a robust, validated framework for quantitative cross-modal comparison, establishing a critical methodological foundation for future translation to in vivo myelin mapping and biomarker discovery.
Tau topography subtypes account for clinical heterogeneity and longitudinal trajectories in early-onset Alzheimer’s disease

Marlene Lin, Konstantinos Chiotis, Piyush Maiti, Jiaxiuxiu Zhang, G. Blazhenets, Salma Rocha, Ranjani P. Shankar, Alinda N. Amuiri, Dustin B. Hammers, A. Eloyan, Kala Kirby, R. Koeppe, P. Aisen, Laurel Beckett, W. Kukull, A. Toga, A. Atri, D. Clark, Gregory S. Day, R. Duara, N. Graff-Radford, Ian M. Grant, Lawrence S. Honig, Erik C. B. Johnson, David T. Jones, Joseph C. Masdeu, Mario F. Mendez, Erik S. Musiek, C. Onyike, M. Riddle, E. Rogalski, S. Salloway, S. Sha, R. Turner, Thomas S. Wingo, D. Wolk, Kyle B. Womack, K. Nudelman, Alexandra Touroutoglou, C. Jack, P. Vemuri, Jacob W. Vogel, S. Dufault, Thomas J. Hoffmann, Maria C. Carrillo, B. Dickerson, Liana G. Apostolova, G. Rabinovici, and R. La Joie

Brain Communications, May 2026

Cited by 1

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Abstract The growing availability of large-scale biomarker datasets has allowed data-driven methods to characterize Alzheimer’s disease biological heterogeneity. However, most prior studies have focused on cohorts of late-onset amnestic cases, leaving early-onset Alzheimer’s disease underexplored. We aimed to characterize tau-PET-based subtypes through a robust data-driven approach in the Longitudinal Early-Onset Alzheimer’s Disease Study. Baseline [18F]Flortaucipir PET scans from 365 amyloid-PET-positive participants with sporadic early-onset Alzheimer’s disease were quantified in the left and right medial temporal, lateral temporal, occipital, parietal, and frontal cortices. Tau PET values were z-scored against 85 amyloid-PET-negative cognitively normal age-matched participants and fitted into Subtype and Stage Inference (SuStaIn)—an unsupervised clustering algorithm that simultaneously models subtypes and progression from cross-sectional data. The derived subtypes were subsequently characterized by baseline and longitudinal clinical, cognitive, MRI, tau and amyloid PET features. We identified three tau-PET-based subtypes: on average, Subtype 1/Typical (n = 144, 40%) showed a predominant bilateral temporoparietal pattern typical of Alzheimer’s disease. Subtype 2/Left temporal (n = 111, 31%) showed predominant left temporal binding. Subtype 3/Posterior (n = 104, 29%) showed early and permeating occipitoparietal involvement. Subtypes did not differ in demographics or global amyloid burden, but were relatively more enriched for specific clinical presentations: S1/Typical for amnestic presentations, S2/Left Temporal for primary progressive aphasia, and S3/Posterior for posterior cortical atrophy. Baseline tau PET subtypes aligned with cortical atrophy patterns and domain-specific cognitive impairment. When follow-up tau PET scans were fitted to SuStaIn trained on baseline data, 85.6% (n = 172/201) of participants retained the same subtype classification, indicating subtype temporal stability, and progressed within subtypes by 0.56 ± 0.70 SuStaIn stage/year. Longitudinal voxel-wise linear mixed-effects modelling revealed tau accumulation patterns for each subtype in regions relatively spared at baseline: occipital lobe accumulation predominated in S1/Typical, bilateral frontal and right temporal in S2/Left Temporal, and bilateral frontotemporal lobes in S3/Posterior. All subtypes showed longitudinal increases in Clinical Dementia Rating-Sum of Boxes, but with slower worsening in S3/Posterior compared with the other subtypes. Our findings reveal robust subtypes in sporadic early-onset Alzheimer’s disease characterized by distinct spatiotemporal tau patterns that parallel differences in clinical presentations and trajectories of neurodegeneration. These subtypes extend beyond traditional clinical syndromes and support a more nuanced framework for individualized prognosis and care. Incorporating tau PET subtyping into clinical trial design could enable more targeted therapeutic approaches for this younger population.
Uncovering distinct spatiotemporal trajectories of T‐N mismatch subtypes with likely co‐pathology in Alzheimer’s disease using event‐based modeling

Xueying Lyu, Christopher A. Brown, M. T. Duong, E. Fischer, Emily McGrew, David J. Irwin, B. Dickerson, I. Nasrallah, R. Shinohara, Alexandra L. Young, Paul Yushkevich, Sandhitsu R. Das, and D. Wolk

Alzheimer’s & Dementia, May 2026

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In Alzheimer’s disease (AD), tau–neurodegeneration (T–N) mismatch has been proposed to reflect non‐AD processes such as transactive response DNA binding protein 43 kDa and vascular disease. We aimed to characterize the spatiotemporal trajectories of T–N mismatch that may reflect non‐AD progression.
Idiotypic-susceptible Alzheimer’s disease: a clinically relevant, neurofibrillary tangle subtype

John L. Robinson, H. Cai, Nicholas Loh, Omar Vazquez, Zahra Khodakaramimaghsoud, Eunran Suh, V. Van Deerlin, Paul Yushkevich, Dawn Mechanic-Hamilton, Sharon X. Xie, Daniel T. Ohm, D. Wolk, David J. Irwin, J. Phillips, and Edward B. Lee

Acta Neuropathologica, May 2026

Cited by 1

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Neurofibrillary tangles in Alzheimer’s disease (AD) stereotypically spread from the medial temporal lobe to association areas and then to idiotypic areas (i.e., primary motor, somatosensory, auditory, and visual). Previous studies have reported variable and clinically relevant tangle densities across the hippocampus and association cortices, but the idiotypic tangle burden is understudied. In this study, we measured tangle density using immunohistochemistry in three idiotypic cortices (primary motor, somatosensory, and visual), three association cortices (middle frontal, superior temporal, and inferior parietal), and two hippocampal sectors (CA1 and subiculum) in 144 cases with a high level of AD neuropathologic change. Clinical diagnoses included late-onset AD (LOAD, n = 50), early-onset AD (EOAD, n = 21), behavioral variant frontotemporal dementia (bvFTD, n = 19), corticobasal syndrome (CBS, n = 18), logopenic primary progressive aphasia (lvPPA, n = 21), and posterior cortical atrophy (PCA, n = 15). We algorithmically assigned cases outside the interquartile ranges of mean tangle ratios of association:hippocampal, idiotypic:association, and idiotypic:hippocampal to mutually exclusive subtypes: idiotypic-susceptible, associative-predominant, limbic-predominant, or typical Braak (for all remaining cases). Regional tangle burdens differentiated subtypes, while female sex, younger ages, and longer disease durations also influenced tangle severity. Compared to typical Braak cases, idiotypic-susceptible and associative-predominant cases exhibited shorter disease duration and younger age at death while limbic-predominant cases were older. The MAPT H1H1 haplotype also differed by subtype, being most prevalent in limbic-predominant and least common in idiotypic-susceptible and associative-predominant subtypes. Clinically, the idiotypic-susceptible subtype associated with CBS (56%), the associative-predominant subtype with bvFTD (53%), and the limbic-predominant subtype with LOAD (14%). The typical Braak subtype characterized 74–76% of amnestic AD cases and 32–53% of non-amnestic AD cases. Moreover, k-means clustering corroborated four clusters including the idiotypic-susceptible and associative-predominant patterns. Our results confirm previously described tau subtypes and describe an idiotypic-predominant subtype with clinical relevance and distinct demographic and genetic characteristics in AD. Supplementary Information The online version contains supplementary material available at 10.1007/s00401-026-03013-6.
Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegeneration.

Nikhil N. Chaudhari, Owen M Vega, P. Imms, Jaron Kawamura, Nahian F. Chowdhury, Tamara Jafar, Andrei Irimia, Michael W. Weiner, P. Aisen, Ron Petersen, C. Jack, W. Jagust, Susan M. Landau, M. Rivera-Mindt, Ozioma C. Okonkwo, Leslie M. Shaw, Edward B. Lee, A. Toga, L. Beckett, D. Harvey, R. C. Green, A. Saykin, K. Nho, R. Perrin, D. Tosun, P. Sachdev, Erin Drake, T. Montine, Cat Conti, Michael W. Weiner, R. Nosheny, D. Sacrey, J. Fockler, Melanie J Miller, Cat Conti, W. Kwang, Chengshi Jin, Adam Diaz, Miriam Ashford, D. Flenniken, A. Kormos, M. Rafii, R. Raman, G. Jimenez, Michael Donohue, J. Salazar, Andrea Fidell, Virginia Boatwright, Justin Robison, Caileigh N. Zimmerman, and 450 more authors

GeroScience, Apr 2026

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Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves many neuroanatomic features whose effects on brain structure remain unexplored. To address this challenge, we trained interpretable deep neural networks (DNNs) to estimate brain age (BA) from T1-weighted (T1w) MRI. By identifying MRI features unapparent to humans, DNNs can find aging-related structural alterations above and beyond cortical thickness and atrophy. Using a novel approach to DNN interpretability, we mapped brain aging progression in 25,539 cognitively normal UK Biobank adults aged 45-83 years. Cortical aging is found to involve anatomic features becoming prominent during the 50s within frontolateral, mesolimbic, cuneal, and occipitotemporal regions. From these foci, aging-related features propagate to adjacent areas at rates peaking in the 60s. Cortical thinning and atrophy do not trend closely with neurodegeneration, but important DNN-identifiable anatomic features have spatiotemporal dynamics that match those of amyloid or tau. Our results challenge the assumption that MRI cannot map anatomic features trending with neurodegeneration. Interpretable DNNs can empower MRI to quantify anatomic aging as a process of spatial feature expansion from focal regions into nearby structures in the sequence of neurodegenerative pathology. Traditional morphometrics explain only ∼1% of variance in DNN-identifiable features, which clarifies why the former are insensitive to anatomic changes involving neurodegeneration. Our results conceptualize brain aging in the context of spatial and temporal parallels between anatomic senescence and neuropathology. These findings may help to map cognitively normal adults’ neurodegenerative anatomy even without PET measurements.
Medial temporal lobe Tau-Neurodegeneration mismatch from structural imaging and plasma biomarkers

Xueying Lyu, N. S. Mundada, Christopher A. Brown, Niyousha Sadeghpour, Emily McGrew, Long Xie, Yue Li, A. Wuestefeld, M. T. Duong, P. Cook, J. Gee, I. Nasrallah, Alice S Chen-Plotkin, Leslie M. Shaw, D. Mechanic-Hamilton, L. Wisse, Paul A. Yushkevich, Sandhitsu R. Das, and D. Wolk

Brain : a journal of neurology, Apr 2026

Cited by 1

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While tau pathology is closely associated with neurodegeneration in Alzheimer’s disease (AD), our prior work using multi-modality imaging revealed that mismatch between tau (T) and neurodegeneration (N) may reflect contributions from non-AD processes. The medial temporal lobe (MTL), an early site of AD pathology, is also a common target of co-pathologies such as limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC), often following an anterior–posterior atrophy gradient. Given the susceptibility of MTL to co-pathologies, here we explored T-N mismatch specifically within MTL using plasma ptau217 and MTL morphometry for identifying vulnerabilities and resilience in cognitively impaired or unimpaired AD patients. We parcellated the MTL into 100 spatially contiguous segments and calculated their T-N mismatch using plasma ptau217 as a measure for T and thickness as a marker of N. Based on these mismatch profiles, we clustered 447 amyloid-positive individuals from ADNI cohort into data-driven T-N phenotypes. We characterized the T-N phenotypes by examining their cross-sectional and longitudinal atrophy both within the MTL and across the whole brain, as well as cognitive trajectories. This framework was replicated in an independent cohort and finally translated to a real-world clinical sample of 50 patients undergoing anti-amyloid therapy. Clustering identified three T-N phenotypes with different MTL T-N mismatch profiles, atrophy patterns, and cognitive outcomes, despite comparable AD severity. The “canonical” group, characterized by low T-N residuals (N T), showed AD-like neurodegeneration patterns. The “vulnerable” group, characterized by disproportionately greater neurodegeneration than tau (N > T), showed atrophy primarily in the anterior MTL that extended into temporal-limbic regions, both in cross-sectional and longitudinal analyses. This group also exhibited neurodegeneration that preceded estimated tau onset and experienced faster cognitive decline across multiple domains, aligning with the typical characteristics of mixed LATE-NC with AD. In contrast, the “resilient” group (N < T) showed minimal atrophy and preserved cognitive function. These phenotypes were reproducible in an independent research cohort. Importantly, in a feasibility study applying the model developed from ADNI to a clinical cohort of patients receiving lecanemab, we identified vulnerable individuals with LATE-like atrophy patterns. This highlights its potential utility for identifying individuals with co-pathology in clinical settings. Our findings demonstrate that T-N mismatch within MTL using MRI and plasma biomarkers can reveal AD groups with varying vulnerability/resilience, with the vulnerable group displaying structural and cognitive outcomes suggestive of LATE-NC. This approach offers a cost-effective strategy for clinical trial stratification and precision medicine for AD therapeutics.
ICHOR: A Robust Representation Learning Approach for ASL CBF Maps with Self-Supervised Masked Autoencoders

Xavier Beltran-Urbano, Yiran Li, Xinglin Zeng, Katie R. Jobson, Manuel Taso, Christopher A. Brown, D. Wolk, Corey T. McMillan, Ilya M. Nashrallah, Paul Yushkevich, Ze Wang, John A. Detre, and S. Dolui

ArXiv, Mar 2026

Abs DOI arXiv

Arterial spin labeling (ASL) perfusion MRI allows direct quantification of regional cerebral blood flow (CBF) without exogenous contrast, enabling noninvasive measurements that can be repeated without constraints imposed by contrast injection. ASL is increasingly acquired in research studies and clinical MRI protocols. Building on successes in structural imaging, recent efforts have implemented deep learning based methods to improve image quality, enable automated quality control, and derive robust quantitative and predictive biomarkers with ASL derived CBF. However, progress has been limited by variable image quality, substantial inter-site, vendor and protocol differences, and limited availability of labeled datasets needed to train models that generalize across cohorts. To address these challenges, we introduce ICHOR, a self supervised pre-training approach for ASL CBF maps that learns transferable representations using 3D masked autoencoders. ICHOR is pretrained via masked image modeling using a Vision Transformer backbone and can be used as a general-purpose encoder for downstream ASL tasks. For pre-training, we curated one of the largest ASL datasets to date, comprising 11,405 ASL CBF scans from 14 studies spanning multiple sites and acquisition protocols. We evaluated the pre-trained ICHOR encoder on three downstream diagnostic classification tasks and one ASL CBF map quality prediction regression task. Across all evaluations, ICHOR outperformed existing neuroimaging self-supervised pre-training methods adapted to ASL. Pre-trained weights and code will be made publicly available.
Temporal Modeling of Amyloid and Tau Trajectories in Alzheimer’s Disease Using PET and Plasma Biomarkers

Christopher A. Brown, K. Cousins, M. Korecka, Emily McGrew, Alice S. Chen-Plotkin, John A. Detre, Corey T. McMillan, Edward B. Lee, Sandhitsu R. Das, Dawn Mechanic-Hamilton, Paul Yushkevich, I. Nasrallah, L. Shaw, and D. Wolk

Annals of Neurology, Mar 2026

Cited by 1

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This study aimed to compare positron emission tomography (PET) and plasma‐based temporal modeling of amyloid and tau biomarkers in Alzheimer’s disease.
Temporal Modeling of Amyloid and Tau Trajectories in Alzheimer’s Disease Using PET and Plasma Biomarkers.

C. A. Brown, K. Cousins, M. Korecka, E. McGrew, A. Chen-Plotkin, John A. Detre, Corey T McMillan, Edward B Lee, Sandhitsu R Das, D. Mechanic‐Hamilton, Paul Yushkevich, I. Nasrallah, Leslie M Shaw, and David A. Wolk

Annals of neurology, Mar 2026

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OBJECTIVE This study aimed to compare positron emission tomography (PET) and plasma-based temporal modeling of amyloid and tau biomarkers in Alzheimer’s disease. METHODS Longitudinal amyloid PET (n = 1,097, mean age ± SD = 72.5 ± 7.38 year, 51.4% male), 18F-flortaucipir tau-PET (n = 230, 74.3 ± 7.18 year, 52.2% female), and Fujirebio Lumipulse plasma p-tau217 (n = 752, 72.8 ± 6.93 year, 51.3% male) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and University of Pennsylvania Alzheimer’s Disease Research Center (Penn ADRC) were used to generate biomarker trajectory models using sampled-iterative Local approximation (SILA). SILA models using plasma p-tau217 were compared to amyloid and tau PET-based models to estimate amyloid and tau onset, and factors influencing tau onset and time from tau onset to dementia were evaluated for PET and plasma models. RESULTS Plasma and PET models generated similar results for estimated amyloid and tau onset, with stronger model agreement for tau (r = 0.88[0.86, 0.89], t = 57.4, p < 0.001) than amyloid (r = 0.75[0.72, 0.77], t = 37.4, p < 0.001) onset. Accuracy of estimated onset compared to actual onset was high within modality (mean absolute error [MAE] ≤ 2.03) with slightly greater error (MAE 3.09-3.42) when comparing across modalities (ie, plasma to PET). For both plasma and PET, earlier tau onset was associated with younger amyloid onset, female sex, and ≥1 apolipoprotein (ApoE) ε4 allele. Earlier dementia onset after tau was associated with later tau onset for both plasma and PET, while male sex was associated with shorter tau to dementia gap in plasma models. INTERPRETATION Temporal modeling of plasma biomarkers provides comparable information to PET-based models, particularly for tau onset age, and can serve as a widely accessible tool for clinical assessment of biological disease severity. ANN NEUROL 2026.
Discordance of Dopaminergic Dysfunction and Subcortical Atrophy by α‐Synuclein Status in Sporadic and Genetic Parkinson’s Disease

M. T. Duong, Sandhitsu R. Das, Pulkit Khandelwal, Joaquin A. Vizcarra, Yue Li, Long Xie, Paul Yushkevich, L. M. Shaw, J. Dubroff, A. Siderowf, D. Wolk, and I. Nasrallah

Movement Disorders, Jan 2026

Cited by 4

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Parkinson’s disease (PD) is characterized by predominantly neuronal α‐synuclein pathology and dopaminergic dysfunction. Cerebrospinal fluid (CSF) seeding amplification assays (SAA) detect α‐synuclein aggregates in vivo, but not all patients with PD have a positive SAA. This pathological heterogeneity among patients may not be entirely captured by binary results from α‐synuclein SAA positivity (S+) versus negativity (S–). To further dissect this biological variability, we explored spatial neuroimaging differences in S+ versus S– patients.
Discordance of Dopaminergic Dysfunction and Subcortical Atrophy by α-Synuclein Status in Sporadic and Genetic Parkinson’s Disease.

M. Duong, Sandhitsu R. Das, Pulkit Khandelwal, Joaquin A Vizcarra, Yue Li, L. Xie, Paul Yushkevich, L. Shaw, J. Dubroff, Andrew D Siderowf, D. Wolk, and I. Nasrallah

Movement disorders : official journal of the Movement Disorder Society, Jan 2026

Cited by 1

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BACKGROUND Parkinson’s disease (PD) is characterized by predominantly neuronal α-synuclein pathology and dopaminergic dysfunction. Cerebrospinal fluid (CSF) seeding amplification assays (SAA) detect α-synuclein aggregates in vivo, but not all patients with PD have a positive SAA. This pathological heterogeneity among patients may not be entirely captured by binary results from α-synuclein SAA positivity (S+) versus negativity (S-). To further dissect this biological variability, we explored spatial neuroimaging differences in S+ versus S- patients. OBJECTIVE The study aim was to investigate how SAA status influences imaging measures of dopamine denervation and atrophy. METHODS We compare SAA status with CSF proteinopathy markers, 123I-Ioflupane dopamine transporter (DAT), and magnetic resonance imaging (MRI) in participants with sporadic (n = 490), LRRK2-associated (n = 158), and GBA-associated (n = 80) PD from the Parkinson’s Progression Markers Initiative (PPMI). RESULTS Between 64% and 95% of participants in these groups have S+ status. For all groups, S+ participants have decreased putamen DAT neurotransmission compared to S- participants, whereas S- participants have reduced MRI volume in basal ganglia structures relative to S+ participants. With striatal DAT/MRI ratios, S+ participants have disproportionately lower putamen DAT uptake relative to atrophy. In exploratory analyses, participants with cognitive impairment or hyposmia are associated with worse DAT/MRI discordance. By CSF markers, S- participants with sporadic PD have higher CSF pTau181/amyloid-β42 ratio, suggesting Alzheimer’s copathology. CONCLUSIONS S+ patients exhibit more dopaminergic deficit, whereas S- patients have more subcortical atrophy across sporadic and genetic PD. Together, our findings reveal structure/function and DAT/MRI discordance, providing insight into biomarkers and pathophysiology of synucleinopathy and PD. © 2026 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Deep learning enhanced ALPS reveals genetic and environmental factors of brain glymphatic function

Chang-jun Lin, Hao Wu, W. Xian, Yifan Zheng, Wenxuan Du, Xinyi Chen, Jinxia Li, Weineng Chen, Lishan Lin, Fengjuan Su, Zhong Pei, Ganqiang Liu, Michael W. Weiner, P. Aisen, Ron Petersen, C. Jack, W. Jagust, Susan M. Landau, M. Rivera-Mindt, Ozioma C. Okonkwo, Leslie M. Shaw, Edward B. Lee, A. Toga, L. Beckett, Danielle J Harvey, Robert C. Green, A. Saykin, K. Nho, R. Perrin, Duygu Tosun, P. Sachdev, T. Montine, Cat Conti, Michael W. Weiner, R. Nosheny, J. Fockler, Melanie J Miller, W. Kwang, Chengshi Jin, Adam Diaz, Miriam Ashford, M. Rafii, Rema Raman, G. Jimenez, Michael Donohue, J. Salazar, Andrea Fidell, Virginia Boatwright, Justin Robison, Caileigh N. Zimmerman, and 450 more authors

eBioMedicine, Jan 2026

Cited by 4

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Summary Background The glymphatic system plays a critical role in brain waste clearance and health. Diffusion tensor imaging along the perivascular space (DTI-ALPS) is an emerging approach to assess glymphatic function, but manual analysis is limited by its subjectivity and laboriousness in clinical practice. To address these challenges, we developed a deep learning-enhanced DTI-ALPS (dALPS) method that automates and enhances measurement of DTI-ALPS in large-scale cohorts, enabling us to uncover its genetic and environmental determinants. Methods We proposed an automated workflow combining convolutional neural network (CNN) and You Only Look Once (YOLO) for region-of-interest detection in DTI images. Using this method, we calculated dALPS index for over 65,000 participants from UK Biobank and multiple cohorts, and performed a genome-wide association study (GWAS). Additionally, we conducted transcriptome-wide association study (TWAS) and proteome-wide association study (PWAS) to explore the genetic and molecular underpinnings of glymphatic function. Associations between dALPS and demographic, lifestyle, and clinical traits were comprehensively evaluated. Mediation analysis was conducted to explore the potential mediating role of pharmacological treatments, including antidepressants and sleep medications, in the relationship between disease status and dALPS outcomes. Findings Our automated dALPS index showed excellent reliability and reproducibility compared to conventional manual techniques (intraclass correlation coefficient = 0·95). We observed that the dALPS index was associated with a wide range of body composition measures and brain structures across different age groups and sex. GWAS identified five significant genetic loci associated with dALPS, two of which were replicated in an independent dataset. Subsequent TWAS and PWAS analyses highlighted potential causal genes and proteins linked to brain fluid dynamics. We found that higher healthy lifestyle index (HLI) was positively correlated with improved dALPS, and confirmed the associations between reduced dALPS and various central nervous system (CNS) disorders, including depression, anxiety and neurodegenerative diseases. Notably, mediation analysis indicated that antidepressants were a risk factor for lower brain glymphatic function (P = 0·004) by partly mediating the risk factor of depression. Interpretation The dALPS analysis provides a reliable, precise, and automated biomarker for assessing brain glymphatic function. Our findings illuminate the genetic and environmental determinants of glymphatic activity, underscoring the potential of dALPS in clinical assessment, disease prediction and targeted therapeutic strategies. Funding G.L.’s work is supported by 10.13039/501100001809National Natural Science Foundation of China (No. 32470708, No. 32270701), 10.13039/501100017607Shenzhen Fundamental Research Program (JCYJ20240813151132042), Young Talent Recruitment Project of Guangdong (2019QN01Y139), Shenzhen Key Laboratory for Systems Medicine in Inflammatory Diseases (ZDSYS20220606100803007) and The Science and Technology Planning Project of Guangdong Province (2023B1212060018). Z.P.’s work is supported by National Natural Science Foundation of China (No. 82271266) and The Shenzhen Medical Research Fund (C2501030).
Hippocampal Volume and Brain Tau Pathology in Opioid Use Disorder: Associations with Non-Fatal Opioid Overdose

Delaney McKinstry, Zhen-Hao Shi, A. Ramos-Rolón, Jeffrey Phillips, Sandhitsu R. Das, Xin-Yi Li, Nathan M. Hager, T. Pond, Nora D. Volkow, Henry R. Kranzler, J. Dubroff, I. Nasrallah, and C. Wiers

Addiction neuroscience, Jan 2026

Cited by 4

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Opioid use disorder (OUD) is associated with high rates of overdose (OD)-related morbidity and mortality. OD can cause hypoxic-ischemic injury to oxygen-sensitive brain regions such as the hippocampus. Post-mortem studies show Alzheimer’s disease-like hyperphosphorylated tau pathology in the brains of individuals with OUD. Neurocognitive impairments in individuals with OUD may reflect incipient dementia and contribute to poor clinical outcomes. Alternatively, OUD and OD could be independent risk factors for Alzheimer’s disease. To date, no study has evaluated the effects of non-fatal ODs or chronic OUD on hippocampal volume and tau deposition in the human brain in vivo. To fill this gap, we examined hippocampal volumes in OUD individuals (n=60) and healthy controls (HC, n=30) using T1-weighted magnetic resonance imaging (MRI). We found lower bilateral hippocampal volumes in OUD patients than HCs (p<0.001), but no differences between OUD individuals with a history of OD and those without (NOD) (p=0.92). We measured brain tau deposition using Positron Emission Tomography (PET) with [18F]PI-2620 in n=4 HC, n=4 OUD-NOD, and n=4 OUD-OD individuals, and found no difference in brain tau between groups. Functional MRI assessment of episodic memory showed no differences in memory performance or hippocampal activity between groups, although OUD-OD individuals had poorer performance than HC with a medium effect size (d=0.56). In summary, we confirm prior findings of smaller hippocampal volumes in participants with OUD than in HC. However, with a limited sample size, our findings do not show evidence of brain tau deposition in OUD participants with or without OD histories.

2025

Alzheimer’s Imaging Consortium.

Amanda Annettesdotter, N. Spotorno, A. Wuestefeld, N. Mattsson-Carlgren, O. Strandberg, R. Ossenkoppele, E. Stomrud, S. Palmqvist, D. Wolk, O. Hansson, and L. Wisse

Alzheimer’s & dementia : the journal of the Alzheimer’s Association, Dec 2025

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BACKGROUND A considerable portion of patients with amnestic mild cognitive impairment (aMCI) have negative amyloid-β (Aβ) biomarkers and are therefore unlikely to have Alzheimer’s disease (AD). Potential causes of cognitive decline in this heterogeneous group include limbic-predominant age-related TDP-43 encephalopathy (LATE), cardio/cerebrovascular diseases, primary age-related tauopathy (PART), and subthreshold Aβ. The prognosis of Aβ-negative (Aβ-) aMCI patients, putatively more benign, is unclear. We aim to investigate which predictors - including demographics, baseline cognition, fluid and imaging biomarkers - can best predict cognitive decline and progression to dementia in Aβ- aMCI. METHOD We included 140 Aβ- aMCI patients (Aβ status based on cerebrospinal fluid (CSF) and positron emission tomography, when available; ’amnestic’ based on norm scores for AD Assessment Scale delayed word recall) from BioFINDER-1/2 with longitudinal Mini-Mental State Examination (MMSE), and subsets with longitudinal data on Clinical Dementia Rating Sum of Boxes (CDR-SB; n = 67) and progression to dementia (n = 134, 43% progressors; Table 1). Predictors included global and regional atrophy measures, specific for LATE and PART, CSF Aβ42/40 and p-tau181, hypertension, white matter hyperintensities and global cognition. Individual MMSE and CDR-SB slopes were estimated with linear mixed-effects models. Associations of predictors with MMSE/CDR-SB slopes and progression to dementia were tested. Significant predictors and demographic variables were included in the model selection process using R package MuMIn, which tests linear combinations of variables and ranks models by the Akaike information criterion (AIC). RESULTS Figure 1 shows individual associations for the identification of significant predictors for the model selection process. For MMSE (AIC: 350.57; Figure 2a), the selected most parsimonious model included baseline MMSE and whole-brain cortical thickness. For CDR-SB (AIC: 176.73; Figure 2b), baseline CDR-SB, amygdala volume, and middle frontal gyrus cortical thickness were included. For progression to dementia (AIC: 97.65; Figure 2c), the selected model included MMSE, lateral ventricles volume, entorhinal and whole-brain cortical thickness, sex and CSF Aβ42/40. CONCLUSIONS Baseline cognition, global and regional atrophy measures are valuable predictors of cognitive decline in Aβ- aMCI, with regional brain measures hinting at specific pathologies. These prediction models are relevant for the new LATE clinical criteria. We aim to validate our findings in ADNI.
Epigenetic age acceleration is faster in Black adults and is associated with plasma amyloid

R. Boyle, Hao Xu, K. Cousins, Nadia Dehghani, C. Morse, Anurag Verma, Leslie M. Shaw, L. Massimo, Wanding Zhou, D. Wolk, C. Mcmillan, and P. Biobank

Alzheimer’s & Dementia, Dec 2025

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We have previously reported accelerated epigenetic aging in Black individuals relative to White counterparts in a population‐based cohort which further associates with increased cognitive impairment and decline. However, the extent to which this disparity relates to AD in unclear. In a diverse and real‐world clinical dataset, we examined whether there are disparities in accelerated epigenetic aging across self‐identified Black and White adults and the extent to which it associates with AD plasma biomarkers.
Evaluation of Copathology and Clinical Trajectories in Individuals With Tau-Clinical Mismatch

Christopher A. Brown, N. S. Mundada, K. Cousins, Niyousha Sadeghpour, Xueying Lyu, Emily McGrew, M. Korecka, Alice S. Chen-Plotkin, Long Xie, L. Wisse, John A. Detre, C. Mcmillan, Edward B. Lee, I. Nasrallah, Sandhitsu R. Das, Dawn Mechanic-Hamilton, Paul Yushkevich, L. M. Shaw, and D. Wolk

JAMA Neurology, Dec 2025

Cited by 10

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This cohort study investigates if tau-clinical mismatch identifies individuals with copathology and differing clinical trajectories.
Fully individualized models for cross-sectional and longitudinal network-based tau spread

Christopher A. Brown, Sandhitsu R. Das, John A. Detre, I. Nasrallah, Paul Yushkevich, C. Mcmillan, and D. Wolk

Imaging Neuroscience, Dec 2025

Cited by 1

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Abstract Heterogeneity in regional tau burden limits evaluation of disease progression using one-size-fits-all approaches. Prior work using tau positron emission tomography (PET) has highlighted the important role of connectivity to epicenters of tau pathology in explaining this heterogeneity. However, previous studies using population-based epicenters or connectomes fall short of a fully individualized approach to predicting regional tau burden. We use diffusion MRI-derived structural connectomes to assess the prediction of regional tau burden using distance along individual structural connectomes from individualized epicenters of tau pathology both cross-sectionally and longitudinally. Fully individualized models of connectivity and epicenters outperformed models using either population-based connectomes or epicenters in explanation of cross-sectional and longitudinal regional tau burden, improved prediction in validation datasets, and produced stronger single-subject level prediction. Together, these findings demonstrate the power of a fully individualized approach to explain regional tau heterogeneity and provide the strongest in vivo evidence to date for network-based spread of tau pathology.
Microstructural and Water Exchange Alterations in ARIA‐E in a Real‐World Cohort Receiving Anti‐Amyloid Therapy

Christopher A. Brown, Manuel Taso, Sandhitsu R. Das, Danielle Hing, Emily McGrew, Paul A. Yushkevich, Dawn Mechanic-Hamilton, I. Nasrallah, D. Alsop, John A. Detre, and D. Wolk

Alzheimer’s & Dementia, Dec 2025

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Abstract Background ARIA‐E represents the greatest risk associated with anti‐amyloid therapy (AAT) and is thought to be due to excessive inflammatory response resulting in FLAIR abnormalities on imaging and occasionally symptomatic manifestations. While FLAIR MRI monitoring for ARIA‐E is now routinely performed, additional MRI contrast mechanisms could provide improved detection and mechanistic insights. We investigated perivascular spaces, microstructural alterations, and parenchymal water permeability in a real‐world cohort receiving AAT using novel MRI techniques. Methods Eight participants receiving AAT at the University of Pennsylvania underwent advanced imaging paired with clinical safety MRIs at baseline and during treatment. Advanced imaging sequences included multi‐shell diffusion MRI to assess microstructure, an ultralong TE T2‐weighted sequence to evaluate perivascular spaces structures, and a novel T2‐saturation based water‐exchange sequence. These sequences add <15 minutes to the MRI protocol and can be performed on clinical 3T scanners. We measured microstructure in a composite ROI consisting of cortical regions typically associated with high amyloid deposition as well as in global white matter. Water exchange was calculated specifically in regions that developed ARIA. Results 2 patients developed ARIA‐E after 2 months of treatment that prompted suspension of treatment: (1) mild symptomatic case that went on to develop mild ARIA‐H at 3 months with resolution of ARIA‐E, (2) moderate case that progressed to severe ARIA‐E at 3 months. At baseline these individuals had lower Neurite Density Index (NDI) and Orientation Dispersion Index (ODI) compared to no ARIA (ARIA‐) patients (Figure 1). At 2 months, they had marked increases in NDI and ODI that resolved by 3 months (Figure 2A). In contrast, there was gradual increase in water exchange and white matter free water fraction (FWF) at 2 and 3 months compared to ARIA‐ (Figure 2B). ARIA‐E and ARIA‐H is also readily visualized on water exchange sensitive maps (Figure 3). Quantification of perivascular volume is ongoing. Conclusion Measures of water diffusion and exchange enhance our understanding of ARIA with findings consistent with transient increases in cellularity at ARIA onset and prolonged increases in parenchymal water permeability and edema. Early results suggest microstructure could predict risk for future ARIA. Additional data collection continues.
Tau Cognitive Mismatch in Alzheimer’s Disease Predicts Presence of Co‐Pathology and Diverging Disease Trajectory

Christopher A. Brown, Sandhitsu R. Das, K. Cousins, Long Xie, Emily McGrew, M. Korecka, T. Tropea, Alice S. Chen-Plotkin, John A. Detre, C. Mcmillan, Eddie B. Lee, I. Nasrallah, Paul Yushkevich, Dawn Mechanic-Hamilton, L. M. Shaw, and D. Wolk

Alzheimer’s & Dementia, Dec 2025

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Abstract Background The revised Alzheimer’s disease staging criteria use the concept of biological‐clinical mismatch with an expected, canonical progression; identifying individuals who have greater clinical impairment than expected for their biological stage as vulnerable or less impairment than expected as resilient. Here we used T1 (plasma p‐tau217) and T2 (18F‐flortaucipir PET) biomarkers to identify mismatch with global clinical severity measured by the CDR‐SB scale. We then investigated differences in brain structure, alpha synuclein positivity, and longitudinal trajectories of cognition, tau accumulation, and atrophy between canonical, vulnerable and resilient groups. Methods Amyloid positive ADNI participants with available Tau PET (n = 373) or p‐tau217 (n = 392) and CDR‐SB score were included. Mismatch was defined using linear regression between global measures of tau burden, using a composite score of PET binding intensity and extent (Tau‐MaX) or p‐tau217, and CDR‐SB to divide individuals into canonical, vulnerable, and resilient groups. We investigated differences in medial temporal lobe (MTL) structure measured using T1‐ASHS, brain‐wide thickness differences using ANTs, and α‐synuclein status measured with CSF seed amplification assay after controlling for age, sex, education, and global tau burden. We examined longitudinal tau PET, atrophy, and cognitive trajectories between mismatch groups using linear mixed models controlling for age, sex, education, and global tau burden. Finally, we applied the mismatch model generated in ADNI to our local Penn ADRC dataset (n = 160) for replication. Results Both Tau‐MaX and p‐tau217 were moderately associated with CDR‐SB (Figure 1A). Vulnerable individuals had greater neurodegeneration in anterior MTL and temporolimbic regions compared to canonical and resilient groups (Figure 1B‐C), as well as higher prevalence of α‐synuclein co‐pathology (Figure 1D). The vulnerable group showed accelerated cognitive decline even after controlling for rate of tau accumulation, which minimally differed by group (Figure 2A). Vulnerable participants also had accelerated atrophy in MTL and temporolimbic regions (Figure 2B‐C). Results in the Penn ADRC dataset (Figure 3A) were consistent with the ADNI dataset findings (Figure 3B‐D). Conclusions Tau‐cognitive mismatch identifies vulnerable individuals who are more likely to have α‐synuclein co‐pathology and neurodegeneration patterns that overlap with LATE. The plasma‐based models also successfully identified similar vulnerable individuals in an independent dataset.
Electronic Health Records to Test Multimorbidity Influences to Plasma Biomarker Interpretation for Alzheimer’s Disease

K. Cousins, R. Boyle, C. Morse, Anurag Verma, Christopher A. Brown, Kyra S. O’Brien, M. Serper, Nadia Dehghani, C. Mcmillan, Edward B. Lee, L. Shaw, and D. Wolk

Annals of Neurology, Dec 2025

Cited by 4

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Plasma biomarkers of Alzheimer’s disease (AD) pathology are frequently tested in specialized research settings, which limits the generalizability of findings. Using electronic health records and banked plasma, we evaluated plasma biomarkers—phosphorylated tau 217 (p‐tau217), β‐amyloid 1–42/1–40 (Aβ42/Aβ40) and p‐tau217/Aβ42—in a real‐world, diverse clinical population with multimorbidities.
Electronic Health Records to Test Multimorbidity Influences to Plasma Biomarker Interpretation for Alzheimer’s Disease

K. Cousins, R. Boyle, Colleen Morse, Anurag Verma, Christopher A. Brown, Kyra S O’Brien, M. Serper, Nadia Dehghani, C. Mcmillan, Edward B. Lee, L. Shaw, and David A. Wolk

Annals of neurology, Dec 2025

Cited by 4

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Plasma biomarkers of Alzheimer’s disease (AD) pathology are frequently tested in specialized research settings, which limits the generalizability of findings. Using electronic health records and banked plasma, we evaluated plasma biomarkers—phosphorylated tau 217 (p‐tau217), β‐amyloid 1–42/1–40 (Aβ42/Aβ40) and p‐tau217/Aβ42—in a real‐world, diverse clinical population with multimorbidities.
Developing Topics.

Sandhitsu R. Das, Christopher D. Brown, P. Cook, Emily McGrew, Danielle Hing, James C. Gee, I. Nasrallah, Dawn Mechanic-Hamilton, Paul Yushkevich, and D. Wolk

Alzheimer’s & dementia : the journal of the Alzheimer’s Association, Dec 2025

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BACKGROUND Paradoxical reductions in brain volume in individuals with Alzheimer’s disease treated with anti-amyloid therapy have been reported in clinical trials. It has been hypothesized that these changes could partly be attributed to processes related to the clearance of amyloid plaques. Further, the presence of amyloid-related imaging abnormalities (ARIA) has been associated with greater ventricular expansion in clinical trials of anti-amyloid immunotherapy, and may also be an important factor driving brain volume loss. Here we measure longitudinal changes from structural MRI during the course of anti-amyloid treatment in brain regions known to accumulate amyloid plaques and ask whether these regions show differences in observed changes depending on presence of ARIA. METHOD We analyzed 125 MRI images from 45 patients undergoing surveillance scanning during the course of lecanemab therapy. Average duration between the earliest and latest scans was 181 days. For each patient, images were included if from an identical MRI protocol and scanner. Measures of gray matter thickness in 100 brain regions were obtained using an unbiased longitudinal pipeline. Regions were nominally dichotomized into amyloid-accumulating and non-amyloid-accumulating based on composite regions used for determining amyloid positivity from PET imaging. Thickness was analyzed using linear mixed effects model that included time and presence of ARIA (ARIA-E or ARIA-H) as explanatory variables and age and sex as nuisance covariates. RESULT Both amyloid-accumulating and non-amyloid-accumulating regions showed thinning during the treatment period. However, there was a significant interaction between time and ARIA status only in amyloid-accumulating regions such that patients with ARIA showed greater observed thinning. Hippocampal volume also showed a decrease over time, but there was no effect of presence of ARIA. CONCLUSION These data show that presence of ARIA may play a role in observed brain parenchymal changes during anti-amyloid treatment. The specificity of the effects in amyloid-accumulating brain regions point to an interaction between amyloid clearance and the emergence of ARIA as confounding factors in measuring longitudinal change. While the underlying mechanism remains unclear, better characterization of such effects can help disentangle their influence on MRI-based measures of change and ultimately improve the usability of MRI as a marker for tracking potential treatment effects.
Brain telomere length associates with hippocampal ptau and is mediated by DNA methylation

Nadia Dehghani, Qi-Jun Chen, Anil R. Wadhwani, David C. Goldberg, Jin Jin, Lasya P. Sreepada, I. Leone, Angelina Jala, D. Wolk, Eddie B. Lee, Kurt Farrell, J. Crary, Wanding Zhou, F. B. Johnson, C. Mcmillan, and Part Working Group

Alzheimer’s & Dementia, Dec 2025

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Telomeres are repetitive DNA sequences at the ends of chromosomes which contribute to maintaining chromosomal stability. Telomere shortening is a hallmark of aging and shorter blood leukocyte telomere length (LTL) has been associated with increased risk for age‐related diseases, however, little is understood about the biology of brain telomeres and how they may be involved in disease. Considering the increased neuropathologic burden of phosphorylated tau (ptau) with age, we investigated how shorter brain telomere length (brain‐TL) may relate to increased ptau burden.
Exploring the Influence of SSDOH and Self‐Identified Race on Resilience and Vulnerability using Machine Learning for NACC UDS

E. Fischer, Zahra Khodakarami, Christopher A. Brown, Dawn Mechanic-Hamilton, Paul Yushkevich, Sandhitsu R. Das, and D. Wolk

Alzheimer’s & Dementia, Dec 2025

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Current cognitive analysis methods in neurodegenerative disease rely on the use of individual neuropsychological assessments, which can be subject to variation and bias. A potentially more robust way to represent cognitive status is to use a cognitive age model to predict an individual’s age from their cognitive assessment scores and demographics. This modeling allows for identification of individuals exhibiting resilience or vulnerability to normal aging processes across diverse datasets.
Integrating individualized connectome with amyloid pathology improves predictive modeling of future cognitive decline

Hengda He, Q. Razlighi, Y. Gazes, C. Habeck, Y. Stern, Michael W. Weiner, P. Aisen, Ronald Petersen, C. Jack, W. Jagust, Susan M. Landau, M. Rivera-Mindt, Ozioma C. Okonkwo, Leslie M. Shaw, Edward B. Lee, A. Toga, Laurel A. Beckett, Danielle J. Harvey, Robert C. Green, A. Saykin, K. Nho, R. Perrin, D. Tosun, P. Sachdev, Erin Drake, T. Montine, Cat Conti, R. Nosheny, D. T. Sacrey, J. Fockler, Melanie J. Miller, Winnie Kwang, Cheng-Shi Jin, Adam Diaz, Miriam Ashford, D. Flenniken, Adrienne Kormos, M. Rafii, Rema Raman, Gustavo Jimenez, Michael Donohue, Jennifer Salazar, Andrea Fidell, Virginia Boatwright, Justin Robison, Caileigh N. Zimmerman, Yuliana Cabrera, Sarah Walter, T. Clanton, E. Shaffer, and 112 more authors

Communications Medicine, Dec 2025

Cited by 3

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The deposition of amyloid-β (Aβ) in the human brain is a hallmark of Alzheimer’s disease and is associated with cognitive decline. Aβ pathology is traditionally assessed at the whole-brain level across neocortical regions using positron emission tomography (PET). However, these measures often show weak associations with future cognitive impairment. A more sensitive pathology metric is needed to quantify early Aβ burden and better predict cognitive decline. Here, we aim to develop a network-based metric of Aβ burden to improve early prediction of cognitive decline in aging populations. We integrated subject-specific brain connectome information with Aβ-PET measures to construct a network-based metric of Aβ burden. Cross-validated predictive modeling was used to evaluate the performance of this metric in predicting longitudinal cognitive decline. Furthermore, we identified a neuropathological signature pattern linked to future cognitive decline, and we validated this pattern in an independent cohort. Our results demonstrate that incorporating individualized structural connectome, but not functional connectome, information into Aβ measures enhances predictive performance for prospective cognitive decline. The identified neuropathological signature pattern is reproducible across cohorts. These findings advance our understanding of the spatial patterns of Aβ pathology and its relationship to brain networks, highlighting the potential of connectome-informed network-based metrics for Aβ-PET imaging in identifying individuals at higher risk of cognitive decline. Amyloid-β peptide is a molecule that is known to accumulate in the brains of people with Alzheimer’s disease. This accumulation starts to occur many years before the symptoms of Alzheimer’s disease, such as memory problems. Current methods to image the brain for amyloid-β peptide usually measure the overall level across the whole brain. In this study, we developed a more sensitive and personalized measure of amyloid-β by also considering how the different parts of a person’s brain are connected. We found that this approach improves the ability to predict future changes in cognition compared to the standard method. Our method might enable earlier identification of people at risk of developing Alzheimer’s disease, which could improve monitoring and treatment. He et al. develop a network-based metric of amyloid-β burden by integrating individualized brain connectomes with amyloid-PET imaging. This approach improves prediction of future cognitive decline in older adults and may support earlier identification of individuals at risk of dementia.
High‐resolution postmortem 7 tesla MRI yields localized atrophy measures that are more sensitive to tau pathology and neuronal loss in Alzheimer’s disease than corresponding measures on antemortem 3 tesla MRI

Pulkit Khandelwal, M. T. Duong, Lisa Levorse, Sydney A. Lim, Amanda E. Denning, Nathaniel Gauthier, Ved Shenoy, W. Trotman, R. Ittyerah, A. Bahena, T. Schuck, M. Gabrielyan, K. Prabhakaran, Daniel T. Ohm, G. Mizsei, John L. Robinson, L. Wisse, John A. Detre, Eddie B. Lee, David J. Irwin, C. Mcmillan, M. Tisdall, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2025

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Abstract Background Postmortem MRI has opened‐up avenues to study brain structure at ultra high‐resolution revealing details not possible to observe with in vivo MRI. Here, we present a novel package (purple‐mri) which performs tissue segmentation, anatomical parcellation and spatial normalization of postmortem MRI. Additionally, we provide a framework to perform point‐wise surface‐based group‐level studies linking morphometry/histopathology in common coordinate system for postmortem MRI. Method We developed a joint voxel‐ and surface‐based pipeline combining deep learning with classical techniques for topology correction, cortical modeling, inflation, and registration for accurate parcellation of postmortem cerebral hemispheres (Figure 1 Khandelwal et al. 2024). Furthermore, using the GM/WM segmentations derived from postmortem hemisphere and FreeSurfer‐processed antemortem MRI, we performed deformable image registration between the ante‐ and postmortem MRI for each brain specimen. To demonstrate the utility of purple‐mri, point‐wise analysis was performed to correlate thickness (mm) with tau and neuronal loss distribution in corresponding specimens (N = 49) of postmortem (7T at 0.3mm3) and antemortem (3T at 0.8mm3) MRI (Table 1) within the AD continuum diagnosis. An additional 26 postmortem 7T scans without corresponding antemortem scans were included in some analyses. The semi‐quantitative average tau and neuronal loss ratings were derived from histopathological examination across the brain. All analyses include age, sex, and postmortem (or antemortem) interval as covariates. Result Our method parcellates postmortem brain hemisphere using a variety of brain atlases even in areas with low contrast (anterior/posterior regions), profound imaging artifacts and severely atrophied brains (Figure 1). Our registration pipeline provides one‐to‐one correspondence between the two modalities. For thickness/pathology associations (Figure 2), small sparse significant clusters only in superior temporal cortex and precuneus in antemortem MRI (N = 49) were observed. However, postmortem MRI showed much stronger associations across large clusters in temporal, entorhinal cortex, and cingulate for both the matched cases (N = 49) and the full cohort (N = 75), regions implicated in ADRD. Conclusion Purple‐mri paves the way for large‐scale postmortem image analysis. Stronger associations between thickness and average tau burden/neuronal loss than antemortem MRI suggests that our pipeline could inform the development of more precise and sensitive invivo biomarkers by mapping information from postmortem to antemortem MRI in a common reference coordinate system.
Postmortem brain MRI reveals differential associations of subcortical and limbic volumes with cortical thinning and neurodegenerative pathologies

Pulkit Khandelwal, M. T. Duong, Lisa Levorse, W. Trotman, A. Bahena, Sydney A. Lim, Amanda E. Denning, E. Chung, Christopher A. Olm, Hamsanandini Radhakrishnan, R. Ittyerah, K. Prabhakaran, G. Mizsei, T. Schuck, Sheina Emrani, Joaquin A Vizcarra, John L. Robinson, Daniel T. Ohm, J. Phillips, Jesse Cohen, L. Wisse, John A. Detre, I. Nasrallah, Christopher A. Brown, Sandhitsu R. Das, Edward B. Lee, M. Tisdall, David J. Irwin, C. Mcmillan, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2025

Cited by 1

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Introduction The impact of different neuropathologies on deep brain structures remains to be understood. We examine subcortical and limbic volumetry in neurodegenerative diseases involving p-tau, α-synuclein and TDP-43. Methods We acquired neuropathological measures and brain segmentations from postmortem analysis of 132 donors with Alzheimer’s disease (AD), Lewy body disease (LBD), Frontotemporal Lobar Degeneration with TDP-43 (FTLD-TDP) and FTLD-Tau. Results LBD had the least subcortical, limbic and cortical atrophy compared to AD, FTLD-TDP and FTLD-Tau. In donors with both AD and LBD pathologies, primary LBD was associated with less atrophy than primary AD. While AD had cortico-subcortical and cortico-limbic morphometric associations, LBD had more limited parieto-occipital cortico-limbic associations. FTLD-TDP had cortico-subcortical while FTLD-Tau had cortico-subcortical and cortico-limbic associations. In AD and FTLD-Tau, hippocampal volumes correlated with p-tau burden, neuron loss and gliosis. In LBD, thalamic α-synuclein severity was associated with subcortical/limbic volumes. Discussion Postmortem neuroimaging reveals disease- and region-specific structure-pathology relationships.
High‐resolution postmortem 7 tesla MRI yields localized atrophy measures that are more sensitive to tau pathology and neuronal loss in Alzheimer’s disease than corresponding measures on antemortem 3 tesla MRI

Pulkit Khandelwal, M. Duong, Lisa Levorse, Sydney A. Lim, Amanda E Denning, Nathaniel Gauthier, Ved Shenoy, W. Trotman, R. Ittyerah, A. Bahena, T. Schuck, M. Gabrielyan, K. Prabhakaran, Daniel T. Ohm, G. Mizsei, John L. Robinson, L. Wisse, John A Detre, Eddie B. Lee, David J. Irwin, C. Mcmillan, M. Tisdall, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2025

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Postmortem MRI has opened‐up avenues to study brain structure at ultra high‐resolution revealing details not possible to observe with in vivo MRI. Here, we present a novel package (purple‐mri) which performs tissue segmentation, anatomical parcellation and spatial normalization of postmortem MRI. Additionally, we provide a framework to perform point‐wise surface‐based group‐level studies linking morphometry/histopathology in common coordinate system for postmortem MRI.
Segmentation and registration of within‐subject 7 tesla ex vivo and 3 tesla in situ MRI to increase sensitivity of imaging biomarkers

Pulkit Khandelwal, Sydney A. Lim, W. V. D. Berg, Louise Weerd, Paul Yushkevich, and L. Jonkman

Alzheimer’s & Dementia, Dec 2025

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Understanding pathological contribution in mixed etiology dementia and atypical Alzheimer’s disease remains challenging. However, in‐vivo MRI and neuropathology studies are hampered by the years of delay between MRI and brain autopsy. Postmortem in‐situ MRI is a good proxy to mitigate this problem (Frigerio et al. 2021) but is logistically challenging. Ex‐vivo MRI offers significant higher anatomical resolution but is influenced by fixation and possible deformation. Therefore, we propose a whole‐hemisphere ex‐vivo to in‐situ/in‐vivo parcellation and registration pipeline “purple‐mri” (Khandelwal et al. 2024) to cater multi‐resolution, translation, and clinical relevance for T2w 7T 0.3 mm3 exvivo and T1w 3T 1x0.5x0.5 mm3 insitu MRI in 21 (age: 57‐88 years; F=9/M=12) control specimens (Table 1).
Assessing white matter hyperintensities on matched antemortem and postmortem MRI

Zahra Khodakarami, Pulkit Khandelwal, M. T. Duong, Amanda E. Denning, Sydney A. Lim, E. Chung, A. Bahena, K. Prabhakaran, G. Mizsei, T. Schuck, W. Trotman, John L. Robinson, Daniel T. Ohm, A. Brickman, Eddie B. Lee, David J. Irwin, John A. Detre, M. Tisdall, Sandhitsu R. Das, D. Wolk, Paul Yushkevich, and Sheina Emrani

Alzheimer’s & Dementia, Dec 2025

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Abstract Background Postmortem MRI offers superior spatial resolution and contrast compared to antemortem MRI, enabling analysis of pathological processes underlying white matter hyperintensities (WMH). However, its correlation with antemortem WMH remains unclear due to postmortem changes, fixation effects, and tissue dehydration. This study compares WMH burden on antemortem and postmortem MRI in the same individuals to assess the suitability of postmortem MRI for structure‐pathology association studies. Method 7T T2‐weighted postmortem and 3T FLAIR antemortem MRIs were acquired from 41 individuals (Table 1). WMH segmentations were generated using Purple‐MRI for postmortem MRI and WMH‐SynthSeg for antemortem MRI (Figure 1). One hemisphere was scanned postmortem, and the corresponding antemortem hemisphere was used for WMH segmentation. Linear regression models examined (I) Antemortem WMH volume as a predictor of postmortem WMH, (II) age at scan as a predictor of antemortem WMH volume, and (III) age at death as a predictor of postmortem WMH volume. Nuisance covariates included antemortem/postmortem intervals (AMI/PMI) and fixation time, as appropriate. Result Table 1 provides a breakdown of demographics and neuropathological diagnoses. A moderate, statistically significant correlation was found between antemortem and postmortem WMH volume (r = 0.47, p = 0.002;Figure 2), remaining significant after adjusting for age and nuisance covariates (Table 1). Both antemortem and postmortem WMH volumes were significantly associated with age (Table 4 [antemortem MRI] and 3 [postmortem MRI]), with a greater antemortem association in absolute terms (t=2.8 vs. t=2.58, n.s.). Other covariates were not significant. Postmortem WMH volume was, on average, 102±121% higher than antemortem, with only a weak association between their relative difference and AMI (r=0.27, p = 0.04), suggesting that WMH increase is due to greater lesion visibility in postmortem MRI rather than WMH growth. This aligns with histological findings showing WMH‐linked pathology in surrounding normal‐appearing white matter. Conclusion This study highlights both a significant association between antemortem and postmortem WMH volume, and a significant bias towards larger WMH in postmortem MRI, above and beyond factors like AMI and fixation time. In subsequent work, we will use matched MRI and histology to study the contribution of vascular and neurodegenerative pathologies to the extent and appearance of WMH on antemortem and postmortem MRI.
Segmentation of medial temporal lobe subregions in a nearly isotropic space using T2‐weighted MRI with anisotropic resolution

Yue Li, Pulkit Khandelwal, Long Xie, L. Wisse, Nidhi S. Mundada, Christopher A. Brown, Emily McGrew, Amanda E. Denning, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2025

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Abstract Background Morphometry of medial temporal lobe (MTL) subregions in brain MRI is sensitive biomarker to Alzheimer’s Disease and other related conditions. While T2‐weighted (T2w) MRI with high in‐plane resolution is widely used to segment hippocampal subfields due to its higher contrast in hippocampus, its lower out‐of‐plane resolution reduces the accuracy of subregion thickness measurements. To address this issue, we developed a nearly isotropic segmentation pipeline that incorporates image and label upsampling and high‐resolution segmentation in T2w MRI. Method First, a high‐resolution atlas was created based on an existing anisotropic atlas derived from 29 individuals. Both T1‐weighted and T2w images in the atlas were upsampled from their original resolution to a nearly isotropic resolution using a non‐local means approach. Manual segmentations within the atlas were also upsampled to match this resolution using a UNet‐based neural network, which was trained on a cohort consisting of both high‐resolution ex vivo and low‐resolution anisotropic in vivo MRI with manual segmentations (Figure 1a). Second, a multi‐modality deep learning‐based segmentation model was trained within this nearly isotropic atlas (Figure 1b). This method was evaluated on independent sets, including cross‐sectional (N = 196) and longitudinal (N = 31) MRI scans, which were used for the group difference analysis (Amyloid+ mild cognitive impairment (A+MCI) vs. Amyloid‐ cognitively normal (A‐CN)) and longitudinal consistency analysis, respectively (Figure 1c). Result Table 1(a) displays the group differences of cross‐sectional median thickness between A+MCI and A‐CN with age as covariate. The T2w segmentation in isotropic space achieved larger effect sizes in the predicted direction (A+MCI < A‐CN) and outperformed T2w anisotropic segmentation over most subregions. Table 1(b) shows the consistency analysis of longitudinal median thickness. When measured as the sum of absolute median thickness differences, the consistency of isotropic T2w segmentation outperformed that of anisotropic T2w segmentation over most subregions. Figure 2 shows the visualization of the segmentation and point‐wise group difference analysis at different resolutions, with isotropic T2w segmentation demonstrating a smoother surface and larger effect sizes than anisotropic T2w segmentation. Conclusion Nearly isotropic subregion segmentation improved the accuracy of cortical thickness as an imaging biomarker for neurodegeneration in T2w MRI.
Medial temporal lobe Tau‐Neurodegeneration mismatch from MRI and plasma biomarkers identifies vulnerable and resilient phenotypes with AD

Xueying Lyu, Nidhi S. Mundada, Christopher A. Brown, Niyousha Sadeghpour, Emily McGrew, M. T. Duong, Long Xie, M. Dong, Yue Li, I. Nasrallah, L. Wisse, Paul Yushkevich, Sandhitsu R. Das, and D. Wolk

Alzheimer’s & Dementia, Dec 2025

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Abstract Background The heterogeneity of Alzheimer’s disease (AD) and lack of well‐validated markers of non‐AD factors (e.g. TDP‐43) present a substantial challenge for therapeutics. Our prior work showed discordance between tau (T) and neurodegeneration (N) identified non‐AD factors in AD through multi‐modality imaging. Here we tried a simplified approach using plasma ptau217 and medial temporal lobe (MTL) morphometry, given this region’s common association with co‐pathologies, particularly LATE‐NC. Method We included 349 ADNI participants (188 cognitively normal, 161 MCI/dementia) with paired T1‐MRI and plasma ptau217. The MTL was segmented into subregions and further parcellated into 100 bilateral super‐points within regional boundaries. T1‐MRI‐derived thickness and amygdala volume represented N, and plasma p‐Tau217 represented T. T‐N residuals, calculated through regression across super‐points and amygdala, were used for weighted clustering. Result P‐Tau217 showed strong association with MTL atrophy (Figure 1A). Three distinct data‐driven T‐N groups were identified based on mismatch patterns (Figure 1B), including a canonical group (N∼T), a vulnerable group (N>T) with negative residuals primarily in anterior hippocampal and extrahippocampal areas, and a resilient group (N<T) with positive residuals. After clustering, group comparisons were restricted to the AD continuum (i.e. A+). While groups differed in regional volumes (e.g., amygdala), tau severity did not vary (Table 1), suggesting these patterns were not driven by AD pathology. The vulnerable group, displayed greater anterior MTL atrophy aligning with their T‐N residual patterns, while the resilient group had less atrophy in anterior extrahippocampal area (Figure 2A). Outside the MTL, the vulnerable group showed greater anterior limbic atrophy whereas the resilient group showed less (Figure 2B). The T‐N groups differed in Clinical Dementia Rating (CDR) with the vulnerable group having the worst ratings and the resilient group the best (Table 1). Notably, the vulnerable group demonstrated greater baseline memory impairment. Longitudinally, the vulnerable group also declined more severely across multiple cognitive domains while resilient group remained most stable (Figure 2C). Conclusion T‐N mismatch within MTL using MRI and plasma biomarkers revealed groups with varying vulnerability/resilience, with the vulnerable group displaying patterns of atrophy and cognition suggestive of LATE‐NC. It offers a less invasive, cost‐effective method for stratifying individuals for therapeutic interventions.
Monitoring Cognition in Patients Undergoing Anti‐Amyloid Therapies with A Remote App‐Based Digital Cognitive Assessment Tool

Dawn Mechanic-Hamilton, Valerie Humphreys, Danielle Hing, Laura Schankel, Christopher A. Brown, and D. Wolk

Alzheimer’s & Dementia, Dec 2025

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Mobile, valid and engaging cognitive assessments are essential for detecting and tracking change in cognition. With the approval of anti‐amyloid therapies (AATs), there is a need to monitor for both benefits and risks of these therapies. This pilot study aims to determine the feasibility and usability of an at‐home, app‐based cognitive assessment, the mobile cognitive app performance platform (mCAPP), to remotely collect cognitive performance data in a cohort of patients with Mild Cognitive Impairment (MCI) or mild dementia due to Alzheimer’s disease (AD) undergoing AAT.
Technology and Dementia Preconference.

D. Mechanic-Hamilton, Valerie Humphreys, Danielle Hing, Laura Schankel, Christopher A. Brown, and David A. Wolk

Alzheimer’s & dementia : the journal of the Alzheimer’s Association, Dec 2025

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BACKGROUND Mobile, valid and engaging cognitive assessments are essential for detecting and tracking change in cognition. With the approval of anti-amyloid therapies (AATs), there is a need to monitor for both benefits and risks of these therapies. This pilot study aims to determine the feasibility and usability of an at-home, app-based cognitive assessment, the mobile cognitive app performance platform (mCAPP), to remotely collect cognitive performance data in a cohort of patients with Mild Cognitive Impairment (MCI) or mild dementia due to Alzheimer’s disease (AD) undergoing AAT. METHOD mCAPP includes three gamified tasks (Figure 1). Eleven participants with MCI or mild dementia due to AD used mCAPP in the clinic and at home for up to three months while undergoing AAT treatment. They also completed paper and pencil neuropsychological tests and questionnaires about their use of technology and mCAPP usability. Participants included 7 women and 4 men with 15.1±2.6 years of education who were amyloid positive according to either Amyloid PET or cerebrospinal fluid results and deemed eligible for treatment by a multi-disciplinary AAT consensus panel at the University of Pennsylvania. RESULT Participants played the mCAPP tasks in-clinic and consistently engaged in 1-3 sessions per week for up to 3 months at-home. All participants used a smartphone in their daily lives. mCAPP usability rating was 7.1±1.2 (0-9 scale). Most participants rated the difficulty of the tasks as "just right" for Concentration (89%), Brick Drop (78%), and Space Imposters (78%) after playing the games one time. All tasks showed lower performance when comparing low and high cognitive load blocks (p’s<.001). mCAPP measures correlated with some, but not all, paper and pencil measures from analogous domains. An example of one patient’s performance during AAT treatment is shown in Figure 2. CONCLUSION This pilot study shows mCAPP’s usability for both in-clinic and at-home use in a cohort of patients undergoing AAT. Performance across measures indicate initial reliability and validity of mCAPP. Future analyses will include the evaluation of mCAPP performance across multiple timepoints, practice effects compared to participants with unimpaired cognition, and longitudinal data analysis over the course of anti-amyloid treatment.
Clinical Manifestations.

D. Mechanic‐Hamilton, Valerie Humphreys, Danielle Hing, Laura Schankel, Christopher A Brown, and David A. Wolk

Alzheimer’s & dementia : the journal of the Alzheimer’s Association, Dec 2025

DOI
Enrichment of patients with concomitant LATE on the Alzheimer’s disease continuum: comparing structural and cognitive trajectories

Nidhi S. Mundada, Xueying Lyu, Niyousha Sadeghpour, Christopher D. Brown, Emily McGrew, Long Xie, Paul A. Yushkevich, Sandhitsu R. Das, and D. Wolk

Alzheimer’s & Dementia, Dec 2025

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Abstract Background Overlap in clinical presentations, absence of well‐validated in‐vivo biomarkers for Limbic‐predominant age‐related TDP‐43 encephalopathy (LATE), and frequent co‐occurrence with AD, complicates identifying mixed AD/LATE cases. Autopsy studies suggest greater hippocampal atrophy in AD patients with concomitant LATE. We aimed to identify patients along the AD continuum enriched for LATE by defining the lower quartile of hippocampal volume (HV) as a biomarker for possible LATE and explore atrophy patterns and cognitive profiles. Method 164 cognitively impaired participants from ADNI with T1‐MRI and amyloid‐ and tau‐PET within 365 days were grouped based on HV quartiles (adjusted for age/intracranial volume) and amyloid status into suspected 1) AD‐only (HV>50th‐percentile, amyloid‐positive), 2) LATE‐only (HV<25th‐percentile, amyloid‐negative), 3) AD+LATE (HV<25th‐percentile, amyloid‐positive). We used a novel surface‐based pointwise regional thickness analysis framework to examine cross‐sectional and longitudinal atrophy patterns in the medial temporal lobe (MTL) and determine if AD+LATE showed LATE features beyond hippocampal atrophy. We assessed cross‐sectional and longitudinal differences across 4 cognitive domains (memory, executive function, language, visuospatial). Result Suspected‐AD+LATE showed imaging features suggestive of LATE (Figure 1B(II)), lower MMSE, CDR, and HV, but higher ITG‐tau‐SUVR compared to suspected‐AD‐only (Figure 1A). Suspected‐AD‐only showed predominant posterior hippocampal atrophy whereas AD+LATE showed more severe anterior hippocampal and amygdala atrophy (Figure 1B(I)) despite overlapping global tau loads between groups. Patterns of anterior‐posterior atrophy and asymmetry were similar in LATE‐only and AD+LATE (Figure 1B(II)). Cross‐sectionally, AD+LATE showed significantly lower thickness in MTL‐cortex (Figure 2A) compared to AD‐only but primarily in anterior MTL‐cortex when controlling for tau. Longitudinally, LATE‐only showed slower atrophy than AD‐only (stronger effects in Figure 2B(I)>Figure 2B(II)). AD+LATE showed faster atrophy than AD, however, the effect weakened when controlling for tau (Figure 2B(IV‐V). Cross‐sectionally, LATE‐only and AD+LATE group showed lower memory and language scores than AD‐only, even after controlling for tau (Figure 3A); however, longitudinally, AD+LATE declined faster across all domains, differing from AD‐only when controlling for tau, suggesting a more aggressive disease (Figure 3B). Conclusion Patients in lower quartile of HV on the AD continuum exhibit LATE‐like patterns, suggesting underlying LATE pathology. A simple HV percentile‐based metric may help identify patients with concomitant LATE and AD with potential relevance for clinical trials and anti‐amyloid therapies.
Enrichment of patients with concomitant limbic‐predominant age‐related TDP‐43 encephalopathy (LATE) on the Alzheimer’s disease continuum using hippocampal volume

Nidhi S. Mundada, Xueying Lyu, Christopher A. Brown, Niyousha Sadeghpour, Emily McGrew, Long Xie, P. Cook, J. Gee, Paul Yushkevich, Sandhitsu R. Das, and D. Wolk

Alzheimer’s & Dementia, Dec 2025

Cited by 2

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Clinical overlap between Alzheimer’s disease (AD) and limbic‐predominant age‐related transactive response DNA binding protein 43 (TDP‐43) encephalopathy (LATE), combined with the absence of validated in vivo biomarkers, complicates identification of mixed AD/LATE pathology. We labeled individuals along the AD continuum with suspected concomitant LATE using the lower quartile hippocampal volume (HV) cut‐off and examined associated atrophy and cognitive profiles.
Enrichment of patients with concomitant LATE on the Alzheimer’s disease continuum: comparing structural and cognitive trajectories

N. S. Mundada, X. Lyu, N. Sadeghpour, Christopher D. Brown, E. McGrew, L. Xie, Paul Yushkevich, Sandhitsu R Das, and David A. Wolk

Alzheimer’s & Dementia, Dec 2025

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Overlap in clinical presentations, absence of well‐validated in‐vivo biomarkers for Limbic‐predominant age‐related TDP‐43 encephalopathy (LATE), and frequent co‐occurrence with AD, complicates identifying mixed AD/LATE cases. Autopsy studies suggest greater hippocampal atrophy in AD patients with concomitant LATE. We aimed to identify patients along the AD continuum enriched for LATE by defining the lower quartile of hippocampal volume (HV) as a biomarker for possible LATE and explore atrophy patterns and cognitive profiles.
Associations of 18F‐flortaucipir tau PET with quantitative tau histopathology in the medial temporal lobe

J. Phillips, Amanda E. Denning, Lisa Levorse, Christopher A. Brown, L. Wisse, Sanaz Arezoumandan, Sandhitsu R. Das, Eddie B. Lee, R. Insausti, John L. Robinson, R. Ittyerah, Sílvia Porta, C. Mcmillan, Daniel T. Ohm, David J. Irwin, I. Nasrallah, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Dec 2025

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Abstract Background 18F‐Flortaucipir is widely used for positron emission tomography (PET) imaging of Alzheimer’s disease (AD)‐type tau, but its sensitivity in early Braak stages has been questioned, and hippocampal uptake is at least partially confounded by off‐target binding. We investigated associations between antemortem PET uptake and digitally‐quantified tau and TDP‐43 neuropathology. Methods Participants (n = 14, Figure 1) included 5 people with no/low AD neuropathologic change (ADNC) at autopsy, 2 intermediate, and 7 high. Clinical diagnoses included normal cognition (n = 2), AD (n = 5), dementia with Lewy bodies (n = 2), Parkinson’s disease dementia (n = 1), corticobasal syndrome (n = 2), and posterior cortical atrophy (n = 2). We used the Automated Segmentation of Hippocampal Subfields T1 MRI pipeline to segment anterior and posterior hippocampus, Brodmann’s areas (BA) 35 (transentorhinal cortex) & 36, and entorhinal cortex. 18F‐Flortaucipir standardized uptake value ratios (SUVRs) were computed relative to inferior cerebellar grey matter and averaged across hemispheres. Postmortem sampling comprised hippocampal subiculum, CA1, CA2, CA3, and dentate gyrus; BA35 and BA36; and entorhinal cortex. FFPE‐brain tissue was immunostained using PHF1 and phospho‐specific TDP‐43 antibodies and digitally imaged. Two different weakly supervised learning algorithms, Wildcat, were trained to identify tau tangles and threads; or somatic and neuritic phosphorylated TDP‐43 (pTDP‐43) inclusions. Each pathology type was quantified by summary statistics on Wildcat heatmaps, averaged over hippocampal subfields; and over BA35/entorhinal cortex (Denning et al., 2024). We computed non‐parametric correlations between SUVRs and pathology measures at a=0.05 with false discovery rate correction. Results Tangles were associated with SUVRs in BA35/entorhinal cortex (Spearman’s r=0.59, p = 0.029; Figure 2A). The mean hippocampal tangle measure was associated with SUVRs in both anterior (r=0.77, p = 0.002) and posterior (r=0.77, p = 0.002) hippocampus (Figure 2B‐C). Associations between SUVR and tau threads were marginally significant (Figure 2D‐F). In BA35/entorhinal cortex, 9/9 intermediate‐high ADNC cases had SUVRs above an established positivity cutoff of 1.23 (Figure 3). PET SUVRs were not associated with somatic or neuritic pTDP‐43 measures. Conclusion Results suggest 18F‐flortaucipir is sensitive to tau burden in early Braak‐stage regions and primarily reflects neurofibrillary tangles rather than thread‐like tau inclusions.
Clinical correlates of perfusion and diffusion MRI metrics in cognitively unimpaired older adults

Banafsheh Shakibajahromi, S. Dolui, Christopher A. Brown, M. Taghvaei, S. Sadaghiani, Pulkit Khandelwal, Sandhitsu R. Das, Paul Yushkevich, I. Nasrallah, Sharon X. Xie, D. Wolk, and John A. Detre

Journal of Cerebral Blood Flow & Metabolism, Dec 2025

Cited by 2

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Cerebral small vessel disease (CSVD) is associated with vascular risk factors (VRFs) and early executive function (EF) decline. Because periventricular white matter (PVWM) is the most weakly perfused brain region, it may be particularly sensitive to early manifestations of CSVD. Among 101 cognitively unimpaired adults, we assessed the cross-sectional correlations of arterial spin-labeled derived absolute and relative cerebral blood flow (CBF and rCBF, respectively) and diffusion tensor imaging (DTI) metrics in normal-appearing WM (NA-WM) and normal-appearing PVWM (NA-PVWM) with VRFs and EF, and evaluated the mediation and moderation relationships between these variables in amyloid β negative (Aβ−) subjects. CBF, rCBF, and DTI metrics were significantly different in NA-PVWM compared to NA-WM (p < 0.001). In multivariate analysis of the Aβ− group, NA-PVWM rCBF was associated with VRFs (p = 0.012), while NA-PVWM rCBF (p = 0.035) and mean diffusivity (MD) in NA-WM (p = 0.022) and NA-PVWM (p = 0.029) were associated with EF. The association between VRF and EF was not mediated by rCBF and/or MD. However, increased MD was significantly associated with poorer EF for NA-PVWM CBF ⩽16.3 mL/100 g/min and NA-PVWM rCBF ⩽0.35. NA-PVWM rCBF is associated with VRFs and EF and might be an early biomarker for CSVD, especially in the absence of amyloid pathology.
Clinical correlates of perfusion and diffusion MRI metrics in cognitively unimpaired older adults.

Banafsheh Shakibajahromi, Sudipto Dolui, Christopher A. Brown, M. Taghvaei, S. Sadaghiani, Pulkit Khandelwal, Sandhitsu R. Das, Paul Yushkevich, I. Nasrallah, S. Xie, D. Wolk, and John A. Detre

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism, Dec 2025

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Cerebral small vessel disease (CSVD) is associated with vascular risk factors (VRFs) and early executive function (EF) decline. Because periventricular white matter (PVWM) is the most weakly perfused brain region, it may be particularly sensitive to early manifestations of CSVD. Among 101 cognitively unimpaired adults, we assessed the cross-sectional correlations of arterial spin-labeled derived absolute and relative cerebral blood flow (CBF and rCBF, respectively) and diffusion tensor imaging (DTI) metrics in normal-appearing WM (NA-WM) and normal-appearing PVWM (NA-PVWM) with VRFs and EF, and evaluated the mediation and moderation relationships between these variables in amyloid β negative (Aβ-) subjects. CBF, rCBF, and DTI metrics were significantly different in NA-PVWM compared to NA-WM (p < 0.001). In multivariate analysis of the Aβ- group, NA-PVWM rCBF was associated with VRFs (p = 0.012), while NA-PVWM rCBF (p = 0.035) and mean diffusivity (MD) in NA-WM (p = 0.022) and NA-PVWM (p = 0.029) were associated with EF. The association between VRF and EF was not mediated by rCBF and/or MD. However, increased MD was significantly associated with poorer EF for NA-PVWM CBF ⩽16.3 mL/100 g/min and NA-PVWM rCBF ⩽0.35. NA-PVWM rCBF is associated with VRFs and EF and might be an early biomarker for CSVD, especially in the absence of amyloid pathology.
Classifying AD and PART: An Epigenetic Signature of Cognitive Resilience

Anil R. Wadhwani, David C. Goldberg, P. De Jager, David A. A. Bennett, D. Wolk, Eddie B. Lee, Kurt Farrell, J. Crary, Wanding Zhou, and C. Mcmillan

Alzheimer’s & Dementia, Dec 2025

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Whether primary age‐related tauopathy (PART) is a distinct age‐associated disorder or merely a prodrome of Alzheimer’s disease (AD) remains controversial. Both share similar limbic tau but differ in amyloid burden and tau spread. Differential DNA methylation (DNAm) can offers insights into disease biology, biomarkers, and potential therapeutic targets. We therefore used a machine learning classifier trained on DNAm to distinguish PART from AD and then applied the classifier to stratify pathologically‐indeterminate cases.
Deposition patterns of proteinopathies in medial temporal lobe subregions: implications for neuroimaging

L. Wisse, M. Bouwman, A. Wesseling, A. Wuestefeld, Hannah L. Tucker, Daniel T. Ohm, Paul Yushkevich, D. Wolk, and L. Jonkman

Alzheimer’s & Dementia, Dec 2025

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The medial temporal lobe (MTL) is a hotspot for neurodegenerative pathologies and a key region for neuroimaging studies in dementia. A better understanding of proteinopathy deposition patterns would increase the interpretation of neuroimaging measures. We performed a literature review to quantitatively characterize deposition patterns in MTL subregions for six major proteinopathies targeting the MTL.
Associations between Quantitative Neuronal Loss Measures and Postmortem MRI Atrophy Measures in the Human Medial Temporal Lobe in AD and LATE

Paul Yushkevich, S. Ravikumar, L. Wisse, Sydney A. Lim, Lisa Levorse, Amanda E. Denning, R. Ittyerah, P. Clemensson, Niyousha Sadeghpour, K. Prabhakaran, W. Trotman, Maria Mercedes Iniguez Onzono Martin, Esther Buendia, Alicia Vela, M. Muñoz, José Carlos Delgado González, Maria Pilar Marcos Rabal, S. C. Sánchez, Carlos Rosa Prieto, Noemi Villaseca, Daniel T. Ohm, John L. Robinson, T. Schuck, M. Tisdall, David J. Irwin, Eddie B. Lee, Christopher D. Brown, Sandhitsu R. Das, D. Wolk, Maria Mar Arroyo Jimenez, R. Insausti, and A. Insausti

Alzheimer’s & Dementia, Dec 2025

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Abstract Background Medial temporal lobe (MTL) atrophy measured on MRI is a sensitive biomarker of AD‐linked neurodegeneration but is not specific to AD. LATE is a common AD co‐pathology that is challenging to distinguish from AD based on available validated biomarkers. LATE and AD are both associated with hippocampus and entorhinal cortex atrophy, but recent studies suggest that there are differences in the severity and spatial patterns of atrophy. We sought to use postmortem MRI and histology to examine how MRI morphometric measures in AD and LATE relate to direct measures of neurodegeneration, including neuron number, size, and density. Method Thionin‐stained 50µm histology sections from 24 brain donors (5 AD‐LATE‐, 14 AD+LATE‐, 5 AD+LATE+) with available 9.4T postmortem MRI were used to delineate subfields CA1, subiculum and entorhinal cortex. Deep learning method StarDist was used to detect star‐shaped objects in thionine slides, combined with weakly‐supervised learning to identify artifact‐free cortical regions and Gaussian mixture modeling to distinguish neurons from glia (Figure 1AB). Validation against stereology measures of neuronal/glial density was performed in 50 separate regions. Neuronal measures were compared to MTL volume and thickness measures extracted from MRI. Result Automated neuronal density estimates (r=0.72, Figure 1C) agreed with stereology, but not glial density. Estimated number and size of neurons in CA1 and ERC were higher in individuals with less CA1/ERC atrophy (Figure 2) consistent with greater neuronal loss in advanced AD and LATE. However, CA1 neuronal and glial density, and ERC glial density, were higher in individuals with greater atrophy, suggesting tighter packing of neurons in remaining tissue and significant contribution of neuropil loss to MRI‐based atrophy measures. Pointwise analysis in Figure 3 shows patterns of association between regional MTL thickness and CA1 neuronal count, size, and density measures. Conclusion These initial feasibility results in two sections in 24 brain donors encourage us to apply this pipeline to a larger dataset of paired postmortem MRI and serial histology sections (Ravikumar et al., 2024) and to study associations between tau pathology, neuronal loss, and MRI‐based measures of atrophy, with the aim of better differentiating atrophy linked to LATE and AD.
Challenges and best practices when using ComBAT to harmonize diffusion MRI data

Pierre-Marc Jodoin, M. Edde, Gabriel Girard, F’elix Dumais, Guillaume Théaud, M. Dumont, Jean-Christophe Houde, Yoan David, Maxime Descoteaux, Michael W. Weiner, P. Aisen, Ronald Petersen, C. Jack, W. Jagust, Susan M. Landau, M. Rivera-Mindt, Ozioma C. Okonkwo, Leslie M. Shaw, Edward B. Lee, A. Toga, Laurel A. Beckett, Danielle Harvey, Robert C. Green, A. Saykin, K. Nho, R. Perrin, D. Tosun, P. Sachdev, Erin Drake, T. Montine, Cat Conti, R. Nosheny, D. Truran-Sacrey, J. Fockler, Melanie J. Miller, Cat Conti, Winnie Kwang, Cheng-Shi Jin, Adam Diaz, Miriam Ashford, D. Flenniken, Adrienne Kormos, M. Rafii, Rema Raman, Gustavo Jimenez, Michael Donohue, Jennifer Salazar, Andrea Fidell, Virginia Boatwright, Justin Robison, and 114 more authors

Scientific Reports, Nov 2025

Cited by 12

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Over the years, ComBAT has become the standard method for harmonizing MRI-derived measurements, with its ability to compensate for site-related additive and multiplicative biases while preserving biological variability. However, ComBAT relies on a set of assumptions that, when violated, can result in flawed harmonization. In this paper, we thoroughly review ComBAT’s mathematical foundation, outlining these assumptions, and exploring their implications for the demographic composition necessary for optimal results. Through a series of experiments involving a slightly modified version of ComBAT called Pairwise-ComBAT tailored for normative modeling applications, we assess the impact of various population characteristics, including population size, age distribution, the absence of certain covariates, and the magnitude of additive and multiplicative factors. Based on these experiments, we present five essential recommendations that should be carefully considered to enhance consistency and supporting reproducibility, two essential factors for open science, collaborative research, and real-life clinical deployment.
Temporal Modeling of Amyloid and Tau Trajectories in Alzheimer’s Disease using PET and Plasma Biomarkers

Christopher A. Brown, K. Cousins, M. Korecka, Emily McGrew, Alice S. Chen-Plotkin, John A. Detre, C. Mcmillan, Edward B. Lee, Sandhitsu R. Das, Dawn Mechanic-Hamilton, Paul Yushkevich, I. Nasrallah, Leslie M. Shaw, and D. Wolk

medRxiv, Sep 2025

Cited by 2

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Objective: To compare PET and plasma-based temporal modeling of amyloid and tau biomarkers in Alzheimer’s disease Methods: Longitudinal amyloid PET, 18F-flortaucipir tau-PET, and Fujirebio Lumipulse plasma p-tau217 from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and University of Pennsylvania Alzheimer’s Disease Research Center (Penn ADRC) were used to generate biomarker trajectory models using Sampled Iterative Local Approximation (SILA). SILA models using plasma p-tau217 were compared to amyloid and tau PET-based models to estimate tau onset age (ETOA) and estimate amyloid onset age (EAOA), and factors influencing ETOA and time from ETOA to dementia were evaluated for PET and plasma-based models. Results: Plasma-based models generated similar results to PET for EAOA and ETOA, with stronger model agreement for ETOA than EAOA. Accuracy of estimated onset age compared to actual onset age was high within modality with slightly greater error when comparing across modalities (i.e. plasma to PET). For both plasma and PET models, earlier ETOA was associated with younger EAOA, female sex, and [≥]1 ApoE epsilon4 allele. Earlier dementia onset after ETOA was associated with later ETOA for both plasma and PET models, while male sex was associated with shorter tau to dementia gap in plasma models. Interpretation: Temporal modeling of plasma biomarkers provides comparable information to PET-based models, particularly for tau onset age. Plasma-based temporal modeling can serve as a widely accessible tool for clinical assessment of biological disease duration that places the patient on the disease timeline, which may allow for improved discussion of prognosis and treatment decisions.
Achieving detailed medial temporal lobe segmentation with upsampled isotropic training from implicit neural representation.

Yue Li, Pulkit Khandelwal, Rohit Jena, Long Xie, M. T. Duong, Amanda E. Denning, Christopher A. Brown, L. Wisse, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

NeuroImage, Aug 2025

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Imaging biomarkers in magnetic resonance imaging (MRI) are important tools for diagnosing, tracking and treating Alzheimer’s disease (AD). Neurofibrillary tau pathology in AD is closely linked to neurodegeneration and generally follows a pattern of spread in the brain, with early stages involving subregions of the medial temporal lobe (MTL). Accurate segmentation of MTL subregions is needed to extract granular biomarkers of AD progression. MTL subregions are often imaged using T2-weighted (T2w) MRI scans that are highly anisotropic due to constraints of MRI physics and image acquisition, making it difficult to reliably model MTL subregions geometrically and extract morphological measures, such as thickness. In this study, we propose a segmentation framework for MTL subregions in isotropic space, in which an implicit neural representation is used to construct the isotropic training atlas from the anisotropic low-resolution T2w data, with T1w MRI as an auxiliary modality to support the INR and segmentation. In an independent test set, the morphological measures extracted using this isotropic model showed stronger effect sizes than those from models trained on anisotropic data in distinguishing participants with mild cognitive impairment (MCI) from cognitively unimpaired individuals. In the test-retest analysis, the morphological measures extracted using the isotropic model showed greater stability than those from the anisotropic segmentation. This study demonstrates improved reliability of MRI-derived MTL subregion biomarkers without additional atlas annotation effort, which may more accurately quantify and track the relationship between AD pathology and brain atrophy for monitoring disease progression.
Achieving detailed medial temporal lobe segmentation with upsampled isotropic training from implicit neural representation

Yue Li, Pulkit Khandelwal, Rohit Jena, Long Xie, M. Duong, Amanda E Denning, Christopher A. Brown, L. Wisse, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

Aug 2025

Abs arXiv

Imaging biomarkers in magnetic resonance imaging (MRI) are important tools for diagnosing, tracking and treating Alzheimer’s disease (AD). Neurofibrillary tau pathology in AD is closely linked to neurodegeneration and generally follows a pattern of spread in the brain, with early stages involving subregions of the medial temporal lobe (MTL). Accurate segmentation of MTL subregions is needed to extract granular biomarkers of AD progression. MTL subregions are often imaged using T2-weighted (T2w) MRI scans that are highly anisotropic due to constraints of MRI physics and image acquisition, making it difficult to reliably model MTL subregions geometrically and extract morphological measures, such as thickness. In this study, we used an implicit neural representation method to combine isotropic T1-weighted (T1w) and anisotropic T2w MRI to upsample an atlas set of expert-annotated MTL subregions, establishing a multi-modality, high-resolution training set of isotropic data for automatic segmentation with the nnU-Net framework. In an independent test set, the morphological measures extracted using this isotropic model showed stronger effect sizes than models trained on anisotropic in distinguishing participants with mild cognitive impairment (MCI) and cognitively unimpaired individuals. In test-retest analysis, morphological measures extracted using the isotropic model had greater stability. This study demonstrates improved reliability of MRI-derived MTL subregion biomarkers without additional atlas annotation effort, which may more accurately quantify and track the relationship between AD pathology and brain atrophy for monitoring disease progression.
Medial temporal lobe Tau-Neurodegeneration mismatch from MRI and plasma biomarkers identifies vulnerable and resilient phenotypes with AD

Xueying Lyu, N. S. Mundada, Christopher A. Brown, Niyousha Sadeghpour, Emily McGrew, Long Xie, Yue Li, A. Wuestefeld, M. T. Duong, P. Cook, J. Gee, I. Nasrallah, Alice S. Chen-Plotkin, L. M. Shaw, Dawn Mechanic-Hamilton, L. Wisse, Paul Yushkevich, Sandhitsu R. Das, and D. Wolk

medRxiv : the preprint server for health sciences, Aug 2025

Cited by 1

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Enrichment of patients with concomitant LATE on the Alzheimer’s disease continuum using hippocampal volume

N. S. Mundada, Xueying Lyu, Christopher A. Brown, Niyousha Sadeghpour, Emily McGrew, L. Xie, P. Cook, J. Gee, Paul Yushkevich, Sandhitsu Das, and D. Wolk

medRxiv, Aug 2025

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Introduction: Clinical overlap between Alzheimer’s disease (AD) and limbic-predominant age-related TDP-43 encephalopathy (LATE), combined with absence of validated in vivo biomarkers, complicates identification of mixed AD/LATE pathology. We labeled individuals along the AD continuum with suspected concomitant LATE using the lower quartile hippocampal volume (HV) cut-off and examined associated atrophy and cognitive profiles. Methods: We studied cognitively impaired ADNI participants with T1-MRI and amyloid- and tau-PET. Participants were classified into suspected (s) AD+sLATE-, AD-sLATE+, or AD+sLATE+ based on amyloid status and HV quartiles. Medial temporal lobe (MTL) and whole-brain atrophy patterns and cognitive profiles were compared cross-sectionally and longitudinally. Classification was validated in an autopsy cohort. Results: AD+sLATE+ showed greater anterior hippocampal and amygdala atrophy than AD+sLATE-. AD-sLATE+ and AD+sLATE+ showed greater anterior MTL atrophy and worse memory and language performance. AD+sLATE+ also exhibited faster cognitive decline. Discussion: A simple HV quartile cut-off may help identify mixed AD/LATE pathology and support clinical trial enrichment.
A wireless, 60-channel, AI-enabled neurostimulation platform

D. Rizzuto, Haydn G. Herrema, Zhe Hu, Daniel Utin, Josh Kahn, C. Ho, Andrew B. Smiles, Robert E. Gross, Bradley C. Lega, Sandhitsu R. Das, and M. Kahana

bioRxiv, Aug 2025

Cited by 1

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Objective Closed-loop neuromodulatory therapies require devices that can both decode ongoing brain states and deliver multi-site stimulation. Methods We describe the Smart Neurostimulation System (SNS), a cranially mounted implant with 60 configurable recording/stimulation channels, inductive power, and onboard spectral-feature classification. In three freely-moving sheep we streamed local-field potentials and conducted two parameter sweep experiments. Results Cross-validated movement classifiers achieved an average AUC > 0.95. Increasing stimulation amplitude and frequency produced post-stimulation elevations in α-band (8-12 Hz) and γ-band (78-82 Hz) power at most target locations. Conclusion The SNS unifies high-density sensing, real-time brain state decoding, and programmable closed-loop stimulation in a single device, demonstrating behavioral-state prediction and parameter-dependent neuromodulation in vivo. Significance These findings establish a preclinical foundation for biomarker-guided stimulation targeting distributed cortical networks underlying memory and cognition. Highlights Wireless 60-channel implant enables simultaneous sensing and stimulation vine study demonstrates reliable classification of movement and stimulation-related modulation of spectral activity The SNS represents a platform for biomarker-guided neuromodulation therapies
Tau burden is best captured by magnitude and extent: Tau‐MaX as a measure of global tau

Christopher A. Brown, Sandhitsu R. Das, K. Cousins, T. Tropea, Alice-Chen Plotkin, John A. Detre, Paul Yushkevich, C. Mcmillan, Edward B. Lee, Leslie M. Shaw, I. Nasrallah, and D. Wolk

Alzheimer’s & Dementia, Jul 2025

Cited by 9

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Tau burden consists of both spatial spread and local accumulation, but no study has combined these measures into a single metric to capture overall global tau burden. Here we investigate a new measure combining magnitude and extent—Tau‐MaX—as a marker of Alzheimer’s disease (AD) severity.
Tau-Clinical Mismatch Identifies Individuals with Co-Pathology and Predicts Clinical Trajectory

Christopher A. Brown, Nidhi S. Mundada, K. Cousins, Niyousha Sadeghpour, Xueying Lyu, Emily McGrew, Magdalena Korecka, Alice S. Chen-Plotkin, Long Xie, L. Wisse, John A. Detre, C. Mcmillan, Edward B. Lee, I. Nasrallah, Sandhitsu R. Das, Dawn Mechanic-Hamilton, Paul A. Yushkevich, Leslie M. Shaw, and D. Wolk

medRxiv, Jul 2025

Cited by 2

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Importance: The heterogeneous course of Alzheimer’s disease makes it difficult to predict individuals’ cognitive trajectories, which is particularly important in the era of disease modifying therapy. Identifying individuals more likely to have co-pathology and differing disease courses using clinically practical tools remains a critical gap. Objective: To evaluate tau-clinical mismatch for identifying resilient and vulnerable individuals and compare levels of co-pathology and clinical trajectories between groups. Design, Setting, and Participants: Participants were selected from the Alzheimer’s Disease Neuroimaging Initiative (ADNI, inclusion from 2005-2024), Penn Alzheimer’s Disease Research Center Cohort (Penn-ADRC, inclusion from 2002-2025), and Penn Anti-amyloid Therapy Monitoring (Penn-ATM) cohort (inclusion from 2024-2025). All participants were amyloid-beta positive, had clinical assessment, and measures of Tau-PET or plasma p-tau217 available. Exposures: Clinical assessment (CDR-SB) and tau burden (tau-PET or p-tau217) for mismatch group classification. Main Outcomes and Measures: Cross-sectional measures of neurodegeneration (medial temporal lobe volume and thickness, cortical thickness, TAR DNA-binding protein 43 [TDP-43] imaging signature), -synuclein cerebrospinal fluid seed-amplification assay, longitudinal CDR-SB Results: 365 ADNI Tau-PET participants (ages 55-93, 52.6% women) and 524 ADNI p-tau217 participants (ages 56-95, 49.0% women) were used to generate tau-clinical mismatch models with 55.6-57.1% classified as canonical (CDR-SB Tau), 23.7-24.7% as resilient (CDR-SB < Tau), and 19.3-19.7% as vulnerable (CDR-SB > Tau). Groups showed diverging clinical courses with earlier cognitive impairment seen in vulnerable groups and later impairment in resilient groups. Vulnerable groups showed higher frequencies of co-pathology, with TDP-43 neurodegeneration patterns and -synuclein positivity. Similar findings were seen when applying these models to an independent dataset of 244 individuals (54-92 age, 57.0% women) in Penn-ADRC. Finally, these models were applied to a cohort receiving anti-amyloid therapy to show the utility of this method for predicting individual cognitive trajectories during therapy. Conclusion and Relevance: Tau-clinical mismatch identifies individuals more likely to harbor co-pathology and have diverging clinical trajectories. Plasma-based models produced similar results to Tau-PET models and could be replicated in independent datasets. These models provide an important tool that can be implemented in clinical practice to provide improved individualized prognosis and, potentially, monitoring of response to disease-modifying therapy.
Relationships of PGRN with sTREM2 in AD continuum and non-AD pathophysiology and their reciprocal roles in modulating amyloid pathology: two population-based study

Liang-Yu Huang, Chen-Chen Tan, Wei Xu, Lan Tan, Michael W. Paul Ronald Clifford R. William John Q. Arthur Weiner Aisen Petersen Jack Jagust Trojanowki Toga, Michael W. Weiner, P. Aisen, Ron Petersen, C. Jack, W. Jagust, J. Trojanowki, A. Toga, L. Beckett, Robert C. Green, A. Saykin, John C. Morris, R. Perrin, L. Shaw, M. Carrillo, W. Potter, L. Barnes, M. Bernard, H. González, Carole Ho, John K. Hsiao, Jonathan Jackson, E. Masliah, Donna Masterman, Ozioma C. Okonkwo, R. Perrin, Laurie Ryan, N. Silverberg, A. Fleisher, J. Fockler, Cat Conti, D. Veitch, J. Neuhaus, Chengshi Jin, R. Nosheny, Miriam Ashford, D. Flenniken, A. Kormos, G. Jimenez, Michael Donohue, D. Gessert, J. Salazar, Caileigh N. Zimmerman, Y. Cabrera, Sarah Walter, G. Miller, and 409 more authors

Translational Psychiatry, Jul 2025

Cited by 5

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Progranulin (PGRN) and soluble triggering receptor expressed on myeloid cells-2 (sTREM2) are emerging biomarkers of Alzheimer’s disease (AD). This study explores the roles of their interplay in modulating amyloid pathology. We analyzed data from 905 participants (mean age = 62.0) in the CABLE cohort and 973 participants (mean age = 73.1) in the ADNI, classified using the A/T/N biomarker framework. One-way ANOVA was used to assess whether cerebrospinal fluid (CSF) PGRN and sTREM2 differed across biomarker profiles and clinical stages. Multiple linear regression models and linear mixed-effects models were used to test the relationships among PGRN, sTREM2, and CSF Aβ1–42 levels. Mediation analysis was used to explore the reciprocal relationships between sTREM2 and PGRN in influencing amyloid pathology. CSF proteomic and bioinformatic analyses were finally used to investigate the underlying biological mechanisms. In both cohorts, PGRN and sTREM2 were higher in individuals within the TN+ profile irrespective of the A status, and followed similar trajectory across different clinical and biomarker stage. CSF PGRN was associated with higher sTREM2 across AD continuum and non-AD pathophysiology. Bidirectional mediation was observed between PGRN (14.6% in CABLE, 15.6% in ADNI) and sTREM2 (29.7% in CABLE, 33.5% in ADNI) in modulating Aβ pathology (p < 0.0001). Proteomic analysis identified 1539 CSF proteins (Bonferroni-corrected p < 7.13 × 10−6) simultaneously associated with PGRN, sTREM2, and Aβ1–42. These proteins are mainly enriched in immune processes and neural plasticity. These findings suggest that the interplay between lysosome function and microglia-related neuroinflammation plays key roles in amyloid metabolism.
Tau, atrophy, and domain‐specific cognitive impairment in typical Alzheimer’s disease

A. Wuestefeld, Long Xie, Emily McGrew, Alexa Pichet-Binette, N. Spotorno, D. Westen, N. Mattsson-Carlgren, Paul Yushkevich, Sandhitsu R. Das, D. Wolk, and L. Wisse

Alzheimer’s & Dementia, Jul 2025

Cited by 10

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A granular understanding of the mechanisms linking tau pathology to cognitive decline in Alzheimer’s disease is crucial. We investigate mediating effects of medial temporal lobe (MTL) and neocortical neurodegeneration on tau‐induced domain‐specific cognitive impairment in amyloid‐beta (Aβ) positive cognitively normal and impaired adults.
White Matter Abnormalities and Cognition in Aging and Alzheimer Disease

C. Peter, A. Sathe, N. Shashikumar, Kimberly R. Pechman, Abigail W. Workmeister, T. B. Jackson, Yuankai Huo, S. Mukherjee, J. Mez, L. Dumitrescu, K. Gifford, C. Bolton, Leslie S. Gaynor, S. Risacher, Lori L. Beason-Held, Yang An, K. Arfanakis, G. Erus, C. Davatzikos, D. Tosun-Turgut, Mohamad Habes, Di Wang, A. Toga, Paul M. Thompson, Panpan Zhang, K. Schilling, Marilyn S. Albert, Walter W. Kukull, Sarah A. Biber, B. Landman, B. Bendlin, Sterling C. Johnson, J. Schneider, L. Barnes, David A. Bennett, A. Jefferson, Susan M. Resnick, A. Saykin, P. K. Crane, M. Cuccaro, T. Hohman, D. Archer, O. Adegoke, P. Aisen, L. Apostolova, Miriam Ashford, L. Barnes, L. Beckett, M. Bernard, H. Bernhardt, and 293 more authors

JAMA Neurology, Jun 2025

Cited by 46

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Key Points Question What is the association between white matter microstructure and cognitive performance and decline in aging and Alzheimer disease (AD)? Findings In this large, multicohort prognostic study of 4467 participants and 9208 longitudinal cognitive sessions, white matter free water was associated with cognitive performance and decline, especially memory. Limbic tracts (eg, cingulum, fornix) were most strongly associated across domains, and abnormal AD endophenotypes (eg, SPARE-AD index, APOE ε4 status, amyloid positivity) exacerbated cognitive decline. Meaning White matter microstructural changes were associated with cognitive decline, emphasizing their role in aging and AD assessment; interaction models support a multimodal approach to improve the prediction of cognitive decline.
Biological age acceleration in Alzheimer’s disease modulates relative cortical to medial temporal lobe neurodegeneration

Lasya P. Sreepada, Christopher A. Brown, Sandhitsu R. Das, Paul Yushkevich, D. Wolk, and C. Mcmillan

Neurobiology of aging, Jun 2025

Cited by 4

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Alzheimer’s disease (AD) is highly associated with aging, typically presenting with amnestic, multi-domain cognitive impairment and greater medial temporal lobe (MTL) atrophy relative to cortex. However, approximately 15 % of AD cases present atypically, often at younger ages and with greater cortical involvement relative to MTL. This association between age and AD presentation is imperfect: some younger-onset cases are typical, amnestic presentations while some older-onset cases present less typically. We hypothesize that this discordance may be partially modulated by discordance between chronological age and biological age, defined epigenetically. Participants from the Alzheimer’s Disease Neuroimaging Initiative with MRI and known amyloid status were selected (n = 1011, 44.4 % female, 75.33 ± 7.28 years) and classified as amyloid-negative, cognitively unimpaired (n = 329) or amyloid-positive, symptomatic individuals with mild cognitive impairment or dementia (n = 682). Biological age was estimated in individuals with DNA methylation (n = 448) using established epigenetic clocks. Biological age gap (BAG) was calculated to categorize individuals into “accelerated” (biological age > chronological age) or “decelerated” (biological age < chronological age) groups. We define the Cortico-Medial Temporal index (CoMeT), derived from MRI, to quantify age-adjusted relative differences between cortical and MTL structures. Lower CoMeT scores indicate relatively greater cortical involvement. BAG and CoMeT were significantly correlated (Pearson R=0.13, p = 0.023). Symptomatic individuals with decelerated BAG exhibited significantly lower CoMeT scores than individuals with accelerated BAG, with a large effect size, reflecting greater cortical involvement relative to MTL (Wilcoxon p = 0.023, rank-biserial correlation=−0.98). We conclude that biological aging modulates AD presentation beyond chronological age, providing novel insights into mechanisms underlying AD heterogeneity.
Biological age acceleration in Alzheimer’s disease modulates relative cortical to medial temporal lobe neurodegeneration.

Lasya P. Sreepada, Christopher A. Brown, Sandhitsu R. Das, Paul Yushkevich, D. Wolk, and C. Mcmillan

Neurobiology of aging, Jun 2025

Abs DOI

Alzheimer’s disease (AD) is highly associated with aging, typically presenting with amnestic, multi-domain cognitive impairment and greater medial temporal lobe (MTL) atrophy relative to cortex. However, approximately 15 % of AD cases present atypically, often at younger ages and with greater cortical involvement relative to MTL. This association between age and AD presentation is imperfect: some younger-onset cases are typical, amnestic presentations while some older-onset cases present less typically. We hypothesize that this discordance may be partially modulated by discordance between chronological age and biological age, defined epigenetically. Participants from the Alzheimer’s Disease Neuroimaging Initiative with MRI and known amyloid status were selected (n = 1011, 44.4 % female, 75.33 ± 7.28 years) and classified as amyloid-negative, cognitively unimpaired (n = 329) or amyloid-positive, symptomatic individuals with mild cognitive impairment or dementia (n = 682). Biological age was estimated in individuals with DNA methylation (n = 448) using established epigenetic clocks. Biological age gap (BAG) was calculated to categorize individuals into "accelerated" (biological age > chronological age) or "decelerated" (biological age < chronological age) groups. We define the Cortico-Medial Temporal index (CoMeT), derived from MRI, to quantify age-adjusted relative differences between cortical and MTL structures. Lower CoMeT scores indicate relatively greater cortical involvement. BAG and CoMeT were significantly correlated (Pearson R=0.13, p = 0.023). Symptomatic individuals with decelerated BAG exhibited significantly lower CoMeT scores than individuals with accelerated BAG, with a large effect size, reflecting greater cortical involvement relative to MTL (Wilcoxon p = 0.023, rank-biserial correlation=-0.98). We conclude that biological aging modulates AD presentation beyond chronological age, providing novel insights into mechanisms underlying AD heterogeneity.
Operationalizing postmortem pathology-MRI association studies in Alzheimer’s disease and related disorders with MRI-guided histology sampling

Chinmayee Athalye, A. Bahena, Pulkit Khandelwal, Sheina Emrani, W. Trotman, Lisa Levorse, Zahra Khodakarami, Daniel T. Ohm, Eric Teunissen-Bermeo, N. Capp, S. Sadaghiani, Sanaz Arezoumandan, Sydney A. Lim, K. Prabhakaran, R. Ittyerah, John L. Robinson, T. Schuck, Edward B. Lee, M. Tisdall, Sandhitsu R. Das, D. Wolk, David J. Irwin, and Paul Yushkevich

Acta Neuropathologica Communications, May 2025

Cited by 8

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Postmortem neuropathological examination, while the gold standard for diagnosing neurodegenerative diseases, often relies on limited regional sampling that may miss critical areas affected by Alzheimer’s disease and related disorders. Ultra-high resolution postmortem MRI can help identify regions that fall outside the diagnostic sampling criteria for additional histopathologic evaluation. However, there are no standardized guidelines for integrating histology and MRI in a traditional brain bank. We developed a comprehensive protocol for whole hemisphere postmortem 7T MRI-guided histopathological sampling with whole-slide digital imaging and histopathological analysis, providing a reliable pipeline for high-volume brain banking in heterogeneous brain tissue. Our method uses patient-specific 3D printed molds built from postmortem MRI, allowing standardized tissue processing with a permanent spatial reference frame. To facilitate pathology-MRI association studies, we created a semi-automated MRI to histology registration pipeline and developed a quantitative pathology scoring system using weakly supervised deep learning. We validated this protocol on a cohort of 29 brains with diagnosis on the AD spectrum that revealed correlations between cortical thickness and phosphorylated tau accumulation. This pipeline has broad applicability across neuropathological research and brain banking, facilitating large-scale studies that integrate histology with neuroimaging. The innovations presented here provide a scalable and reproducible approach to studying postmortem brain pathology, with implications for advancing diagnostic and therapeutic strategies for Alzheimer’s disease and related disorders.
Streamlining 4D Cardiac Image Workflows: Open-Source Tools for Segmentation, Registration, and Visualization

Jilei Hao, Paul Yushkevich, Ningjun J. Dong, Silvani Amin, Zaiyang Guo, N. Yushkevich, Ankush Aggarwal, and Alison M. Pouch

Functional imaging and modeling of the heart : ... International Workshop, FIMH ..., proceedings. FIMH (Conference), May 2025

Cited by 1

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4D cardiac imaging offers impactful insights into structural heart dynamics. However, analyzing 4D data using conventional 3D software tools requires additional effort. This paper introduces three natively 4D-optimized software applications we have developed: ITK-SNAP 4 for 4D image I/O, visualization, and segmentation; Greedy Propagation for intra-series registration and creation of 4D segmentation from sparse 3D segmentations; and Scherzo for fast web-based 4D model generation and visualization. These open-source tools provide a streamlined user experience, comprehensive features, and broad file type support including common 4D cardiac image formats. Experiments on core features demonstrate feasibility and consistency.
Medial temporal lobe atrophy in Down syndrome along the Alzheimer’s disease continuum.

B. Buehner, A. Morcillo-Nieto, Sara E. Zsadanyi, M. Rozalem Aranha, J. Arriola-Infante, L. Vaqué-Alcázar, J. Arranz, Í. Rodríguez-Baz, Lucía Maure Blesa, L. Videla, I. Barroeta, L. Hoyo Soriano, B. Benejam, S. Fernández, Aida Sanjuan Hernandez, Núria Bargalló, S. González-Ortiz, S. Giménez, R. Flores, Paul Yushkevich, D. Alcolea, O. Belbin, A. Lleó, M. Carmona-Iragui, J. Fortea, and A. Bejanin

Brain : a journal of neurology, Apr 2025

Cited by 7

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Medial temporal lobe structures are among the first areas impacted by neurofibrillary tangle pathology, making volumetric changes of these areas promising biomarkers for Alzheimer’s disease. To date, little is known about the integrity of these regions in individuals with Down syndrome, a population which almost invariably develops Alzheimer’s disease and thus offers a unique opportunity to determine the earliest structural changes related to the disease. We aimed to characterize the sequential involvement of medial temporal lobe structures with Alzheimer’s disease progression, explore associations with fluid biomarkers of Alzheimer’s pathology, and assess the utility of regional volumes and cortical thickness in distinguishing Alzheimer’s disease clinical stages in Down syndrome. 138 euploid controls and 259 adults with Down syndrome underwent clinical assessment and MRI scanning, followed by automated segmentation of the medial temporal lobe on T1-weighted images. Parametric statistical tests and local regression models were used to assess the cross-sectional association between regional volumes/cortical thickness and Alzheimer’s disease clinical stage, estimated years of onset, and CSF biomarkers. Additionally, markers were assessed in their ability to distinguish clinical stages using area under the receiver-operating characteristic curves. Results showed a progressive loss of volume and cortical thickness in medial temporal lobe with advancing Alzheimer’s disease stage, showing reduced volume/thickness at the dementia stage in all subregions. The asymptomatic and prodromal groups showed significant differences in the anterior and posterior hippocampus. We identified the entorhinal cortex and posterior hippocampus as the regions showing the earliest loss in Down syndrome, starting 13-15 years before Alzheimer’s disease symptom onset. We observed non-linear structural changes with disease progression, with certain structures (e.g., the parahippocampal cortex) characterized by an initial increase in cortical thickness followed by subsequent thinning. Of all subregions, the hippocampal volumes showed the closest correlation to CSF Aβ42/40, pTau181, and neurofilament light chain levels. Further analyses demonstrated a high predictive value, similar to CSF biomarkers, of the hippocampus in differentiating between individuals with asymptomatic versus prodromal/demented Alzheimer’s disease in Down syndrome. This study provides a novel understanding of the progressive, non-linear volumetric changes of medial temporal lobe structures in relation to Alzheimer’s disease pathology in Down syndrome, which can have important implications for clinical trials monitoring neurodegeneration using MRI. We also show that MRI information can refine the prediction of clinical status in Down syndrome. This is particularly relevant in Down syndrome, where early clinical stages can be challenging to detect due to neurodevelopmental intellectual disability.
Imaging Biomarkers for Neurodegenerative Diseases from Detailed Segmentation of Medial Temporal Lobe Subregions on in vivo Brain MRI Using Upsampling Strategy Guided by High-resolution ex vivo MRI

Yue Li, Pulkit Khandelwal, Long Xie, L. Wisse, Amanda E. Denning, Christopher A. Brown, Emily McGrew, Sydney A. Lim, Niyousha Sadeghpour, S. Ravikumar, Ranjit Ittyerah, E. Chung, Daniel T. Ohm, Nidhi S. Mundada, Mar’ia Mercedes ’Iniguez Onzono Mart’in, Mar’ia Mar Arroyo Jim’enez, M. Muñoz, Maria Pilar Marcos Rabal, David J. Irwin, Edward B. Lee, R. Insausti, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

Apr 2025

Abs arXiv

The medial temporal lobe (MTL) is a region impacted extensively and non-uniformly in early stages of Alzheimer’s disease (AD). Regional MTL morphometric measures extracted from magnetic resonance imaging (MRI) are supportive features for the diagnosis of AD and related disorders (ADRD). Different MRI modalities have distinct advantages for MTL morphometry. Anisotropic T2-weighted (T2w) MRI is preferred for hippocampal subfields due to its higher contrast between hippocampal layers. Isotropic T1-weighted (T1w) MRI is beneficial for thickness calculation of extra-hippocampal subregions due to its stable image quality and isotropic resolution. We propose a multi-modality MTL segmentation algorithm that bridges the T1w and T2w modalities by bringing both to a nearly isotropic voxel space. Guided by high-resolution ex vivo 9.4T MRI, an upsampling model was designed for the ground truth segmentations. Combined with non-local means upsampling, this model was used to construct a nearly iso-tropic T1w and T2w MTL subregion segmentation training set, which was used to train a nnUNet model. Morphometric biomarkers extracted by this model were compared to those extracted using conventional models operating in anisotropic spaces on downstream tasks. Biomarkers extracted using the proposed model had greater ability to discriminate between individuals with mild cognitive impairment and cognitively unimpaired; and had great-er longitudinal stability. These findings suggest that the biomarkers derived from T1w and T2w MRI unsampled to nearly isotropic resolution have sig-nificant potential for improving disease diagnosis and monitoring disease progression in ADRD.
Predicting the progression of MCI and Alzheimer’s disease on structural brain integrity and other features with machine learning

Marthe Mieling, Mushfa Yousuf, Nico Bunzeck, Michael W. Weiner, P. Aisen, Ron Petersen, C. Jack, W. Jagust, Susan M. Landau, M. Rivera-Mindt, L. Shaw, Edward B. Lee, A. Toga, L. Beckett, Danielle J Harvey, Robert C. Green, A. Saykin, K. Nho, R. Perrin, D. Tosun, Erin Drake, T. Montine, Cat Conti, R. Nosheny, D. Sacrey, J. Fockler, Melanie J Miller, W. Kwang, Chengshi Jin, Adam Diaz, Miriam Ashford, D. Flenniken, A. Kormos, M. Rafii, Rema Raman, G. Jimenez, Michael Donohue, J. Salazar, Andrea Fidell, Virginia Boatwright, Justin Robison, Caileigh N. Zimmerman, Y. Cabrera, Sarah Walter, T. Clanton, E. Shaffer, Caitlin Webb, L. Hergesheimer, Stephanie Smith, Sheila Ogwang, and 450 more authors

GeroScience, Apr 2025

Cited by 11

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Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer’s disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, those with mild cognitive impairment (MCI) and AD dementia patients. Features included structural MRI, CSF status, demographics, and genetic data. Analyses comprised one cross-sectional multi-class classification (CN vs. MCI vs. AD dementia, n = 568) and two longitudinal binary-class classifications (CN-to-MCI converters vs. CN stable, n = 92; MCI-to-AD converters vs. MCI stable, n = 378). All classifications achieved 70–77% accuracy and 61–83% precision. Key features were CSF status, hippocampal volume, entorhinal thickness, and amygdala volume, with a clear dissociation: hippocampal properties contributed to the conversion to MCI, while the entorhinal cortex characterized the conversion to AD dementia. The findings highlight explainable, trajectory-specific insights into AD progression. Supplementary Information The online version contains supplementary material available at 10.1007/s11357-025-01626-5.
Effects of APOE Genotypes on Periventricular White Matter Cerebral Blood Flow in Cognitively Intact Adults (P3-3.004)

S. Sadaghiani, M. Taghvaei, S. Dolui, Banafsheh Shakibajahromi, Sandhitsu R. Das, Paul Yushkevich, David Wolk, and John A. Detre

Neurology, Apr 2025

DOI
BOLD amplitude correlates of preclinical Alzheimer’s disease.

S. Hrybouski, Sandhitsu R. Das, Long Xie, Christopher A. Brown, Melissa Flamporis, J. Lane, I. Nasrallah, John A. Detre, Paul Yushkevich, and D. Wolk

Neurobiology of aging, Mar 2025

Cited by 8

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Alzheimer’s disease (AD) is characterized by a long preclinical stage during which molecular markers of amyloid beta and tau pathology rise, but there is minimal neurodegeneration or cognitive decline. Previous literature suggests that measures of brain function might be more sensitive to neuropathologic burden during the preclinical stage of AD than conventional measures of macrostructure, such as cortical thickness. Among studies that used resting-state functional Magnetic Resonance Imaging (fMRI) acquisitions with Blood Oxygenation Level Dependent (BOLD) contrast, most employed connectivity-based analytic approaches. Consequently, little is known about the effects of amyloid and tau pathology on amplitude of intrinsic BOLD signal fluctuations. To address this knowledge gap, we characterized the effects of preclinical and prodromal AD on the amplitude of low-frequency fluctuations (ALFF) of the BOLD signal both at the whole-brain level and at a more granular level focused on subregions of the medial temporal lobe. We observed reduced ALFF in both preclinical and prodromal AD. In preclinical AD, amyloid positivity was associated with a spatially diffuse ALFF reduction in the frontal, medial parietal, and lateral temporal association cortices. In contrast, tau pathology was negatively associated with ALFF in the entorhinal cortex. These ALFF effects were observed in the absence of observable macrostructural changes in preclinical AD and remained after adjusting for structural atrophy in prodromal AD, indicating that ALFF offers additional sensitivity to early disease processes beyond what is provided by traditional structural imaging biomarkers of neurodegeneration. We conclude that ALFF may be a promising imaging-based biomarker in preclinical AD.
Remembering Ricardo Serrano Insausti 1954-2024.

Maria Carmen Lorduy, A. Serrano, M. M. López, L. Wisse, Paul Yushkevich, and D. Amaral

Hippocampus, Mar 2025

DOI
Developing an anatomically valid segmentation protocol for anterior regions of the medial temporal lobe for neurodegenerative diseases

Niyousha Sadeghpour, Sydney A. Lim, A. Wuestefeld, Amanda E. Denning, R. Ittyerah, W. Trotman, E. Chung, S. Sadaghiani, K. Prabhakaran, M. Bedard, DT Ohm, E. Artacho-Pérula, María Mercedes Iñiguez Onzoño Martin, M. Muñoz, F. J. Molina Romero, J. C. Delgado González, María Mar Arroyo Jiménez, M. Rabal, Ana María Insausti Serrano, N. V. González, S. C. Sánchez, C. Rosa Prieto, R. Insausti, Corey T. McMillan, Edward B. Lee, John A. Detre, Sandhitsu R. Das, Long Xie, M. Tisdall, David J. Irwin, D. Wolk, Paul Yushkevich, and L. Wisse

bioRxiv, Feb 2025

Cited by 6

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Background The anterior portion of the medial temporal lobe (MTL) is one of the first regions targeted by pathology in sporadic Alzheimer’s disease (AD) and Limbic-predominant Age-related TDP-43 Encephalopathy (LATE) indicating a potential for metrics from this region to serve as imaging biomarkers. Leveraging a unique post-mortem dataset of histology and magnetic resonance imaging (MRI) scans we aimed to 1) develop an anatomically valid segmentation protocol for anterior entorhinal cortex (ERC), Brodmann Area (BA) 35, and BA36 for in vivo 3 tesla (T) MRI and 2) incorporate this protocol in an automated approach. Methods We included 20 cases (61-97 years old, 50% females) with and without neurodegenerative diseases (11 vs. 9 cases) to ensure generalizability of the developed protocol. Digitized MTL Nissl-stained coronal histology sections from these cases were annotated and registered to same-subject post-mortem MRI. The protocol was developed by determining the location of histological borders of the MTL cortices in relation to anatomical landmarks. Subsequently the protocol was applied to 15 cases twice, with a 2-week interval, to assess intra-rater reliability with the Dice Similarity Index (DSI). Thereafter it was implemented in our in- house Automatic Segmentation of Hippocampal Subfields (ASHS)-T1 approach and evaluated with DSIs. Results The anterior histological border distances of ERC, BA35 and BA36 were evaluated with respect to various anatomical landmarks and the distance relative to the beginning of the hippocampus was chosen. To formulate segmentation rules, we examined the histological sections for the location of borders in relationship to anatomical landmarks in the coronal sections. The DSI for the anterior MTL cortices for the intra-rater reliability was 0.85-0.88 and for the ASHS-T1 against the manual segmentation was 0.62-0.65. Discussion We developed a reliable segmentation protocol and incorporated it in an automated approach. Given the vulnerability of the anterior MTL cortices to tau deposition in AD and LATE, the updated approach is expected to improve imaging biomarkers for these diseases.
Tau Burden is Best Captured by Magnitude and Extent: Tau-MaX as a Measure of Global Tau

Christopher A. Brown, Sandhitsu R. Das, K. Cousins, T. Tropea, Alice-Chen Plotkin, John A. Detre, Paul Yushkevich, C. Mcmillan, Edward B. Lee, Leslie M. Shaw, I. Nasrallah, and D. Wolk

medRxiv, Jan 2025

Cited by 9

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Tau exhibits change in both spatial extent and density of pathology along the Alzheimer’s disease (AD) spectrum with each aspect contributing to the overall burden of pathological tau. Nevertheless, studies using Tau PET have measured either magnitude using standardized uptake value ratios (SUVRs) or extent using number of Tau+ regions. We hypothesized that combining these two dimensions into a single measure of Magnitude and eXtent, Tau-MaX, would provide improved quantification of global tau burden as well as allowing for a region-agnostic measure of global tau burden that does not require a pre-specified region of interest (ROI) or meta-ROI. To test this hypothesis, we analyzed 18F-flortaucipir PET scans from local and national consortium data (n=1077 participants total) and used Gaussian-mixture models for data from 64 brain regions, to define both tau positivity and magnitude. We examined cross-sectional and longitudinal change in Tau-MaX across the Alzheimer’s disease (AD) spectrum and compared the association of Tau-MaX, magnitude, and extent with plasma p-tau217 and global cognition. We also compared Tau-MaX using a global, region-agnostic approach to temporal lobe or Braak stage meta-ROIs. Whereas separate assessments of extent and magnitude across the disease spectrum found earlier increases in Tau spatial extent and later increases in magnitude, Tau-MaX was able to dynamically capture this shift demonstrating a stronger association with extent in the preclinical stage and a stronger association with magnitude in clinical stages. Global Tau-MaX differed between disease stages cross-sectionally and changed over time in all stages of disease. Further, Tau-MaX significantly improved associations with plasma p-tau217 and global cognition compared to magnitude or extent alone. Finally, global measures of Tau-MaX performed similarly to meta-ROI measures of Tau-MaX. Together, these findings indicate that combining magnitude and extent provides a robust measure of global tau burden that changes throughout the disease course and is associated with blood-based biomarkers and cognition. This measure may be of particular use for disease staging, as well as serving as an outcome measure to monitor response to therapeutic intervention.
Fully automated segmentation of the locus coeruleus: application to assess the effects of age, sex and education

R. Flores, T. Blanchard, E. Foyard, M. Naveau, N. Delcroix, L. Chauveau, B. Landeau, D. Vivien, Paul Yushkevich, G. Chételat, and Medit-Ageing Research Group

medRxiv, Jan 2025

Cited by 1

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Background:Locus coeruleus (LC) imaging using neuromelanin-sensitive (NM) MRI sequences is a promising biomarker for detecting early Alzheimer’s Disease (AD) and Parkinson’s Disease (PD). Although semi or fully automatic approaches have been developed to estimate LC integrity by measuring its intensity, these techniques most often rely on a single template built in a standardized space and/or depend on a number of voxels to be accounted that is defined a priori. Thus, these algorithms make it impossible to perform direct volumetric analyses and do not properly account for inter-individual anatomical variability. To fill this gap, our aim was to develop a new multi-atlas fully automated segmentation method using the Automatic Segmentation of Hippocampal Subfields (ASHS) software. A second aim was to investigate the effects of age, sex and education on LC intensity and volume. Method: We used cross-sectional data from 101 cognitively unimpaired older adults (mean age: 73.8+/-6.6 years; mean education: 13.2+/-3.0 years; 58 women, 43 men) from the Age-Well randomized controlled trial for whom high-resolution NM-MRI (T1-w with magnetization transfer; 0.3x0.3x0.75mm3) and standard T1-w MRI (1x1x1mm3) were available. The LC were manually segmented in 30 randomly selected participants on NM-MRI, and the standard T1-w MRI, NM-MRI and bilateral segmentations were fed into the ASHS training pipeline to generate a new atlas (ASHS-LC). ASHS-LC was applied to the 71 remaining subjects to segment the LC and we assessed the effects of age, sex and education on both i) LC intensity (normalized by the intensity of the pons) and ii) LC volume (normalized by the total intracranial volume). Result: Five-fold cross-validation experiments revealed high accuracy of the automatic segmentation relative to manual segmentation (Dice coefficient 0,83+/-0,04). ICCs demonstrated excellent reliability for intensity (ICC = 0.99), whereas reliability for volume was lower (ICC = 0.43). LC intensity was significantly higher in women than in men (Cohen’s d = 0.94, p < 0.001) while no associations with age (beta = -0.0002, p = 0.98) or education (beta = 0.11, p = 0.37) were found. In contrast, LC volume was not different between men and women (Cohen’s d = 0.10, p= 0.55) but was significantly negatively associated with age (beta = -0.25, p = 0.04) and education (beta = -0.27, p = 0.04). Lastly, LC intensity and volume were not statistically correlated, neither using manual segmentation (atlas set: beta = 0.05, p = 0.78) nor ASHS segmentation (atlas set: beta = 0.11, p = 0.57; analysis set: beta = -0.07, p = 0.55). Conclusion: Overall, this new method allows to automatically and accurately segment the LC and offers the opportunity to measure its integrity both in terms of intensity and volume. This is of importance since these two metrics may offer complementary insights into LC integrity, as evidenced by the differing influences of demographic factors on LC intensity and volume.
A multi‐cohort study of longitudinal and cross‐sectional Alzheimer’s disease biomarkers in cognitively unimpaired older adults

Long Xie, Sandhitsu R. Das, Yue Li, L. Wisse, Emily McGrew, Xueying Lyu, Michael Dicalogero, Ujashi Shah, Ademola Ilesanmi, Amanda E. Denning, Christopher A. Brown, Jesse S. Cohen, Lasya P. Sreepada, M. Dong, Niyousha Sadeghpour, Pulkit Khandelwal, R. Ittyerah, S. Ravikumar, S. Sadaghiani, S. Hrybouski, R. Flores, Eli Gibson, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jan 2025

Cited by 15

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The generalizability of neuroimaging and cognitive biomarkers in their sensitivity to detect preclinical Alzheimer’s disease (AD) and power to predict progression in large, multisite cohorts remains unclear.
VIOLET: Volumetric Image registration via Optimization and Learning for Efficient image Translation

Pulkit Khandelwal, M. T. Duong, Lisa Levorse, Sydney A. Lim, Nathaniel Gauthier, Ved Shenoy, E. Chung, Amanda E. Denning, A. Bahena, W. Trotman, Christopher A. Olm, Hamsanandini Radhakrishnan, R. Ittyerah, K. Prabhakaran, G. Mizsei, T. Schuck, John L. Robinson, Daniel T. Ohm, Jeffrey S. Phillips, John A. Detre, Edward B. Lee, David J. Irwin, Corey T. McMillan, M. Tisdall, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

In SASHIMI@MICCAI 2025, Jan 2025

Cited by 1

DOI

2024

A harmonized, histology‐based protocol for selection of medial temporal lobe cortical subregion ranges on magnetic resonance imaging

Jenna N. Adams, H. Baumeister, Thanh P. Doan, A. Maass, N. Mazloum-Farzaghi, Tammy T. Tran, A. Wuestefeld, Jean C. Augustinack, Song‐Lin Ding, R. Insausti, O. Kedo, Arnold Bakker, D. Berron, K. Canada, V. Carr, M. A. Dalton, Ana.M. Daugherty, R. Flores, R. La Joie, Susanne G. Mueller, R. Olsen, C. Stark, Lei Wang, L. Wisse, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2024

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The medial temporal lobe (MTL) has distinct cortical subregions that are differentially vulnerable to pathology and neurodegeneration in diseases such as Alzheimer’s disease. However, previous protocols for segmentation of MTL cortical subregions on magnetic resonance imaging (MRI) vary substantially across research groups, and have been informed by different cytoarchitectonic definitions, precluding consistent interpretations. The Hippocampal Subfields Group aims to create a harmonized, histology‐based protocol for segmentation of MTL cortical subregions that can reliably be applied to T2‐weighted MRI with high in‐plane resolution.
Mapping local and distal effects of different neuropathologies on amygdala volume

Amanda Annettesdotter, Katja Selezneva, Amanda E. Denning, A. Wuestefeld, S. Ravikumar, R. Ittyerah, Lisa Levorse, M. Bedard, E. Chung, John L. Robinson, T. Schuck, Eddie B. Lee, Sydney A. Lim, W. Trotman, A. Bahena, David J. Irwin, María Mar Arroyo Jiménez, Alicia Vela, Esther Buendia, Maria Mercedes Iniguez Onzono Martin, M. Rabal, M. Muñoz, N. Spotorno, O. Hansson, R. Insausti, Paul Yushkevich, and L. Wisse

Alzheimer’s & Dementia, Dec 2024

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The amygdala is a hotspot for neuropathologies; however, it is unclear 1) which neuropathologies lead to amygdala neurodegeneration, 2) what specific amygdala subnuclei are affected, and 3) if the neuropathologies related to amygdala volume are local (inside the amygdala), or distal (in other regions). We investigate the relationships between different neuropathologies (tau, amyloid‐β [Aβ], α‐synuclein [α‐syn], and transactive response DNA‐binding protein 43 [TDP‐43]) and amygdala volumes.
Automated Neurofibrillary tangle detections in digital histopathology sections of the brain

Sanaz Arezoumandan, Eric Teunissen-Bermeo, N. Capp, Jamila Zablah, Daniel T. Ohm, J. Phillips, C. Mcmillan, Eddie B. Lee, D. Wolk, Paul A. Yushkevich, and David J. Irwin

Alzheimer’s & Dementia, Dec 2024

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Alzheimer’s disease (AD) is the most common neurodegenerative disease, and it is characterized by aggregation of misfolded proteins in the brain. Intraneuronal accumulation of tau pathology form neurofibrillary tangles (NFT) in AD. The assessment of the severity of intraneuronal inclusions holds significance in studying the clinicopathological associations in neurodegenerative diseases. Using machine learning methods, we have developed an automated tool to detect NFTs in immunohistochemically stained sections.
NFT maturation and tau mediated neurodegeneration in Alzheimer’s disease with concomitant LATE

Sanaz Arezoumandan, Sheina Emrani, N. Capp, Daniel T. Ohm, J. Phillips, C. Mcmillan, Eddie B. Lee, D. Wolk, and David J. Irwin

Alzheimer’s & Dementia, Dec 2024

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Limbic predominant age‐related TDP‐43 encephalopathy (LATE) is a common co‐pathology in Alzheimer’s disease (AD) and is associated with advanced cognitive impairment and severe atrophy in limbic regions. In AD, various maturation stages for tau neurofibrillary tangles have been characterized and can be selectively marked by monoclonal tau antibodies, providing insight into disease progression. Indeed, AD tau pathology progresses from an early “paperclip” conformation, marked by the MC1 epitope to a C‐terminally truncated form of tau, marked by MN423 epitope. Moreover, MC1‐reactive inclusions in AD largely take the form of pre‐tangles/threads and are less prominent in patients with more advanced AD, where there is a higher burden of MN423‐reactive inclusions that largely take the form of extracellular ghost tangles. In this study we tested the hypothesis that hippocampal tau maturation is more advanced in AD with concomitant LATE compared to the pure AD.
Basic Science and Pathogenesis.

Sanaz Arezoumandan, Eric Teunissen‐Bermeo, Noah Capp, Jamila Zablah, Daniel T. Ohm, J. Phillips, C. Mcmillan, Eddie B. Lee, D. Wolk, Paul Yushkevich, and David J. Irwin

Alzheimer’s & dementia : the journal of the Alzheimer’s Association, Dec 2024

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BACKGROUND Alzheimer’s disease (AD) is the most common neurodegenerative disease, and it is characterized by aggregation of misfolded proteins in the brain. Intraneuronal accumulation of tau pathology form neurofibrillary tangles (NFT) in AD. The assessment of the severity of intraneuronal inclusions holds significance in studying the clinicopathological associations in neurodegenerative diseases. Using machine learning methods, we have developed an automated tool to detect NFTs in immunohistochemically stained sections. METHOD We trained a weakly supervised machine learning algorithm called WildCat to classify inclusions in AT8-stained 6µm sections of the hippocampus and locate areas with high probability of NFTs in the tissue. Next, we utilized the WildCat activation outputs and improved the NFT detections by thresholding and applying morphological filters. Finally, in order to validate our methods, we generated a validation dataset using QuPath software by manually annotating NFTs (N = 600) in 175 × 175µm regions of interest (N = 103). We then tested the correlation between manual and automated measurements to validate our method (Fig. 1). RESULT The WildCat classification model showed outstanding performance by accurately distinguishing NFTs from non-tangle inclusions, achieving high accuracy (97.31%), recall (99.37%), and precision (99.3%). In addition, we tested the correlation between final output of our model with manual measurements of tangles in our validation dataset, where we found strong correlations in tangle counts and tangle percent area-occupied between the two methods (R = 0.84-0.88, p<0.001) (Fig. 1). CONCLUSION Automated tools can reliably generate measurements of NFT density in AD tissue sections. Moreover, this method can be applied to other types of pathologies and may offer a helpful tool for the study of other neurodegenerative diseases.
Operationalizing postmortem pathology‐MRI association studies in ADRD with MRI‐guided histology sampling: does closer proximity lead to stronger associations?

Chinmayee Athalye, Pulkit Khandelwal, A. Bahena, W. Trotman, Daniel T. Ohm, Sheina Emrani, Eric Teunissen-Bermeo, N. Capp, Sydney A. Lim, Lisa Levorse, Amanda E. Denning, R. Ittyerah, T. Schuck, M. Gabrielyan, K. Prabhakaran, G. Mizsei, John L. Robinson, John A. Detre, Eddie B. Lee, David J. Irwin, C. Mcmillan, M. Tisdall, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2024

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Histopathological analysis of autopsied brains is the gold standard of diagnosis in neurodegenerative disorders. Co‐registered histology and MRI scans aid in understanding pathology and structural features. Previous studies focused on the medial temporal lobe (MTL) for atrophy patterns in phosphorylated tau (p‐tau) pathology and in whole hemisphere scans with contralateral semi‐quantitative p‐tau measures. Here, we extend this to study ipsilateral quantitative p‐tau and cortical thickness.
Support for transmission of tau pathology in humans using individualized epicenters and structural connectomes

Christopher D. Brown, Sandhitsu R. Das, I. Nasrallah, John A. Detre, Paul Yushkevich, C. Mcmillan, and D. Wolk

Alzheimer’s & Dementia, Dec 2024

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Population‐based functional connectomes help explain heterogeneity in tau spread in Alzheimer’s disease by demonstrating spread among connected neurons from canonical epicenters. However, if the hypothesis of cell‐to‐cell transmission of tau is correct, individual structural connectomes seeded from individual‐specific epicenters of PET‐tau pathology should improve prediction of regional tau patterns.
Tau Magnitude and eXent–Tau‐MaX: Capturing tau spread and local accumulation provides a robust metric of tau burden

Christopher D. Brown, Sandhitsu R. Das, K. Cousins, T. Tropea, A. Chen-Plotkin, Eddie B. Lee, I. Nasrallah, John A. Detre, Paul Yushkevich, Leslie M. Shaw, and D. Wolk

Alzheimer’s & Dementia, Dec 2024

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Measures of tau burden have typically relied upon measures of magnitude, such as mean standardized uptake value ratio (SUVR), or extent, such as number of tau positive regions. However, heterogenous patterns of tau spread and accumulation present challenges to using these measures in isolation to quantify tau burden. Therefore, we hypothesized that a combined measure of tau magnitude and extent (Tau‐MaX) would outperform either measure in isolation.
Connectivity as a universal predictor of tau spreading in typical and atypical Alzheimer’s disease

H. Bruin, C. Groot, H. Barthel, G. Bischof, R. Boellaard, M. Brendel, D. Cash, W. Coath, Gregory S. Day, B. Dickerson, E. Doering, A. Drzezga, C. Dyck, T. Eimeren, W. M. Flier, Carolyn A. Fredericks, T. Fryer, E. M. Giessen, Brian A. Gordon, J. Graff-Radford, Diana Hobbs, G. Höglinger, Merle Hönig, David J. Irwin, P. S. Jones, K. Josephs, Yuta Katsumi, Eddie B. Lee, Johannes Levin, M. Malpetti, S. McGinnis, A. Mecca, I. Nasrallah, J. T. O’Brien, Ryan S. O’Dell, C. Palleis, R. Perneczky, J. Phillips, Y. Pijnenburg, Deepti Putcha, N. Rahmouni, P. Rosa-Neto, J. Rowe, M. Rullmann, O. Sabri, D. Saur, A. Schildan, J. Schott, M. Schroeter, S. Servaes, and 11 more authors

Alzheimer’s & Dementia, Dec 2024

Cited by 1

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There is a strong link between tau and progression of Alzheimer’s disease (AD), necessitating an understanding of tau spreading mechanisms. Prior research, predominantly in typical AD, suggested that tau propagates from epicenters (regions with earliest tau) to functionally connected regions. However, given the constrained spatial heterogeneity of tau in typical AD, validating this connectivity‐based tau spreading model in AD variants with distinct tau deposition patterns is crucial.
Modelling Small Vessel Disease Using Regional MRI Markers, and Mediating Effects on Cognitive Decline

S. Charisis, T. Rashid, C. Dintica, Mitzi M. Gonzales, Hangfan Liu, Jeffrey B. Ware, T. R. Austin, Paul N. Jensen, Alison E. Fohner, Jordan Tanley, Jing-Zhong Ding, J. Luchsinger, Bonnie C. Sachs, I. Nasrallah, R. Bryan, K. Hayden, D. Wolk, K. Rascovsky, Christos Davatzikos, W. Longstreth, K. Yaffe, S. Seshadri, S. Heckbert, Timothy M. Hughes, and M. Habes

Alzheimer’s & Dementia, Dec 2024

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The location of proposed brain MRI markers of small vessel disease (SVD) might reflect their pathogenesis and may translate into differential associations with cognition. We derived regional MRI markers of SVD and studied: (i) associations with cognitive performance, (ii) patterns most likely to reflect underlying SVD, (iii) mediating effects on the relationships of age and cardiovascular disease (CVD) risk with cognition.
Subject‐Level Segmentation Precision Weights for Volumetric Studies Involving Label Fusion

Christina Chen, Sandhitsu R. Das, M. Tisdall, Feng-Ling Hu, Andrew A. Chen, Paul Yushkevich, D. Wolk, and R. Shinohara

Human Brain Mapping, Dec 2024

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In neuroimaging research, volumetric data contribute valuable information for understanding brain changes during both healthy aging and pathological processes. Extracting these measures from images requires segmenting the regions of interest (ROIs), and many popular methods accomplish this by fusing labels from multiple expert‐segmented images called atlases. However, post‐segmentation, current practices typically treat each subject’s measurement equally without incorporating any information about variation in their segmentation precision. This naïve approach hinders comparing ROI volumes between different samples to identify associations between tissue volume and disease or phenotype. We propose a novel method that estimates the variance of the measured ROI volume for each subject due to the multi‐atlas segmentation procedure. We demonstrate in real data that weighting by these estimates markedly improves the power to detect a mean difference in hippocampal volume between controls and subjects with mild cognitive impairment or Alzheimer’s disease.
Posterior hippocampal sparing in Lewy body disorders with Alzheimer’s copathology: An in vivo MRI study

Jesse S. Cohen, Jeffrey Phillips, Sandhitsu R. Das, Christopher A. Olm, Hamsanandini Radhakrishnan, E. Rhodes, K. Cousins, Sharon X. Xie, I. Nasrallah, Paul Yushkevich, D. Wolk, Edward B. Lee, D. Weintraub, D. Irwin, and C. Mcmillan

NeuroImage : Clinical, Dec 2024

Cited by 5

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Highlights • LBD/AD+ shows a subregion-specific pattern of medial temporal lobe atrophy.• Atrophy severity largely follows expectations from Braak tau stages.• However, posterior hippocampus is spared, deviating from Braak.• Radiopathologic correlation is consistent with tau-dependent neurodegeneration.• MRI in LBD/AD+ could help stratify individuals for therapy trials.
Combining plasma biomarkers for β‐amyloid diagnosis and cognitive prognosis across the clinical spectrum: normal, amnestic, and non‐amnestic

K. Cousins, Jeffrey S. Phillips, Sandhitsu R. Das, Kyra S. O’Brien, T. Tropea, A. Chen-Plotkin, Leslie M. Shaw, I. Nasrallah, D. Mechanic-Hamilton, C. Mcmillan, David J. Irwin, Eddie B. Lee, and D. Wolk

Alzheimer’s & Dementia, Dec 2024

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Alzheimer’s disease (AD) is clinically heterogeneous, and can manifest as amnestic or non‐amnestic dementia, or be pre‐manifest in persons with normal cognition (NormCog). Utility of plasma biomarkers to diagnose AD and prognose cognitive decline must be evaluated in a clinically heterogeneous population representative of the AD spectrum. We investigate pathological and cognitive correlates of plasma phosphorylated tau 181 (p‐tau181), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) across AD and AD‐related dementias (ADRD). We test 1.) if combing biomarkers improves diagnostic accuracy for β‐amyloid (Aβ) in NormCog and impaired cognition (ImpCog), 2.) if Aβ diagnostic accuracy in ImpCog differs by clinical syndrome (amnestic dementia vs. non‐amnestic dementia vs. mild cognitive impairment [MCI]), and 3.) how biomarkers predict future cognitive decline in Aβ+ and Aβ‐.
Association of quantitative measurements of postmortem tau tangle and thread pathology with antemortem cortical thickness measurements in neuropathologically confirmed Alzheimer’s Disease continuum patients

Amanda E. Denning, R. Ittyerah, Niyousha Sadeghpour, Lisa Levorse, E. Chung, Chinmayee Athalye, S. Ravikumar, M. Dong, M. T. Duong, Yue Li, Ademola Ilesanmi, S. Hrybouski, Lasya P. Sreepada, Philip Sabatini, MaKayla Lowe, A. Bahena, Ryohei Watanabe, Boram Kim, R. Flores, John L. Robinson, T. Schuck, Daniel T. Ohm, Sanaz Arezoumandan, R. Insausti, L. Wisse, David J. Irwin, Eddie B. Lee, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2024

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Tau pathology and neurodegeneration in the medial temporal lobe (MTL) are highly associated in Alzheimer’s Disease (AD). However, the spatial pattern of neurodegeneration, contribution of individual tau inclusion types, and influence of MTL co‐pathologies (i.e., TDP‐43) remain poorly understood. Traditional semi‐quantitative ratings or staging schemes of tau pathology capture limited variability in severity and provide no differentiation between inclusion types (i.e., tangles, threads). We correlate semi‐quantitative and quantitative measures of MTL tau pathology from postmortem tissue samples with MTL cortical thickness measures from antemortem MRI.
Mapping Anatomical Boundaries from Histology to Antemortem MRI to Inform Automatic Segmentation of Medial Temporal Lobe Subregions

Amanda E. Denning, Sydney A. Lim, Yue Li, Niyousha Sadeghpour, S. Ravikumar, R. Ittyerah, E. Chung, M. Bedard, K. Prabhakaran, W. Trotman, A. Bahena, Daniel T. Ohm, John L. Robinson, T. Schuck, D. Tisdall, E. Artacho-Pérula, Maria Mercedes Iñiguez Onzoño Martin, M. Muñoz, Francisco Javier Molina Romero, José Carlos Delgado González, María Mar Arroyo Jiménez, M. Rabal, S. C. Sánchez, Carlos Rosa Prieto, Marta Córcoles Parada, David J. Irwin, Eddie B. Lee, Sandhitsu R. Das, D. Wolk, Paul Yushkevich, R. Insausti, and L. Wisse

Alzheimer’s & Dementia, Dec 2024

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The medial temporal lobe (MTL) is the epicenter of both primary and concomitant molecular pathologies in Alzheimer’s disease (AD). The intricate anatomy of the MTL has been the subject of extensive study over the past two centuries. However, current PET and MRI AD biomarkers use often crude parcellations of the MTL that have not been sufficiently validated vis‐à‐vis anatomical ground truth. Here we use a unique dataset of finely annotated serial histology, ex vivo MRI and antemortem 3T in vivo MRI of the MTL from 17 brain donors to train and evaluate an automatic MTL subregion segmentation algorithm. To our knowledge, this is the most comprehensive attempt to infuse MRI biomarkers with cytoarchitectural reference annotations.
Patterns of iron‐rich gliosis in FTLD‐TDP versus FTLD‐Tau

Sheina Emrani, Sanaz Arezoumandan, K. Cousins, N. Capp, Eddie B. Lee, D. Wolk, Paul A. Yushkevich, C. Mcmillan, M. Tisdall, and David J. Irwin

Alzheimer’s & Dementia, Dec 2024

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We recently found region‐specific patterns of iron‐rich gliosis in frontotemporal lobar degeneration (FTLD) groups with tau (FTLD‐Tau; PSP) and TDP‐43 (FTLD‐TDP) pathology using iron‐sensitive MRI of whole‐hemispheres. These patterns largely corresponded to regions of early pathology reported in previous traditional histopathologic staging schemes of protein inclusions for FTLD‐Tau and FTLD‐TDP. Ferritin light chain (FLC) reactivity highlights activated glia but has not been studied extensively in FTLD. We hypothesize neuroinflammation marked by FLC‐reactive glia may relate to protein aggregation and contribute to partially distinct regional patterns of Tau vs TDP‐43 propagation in FTLD.
Multi‐atlas fully automated segmentation of the locus coeruleus in in vivo neuromelanin‐sensitive MRI

R. Flores, T. Blanchard, E. Foyard, M. Naveau, N. Delcroix, B. Landeau, Paul Yushkevich, and G. Chételat

Alzheimer’s & Dementia, Dec 2024

Cited by 1

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Locus coeruleus (LC) imaging using neuromelanin‐sensitive (NM) MRI sequences is a promising biomarker for detecting early Alzheimer’s Disease (AD). Although automatic approaches have been developed to estimate LC integrity by measuring its intensity, these techniques most often rely on a single template built in a standardized space and/or depend on a number of voxels to be accounted that is defined a priori. Thus, these algorithms make it impossible to perform direct volumetric analyses and do not properly account for inter‐individual anatomical variability. To fill this gap, our aim was to develop a new multi‐atlas fully automated segmentation method using the Automatic Segmentation of Hippocampal Subfields (ASHS) software.
BOLD fMRI signal changes in preclinical Alzheimer’s disease

S. Hrybouski, Sandhitsu R. Das, Long Xie, Xueying Lyu, L. Wisse, M. Kelley, J. Lane, Monica Sherin, Michael Dicalogero, I. Nasrallah, John A. Detre, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Dec 2024

Cited by 2

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Previous work suggests functional abnormalities in the human brain in preclinical Alzheimer’s disease. However, little has been explored about the relationship between BOLD fMRI signal amplitude/energy over time and AD pathology. In this work we analyzed the effects of AD progression on amplitude of low‐frequency fluctuations (ALFF) during resting‐state fMRI scans both at the whole‐brain level and at a more granular level, focused on regions of the medial temporal lobe (MTL) that are most vulnerable to AD pathology.
MTL networks are differentially affected by tau pathology

S. Hrybouski, Sandhitsu R. Das, Long Xie, L. Wisse, M. Kelley, J. Lane, Monica Sherin, Michael Dicalogero, I. Nasrallah, John A. Detre, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Dec 2024

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The extent to which pathological processes in aging and Alzheimer’s disease (AD) relate to functional alterations in the medial temporal lobe (MTL)‐dependent brain networks is poorly understood. Here, we examined the relationship between tau accumulation in the (trans)entorhinal cortex and functional connectivity (FC) in two MTL‐affiliated brain networks — the Anterior‐Temporal (AT) and Posterior‐Medial (PM) — in normal agers, individuals with preclinical AD, and patients with symptomatic AD.
Diffuse juxtacortical white matter texture changes in pre‐clinical Alzheimer’s disease

Ademola Ilesanmi, Xueying Lyu, Emily McGrew, Paul Yushkevich, Sandhitsu R. Das, and D. Wolk

Alzheimer’s & Dementia, Dec 2024

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Detection of neurodegeneration during preclinical stages of Alzheimer’s disease (AD) is critical for disease prediction and monitoring. Macrostructural brain changes (volume/thickness) during preclinical AD are often not detectable in cross‐sectional studies. Microstructural changes manifested as alterations in texture features may capture subtle neurodegeneration at this stage. Here we investigated the discriminative ability of texture‐based radiomics features in both gray and juxtacortical white matter in preclinical AD.
High‐resolution 7 tesla postmortem MRI for quantitative analysis of structure‐pathology correlations in neurodegenerative diseases

Pulkit Khandelwal, M. T. Duong, S. Sadaghiani, Sydney A. Lim, Amanda E. Denning, E. Chung, S. Ravikumar, Sanaz Arezoumandan, Claire S. Peterson, M. Bedard, N. Capp, R. Ittyerah, Elyse Migdal, Grace Choi, Emily Kopp, Bridget Loja Patino, Eusha Hasan, Jiacheng Li, A. Bahena, K. Prabhakaran, G. Mizsei, M. Gabrielyan, T. Schuck, W. Trotman, John L. Robinson, Daniel T. Ohm, Eddie B. Lee, J. Trojanowski, C. Mcmillan, M. Grossman, David J. Irwin, John A. Detre, D. Tisdall, Sandhitsu R. Das, L. Wisse, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2024

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Postmortem MRI allows brain anatomy to be examined at high‐resolution linking pathology with morphometric measurements. However, automated methods for analyzing postmortem MRI are not well developed. We present a deep learning‐based framework for automated segmentation of cortical mantle, subcortical structures (caudate, putamen, globus pallidus, and thalamus), white matter hyperintensities (WMH), and normal appearing white matter in (n = 135) postmortem human brain tissue specimens (Table 1) imaged at 0.3 mm3 T2w 7T spanning Alzheimer’s disease and related dementias. We show generalizing capabilities across unseen images acquired at 0.28 mm3 and 0.16 mm3 T2*w 7T FLASH sequence. We report associations between localized cortical thickness and volumetric measurements across key regions and semi‐quantitative neuropathological ratings.
Robust multi‐modality segmentation of medial temporal lobe subregions using both 3‐tesla and 7‐tesla magnetic resonance imaging

Yue Li, Pulkit Khandelwal, Long Xie, Christopher D. Brown, Xueying Lyu, Amanda E. Denning, M. Dong, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2024

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Volumetry of subregions in the medial temporal lobe (MTL) computed from automatic segmentation in MRI can track neurodegeneration in Alzheimer’s disease. However, dropout artifacts are present in some modalities, leading to poor image quality and unreliable segmentation of MTL subregions. Considering that MRI modalities with different field strength offer distinct advantages in imaging different parts of the MTL, we developed a muti‐modality segmentation model using both 7‐tesla (7T) and 3‐tesla (3T) structural MRI to obtain robust segmentation in poor‐quality images.
Event‐based modeling of T‐N mismatch reveals distinct spatio‐temporal trajectories of subtypes with likely co‐pathology in Alzheimer’s disease

Xueying Lyu, Paul Yushkevich, S. Hrybouski, Yue Li, M. T. Duong, Long Xie, L. Wisse, R. Flores, David J. Irwin, B. Dickerson, I. Nasrallah, Sandhitsu R. Das, and D. Wolk

Alzheimer’s & Dementia, Dec 2024

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The heterogeneity of Alzheimer’s disease (AD) and lack of well‐validated markers of co‐pathologies present a substantial challenge for therapeutics. We previously found phenotypes defined by Tau (T) ‐ Neurodegeneration (N) discordance linked to non‐Alzheimer’s pathologies (e.g. TDP‐43, vascular disease). In this work, we aim to leverage T‐N mismatch for identifying distinct spatial‐temporal progression patterns of non‐AD pathologies.
Pathological Associations with Rate of Progression of Frontotemporal Dementia

R. Magee, DT Ohm, E. Rhodes, L. Massimo, D. Wolk, Eddie B. Lee, C. Mcmillan, and David J. Irwin

Alzheimer’s & Dementia, Dec 2024

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There is considerable variability in the rate of clinical progression among individuals with frontotemporal dementia (FTD) and prognostic markers are lacking. Moreover, due to the rarity of postmortem data, the relationship between rate of progression and postmortem tau and TDP‐43 proteinopathy is understudied.
Remote App‐Based Cognitive Assessment in Aging and Pre‐Clinical Alzheimer’s Disease in a Diverse Sample of Older Adults

D. Mechanic-Hamilton, Valerie Humphreys, Alex Prusky, Kimberly Halberstadter, and D. Wolk

Alzheimer’s & Dementia, Dec 2024

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Mobile, valid and engaging cognitive assessments are essential for detecting and tracking change in research participants and patients at risk for Alzheimer’s Disease and Related Dementias (ADRDs). This pilot study aims to determine the feasibility and generalizability of an at‐home, app‐based cognitive assessment, the mobile cognitive app performance platform (mCAPP), to detect cognitive changes associated with aging and preclinical AD.
Percentile‐based hippocampal volume MRI biomarker for distinguishing concomitant LATE and AD from pure LATE and pure AD

Nidhi S. Mundada, Xueying Lyu, Emily McGrew, Long Xie, Paul Yushkevich, Sandhitsu R. Das, and D. Wolk

Alzheimer’s & Dementia, Dec 2024

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Due to the lack of in vivo molecular biomarkers for Limbic‐predominant age‐related TDP‐43 encephalopathy (LATE), which commonly co‐occurs with Alzheimer’s disease (AD), it is challenging to identify patients with mixed AD/LATE pathology. Autopsy studies have suggested that AD patients with greater hippocampal atrophy are disproportionately enriched in having concomitant LATE. Here we define the lower quartile of hippocampal volume as a biomarker of possible LATE with AD.
Sensitivity of Remote App‐Based Assessment of Cognition to Sleep‐Mediated Differences in Cognitive Functioning Among Older Adults

Rachel Rovere, Erin Liebenberg, Kimberly Halberstadter, D. Wolk, and D. Mechanic-Hamilton

Alzheimer’s & Dementia, Dec 2024

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This study assesses the sensitivity of the mobile cognitive app performance platform (mCAPP), a mobile and engaging cognitive assessment tool, to participant sleep duration.
Postmortem MRI signature of Hippocampal Sclerosis of Aging

G. Rådman, Amanda E. Denning, S. Ravikumar, N. Spotorno, R. Ittyerah, Lisa Levorse, M. Bedard, E. Chung, John L. Robinson, T. Schuck, Eddie B. Lee, Sydney A. Lim, W. Trotman, A. Bahena, R. Olsen, David J. Irwin, María Mar Arroyo Jiménez, Alicia Vela, Esther Buendia, Maria Mercedes Iniguez Onzono Martin, M. Rabal, M. Muñoz, R. Insausti, Paul Yushkevich, and L. Wisse

Alzheimer’s & Dementia, Dec 2024

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Hippocampal Sclerosis of aging (HS) refers to age‐related selective neuronal loss and gliosis in hippocampal cornu ammonis 1 (CA1) and subiculum that is out of proportion to tau pathology in Alzheimer’s Disease (AD). HS is related to cognitive decline and memory impairments separately from other neurodegenerative pathologies. To date, in vivo imaging biomarkers of HS of aging are non‐existent, and their development would greatly improve diagnosis and prognosis in memory clinics. We therefore aimed to characterize the magnetic resonance imaging (MRI) signature of HS among autopsy confirmed cases of HS.
Developing an anatomically valid segmentation protocol for anterior regions of the medial temporal lobe

Niyousha Sadeghpour, Sydney A. Lim, A. Wuestefeld, Amanda E. Denning, R. Ittyerah, W. Trotman, E. Chung, S. Sadaghiani, K. Prabhakaran, M. Bedard, Daniel T. Ohm, E. Artacho-Pérula, Maria Mercedes Iniguez Onzono Martin, M. Muñoz, Francisco Javier Molina Romero, José Carlos Delgado González, María Mar Arroyo Jiménez, M. Rabal, S. C. Sánchez, Carlos Rosa Prieto, R. Insausti, C. Mcmillan, M. Grossman, Eddie B. Lee, John A. Detre, J. Trojanowski, M. Tisdall, David J. Irwin, D. Wolk, Paul Yushkevich, and L. Wisse

Alzheimer’s & Dementia, Dec 2024

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The anterior portion of the MTL is one of the first regions targeted by pathology in sporadic Alzheimer’s disease (AD) indicating the potential for imaging metrics from this region to serve as valuable imaging biomarkers. However, most existing automated approaches for MTL segmentation do not incorporate anterior MTL subregions, and the few that do fail to account for its complex anatomical variability. Leveraging a unique postmortem dataset consisting of histology and structural MRI scans we aimed to develop an anatomically valid segmentation protocol for anterior entorhinal cortex (ERC), Brodmann Area (BA) 35, and BA36 and apply it for automated MTL segmentation of in vivo 3 tesla (T) MRI.
Implementation and Validation of Face De‐Identification (de‐facing) in ADNI‐4

C. Schwarz, D. Tosun, Paul Yushkevich, M. Choe, Stephanie Rossi, Sandhitsu R. Das, R. Ittyerah, Evan F. Fletcher, Pauline Maillard, Baljeet Singh, Danielle J. Harvey, Ian B. Malone, Lloyd Prosser, M. Senjem, Leonard Matoush, Chadwick P. Ward, Carl M. Prakaashana, C. Decarli, Michael S. W. Weiner, and C. Jack

Alzheimer’s & Dementia, Dec 2024

Cited by 1

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Recent advances in automatic face recognition have increased the risk that de‐identified research imaging data could be re‐identified from face imagery in brain scans.
Does Neurodegeneration Lag Behind Tau Deposition in Alzheimer Dementia?

Ujashi Shah, Long Xie, Emily McGrew, D. Wolk, and Sandhitsu R. Das

Alzheimer’s & Dementia, Dec 2024

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Alzheimer’s disease (AD) is defined by the presence of ß‐amyloid (Aß) plaques and tau‐based neurofibrillary tangles (NFTs). Understanding the temporal relationship of NFTs with atrophy in early AD regions, specifically the medial temporal lobe (MTL), is critical for monitoring disease progression. Accumulation of NFTs has been suggested to precede atrophy because cross‐sectional measures of atrophy are more weakly associated with baseline tracer uptake than prospective longitudinal ones. However, longitudinal measures may be more sensitive to disease‐related atrophy at early AD stages. To address this, we examine cross‐sectional versus longitudinal measures before or after the time of tau PET.
MRI Correlates of Executive Function in Cognitively Normal Older Subjects

Banafsheh Shakibajahromi, S. Dolui, Christopher D. Brown, M. Taghvaei, Pulkit Khandelwal, Qichao Wu, S. Sadaghiani, Paul Yushkevich, D. Wolk, and John A. Detre

Alzheimer’s & Dementia, Dec 2024

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Cerebral small vessel disease (CSVD) is the most prevalent cause of vascular cognitive impairment. Executive function impairment and white matter (WM) lesions occur early in CSVD, the latter typically in periventricular WM (PVWM) ‐ the least perfused brain region. Accounting for vascular risk factors (VRF) and amyloid status in cognitively normal older subjects, we assessed the relationship between Trail‐making test (TMT) performance and MRI measures preceding WM lesions: arterial spin labeling (ASL)‐derived cerebral blood flow (CBF) and diffusion tensor imaging (DTI) indices in normal‐appearing WM (NAWM) and normal‐appearing PVWM (NAPVWM).
Biological aging is associated with atypical neurodegenerative patterns in Alzheimer’s disease

Lasya P. Sreepada, Christopher D. Brown, Sandhitsu R. Das, Paul Yushkevich, D. Wolk, and C. Mcmillan

Alzheimer’s & Dementia, Dec 2024

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Atypical presentations of Alzheimer’s disease (AD), which demonstrate more cortical involvement relative to medial temporal lobe (MTL), are generally associated with younger age of onset. Age, defined chronologically, is a primary driver of AD pathology and neurodegeneration. However, some young onset cases are typical, amnestic presentations and some older onset cases present more cortical atrophy. We hypothesize that a biological definition of age, defined using epigenetic clock measures, may be even more tightly linked to atypicality than chronological age.
Biological aging is associated with atypical neurodegenerative patterns in Alzheimer’s disease

Lasya P. Sreepada, Christopher D. Brown, Sandhitsu R. Das, Paul Yushkevich, D. Wolk, and C. Mcmillan

Alzheimer’s & Dementia, Dec 2024

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Atypical presentations of Alzheimer’s disease (AD), which demonstrate more cortical involvement relative to medial temporal lobe (MTL), are generally associated with younger age of onset. Age, defined chronologically, is a primary driver of AD pathology and neurodegeneration. However, some young onset cases are typical, amnestic presentations and some older onset cases present more cortical atrophy. We hypothesize that a biological definition of age, defined using epigenetic clock measures, may be even more tightly linked to atypicality than chronological age.
Effects of Amyloid Pathology and Vascular Risk Factors on Regional Cerebral Blood Flow Patterns

M. Taghvaei, S. Sadaghiani, Banafsheh Shakibajahromi, Pulkit Khandelwal, Sandhitsu R. Das, I. Nasrallah, Paul Yushkevich, D. Wolk, John A. Detre, and S. Dolui

Alzheimer’s & Dementia, Dec 2024

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Regional cerebral blood flow (CBF) can be noninvasively quantified using arterial spin labeled (ASL) perfusion MRI. In Alzheimer’s disease (AD) and mild cognitive impairment (MCI), hypoperfusion typically occurs in precuneus, posterior cingulate cortex (PCC), and hippocampus. Small vessel disease (SVD), a systemic disorder that commonly underlies vascular cognitive impairment, also causes brain hypoperfusion. Many dementia patients demonstrate both neurodegenerative and vascular pathologies, which may interact to accelerate cognitive decline. Here we used advanced background‐suppressed 3D ASL to assess CBF variations across the AD spectrum and in relation to risk factors for AD and SVD.
Regional cerebral blood flow reflects both neurodegeneration and microvascular integrity across the Alzheimer’s continuum

M. Taghvaei, S. Dolui, S. Sadaghiani, Banafsheh Shakibajahromi, Christopher A. Brown, Pulkit Khandelwal, Sharon X. Xie, Sandhitsu R. Das, Paul Yushkevich, D. Wolk, and John A. Detre

Alzheimer’s & Dementia, Dec 2024

Cited by 13

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Alzheimer’s disease (AD) typically involves both neurodegenerative and vascular pathologies, each associated with reductions in cerebral blood flow (CBF). However, it remains unclear whether vascular and neural contributions to regional CBF can be differentiated.
Shared and Distinct Epigenetic Profiles in Primary Age‐Related Tauopathy and Alzheimer’s Disease: Insights into Tangle Formation and Spread

Anil R. Wadhwani, David C. Goldberg, D. Wolk, Eddie B. Lee, Kurt Farrell, J. Crary, David A. A. Bennett, P. De Jager, Julie A. Schneider, Wanding Zhou, C. Mcmillan, and Part Working Group

Alzheimer’s & Dementia, Dec 2024

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Alzheimer’s disease (AD) is characterized by neocortical dissemination of neurofibrillary tangles (NFTs) while primary age‐related tauopathy (PART) has NFTs largely confined to the hippocampus and adjacent structures. Thus, PART and AD represent two extremes of a spectrum of NFT spread. We investigated epigenetic mechanisms of interindividual variation in NFT spread.
The association between tau pathology and later stages of memory processing is mediated by medial temporal lobe atrophy in typical Alzheimer’s Disease

A. Wuestefeld, Salena Cui, Sandhitsu R. Das, Long Xie, Emily McGrew, Paul A. Yushkevich, L. Wisse, and D. Wolk

Alzheimer’s & Dementia, Dec 2024

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Tau pathology is closely related to cognitive decline in Alzheimer’s disease (AD). Neurodegeneration is the putative mechanism by which tau leads to cognitive deficits. However, there is limited work on the associations between tau, neurodegeneration, and specific cognitive domains. We investigate potential mediating effects of medial temporal lobe (MTL) and neocortical neurodegeneration for different cognitive domains in amyloid‐β‐positive (Aβ+) adults.
The association between tau pathology and later stages of memory processing is mediated by medial temporal lobe atrophy in typical Alzheimer’s Disease

A. Wuestefeld, Salena Cui, Sandhitsu R. Das, Long Xie, Emily McGrew, Paul Yushkevich, L. Wisse, and D. Wolk

Alzheimer’s & Dementia, Dec 2024

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Tau pathology is closely related to cognitive decline in Alzheimer’s disease (AD). Neurodegeneration is the putative mechanism by which tau leads to cognitive deficits. However, there is limited work on the associations between tau, neurodegeneration, and specific cognitive domains. We investigate potential mediating effects of medial temporal lobe (MTL) and neocortical neurodegeneration for different cognitive domains in amyloid‐ß‐positive (Aß+) adults.
Spatial Pattern of Medial Temporal Lobe Cross‐Sectional and Longitudinal Structural Change in Cognitively Normal Individuals

Long Xie, Sandhitsu R. Das, Yue Li, L. Wisse, Emily McGrew, Xueying Lyu, Michael Dicalogero, Ujashi Shah, Ademola Ilesanmi, Amanda E. Denning, Christopher D. Brown, Jesse S. Cohen, Lasya P. Sreepada, M. Dong, Niyousha Sadeghpour, Pulkit Khandelwal, R. Ittyerah, S. Ravikumar, S. Sadaghiani, S. Hrybouski, R. Flores, Eli Gibson, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Dec 2024

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The medial temporal lobe’s (MTL) early involvement in tau pathology makes it a key focus in the development of preclinical Alzheimer’s disease (AD) biomarkers. ROI analyses in prior studies reported significant MTL structural differences in cognitively normal individuals with and without β‐amyloid (A+/‐CN). Pointwise analysis, offering spatial information of early neurodegeneration, has potential to pinpoint “signature regions” of pathological change, but has been underexplored in the MTL. This study employs a specialized pointwise analysis pipeline to examine the spatial pattern of MTL structural change in subgroups dichotomized by both β‐amyloid and tau status in a large cohort of CN individuals.
Utilizing Advanced Artificial Intelligence for Automated Detection and Segmentation of Amyloid‐Related Imaging Abnormality (ARIA)

Long Xie, Paul Yushkevich, Sandhitsu R. Das, D. Wolk, and Eli Gibson

Alzheimer’s & Dementia, Dec 2024

Cited by 1

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The recent breakthrough in monoclonal antibody treatment for Alzheimer’s disease (AD) has ushered in a new phase in AD healthcare. However, associated amyloid‐related imaging abnormalities (ARIA) present a significant risk to patients, necessitating careful monitoring. Detection by radiologists can be challenging and may suffer from inconsistency. This study investigates the potential of advanced artificial intelligence (AI) for automated detection of micro‐hemorrhage (mH) in GRE MRI and ARIA‐like abnormal hyper‐intensity in FLAIR MRI, the two primary manifestations of ARIA.
Insights into LATE from postmortem imaging

Paul Yushkevich, Amanda E. Denning, Lisa Levorse, R. Ittyerah, Niyousha Sadeghpour, John L. Robinson, Sanaz Arezoumandan, S. Ravikumar, Daniel T. Ohm, T. Schuck, David J. Irwin, Eddie B. Lee, A. Bahena, W. Trotman, Sandhitsu R. Das, D. Wolk, L. Wisse, R. Flores, R. Insausti, Pulkit Khandelwal, and Chinmayee Athalye

Alzheimer’s & Dementia, Dec 2024

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Limbic‐predominant age‐related TDP‐43 encephalopathy (LATE) is a neurodegenerative disease that is often comorbid with Alzheimer’s disease (AD) and for which there are no reliable specific chemical or PET biomarkers available. Recent progress in disease‐modifying treatments for AD elevates the need for reliable in vivo detection of LATE and other comorbid neurodegenerative diseases. The promise of postmortem and antemortem MRI studies in LATE is that they will lead to the discovery of patterns of neurodegeneration associated with TDP‐43 pathology that could be reliably detected in vivo and used as a biomarker of LATE.
Hypometabolic mismatch with atrophy and tau pathology in mixed Alzheimer and Lewy body disease.

M. T. Duong, Sandhitsu R. Das, Pulkit Khandelwal, Xueying Lyu, Long Xie, Emily McGrew, Nadia Dehghani, C. Mcmillan, Edward B. Lee, Leslie M. Shaw, Paul Yushkevich, D. Wolk, and I. Nasrallah

Brain : a journal of neurology, Nov 2024

Cited by 19

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Polypathology is a major driver of heterogeneity in clinical presentation and extent of neurodegeneration (N) in patients with Alzheimer Disease (AD). Beyond amyloid (A) and tau (T) pathologies, over half of patients with AD have concomitant pathology such as α-synuclein (S) in mixed AD with Lewy Body Disease (LBD). Patients with Mixed Etiology Dementia (MED) such as AD+LBD have faster progression and potentially differential responses to targeted treatments, though the diagnosis of AD+LBD can be challenging given overlapping clinical and imaging features. Development and validation of improved in vivo biomarkers are required to study relationships between N and S and identify imaging patterns reflecting mixed AD+LBD pathologies. We hypothesize that individual proteinopathies, such as T and S, are associated with commensurate levels of N. Thus, we assessed biomarkers of A, T, N and S with positron emission tomography (PET), magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) seeding amplification assay (SAA) data to determine molecular presentations of mixed A+S+ vs. A+S- cognitively impaired patients from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We found A+S+ patients had parieto-occipital 18F-Fluorodeoxyglucose hypometabolism (a measure of N) disproportionate to the degree of regional atrophy or T burden, highlighting worse hypometabolism associated with S+ SAA. Following up on this hypometabolic mismatch with CSF metabolite and proteome analyses, we found that A+S+ patients exhibited lower CSF levels of dopamine metabolites and synaptic markers like neuronal pentraxin-2 (NPTX2), suggesting that altered neurotransmission and neuron integrity contribute to this dissociation between metabolic PET and MRI. Potential confounders exist when studying relations between N, AD and LBD pathologies, including neuroinflammation and other non-Alzheimer pathologies in MED, though our findings imply posterior hypometabolic mismatch is related more to S than vascular or TDP-43 pathology. A+S+ patients had posterior mismatch with excessive 18F-Fluorodeoxyglucose hypometabolism relative to atrophy or T load, possibly reflecting impaired neuron integrity. Further research must disentangle the impact of multiple proteinopathies and clinicopathologic factors on hypometabolism and atrophy. Cumulatively, patients with mixed AD+LBD etiologies harbor a unique metabolic PET mismatch signature.
Feasibility, validity, and normative data for the remote Uniform Data Set neuropsychological battery at the University of Pennsylvania Alzheimer’s Disease Research Center

Katherine Hackett, Yidan Shi, Laura Schankel, Nicole Oliveira, M. Kelley, Hannah McCoubrey, Sara Manning Peskin, Kyra S. O’Brien, Sharon X. Xie, D. Wolk, and Dawn Mechanic-Hamilton

Alzheimer’s & Dementia : Diagnosis, Assessment & Disease Monitoring, Oct 2024

Cited by 2

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We investigated the feasibility and validity of the remotely‐administered neuropsychological battery from the National Alzheimer’s Coordinating Center Uniform Data Set (UDS T‐Cog).
BOLD Amplitude Correlates of Preclinical Alzheimer’s Disease

S. Hrybouski, Sandhitsu R. Das, Long Xie, Christopher A. Brown, Melissa Flamporis, J. Lane, I. Nasrallah, John A. Detre, Paul Yushkevich, and D. Wolk

medRxiv : the preprint server for health sciences, Oct 2024

Cited by 1

DOI
Implementation and validation of face de‐identification (de‐facing) in ADNI4

C. Schwarz, M. Choe, Stephanie Rossi, Sandhitsu R. Das, R. Ittyerah, Evan Fletcher, P. Maillard, Baljeet Singh, Danielle J. Harvey, Ian B. Malone, Lloyd Prosser, M. Senjem, Leonard Matoush, Chadwick P. Ward, Carl M. Prakaashana, Susan M. Landau, R. Koeppe, JiaQie Lee, C. Decarli, M. Weiner, C. Jack, W. Jagust, Paul Yushkevich, and D. Tosun

Alzheimer’s & Dementia, Oct 2024

Cited by 4

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Recent technological advances have increased the risk that de‐identified brain images could be re‐identified from face imagery. The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is a leading source of publicly available de‐identified brain imaging, who quickly acted to protect participants’ privacy.
Association of quantitative histopathology measurements with antemortem medial temporal lobe cortical thickness in the Alzheimer’s disease continuum

Amanda E. Denning, R. Ittyerah, Lisa Levorse, Niyousha Sadeghpour, Chinmayee Athalye, E. Chung, S. Ravikumar, M. Dong, M. T. Duong, Yue Li, Ademola Ilesanmi, Lasya P. Sreepada, Philip Sabatini, MaKayla Lowe, A. Bahena, Jamila Zablah, Barbara E. Spencer, Ryohei Watanabe, Boram Kim, Maja Højvang Sørensen, Pulkit Khandelwal, Christopher A. Brown, S. Hrybouski, Sharon X. Xie, R. Flores, John L. Robinson, T. Schuck, Daniel T. Ohm, Sanaz Arezoumandan, Sílvia Porta, John A. Detre, R. Insausti, L. Wisse, Sandhitsu R. Das, David J. Irwin, Edward B. Lee, D. Wolk, and Paul Yushkevich

Acta Neuropathologica, Sep 2024

Cited by 19

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The medial temporal lobe (MTL) is a hotspot for neuropathology, and measurements of MTL atrophy are often used as a biomarker for cognitive decline associated with neurodegenerative disease. Due to the aggregation of multiple proteinopathies in this region, the specific relationship of MTL atrophy to distinct neuropathologies is not well understood. Here, we develop two quantitative algorithms using deep learning to measure phosphorylated tau (p-tau) and TDP-43 (pTDP-43) pathology, which are both known to accumulate in the MTL and are associated with MTL neurodegeneration. We focus on these pathologies in the context of Alzheimer’s disease (AD) and limbic predominant age-related TDP-43 encephalopathy (LATE) and apply our deep learning algorithms to distinct histology sections, on which MTL subregions were digitally annotated. We demonstrate that both quantitative pathology measures show high agreement with expert visual ratings of pathology and discriminate well between pathology stages. In 140 cases with antemortem MR imaging, we compare the association of semi-quantitative and quantitative postmortem measures of these pathologies in the hippocampus with in vivo structural measures of the MTL and its subregions. We find widespread associations of p-tau pathology with MTL subregional structural measures, whereas pTDP-43 pathology had more limited associations with the hippocampus and entorhinal cortex. Quantitative measurements of p-tau pathology resulted in a significantly better model of antemortem structural measures than semi-quantitative ratings and showed strong associations with cortical thickness and volume. By providing a more granular measure of pathology, the quantitative p-tau measures also showed a significant negative association with structure in a severe AD subgroup where semi-quantitative ratings displayed a ceiling effect. Our findings demonstrate the advantages of using quantitative neuropathology to understand the relationship of pathology to structure, particularly for p-tau, and motivate the use of quantitative pathology measurements in future studies.
Regional deep atrophy: Using temporal information to automatically identify regions associated with Alzheimer’s disease progression from longitudinal MRI

M. Dong, Long Xie, Sandhitsu R. Das, Jiancong Wang, L. Wisse, R. Flores, D. Wolk, and Paul Yushkevich

Imaging Neuroscience, Sep 2024

Cited by 3

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Abstract Longitudinal assessment of brain atrophy, particularly in the hippocampus, is a well-studied biomarker for neurodegenerative diseases, such as Alzheimer’s disease (AD). Estimating brain progression patterns can be applied to understanding the therapeutic effects of amyloid-clearing drugs in research and detecting the earliest sign of accelerated atrophy in clinical settings. However, most state-of-the-art measurements calculate changes directly by segmentation and/or deformable registration of MRI images, and may misreport head motion or MRI artifacts as neurodegeneration, impacting their accuracy. In our previous study, we developed a deep learning method DeepAtrophy that uses a convolutional neural network to quantify differences between longitudinal MRI scan pairs that are associated with time. DeepAtrophy has high accuracy in inferring temporal information from longitudinal MRI scans, such as temporal order or relative interscan interval. DeepAtrophy also provides an overall atrophy score that was shown to perform well as a potential biomarker of disease progression and treatment efficacy. However, DeepAtrophy is not interpretable, and it is unclear what changes in the MRI contribute to progression measurements. In this paper, we propose Regional Deep Atrophy (RDA), which combines the temporal inference approach from DeepAtrophy with a deformable registration neural network and attention mechanism that highlights regions in the MRI image where longitudinal changes are contributing to temporal inference. RDA has similar prediction accuracy as DeepAtrophy, but its additional interpretability makes it more acceptable for use in clinical settings, and may lead to more sensitive biomarkers for disease monitoring and progression understanding in preclinical AD.
Overview of ADNI MRI

C. Jack, A. Arani, Bret J. Borowski, D. Cash, K. Crawford, Sandhitsu R. Das, C. Decarli, Evan F. Fletcher, N. Fox, J. Gunter, R. Ittyerah, Danielle J. Harvey, N. Jahanshad, P. Maillard, I. Malone, T. Nir, Robert I. Reid, Denise A. Reyes, C. Schwarz, M. Senjem, D. Thomas, Paul M. Thompson, D. Tosun, Paul Yushkevich, Chadwick P. Ward, and Michael W. Weiner

Alzheimer’s & Dementia, Sep 2024

Cited by 73

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The magnetic resonance imaging (MRI) Core has been operating since Alzheimer’s Disease Neuroimaging Initiative’s (ADNI) inception, providing 20 years of data including reliable, multi‐platform standardized protocols, carefully curated image data, and quantitative measures provided by expert investigators. The overarching purposes of the MRI Core include: (1) optimizing and standardizing MRI acquisition methods, which have been adopted by many multicenter studies and trials worldwide and (2) providing curated images and numeric summary values from relevant MRI sequences/contrasts to the scientific community. Over time, ADNI MRI has become increasingly complex. To remain technically current, the ADNI MRI protocol has changed substantially over the past two decades. The ADNI 4 protocol contains nine different imaging types (e.g., three dimensional [3D] T1‐weighted and fluid‐attenuated inversion recovery [FLAIR]). Our view is that the ADNI MRI data are a greatly underutilized resource. The purpose of this paper is to educate the scientific community on ADNI MRI methods and content to promote greater awareness, accessibility, and use.
Medial temporal lobe atrophy patterns in early-versus late-onset amnestic Alzheimer’s disease

A. Wuestefeld, A. Pichet Binette, D. Westen, O. Strandberg, E. Stomrud, N. Mattsson-Carlgren, S. Janelidze, Ruben Smith, S. Palmqvist, H. Baumeister, D. Berron, Paul Yushkevich, O. Hansson, N. Spotorno, and L. Wisse

Alzheimer’s Research & Therapy, Sep 2024

Cited by 8

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The medial temporal lobe (MTL) is hypothesized to be relatively spared in early-onset Alzheimer’s disease (EOAD). Yet, detailed examination of MTL subfields and drivers of atrophy in amnestic EOAD is lacking. BioFINDER-2 participants with memory impairment, abnormal amyloid-β and tau-PET were included. Forty-one amnestic EOAD individuals ≤65 years and, as comparison, late-onset AD (aLOAD, ≥70 years, n = 154) and amyloid-β-negative cognitively unimpaired controls were included. MTL subregions and biomarkers of (co-)pathologies were measured. AD groups showed smaller MTL subregions compared to controls. Atrophy patterns were similar across AD groups: aLOAD showed thinner entorhinal cortices than aEOAD; aEOAD showed thinner parietal regions than aLOAD. aEOAD showed lower white matter hyperintensities than aLOAD. No differences in MTL tau-PET or transactive response DNA binding protein 43-proxy positivity were found. We found evidence for MTL atrophy in amnestic EOAD and overall similar levels to aLOAD of MTL tau pathology and co-pathologies.
Morphometry of medial temporal lobe subregions using high‐resolution T2‐weighted MRI in ADNI3: Why, how, and what’s next?

Paul Yushkevich, R. Ittyerah, Yue Li, Amanda E. Denning, Niyousha Sadeghpour, Sydney A. Lim, Emily McGrew, Long Xie, R. Flores, Christopher A. Brown, L. Wisse, D. Wolk, and Sandhitsu R. Das

Alzheimer’s & Dementia, Sep 2024

Cited by 11

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This paper for the 20th anniversary of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) provides an overview of magnetic resonance imaging (MRI) of medial temporal lobe (MTL) subregions in ADNI using a dedicated high‐resolution T2‐weighted sequence. A review of the work that supported the inclusion of this imaging modality into ADNI Phase 3 is followed by a brief description of the ADNI MTL imaging and analysis protocols and a summary of studies that have used these data. This review is supplemented by a new study that uses novel surface‐based tools to characterize MTL neurodegeneration across biomarker‐defined AD stages. This analysis reveals a pattern of spreading cortical thinning associated with increasing levels of tau pathology in the presence of elevated amyloid beta, with apparent epicenters in the transentorhinal region and inferior hippocampal subfields. The paper concludes with an outlook for high‐resolution imaging of the MTL in ADNI Phase 4.
Microstructural changes in the inferior tuberal hypothalamus correlate with daytime sleepiness in Lewy body disease

Jesse S. Cohen, Hamsanandini Radhakrishnan, Christopher A. Olm, Sandhitsu R. Das, Philip A. Cook, D. Wolk, D. Weintraub, D. Irwin, and C. McMillan

medRxiv, Aug 2024

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Background: Excessive daytime sleepiness (EDS) is a disabling symptom of Lewy body disorders (LBD). The hypothalamus is a key sleep-wake regulator, but its contribution to EDS in LBD remains unclear. Objectives: Use diffusion MRI to evaluate the relationship of hypothalamic microstructure to EDS symptoms in LBD. Methods: We studied 102 patients with clinically-defined LBD (Parkinson’s disease, n=93; Parkinson’s disease dementia, n=4; and dementia with Lewy bodies, n=5) and Epworth Sleepiness Scale (ESS) within 2 years of MRI. Mean diffusivity (MD) was compared between EDS+ (ESS>=10, n=37) and EDS- (ESS<10, n=65) groups in the whole hypothalamus and three subregions, covarying for age and sex. Secondary analyses tested correlations between subregion MD and continuous ESS, global cognition, and motor scores; and between subregion volume and continuous ESS. Results: MD was increased in EDS+ compared to EDS- only in the inferior tuberal subregion (Cohen’s d=0.43, p=0.043, beta=0.117+/-0.057), with trend level differences in the whole hypothalamus (Cohen’s d=0.39, p=0.064, beta=0.070+/-0.037) and superior tuberal subregion (Cohen’s d=0.38, p=0.073, beta=0.063+/-0.035). No difference was seen in the posterior subregion (Cohen’s d=0.1, p=0.628, beta=0.019+/-0.038). Significant correlations with continuous ESS were seen in MD of whole hypothalamus (r2=0.074, p=0.0057), superior tuberal (r2=0.081, p=0.0038), and inferior tuberal (r2=0.073, p=0.0059) subregions. There was no correlation of hypothalamic MD with global cognition or motor scores, and no correlation of whole/subregional hypothalamic volumes with ESS. Conclusions: Daytime sleepiness associates with increased MD in the inferior tuberal hypothalamus in an LBD cohort. This suggests degeneration within this region could contribute to EDS symptoms.
Beyond Macrostructure: Is There a Role for Radiomics Analysis in Neuroimaging ?

Sandhitsu R. Das, Ademola Ilesanmi, D. Wolk, and James C. Gee

Magnetic Resonance in Medical Sciences, Jun 2024

Cited by 16

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The most commonly used neuroimaging biomarkers of brain structure, particularly in neurodegenerative diseases, have traditionally been summary measurements from ROIs derived from structural MRI, such as volume and thickness. Advances in MR acquisition techniques, including high-field imaging, and emergence of learning-based methods have opened up opportunities to interrogate brain structure in finer detail, allowing investigators to move beyond macrostructural measurements. On the one hand, superior signal contrast has the potential to make appearance-based metrics that directly analyze intensity patterns, such as texture analysis and radiomics features, more reliable. Quantitative MRI, particularly at high-field, can also provide a richer set of measures with greater interpretability. On the other hand, use of neural networks-based techniques has the potential to exploit subtle patterns in images that can now be mined with advanced imaging. Finally, there are opportunities for integration of multimodal data at different spatial scales that is enabled by developments in many of the above techniques—for example, by combining digital histopathology with high-resolution ex-vivo and in-vivo MRI. Some of these approaches are at early stages of development and present their own set of challenges. Nonetheless, they hold promise to drive the next generation of validation and biomarker studies. This article will survey recent developments in this area, with a particular focus on Alzheimer’s disease and related disorders. However, most of the discussion is equally relevant to imaging of other neurological disorders, and even to other organ systems of interest. It is not meant to be an exhaustive review of the available literature, but rather presented as a summary of recent trends through the discussion of a collection of representative studies with an eye towards what the future may hold.
Postmortem imaging reveals patterns of medial temporal lobe vulnerability to tau pathology in Alzheimer’s disease

S. Ravikumar, Amanda E. Denning, Sydney A. Lim, E. Chung, Niyousha Sadeghpour, R. Ittyerah, L. Wisse, Sandhitsu R. Das, Long Xie, John L. Robinson, T. Schuck, Edward B. Lee, John A. Detre, M. Tisdall, K. Prabhakaran, G. Mizsei, Maria Mercedes Iñiguez Onzoño Martin, María Mar Arroyo Jiménez, M. Muñoz, María Del Pilar Marcos Rabal, S. Cebada Sánchez, J. C. Delgado González, C. Rosa Prieto, David J. Irwin, D. Wolk, R. Insausti, and Paul Yushkevich

Nature Communications, Jun 2024

Cited by 40

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Our current understanding of the spread and neurodegenerative effects of tau neurofibrillary tangles (NFTs) within the medial temporal lobe (MTL) during the early stages of Alzheimer’s Disease (AD) is limited by the presence of confounding non-AD pathologies and the two-dimensional (2-D) nature of conventional histology studies. Here, we combine ex vivo MRI and serial histological imaging from 25 human MTL specimens to present a detailed, 3-D characterization of quantitative NFT burden measures in the space of a high-resolution, ex vivo atlas with cytoarchitecturally-defined subregion labels, that can be used to inform future in vivo neuroimaging studies. Average maps show a clear anterior to poster gradient in NFT distribution and a precise, spatial pattern with highest levels of NFTs found not just within the transentorhinal region but also the cornu ammonis (CA1) subfield. Additionally, we identify granular MTL regions where measures of neurodegeneration are likely to be linked to NFTs specifically, and thus potentially more sensitive as early AD biomarkers. Using high-resolution ex vivo MRI and serial histology, Ravikumar et al. characterise 3D tau spread across histologically defined medial temporal lobe subregions thus providing a postmortem reference for in vivo studies on early Alzheimer’s disease.
Medial temporal lobe gray matter microstructure in preclinical Alzheimer’s disease

Christopher A. Brown, Sandhitsu R. Das, Long Xie, I. Nasrallah, John A. Detre, A. Chen-Plotkin, Leslie M. Shaw, Corey T. McMillan, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, May 2024

Cited by 14

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Typical MRI measures of neurodegeneration have limited sensitivity in early disease stages. Diffusion MRI (dMRI) microstructural measures may allow for detection in preclinical stages.
Open-source graphical user interface for the creation of synthetic skeletons for medical image analysis

Christian Herz, Nicolas Vergnet, Si-Jie Tian, Abdullah H. Aly, Matthew A. Jolley, Nathanael Tran, Gabriel Arenas, Andras Lasso, Nadav Schwartz, Kathleen E. O’Neill, Paul Yushkevich, and Alison M. Pouch

Journal of Medical Imaging, May 2024

Cited by 4

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Abstract. Purpose Deformable medial modeling is an inverse skeletonization approach to representing anatomy in medical images, which can be used for statistical shape analysis and assessment of patient-specific anatomical features such as locally varying thickness. It involves deforming a pre-defined synthetic skeleton, or template, to anatomical structures of the same class. The lack of software for creating such skeletons has been a limitation to more widespread use of deformable medial modeling. Therefore, the objective of this work is to present an open-source user interface (UI) for the creation of synthetic skeletons for a range of medial modeling applications in medical imaging. Approach A UI for interactive design of synthetic skeletons was implemented in 3D Slicer, an open-source medical image analysis application. The steps in synthetic skeleton design include importation and skeletonization of a 3D segmentation, followed by interactive 3D point placement and triangulation of the medial surface such that the desired branching configuration of the anatomical structure’s medial axis is achieved. Synthetic skeleton design was evaluated in five clinical applications. Compatibility of the synthetic skeletons with open-source software for deformable medial modeling was tested, and representational accuracy of the deformed medial models was evaluated. Results Three users designed synthetic skeletons of anatomies with various topologies: the placenta, aortic root wall, mitral valve, cardiac ventricles, and the uterus. The skeletons were compatible with skeleton-first and boundary-first software for deformable medial modeling. The fitted medial models achieved good representational accuracy with respect to the 3D segmentations from which the synthetic skeletons were generated. Conclusions Synthetic skeleton design has been a practical challenge in leveraging deformable medial modeling for new clinical applications. This work demonstrates an open-source UI for user-friendly design of synthetic skeletons for anatomies with a wide range of topologies.
Automated deep learning segmentation of high-resolution 7 Tesla postmortem MRI for quantitative analysis of structure-pathology correlations in neurodegenerative diseases

Pulkit Khandelwal, M. T. Duong, S. Sadaghiani, Sydney A. Lim, Amanda E. Denning, E. Chung, S. Ravikumar, Sanaz Arezoumandan, Claire S. Peterson, M. Bedard, N. Capp, R. Ittyerah, Elyse Migdal, Grace Choi, Emily Kopp, Bridget Loja, Eusha Hasan, Jiacheng Li, A. Bahena, K. Prabhakaran, G. Mizsei, M. Gabrielyan, T. Schuck, W. Trotman, John L. Robinson, Daniel T. Ohm, Edward B. Lee, J. Trojanowski, Corey T. McMillan, M. Grossman, David J. Irwin, J. A. Detre, M. Tisdall, Sandhitsu R. Das, L. Wisse, D. Wolk, and Paul Yushkevich

Imaging Neuroscience, May 2024

Cited by 12

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Abstract Postmortem MRI allows brain anatomy to be examined at high resolution and to link pathology measures with morphometric measurements. However, automated segmentation methods for brain mapping in postmortem MRI are not well developed, primarily due to limited availability of labeled datasets, and heterogeneity in scanner hardware and acquisition protocols. In this work, we present a high-resolution dataset of 135 postmortem human brain tissue specimens imaged at 0.3 mm3 isotropic using a T2w sequence on a 7T whole-body MRI scanner. We developed a deep learning pipeline to segment the cortical mantle by benchmarking the performance of nine deep neural architectures, followed by post-hoc topological correction. We evaluate the reliability of this pipeline via overlap metrics with manual segmentation in 6 specimens, and intra-class correlation between cortical thickness measures extracted from the automatic segmentation and expert-generated reference measures in 36 specimens. We also segment four subcortical structures (caudate, putamen, globus pallidus, and thalamus), white matter hyperintensities, and the normal appearing white matter, providing a limited evaluation of accuracy. We show generalizing capabilities across whole-brain hemispheres in different specimens, and also on unseen images acquired at 0.28 mm3 and 0.16 mm3 isotropic T2*w fast low angle shot (FLASH) sequence at 7T. We report associations between localized cortical thickness and volumetric measurements across key regions, and semi-quantitative neuropathological ratings in a subset of 82 individuals with Alzheimer’s disease (AD) continuum diagnoses. Our code, Jupyter notebooks, and the containerized executables are publicly available at the project webpage (https://pulkit-khandelwal.github.io/exvivo-brain-upenn/).
Automatic segmentation of medial temporal lobe subregions in multi-scanner, multi-modality magnetic resonance imaging of variable quality

Yue Li, Long Xie, Pulkit Khandelwal, L. Wisse, Christopher A. Brown, K. Prabhakaran, M. Tisdall, D. Mechanic-Hamilton, John A. Detre, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

bioRxiv, May 2024

Cited by 3

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Objectives Volumetry of subregions in the medial temporal lobe (MTL) computed from automatic segmentation in MRI can track neurodegeneration in Alzheimer’s disease. However, poor quality MR images can lead to unreliable segmentation of MTL subregions. Considering that different MRI contrast mechanisms and field strengths (jointly referred to as “modalities” here) offer distinct advantages in imaging different parts of the MTL, we developed a muti-modality segmentation model using both 7 tesla (7T) and 3 tesla (3T) structural MRI to obtain robust segmentation in poor-quality images. Method MRI modalities including 3T T1-weighted, 3T T2-weighted, 7T T1-weighted and 7T T2-weighted (7T-T2w) of 197 participants were collected from a longitudinal aging study at the Penn Alzheimer’s Disease Research Center. Among them, 7T-T2w was used as the primary modality, and all other modalities were rigidly registered to the 7T-T2w. A model derived from nnU-Net took these registered modalities as input and outputted subregion segmentation in 7T-T2w space. 7T-T2w images most of which had high quality from 25 selected training participants were manually segmented to train the multi-modality model. Modality augmentation, which randomly replaced certain modalities with Gaussian noise, was applied during training to guide the model to extract information from all modalities. Results The multi-modality model delivered good performance regardless of 7T-T2w quality, while the single-modality model under-segmented subregions in poor-quality images. The multi-modality model generally demonstrated stronger discrimination of A+MCI versus A-CU. Intra-class correlation and Bland-Altman plots demonstrate that the multi-modality model had higher longitudinal segmentation consistency in all subregions while the single-modality model had low consistency in poor-quality images. Conclusion The multi-modality MRI segmentation model provides an improved biomarker for neurodegeneration in the MTL that is robust to image quality. It also provides a framework for other studies which may benefit from multimodal imaging.
Automatic Segmentation of Medial Temporal Lobe Subregions in Multi‐Scanner, Multi‐Modality Magnetic Resonance Imaging of Variable Quality

Yue Li, L. Xie, Pulkit Khandelwal, L. Wisse, Christopher A. Brown, K. Prabhakaran, M. Tisdall, D. Mechanic-Hamilton, John A. Detre, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

Hippocampus, May 2024

Cited by 1

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Objectives Volumetry of subregions in the medial temporal lobe (MTL) computed from automatic segmentation in MRI can track neurodegeneration in Alzheimer’s disease. However, poor quality MR images can lead to unreliable segmentation of MTL subregions. Considering that different MRI contrast mechanisms and field strengths (jointly referred to as “modalities” here) offer distinct advantages in imaging different parts of the MTL, we developed a muti-modality segmentation model using both 7 tesla (7T) and 3 tesla (3T) structural MRI to obtain robust segmentation in poor-quality images. Method MRI modalities including 3T T1-weighted, 3T T2-weighted, 7T T1-weighted and 7T T2-weighted (7T-T2w) of 197 participants were collected from a longitudinal aging study at the Penn Alzheimer’s Disease Research Center. Among them, 7T-T2w was used as the primary modality, and all other modalities were rigidly registered to the 7T-T2w. A model derived from nnU-Net took these registered modalities as input and outputted subregion segmentation in 7T-T2w space. 7T-T2w images most of which had high quality from 25 selected training participants were manually segmented to train the multi-modality model. Modality augmentation, which randomly replaced certain modalities with Gaussian noise, was applied during training to guide the model to extract information from all modalities. Results The multi-modality model delivered good performance regardless of 7T-T2w quality, while the single-modality model under-segmented subregions in poor-quality images. The multi-modality model generally demonstrated stronger discrimination of A+MCI versus A-CU. Intra-class correlation and Bland-Altman plots demonstrate that the multi-modality model had higher longitudinal segmentation consistency in all subregions while the single-modality model had low consistency in poor-quality images. Conclusion The multi-modality MRI segmentation model provides an improved biomarker for neurodegeneration in the MTL that is robust to image quality. It also provides a framework for other studies which may benefit from multimodal imaging.
Medial temporal lobe atrophy patterns in early- versus late-onset amnestic Alzheimer’s disease

A. Wuestefeld, A. Binette, D. Westen, O. Strandberg, E. Stomrud, N. Mattsson-Carlgren, S. Janelidze, Ruben Smith, S. Palmqvist, H. Baumeister, D. Berron, Paul Yushkevich, O. Hansson, N. Spotorno, and L. Wisse

bioRxiv, May 2024

Cited by 7

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Background The medial temporal lobe (MTL) is hypothesized to be relatively spared in early-onset Alzheimer’s disease (EOAD). Yet, detailed examination of MTL subfield volumes and drivers of atrophy in amnestic EOAD is lacking. Methods BioFINDER-2 participants with memory impairment, abnormal amyloid-β status and tau-PET were included. Forty-one EOAD individuals aged ≥65 years and, as comparison, late-onset AD (LOAD, ≤70 years, n=154) and Aβ-negative cognitively unimpaired controls were included. MTL subregions and biomarkers of (co-)pathologies were measured. Results AD groups showed smaller MTL subregions compared to controls. Atrophy patterns were similar across AD groups, although LOAD showed thinner entorhinal cortices compared to EOAD. EOAD showed lower WMH compared to LOAD. No differences in MTL tau-PET or transactive response DNA binding protein 43-proxy positivity was found. Conclusions We found in vivo evidence for MTL atrophy in amnestic EOAD and overall similar levels to LOAD of MTL tau pathology and co-pathologies.
Pathologic and cognitive correlates of plasma biomarkers in neurodegenerative disease

K. Cousins, Jeffrey S. Phillips, Sandhitsu R. Das, Kyra S. O’Brien, T. Tropea, A. Chen-Plotkin, Leslie M. Shaw, I. Nasrallah, D. Mechanic-Hamilton, Corey T. McMillan, David J. Irwin, Edward B. Lee, and D. Wolk

Alzheimer’s & Dementia, Apr 2024

Cited by 17

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We investigate pathological correlates of plasma phosphorylated tau 181 (p‐tau181), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) across a clinically diverse spectrum of neurodegenerative disease, including normal cognition (NormCog) and impaired cognition (ImpCog).
Genetic associations with dementia‐related proteinopathy: Application of item response theory

Y. Katsumata, D. Fardo, Lincoln M. P. Shade, Xian Wu, S. Karanth, T. Hohman, J. Schneider, David A Bennett, J. Farfel, Kathryn M. Gauthreaux, Charles N. Mock, W. Kukull, E. Abner, Peter T Nelson, Maria Eric M. Kewei Donna Robert C. Carole Adam Andrew J Carrillo Reiman Chen Masterman Green Ho Fleisher S, Maria C Carrillo, E. Reiman, Kewei Chen, Donna Masterman, Robert C. Green, Carole Ho, A. Fleisher, A. Saykin, K. Nho, L. Apostolova, S. Risacher, Jonathan Jackson, A. Forghanian-Arani, Bret J. Borowski, C. Ward, C. Schwarz, C. Jack, David Jones, J. Gunter, K. Kantarci, M. Senjem, P. Vemuri, Robert I. Reid, Ronald C. Petersen, John K. Hsiao, W. Potter, Eliezer Masliah, Laurie Ryan, M. Bernard, N. Silverberg, A. Kormos, C. Conti, D. Veitch, D. Flenniken, D. Sacrey, and 99 more authors

Alzheimer’s & Dementia, Mar 2024

Cited by 7

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Although dementia‐related proteinopathy has a strong negative impact on public health, and is highly heritable, understanding of the related genetic architecture is incomplete.
Surface-Based Parcellation and Vertex-wise Analysis of Ultra High-resolution ex vivo 7 tesla MRI in Alzheimer’s disease and related dementias

Pulkit Khandelwal, M. T. Duong, Lisa Levorse, Constanza Fuentes, Amanda E. Denning, W. Trotman, R. Ittyerah, A. Bahena, T. Schuck, M. Gabrielyan, K. Prabhakaran, Daniel T. Ohm, G. Mizsei, John L. Robinson, M. M. López, John A. Detre, Edward B. Lee, David J. Irwin, Corey T. McMillan, M. Tisdall, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

In MLCN@MICCAI, Mar 2024

Cited by 3

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Magnetic resonance imaging (MRI) is the standard modality to understand human brain structure and function in vivo (antemortem). Decades of research in human neuroimaging has led to the widespread development of methods and tools to provide automated volume-based segmentations and surface-based parcellations which help localize brain functions to specialized anatomical regions. Recently ex vivo (postmortem) imaging of the brain has opened-up avenues to study brain structure at sub-millimeter ultra high-resolution revealing details not possible to observe with in vivo MRI. Unfortunately, there has been limited methodological development in ex vivo MRI primarily due to lack of datasets and limited centers with such imaging resources. Therefore, in this work, we present one-of-its-kind dataset of 82 ex vivo T2w whole brain hemispheres MRI at 0.3 mm isotropic resolution spanning Alzheimer’s disease and related dementias. We adapted and developed a fast and easy-to-use automated surface-based pipeline to parcellate, for the first time, ultra high-resolution ex vivo brain tissue at the native subject space resolution using the Desikan-Killiany-Tourville (DKT) brain atlas. This allows us to perform vertex-wise analysis in the template space and thereby link morphometry measures with pathology measurements derived from histology. We will open-source our dataset docker container, Jupyter notebooks for ready-to-use out-of-the-box set of tools and command line options to advance ex vivo MRI clinical brain imaging research on the project webpage.
Comparison of histological delineations of medial temporal lobe cortices by four independent neuroanatomy laboratories

A. Wuestefeld, H. Baumeister, Jenna N. Adams, R. Flores, Carl J. Hodgetts, N. Mazloum-Farzaghi, R. Olsen, Vyash Puliyadi, Tammy T. Tran, A. Bakker, K. Canada, M. Dalton, Ana M. Daugherty, R. La Joie, Lei Wang, M. Bedard, Esther Buendia, E. Chung, Amanda E. Denning, María Del Mar Arroyo-Jiménez, Emilio Artacho-Pérula, D. Irwin, R. Ittyerah, Edward B. Lee, Sydney A. Lim, María Del Pilar Marcos-Rabal, Maria Mercedes Iñiguez Onzoño Martin, M. M. López, Carlos Rosa Prieto, T. Schuck, W. Trotman, A. Vela, Paul Yushkevich, K. Amunts, Jean C. Augustinack, Song-Lin Ding, R. Insausti, O. Kedo, D. Berron, and L. Wisse

Hippocampus, Feb 2024

Cited by 11

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The medial temporal lobe (MTL) cortex, located adjacent to the hippocampus, is crucial for memory and prone to the accumulation of certain neuropathologies such as Alzheimer’s disease neurofibrillary tau tangles. The MTL cortex is composed of several subregions which differ in their functional and cytoarchitectonic features. As neuroanatomical schools rely on different cytoarchitectonic definitions of these subregions, it is unclear to what extent their delineations of MTL cortex subregions overlap. Here, we provide an overview of cytoarchitectonic definitions of the entorhinal and parahippocampal cortices as well as Brodmann areas (BA) 35 and 36, as provided by four neuroanatomists from different laboratories, aiming to identify the rationale for overlapping and diverging delineations. Nissl‐stained series were acquired from the temporal lobes of three human specimens (two right and one left hemisphere). Slices (50 μm thick) were prepared perpendicular to the long axis of the hippocampus spanning the entire longitudinal extent of the MTL cortex. Four neuroanatomists annotated MTL cortex subregions on digitized slices spaced 5 mm apart (pixel size 0.4 μm at 20× magnification). Parcellations, terminology, and border placement were compared among neuroanatomists. Cytoarchitectonic features of each subregion are described in detail. Qualitative analysis of the annotations showed higher agreement in the definitions of the entorhinal cortex and BA35, while the definitions of BA36 and the parahippocampal cortex exhibited less overlap among neuroanatomists. The degree of overlap of cytoarchitectonic definitions was partially reflected in the neuroanatomists’ agreement on the respective delineations. Lower agreement in annotations was observed in transitional zones between structures where seminal cytoarchitectonic features are expressed less saliently. The results highlight that definitions and parcellations of the MTL cortex differ among neuroanatomical schools and thereby increase understanding of why these differences may arise. This work sets a crucial foundation to further advance anatomically‐informed neuroimaging research on the human MTL cortex.
Correction: Baseline structural MRI and plasma biomarkers predict longitudinal structural atrophy and cognitive decline in early Alzheimer’s disease

Long Xie, Sandhitsu R. Das, L. Wisse, R. Ittyerah, R. Flores, Leslie M. Shaw, Paul Yushkevich, and D. Wolk

Alzheimer’s Research & Therapy, Jan 2024

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Surface-based parcellation and vertex-wise analysis of ultra high-resolution ex vivo 7 tesla MRI in neurodegenerative diseases

Pulkit Khandelwal, M. T. Duong, Constanza Fuentes, Amanda E. Denning, W. Trotman, R. Ittyerah, A. Bahena, T. Schuck, M. Gabrielyan, K. Prabhakaran, Daniel T. Ohm, G. Mizsei, John L. Robinson, M. M. López, John A. Detre, Edward B. Lee, David J. Irwin, Corey McMillan, M. Tisdall, Sandhitsu R. Das, David Wolk, and Paul Yushkevich

ArXiv, Jan 2024

DOI

2023

Tau maturation in clinicopathological spectrum of Lewy body and Alzheimer’s disease

Sanaz Arezoumandan, K. Cousins, DT Ohm, MaKayla Lowe, J. Phillips, C. Mcmillan, A. Siderowf, A. Chen-Plotkin, Andres Deik, Meredith Spindler, T. Tropea, D. Weintraub, D. Wolk, M. Grossman, Eddie B. Lee, and David J. Irwin

Alzheimer’s & Dementia, Dec 2023

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In Alzheimer’s disease neuropathologic change (ADNC), maturation of neurofibrillary tangles and tau pathology are characterized by posttranslational modifications of tau. ANDC and Lewy body disease (LBD) commonly co‐exist in aging brains and there are overlapping clinical syndromes and heterogeneity in clinical features among cases with mixed ADNC and LBD pathology. Given this clinical and pathological overlap, we examined the postmortem expression of tau conformational epitopes that mark various stages of tangle maturation in clinicopathologic spectrum of Alzheimer’s disease (AD) and LBD.
Comparison of histological delineation of the entorhinal, perirhinal, ectorhinal, and parahippocampal cortices by different neuroanatomy laboratories

H. Baumeister, A. Wuestefeld, Jenna N. Adams, Arnold Bakker, A. M. Daugherty, R. Flores, Carl J. Hodgetts, R. La Joie, N. Mazloum-Farzaghi, R. Olsen, Vyash Puliyadi, C. Stark, Tammy T. Tran, Lei Wang, Paul Yushkevich, K. Amunts, Jean C. Augustinack, Song‐Lin Ding, R. Insausti, O. Kedo, D. Berron, and L. Wisse

Alzheimer’s & Dementia, Dec 2023

Cited by 1

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The medial temporal lobe (MTL) cortex, located adjacent to the hippocampus, is crucial for memory and a hotspot of neurodegenerative processes (e.g., accumulation of tau tangles or TDP‐43). Importantly, the MTL cortex comprises several subregions with distinct functional, cytoarchitectonic, and macro‐anatomical features (Fig. 1). In vivo imaging studies measuring atrophy or aggregates of pathologies in these subregions rely on various segmentation protocols. Comparability of these imaging studies is limited as segmentation protocols differ, which results from different macro‐anatomical parcellations and cytoarchitectonic definitions of MTL subregions. Thus, it must be clarified to which extent definitions of MTL subregions overlap between neuroanatomists, to establish a harmonized MTL magnetic resonance imaging (MRI) segmentation protocol. We give an overview of cytoarchitectonic definitions of MTL cortex subregions provided by four neuroanatomists from independent laboratories.
Medial temporal lobe gray matter microstructure alterations provide improved sensitivity to detect neurodegeneration associated with Alzheimer’s disease biomarkers

Christopher A. Brown, Sandhitsu R. Das, Long Xie, I. Nasrallah, John A. Detre, C. McMillan, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Dec 2023

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Despite the strengths conventional structural imaging measures to detect atrophy, cross‐sectional relationships between neurodegeneration and Alzheimer’s disease (AD) biomarkers in early stages is limited. Neurite orientation dispersion and density imaging (NODDI) measures microstructural alterations that are unique from conventional structural metrics. Alterations in microstructure have been detected in individuals with AD compared to cognitively normal individuals, but there is sparse data regarding the relationship between these metrics and AD biomarkers. Here we sought to characterize how NODDI metrics in the medial temporal lobe (MTL) are associated with plasma AD biomarkers.
A (Sub)field Guide to Quality Control in Hippocampal Subfield Segmentation on Highresolution T2-weighted MRI

K. Canada, N. Mazloum-Farzaghi, G. Rådman, J.N. Adams, A. Bakker, H. Baumeister, D. Berron, M. Bocchetta, V. Carr, M. A. Dalton, R. Flores, A. Keresztes, R. La Joie, S. Mueller, N. Raz, T. Santini, T. Shaw, C. Stark, T. Tran, L. Wang, L. Wisse, A. Wuestefeld, Paul Yushkevich, R. Olsen, and A. M. Daugherty

bioRxiv, Dec 2023

Cited by 1

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Inquiries into properties of brain structure and function have progressed due to developments in magnetic resonance imaging (MRI). To sustain progress in investigating and quantifying neuroanatomical details in vivo, the reliability and validity of brain measurements are paramount. Quality control (QC) is a set of procedures for mitigating errors and ensuring the validity and reliability of brain measurements. Despite its importance, there is little guidance on best QC practices and reporting procedures. The study of hippocampal subfields in vivo is a critical case for QC because of their small size, inter-dependent boundary definitions, and common artifacts in the MRI data used for subfield measurements. We addressed this gap by surveying the broader scientific community studying hippocampal subfields on their views and approaches to QC. We received responses from 37 investigators spanning 10 countries, covering different career stages, and studying both healthy and pathological development and aging. In this sample, 81% of researchers considered QC to be very important or important, and 19% viewed it as fairly important. Despite this, only 46% of researchers reported on their QC processes in prior publications. In many instances, lack of reporting appeared due to ambiguous guidance on relevant details and guidance for reporting, rather than absence of QC. Here, we provide recommendations for correcting errors to maximize reliability and minimize bias. We also summarize threats to segmentation accuracy, review common QC methods, and make recommendations for best practices and reporting in publications. Implementing the recommended QC practices will collectively improve inferences to the larger population, as well as have implications for clinical practice and public health.
T1 MRI reveals differential hippocampal atrophy in Lewy Body Disorders with and without Alzheimer’s copathology

Jesse S. Cohen, Jeffrey S. Phillips, Sandhitsu R. Das, E. Rhodes, K. Cousins, Paul Yushkevich, D. Wolk, D. Weintraub, David J. Irwin, and C. McMillan

Alzheimer’s & Dementia, Dec 2023

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Lewy body disorders (LBD) include Parkinson disease (PD), Parkinson disease dementia (PDD), and dementia with Lewy bodies (DLB). LBD are the second leading cause of neurodegenerative dementia after Alzheimer’s disease (AD). An estimated 50% of LBD patients have coexisting AD pathology (LBD+AD), which correlates with shorter time to dementia and death. Autopsy evidence suggests that verbal memory impairment correlates with the severity of hippocampal tau pathology in LBD. However, it is unknown whether greater hippocampal tau burden in LBD+AD causes neurodegeneration detectable by in vivo structural MRI, and whether hippocampal atrophy explains verbal memory impairment.
Evaluation of quantitative measurements of tau pathology with semi‐quantitative ratings and age

Amanda E. Denning, R. Ittyerah, Niyousha Sadeghpour, E. Chung, S. Ravikumar, S. Sadaghiani, N. Capp, Eric Teunissen-Bermeo, Sanaz Arezoumandan, Daniel T. Ohm, T. Schuck, John L. Robinson, M. Grossman, Eddie B. Lee, J. Trojanowski, L. Wisse, Sandhitsu R. Das, D. Wolk, David J. Irwin, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2023

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It is assumed quantitative digital neuropathology methods will provide more information than semi‐quantitative ratings, but this presumption lacks formal assessment. Here, we compare quantitative, whole‐slide measurements of phosphorylated tau tangles and threads with semi‐quantitative tau pathology ratings. We evaluate whether quantitative measurements provide additional prediction beyond Braak stage for variables associated with tau pathology, examining the association of quantitative tau measurements in high Braak stages with age at death and measures of severity of TDP‐43 and alpha‐synuclein co‐pathologies. We hypothesized that even within the same high Braak stage, quantitative tau measurements would decrease with age at death, as younger patients often require more tau pathology for disease severity comparable to older patients, and increase with higher co‐pathology ratings, since prior work suggests co‐pathologies increase with disease severity.
Comparison of Focal Hippocampal T2‐Weighted MRI and Whole‐Brain T1‐Weighted MRI for Detection of Longitudinal Atrophy Using Deep Learning‐Based and Conventional Approaches

M. Dong, Long Xie, L. Wisse, R. Flores, Jiancong Wang, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2023

Cited by 1

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Longitudinal measurement of medial temporal lobe (MTL) atrophy is shown to be effective in measuring Alzheimer’s disease (AD) progression and has been extensively studied on T1‐weighted MRI. However, there has been little work analyzing atrophy on high‐resolution T2‐weighted MRI of the hippocampal region, and it is unknown which MRI modality would yield a more effective biomarker of disease progression. We compare atrophy measurements derived from T1 and T2‐weighted MRI using a deep learning framework DeepAtrophy and a deformation‐based morphometry method ALOHA.
Genetic variants underlying the neuro‐anatomical signatures of hypertension measured on structural MRI

S. T. Govindarajan, E. Mamourian, Yu-Han Cui, Jun-Hao Wen, G. Erus, A. Abdulkadir, Randa Melhem, R. Bryan, Hao-Chang Shou, D. Wolk, I. Nasrallah, and Christos Davatzikos

Alzheimer’s & Dementia, Dec 2023

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Hypertension (HTN) is associated with gray matter (GM) atrophy and increased white matter hyperintensity (WMH) burden, increasing their susceptibility to Alzheimer’s disease and related dementias. We developed a machine learning based model to quantify spatial patterns of abnormality recognizing HTN‐related brain changes (SPARE‐HTN) from structural magnetic resonance images (sMRI). We performed a genome wide association study (GWAS) to identify the genetic variants and associated biological traits that underlie the “expression” of HTN‐related brain changes, i.e., the individualized SPARE‐HTN index.
Investigating drug repurposing for the prevention of Alzheimer’s disease and related dementias using electronic health records in the University of Pennsylvania Health System

Lu Li, Qiong Wu, S. Lundin, A. Naj, R. Gur, K. Rascovsky, D. Wolk, Cui Tao, and Yong Chen

Alzheimer’s & Dementia, Dec 2023

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Alzheimer’s disease and related dementias (ADRDs) are a group of complex neurodegenerative diseases and disorders that pose a growing global public health burden. Developing new treatments for ADRDs has been difficult and there is a pressing need for new therapeutic options. Drug repurposing, which involves finding new uses for existing drugs, has gained increasing attention as a potential strategy for ADRD prevention. Here we aimed to identify drugs that may be repurposed for Alzheimer’s disease (AD) or ADRD prevention using a data‐driven approach from a large multi‐site electronic health record (EHR) database.
Tau‐neurodegeneration mismatch reveals vulnerability and resilience to comorbidities in Alzheimer’s continuum

Xueying Lyu, M. T. Duong, Long Xie, R. Flores, Hayley M. Richardson, Gyujoon Hwang, L. Wisse, Michael Dicalogero, C. McMillan, John L. Robinson, Sharon X. Xie, Edward B. Lee, David J. Irwin, B. Dickerson, C. Davatzikos, I. Nasrallah, Paul Yushkevich, D. Wolk, and Sandhitsu R. Das

Alzheimer’s & Dementia, Dec 2023

Cited by 17

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Variability in relationship of tau‐based neurofibrillary tangles (T) and neurodegeneration (N) in Alzheimer’s disease (AD) arises from non‐specific nature of N, modulated by non‐AD co‐pathologies, age‐related changes, and resilience factors.
tau‐neurodegeneration mismatch from inter‐modality image translation using deep learning

Xueying Lyu, Pulkit Khandelwal, M. T. Duong, Jiancong Wang, Long Xie, L. Wisse, Paul Yushkevich, Sandhitsu R. Das, and D. Wolk

Alzheimer’s & Dementia, Dec 2023

Cited by 1

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The relationship between tau neurofibrillary tangles (T) and neurodegeneration (N) may offer clues to potential presence of comorbidities, as well as relative resilience and vulnerability to Alzheimer’s disease (AD) pathology. We have previously developed measures of tau PET (T) and cortical thickness (N) mismatch based on linear model residuals. However, the underlying relationships between T and N are likely complex and non‐linear. Moreover, predicting cortical thickness based on local tau level may miss non‐local contributions of tauopathy. Here we investigate T‐N mismatch using a deep‐learning 3D image translation neural network to estimate synthetic maps of cortical thickness based on tau PET images. Deviation between the synthetic and actual cortical thickness serves as a metric of T‐N mismatch.
Remote App‐Based Assessment of Memory and Executive Functioning in Aging and Pre‐Clinical Alzheimer’s Disease in a Diverse Sample of Older Adults

D. Mechanic-Hamilton, Kimberly Halberstadter, Rachel Rovere, Erin Liebenberg, and D. Wolk

Alzheimer’s & Dementia, Dec 2023

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Mobile, valid and engaging cognitive assessments are essential for detecting and tracking change in research participants and patients at risk for Alzheimer’s Disease and Related Dementias (ADRDs). This pilot study aims to determine the feasibility and generalizability of at‐home, app‐based cognitive assessments included in the mobile cognitive app performance platform (mCAPP), to detect cognitive changes associated with aging and preclinical AD.
Circulating brain‐enriched microRNAs as peripheral biomarkers of neurodegeneration

Alidad Mireskandari, Gyanendra Kumar, Arzu Kunwar, Kenny K. Ablordeppey, Michael Kiefer, D. Wolk, Kira S. Sheinerman, and Samuil R. Umansky

Alzheimer’s & Dementia, Dec 2023

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Minimally invasive diagnostic tools are needed to better characterize heterogeneous groups of patients with mild cognitive impairment (MCI), pre‐MCI, and dementia. At DiamiR, we developed an approach based on targeted selection and quantitative analysis of microRNAs enriched in specific brain regions, present in synapses, and detectable in blood plasma. microRNAs are short, non‐coding regulatory molecules whose levels change in disease.
Hippocampal Enlargement and White Matter Hyperintensities in Obstructive Sleep Apnea Patients

Manasa Mula, Alex Mathew, Sandhitsu R. Das, I. Nasrallah, R. Bryan, John A. Detre, Tammie L. S. Benzinger, D. Wolk, Alexandra Hanlon, Alicia Lozano, Stephen T. Moelter, L. Chi, E. Davis, Cindy Cheng, Abhinav Bhamidipati, N. Gooneratne, and Kathy C. Richards

Alzheimer’s & Dementia, Dec 2023

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Obstructive sleep apnea (OSA), which results from recurrent collapses of the upper airway system, affects around 27% of the geriatric population with mild cognitive impairment (MCI) and causes intermittent hypoxia and sleep fragmentation (Mubashir et al., 2019). Prior research suggests that OSA results in brain ischemic preconditioning, causing hippocampal enlargement due to adaptive hippocampal neurogenesis (Rosenzweig et al., 2013). OSA has also been linked to increased white matter hyperintensities (WMHs) through hypoxic‐ ischemic injury, which contribute to cognitive decline in dementias such as Alzheimer’s disease (Zacharias et al., 2021). Previous research necessitates studying the effects of apnea in an elderly population with MCI.
Pyramidal neurodegeneration is linked to select cytoarchitecture and cognitive impairment in behavioral variant frontotemporal dementia with tau or TDP‐43 pathology

Daniel T. Ohm, A. Bahena, Sanaz Arezoumandan, K. Cousins, J. Phillips, N. Capp, W. Trotman, Emily Xie, D. Wolk, C. Mcmillan, J. Trojanowski, Eddie B. Lee, M. Grossman, and David J. Irwin

Alzheimer’s & Dementia, Dec 2023

Cited by 1

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The behavioral variant of frontotemporal dementia (bvFTD) is primarily caused by either tauopathies (bvFTD‐tau) or TDP‐43 (bvFTD‐TDP) proteinopathies. Frontal cortices are often the earliest sites of degeneration in bvFTD, and previous studies suggest bvFTD‐tau and bvFTD‐TDP share similar patterns of pyramidal neurodegeneration in infragranular layers of agranular cortices. However, neurodegeneration in other cortical layers in more laminated (dysgranular‐to‐granular) cytoarchitecture in bvFTD remain poorly understood. We recently reported that infragranular layers throughout agranular‐to‐granular regions accumulate more protein inclusions in bvFTD‐tau than bvFTD‐TDP. Thus, the current study tested the hypothesis that pyramidal neurodegeneration is greater in more laminated regions of bvFTD‐tau than bvFTD‐TDP and relates to frontal‐mediated cognitive impairment.
A multivariate MRI model of Alzheimer’s disease risk is associated with clinical diagnosis, PET imaging, and plasma biomarkers in a mixed dementia sample

J. Phillips, S. T. Govindarajan, Gyujoon Hwang, G. Erus, K. Cousins, Sandhitsu R. Das, D. Wolk, David J. Irwin, M. Grossman, I. Nasrallah, and Christos Davatzikos

Alzheimer’s & Dementia, Dec 2023

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We sought to validate two structural MRI‐based brain health models: Spatial Pattern of Atrophy for REcognition of Alzheimer’s disease (SPARE‐AD) and SPARE‐Brain Age Gap (SPARE‐BAG), which estimates the discrepancy between biological brain age and chronological age. These models’ generalization to non‐amnestic AD (naAD) syndromes and associations with positron emission tomography (PET) and plasma biomarkers remain underinvestigated. We hypothesized that SPARE‐AD scores in naAD would be lower (less abnormal) than in amnestic AD (aAD) but elevated (more abnormal) relative to controls; and that SPARE‐AD but not SPARE‐BAG scores would be associated with PET and plasma biomarkers of AD.
Quantifying associations of four major proteinopathies with grey matter atrophy: an imaging‐pathology study

Jeffrey S. Phillips, John L. Robinson, K. Cousins, Sandhitsu R. Das, Paul Yushkevich, D. Wolk, Eddie B. Lee, C. McMillan, J. Trojanowski, M. Grossman, and David J. Irwin

Alzheimer’s & Dementia, Dec 2023

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Gross atrophy observed on MRI provides a clinically useful marker of possible neurodegenerative disease. However, autopsy studies of polypathology suggest atrophy is likely driven not by a single proteinopathy but also co‐pathologies. We hypothesized that in a clinically heterogeneous autopsy sample, amyloid‐ß, tau, a‐synuclein, and TDP‐43, would co‐occur within regions, and that co‐pathologies would have independent associations with grey matter atrophy.
Using an ex vivo MRI atlas of the human medial temporal lobe to characterize the 3D distribution of neurofibrillary tangle burden across histologically defined subregions

S. Ravikumar, Amanda E. Denning, Sydney A. Lim, E. Chung, R. Ittyerah, L. Wisse, Long Xie, Sandhitsu R. Das, John L. Robinson, T. Schuck, M. Grossman, Eddie B. Lee, D. Tisdall, K. Prabhakaran, John A. Detre, G. Mizsei, E. Artacho-Pérula, Maria Mercedes Iniguez Onzono Martin, Maria Mar Arroyo Jimenez, M. Muñoz, Francisco Javier Molina Romero, Maria Pilar Marcos Rabal, S. C. Sánchez, José Carlos Delgado González, Carlos-de-la Rosa Prieto, Marta Córcoles Parada, David J. Irwin, J. Trojanowski, D. Wolk, R. Insausti, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2023

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Accumulation of tau neurofibrillary tangles (NFT) in the medial temporal lobe (MTL) is an early pathological change associated with neurodegeneration in Alzheimer’s Disease (AD). Current understanding of the spread of NFTs within the MTL is based on 2‐D histological sections sampled at sparse locations. Here, using human MTL specimens from donors with diagnoses spanning the AD continuum, we examine 3‐D quantitative maps of NFT burden derived from serial histology leveraging a high‐resolution, ex vivo MRI atlas, thus enabling more granular analyses.
Developing an anatomically valid segmentation protocol for early tau regions: the anterior medial temporal lobe cortices

Niyousha Sadeghpour, R. Ittyerah, Amanda E. Denning, W. Trotman, Sydney A. Lim, E. Chung, S. Sadaghiani, K. Prabhakaran, M. Bedard, Daniel T. Ohm, T. Schuck, E. Artacho-Pérula, Maria Mercedes Iniguez Onzono Martin, M. Muñoz, Francisco Javier Molina Romero, José Carlos Delgado González, María Mar Arroyo Jiménez, Maria Pilar Marcos Rabal, S. C. Sánchez, C. Rosa Prieto, Marta Córcoles Parada, R. Insausti, A. Wuestefeld, C. McMillan, M. Grossman, Eddie B. Lee, John A. Detre, J. Trojanowski, D. Tisdall, David J. Irwin, D. Wolk, Paul Yushkevich, and L. Wisse

Alzheimer’s & Dementia, Dec 2023

Cited by 1

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The anterior portion of the medial temporal lobe (MTL) is one of the earliest regions showing tau deposition in Alzheimer’s disease (AD) and hence a key focus area for AD imaging biomarkers. However, the anatomical variability of the anterior MTL presents a challenge for segmentation protocols. Leveraging a novel postmortem dataset with histology and MRI, we aimed to develop a histologically‐informed segmentation protocol for the anterior entorhinal cortex (ERC), Brodmann Area (BA) 35 (approximates transentorhinal cortex), and BA36 for in vivo 3 tesla (T) MRI.
Impact of white matter hyperintensities on structural connectivity and cognition in cognitively intact ADNI participants

M. Taghvaei, D. Mechanic-Hamilton, S. Sadaghiani, Banafsheh Shakibajahromi, S. Dolui, Sandhitsu R. Das, Christopher Brown, William Tackett, Pulkit Khandelwal, Philip A. Cook, R. Shinohara, Paul Yushkevich, Danielle S. Bassett, D. Wolk, and John A. Detre

Neurobiology of aging, Dec 2023

Cited by 10

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We used indirect brain mapping with virtual lesion tractography to test the hypothesis that the extent of white matter tract disconnection due to white matter hyperintensities (WMH) is associated with corresponding tract-specific cognitive performance decrements. To estimate tract disconnection, WMH masks were extracted from FLAIR MRI data of 481 cognitively intact participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and used as regions of avoidance for fiber tracking in diffusion MRI data from 50 healthy young participants from the Human Connectome Project. Estimated tract disconnection in the right inferior fronto-occipital fasciculus, right frontal aslant tract, and right superior longitudinal fasciculus mediated the effects of WMH volume on executive function. Estimated tract disconnection in the left uncinate fasciculus mediated the effects of WMH volume on memory and in the right frontal aslant tract on language. In a subset of ADNI control participants with amyloid data, positive status increased the probability of periventricular WMH and moderated the relationship between WMH burden and tract disconnection in executive function performance.
Impact of white matter hyperintensities on structural connectivity and cognition in cognitively intact ADNI participants.

M. Taghvaei, D. Mechanic-Hamilton, S. Sadaghiani, Banafsheh Shakibajahromi, Sudipto Dolui, Sandhitsu R. Das, Christopher Brown, William Tackett, Pulkit Khandelwal, Philip A Cook, Russell T. Shinohara, Paul Yushkevich, Danielle S. Bassett, D. Wolk, and John A. Detre

Neurobiology of aging, Dec 2023

Cited by 4

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We used indirect brain mapping with virtual lesion tractography to test the hypothesis that the extent of white matter tract disconnection due to white matter hyperintensities (WMH) is associated with corresponding tract-specific cognitive performance decrements. To estimate tract disconnection, WMH masks were extracted from FLAIR MRI data of 481 cognitively intact participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and used as regions of avoidance for fiber tracking in diffusion MRI data from 50 healthy young participants from the Human Connectome Project. Estimated tract disconnection in the right inferior fronto-occipital fasciculus, right frontal aslant tract, and right superior longitudinal fasciculus mediated the effects of WMH volume on executive function. Estimated tract disconnection in the left uncinate fasciculus mediated the effects of WMH volume on memory and in the right frontal aslant tract on language. In a subset of ADNI control participants with amyloid data, positive status increased the probability of periventricular WMH and moderated the relationship between WMH burden and tract disconnection in executive function performance.
Effects of Alzheimer’s disease genetic risk on brain morphometric development in three multiple‐ancestry pediatric datasets

J. Vogel, Laura M. Schultz, B. Larsen, Jakob Seidlitz, N. Al-Sharif, R. Barzilay, M. Cieslak, S. Covitz, Raquel E. Gur, R. Gur, Guillaume Huguet, R. La Joie, C. Mcmillan, Nathalie I. V. Nilsson, J. Poline, K. Ruparel, R. Shinohara, L. Wisse, Daniel H. Wolf, D. Wolk, A. Alexander-Bloch, Laura Almasy, and Theodore Satterthwaite

Alzheimer’s & Dementia, Dec 2023

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Few prior studies have investigated whether genetic risk for Alzheimer’s disease (AD) can manifest through altered neurodevelopment of AD‐vulnerable brain regions. This pre‐registered study tests the effects of AD polygenic risk on morphometric neurodevelopment across 3 large datasets totaling 8,364 youths aged 3‐22 (Table 1)
A multi‐site study of Alzheimer’s disease neuroimaging and cognitive biomarkers in 2819 cognitively normal individuals

Long Xie, Sandhitsu R. Das, L. Wisse, Xueying Lyu, Emily McGrew, R. Flores, Eli Gibson, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Dec 2023

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Developing effective Alzheimer’s disease (AD) biomarkers in cognitively normal (CN) individuals is crucial. Prior studies have identified neuroimaging and cognitive measures that are sensitive to preclinical AD. However, the generalizability of these biomarkers in large, multi‐site cohorts and their power to predict disease progression remain unclear. Structural MRI, tau PET and standardized cognitive tests of 2819 CN adults were pooled from three studies to investigate the power of these measures in discriminating ß‐amyloid positivity (A+/‐) and predicting disease progression.
Differential A/T/N Networks of Cerebrospinal Fluid and Neuroimaging Biomarkers and their Prediction of Cognition between Self‐reported Black/African American and Non‐Hispanic White Individuals

C. Xiong, Rui-Jin Lu, J. Lah, D. Wolk, C. Gleason, E. Roberson, Suzanne E. Schindler, T. Benzinger, Leslie M. Shaw, C. Manzanares, De-Qiang Qiu, Jason J. Hassenstab, K. Moulder, Joyce E. Balls-Berry, R. Sperling, K. Johnson, A. Levey, Sterling C. Johnson, Emily N. Gremminger, Folasade Agboola, E. Grant, Russ C. Hornbeck, Parinaz Massoumzadeh, S. Keefe, Donna L. Dierker, Julia D. Gray, Rachel L. Henson, Marissa L. Streitz, D. Mechanic-Hamilton, S. Stites, and J. C. Morris

Alzheimer’s & Dementia, Dec 2023

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Differences in absolute levels of individual biomarkers from cerebrospinal fluid (CSF), amyloid PET, and MRI imaging between self‐reported Black and White individuals were reported. How the A/T/N network of AD biomarkers is biologically connected within a racialized group and whether it predicts cognition differentially between groups remain unknown.
Discovering Alzheimer’s disease subtypes with imaging and genetic signatures via multi‐view weakly‐supervised deep clustering

Zhi-Jian Yang, Jun-Hao Wen, A. Abdulkadir, Yu-Han Cui, G. Erus, E. Mamourian, Randa Melhem, D. Srinivasan, S. T. Govindarajan, Jiong Chen, M. Habes, Colin L. Masters, P. Maruff, J. Fripp, L. Ferrucci, Marilyn S. Albert, Sterling C. Johnson, John C. Morris, P. LaMontagne, Daniel S. Marcus, T. Benzinger, D. Wolk, Li Shen, J. Bao, S. Resnick, D. Tosun, Hao-Chang Shou, I. Nasrallah, and Christos Davatzikos

Alzheimer’s & Dementia, Dec 2023

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The heterogeneity of neurodegenerative diseases, including Alzheimer’s disease (AD), has hampered precision diagnosis and treatment. Machine learning methods enable the identification of genetically‐explained disease subtypes with distinct brain phenotypes.
Mapping Medial Temporal Lobe Longitudinal Change in Preclinical Alzheimer’s Disease

Paul Yushkevich, Long Xie, L. Wisse, M. Dong, S. Ravikumar, R. Ittyerah, R. Flores, Sandhitsu R. Das, and D. Wolk

Alzheimer’s & Dementia, Dec 2023

Cited by 4

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The medial temporal lobe (MTL) is a site of early tau pathology and neurodegeneration in AD. In recent work [1], we reported that rates of change in MTL subregion volumes on longitudinal structural T1‐MRI differ significantly between cognitively unimpaired individuals with and without amyloid pathology (A+CU vs A‐CU), suggesting that these measures are effective biomarkers for tracking disease progression in preclinical AD. Here, we develop a specialized pipeline that quantifies pointwise longitudinal change across the MTL, revealing more informative spatial patterns of early neurodegeneration than summary volumetric longitudinal measures.
Cross‐scale functional connectivity patterns of the aging brain learned from the multi‐cohort iSTAGing study

Zhen Zhou, Hong-Ming Li, C. Tran, Yuncong Ma, D. Srinivasan, A. Abdulkadir, Jun-Hao Wen, G. Erus, E. Mamourian, I. Nasrallah, Nick Bryan, D. Wolk, Lori L. Beason-Held, Susan M. Resnick, Hao-Chang Shou, Christos Davatzikos, and Yong Fan

Alzheimer’s & Dementia, Dec 2023

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Brain functional connectivity (FC) measures derived from resting‐state fMRI (rsfMRI) data have advanced our understanding of the brain organization. However, most existing studies investigate the brain functional networks (FNs) at a specific scale, ignoring potentially complementary FC information at different levels of spatial granularity as well as the cross‐scale information. Given that the brain is a multi‐scale, hierarchical system, FCs between FNs at different spatial scales may provide complementary information to those measured within‐scales for characterizing the aging brain.
97 Looking in the Webcam Reflection: A Scoping Review of Videoconferencing-Based Teleneuropsychological Assessment Since the Start of the COVID-19 Pandemic

Stan Colcombe, L. Crivelli, Joshua Fox-Fuller, Preeti Sunderaraman, C. Cullum, Yakeel T. Quiroz, Dawn Mechanic-Hamilton, Kimberly Halberstadter, M. Dicalogero, Rachel Rovere, La’cendria Pulley, and David A Wolk

Journal of the International Neuropsychological Society, Nov 2023

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Objective: Following the start of the SARS-COV-2 (COVID-19) pandemic there was a rapid uptake in teleneuropsychology (TeleNP). Many clinicians and researchers used videoconferencing technologies (e.g., Zoom®) to conduct remote neuropsychological assessments. Prior reviews (e.g., Marra et al., 2020) have indicated promise for the use of videoconference-based approaches to cognitive assessment under certain circumstances, though arguably nobody foresaw the widespread use of teleNP during the pandemic. Given the rapid expansion in the teleNP literature in the past couple of years, in this scoping review we specifically discuss research updates made during the COVID-19 pandemic pertaining to teleNP assessment of adults conducted via videoconferencing and their potential clinical applications. Participants and Methods: GoogleScholar and PubMed were used to search for peer-reviewed original research articles published between January 1, 2020 (i.e., the approximate beginning of the COVID-19 pandemic) and August 1, 2022. Broad search terms were used pertaining to teleNP, remote cognitive assessment, videoconferencing, and neuropsychological assessment, resulting in 16 articles. Results: Though most of the included studies were based in the United States (n=5), there was international representation across studies (Chile=1; United Kingdom=1; Australia=2; New Zealand=1; France=2; Greece=1; Japan=2, Singapore=1). All of the identified articles examined TeleNP-related research questions using cognitive tests administered via videoconferencing that have been previously studied in-person to varying degrees. Several of the studies focused on psychometric characterization (i.e., reliability and validity) of the examined tests when delivered via videoconferencing, whereas others focused on demonstrating the relative equivalence of neuropsychological scores obtained via videoconferencing versus in-person evaluations. Conclusions: Formal psychometric studies of traditional in-person neuropsychological tests delivered via videoconferencing since the start of the COVID-19 pandemic suggest that this remote modality of assessment is generally reliable and valid. Moreover, multiple recent studies have demonstrated relative equivalence of neuropsychological scores obtained via videoconferencing versus neuropsychological test scores obtained in-person. When considered alongside teleNP research conducted prior to the COVID-19 pandemic (e.g. Cullum et al., 2014), recent studies on videoconference-based neuropsychological assessment indicate that videoconferencing may not necessarily be a complete substitute for an in-person comprehensive evaluation given the inherent limitations of the procedure. However, teleNP via videoconferencing may be a promising tool in the neuropsychologist’s toolbox because it can help reduce common barriers to in-person neuropsychological assessment (e.g., travel time to clinics). Additional research on videoconferencing-based cognitive assessment is needed, especially in low-and-middle income countries (LMIC) and diverse populations where there may be more economic barriers to remote neuropsychological assessment relative to more economically-developed countries. Notably it is possible that research from LMIC may have been missed through the screening processes used in this review (e.g., inclusion of articles written in English).
42 Cognitive and Neuroanatomic Correlates of Olfactory Function in Cognitively Unimpaired and Impaired Older Adults

Michael Dicalogero, Vidyulata Kamath, D. Wolk, Sandhitsu R. Das, Long Xie, J. Lane, Kimberly Halberstadter, and D. Mechanic-Hamilton

Journal of the International Neuropsychological Society, Nov 2023

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Objective: Olfactory function declines during normal aging; however, accelerated olfactory decline is observed in neurodegenerative diseases, such as Alzheimer’s disease (AD). Moreover, olfactory deficits in pre-clinical AD are associated with future cognitive decline. Odor identification and memory deficits have been consistently reported in early stage AD indicating its potential sensitivity to AD pathophysiology in olfactory and limbic structures, yet few studies of olfaction have incorporated structural measures in a well-characterized cohort of older adults. In the current study we examined the association between odor identification impairment, cognition, and medial temporal lobe (MTL) sub-regions in cognitively unimpaired and impaired older adults. Participants and Methods: We enrolled 140 participants (age=72.25±6.54, 56% female, years of education=16.30±2.63, 82% Caucasian, 15% Black/AA, 3% Multiracial) from the Penn Alzheimer’s Disease Research Center Clinical Cohort. Participants completed the Sniffin’ Sticks Odor Identification Test (SS-OIT), cognitive testing (NACC UDS2 or UDS3 and additional cognitive tests), and MRI scans (3T Siemens MAGNETOM Prisma MRI scanner). For the SS-OIT, participants were presented with 16 odorants using felt-tipped pen dispensers and asked to identify each odor from four multiple-choice options. Scores range from 0 to 16. Additionally, cognitive domains were created by averaging z-scores from tests within each domain: attention, memory, language, executive function, and visuospatial. This cohort was divided into participants with unimpaired cognition (n=96) and impaired cognition (MCI, dementia; n=44) using established normative data and consensus diagnosis. Linear regressions were performed to examine the association between SS-OIT score, each cognitive domain, and MTL measurements for unimpaired and impaired groups. For all analyses, we controlled for age, race, sex, education, smoking status, and hypertension and additionally for MOCA score and intracranial volume with MTL measurements. Results: In the unimpaired group, SS-OIT significantly associated with language (p<.05). In the impaired group, SS-OIT significantly associated with language and memory (p<.05). In the unimpaired group, SS-OIT significantly associated with right anterior hippocampal volume (p<.05). In the impaired group, significant associations were found between SS-OIT and right anterior hippocampal volume (p<.05) and left hippocampal mean thickness (p<.05). Additionally, SS-OIT significantly associated with left and right entorhinal cortex volume (p<.05) and mean thickness (p<.05). Conclusions: This study reveals that lower odor identification performance is related to lower performance on measures of cognition and atrophy in MTL sub-regions in unimpaired and impaired older adults. Our findings support prior results demonstrating relationships between olfactory function, cognition, and MTL sub-regions. Specifically, olfactory function and episodic memory have been shown to follow similar patterns of decline in the course of AD, potentially reflecting AD pathology in shared regions of the MTL subserving episodic memory and olfactory function. Our findings demonstrate that reductions in both cortical thickness and grey matter volume of MTL regions are linked to olfactory deficits in individuals at risk for Alzheimer’s dementia. Future steps will include the analysis of longitudinal cognitive and imaging indices and the incorporation of fluid biomarker data.
89 Performance and Usability of a Remote App-Based Assessment of Cognition Among Older Adult Mobile Game Players and Non-Players

Kimberly Halberstadter, La’cendria Pulley, Rachel Rovere, Michael Dicalogero, D. Wolk, and D. Mechanic-Hamilton

Journal of the International Neuropsychological Society, Nov 2023

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Objective: Mobile, valid, and engaging cognitive assessments are essential for detecting and tracking change in research participants and patients at risk for Alzheimer’s Disease and Related Dementias (ADRDs). The mobile cognitive app performance platform (mCAPP) includes memory and executive functioning tasks to remotely detect cognitive changes associated with aging and preclinical Alzheimer’s disease. This study assesses participants’ comfort and subjective experiences with mCAPP as the potential utility and advantage of mobile app-based assessments for remote monitoring among older adults will depend upon usability and adoptability of such technology. Participants and Methods: The mCAPP includes three gamified tasks: (1) a memory task involving learning and matching hidden card pairs (“Concentration”) (2) a stroop-like task (“Brick Drop”), and (3) a digit-symbol coding-like task (“Space Imposters”). Participants included 37 older adults (60% female; age=72±4.4; years of education=17±2.5; 67% White) with normal cognition enrolled in the Penn ADRC cohort. Participants completed one baseline session of mCAPP in-person, followed by two weeks of at-home use with eight scheduled sessions. Information on prior experience with mobile technology and games was collected, and usability of mCAPP was measured at baseline and after 2-weeks of use with the IBM Computer Usability Satisfaction Questionnaire and the mHeath App Usability Questionnaire (MAUQ) respectively. Feedback on perceived difficulty, enjoyment, and likelihood to play mCAPP games again on their own was collected. Results: Participants completed on average 11±4.9 sessions over 2 weeks, with each session lasting 11.5±2.5 minutes. 59% of participants reported using their mobile device to play games (“mobile game players”). Performance on mCAPP tasks was slower at baseline for non-players, with trend-level differences on higher-load blocks of Space Imposters (p=.057 and .059). No differences in game performance were seen between groups after playing 8 sessions at-home. There were no differences in usability of mCAPP between groups, with average usability 8.2±1.5 (IBM, 0-9 scale) at T1 and 6.2±0.8 (MAUQ, 1-7 scale) after completion of two weeks of at-home use (TLast). Reported enjoyment was moderate to high for both groups at baseline and increased over time. Likelihood to play Concentration and Brick Drop again trended lower among nonplayers at T1 (p=.061 and .054), but not at TLast. Further, change in likelihood to play mCAPP from T1 to TLast was positive among non-players, with change for Concentration significantly higher for non-players than for players (p=.037). Conclusions: Participants were willing and able to complete at-home cognitive testing and most completed more than the assigned sessions. While participants who do not play games on their own mobile device were slower on some tasks at baseline, these differences dissipated with further play at-home. Usability and enjoyment of mCAPP games were high regardless of mobile game-playing status, and non-players demonstrated increased willingness to play mCAPP games again at the end of participation compared to baseline. This pilot study shows preliminary feasibility and adoptability of mobile app-based assessment regardless of prior experience with mobile games.
98 Remote App-Based Assessment of Memory and Executive Functioning in Aging and Pre-Clinical Alzheimer’s Disease

D. Mechanic-Hamilton, Kimberly Halberstadter, Michael Dicalogero, Rachel Rovere, La’cendria Pulley, and D. Wolk

Journal of the International Neuropsychological Society, Nov 2023

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Objective: Mobile, valid, and engaging cognitive assessments are essential for detecting and tracking change in research participants and patients at risk for Alzheimer’s Disease and Related Dementias (ADRDs). This pilot study aims to determine the feasibility and performance of app-based memory and executive functioning tasks included in the mobile cognitive app performance platform (mCAPP), to remotely detect cognitive changes associated with aging and preclinical Alzheimer’s Disease (AD). Participants and Methods: The mCAPP includes three gamified tasks: (1) a memory task that includes learning and matching hidden card pairs and incorporates increasing memory load, pattern separation features (lure vs. non-lure), and spatial memory (2) a stroop-like task (“brick drop”) with speeded word and color identification and response inhibition components and (3) a digit-symbol coding-like task (“space imposters”) with increasing pairs and incidental learning components. The cohort completed the NACC UDS3 neuropsychological battery, selected NIH Toolbox tasks, and additional cognitive testing sensitive to pre-clinical AD, within six months of the mCAPP testing. Participants included thirty-seven older adults (60% female; age=72±4.4, years of education=17±2.5; 67% Caucasian, 30% Black/AA, 3% Multiracial) with normal cognition who are enrolled in the Penn Alzheimer’s Disease Research Center (ADRC) cohort. Participants completed one in-person session and two weeks of at-home testing, with eight scheduled sessions, four in the morning and four in the afternoon. Participants also completed questionnaires and an interview about technology use and wore activity trackers to collect daily step and sleep data and answered questions about mood, anxiety, and fatigue throughout the two weeks of at-home data collection. Results: The participants completed an average of 11 at-home sessions, with the majority choosing to play extra sessions. Participants reported high usability ratings for all tasks and the majority rated the task difficulty as acceptable. On all mCAPP tasks, participant performance declined in accuracy and speed with increasing memory load and task complexity. mCAPP tasks correlated significantly with paper and pencil measures and several NIH Toolbox tasks (p<0.05). Examination of performance trends over multiple sessions indicates stabilization of performance within 4-6 sessions on memory mCAPP measures and 5-7 sessions on executive functioning mCAPP measures. Preliminary analyses indicate differences in mCAPP measures and imaging biomarkers. Conclusions: Participants were willing and able to complete at-home cognitive testing and most chose to complete more than the assigned sessions. Remote data collection is feasible and well-tolerated. We show preliminary construct validity with the UDS3 and NIH Toolbox and test-retest reliability following a period of task learning and performance improvement and stabilization. This work will help to advance remote detection and monitoring of early cognitive changes associated with preclinical AD. Future directions will include further evaluation of the relationships between mCAPP performance, behavioral states, and neuroimaging biomarkers as well as the utility of detection of practice effects in identifying longitudinal change and risk for ADRD-related cognitive decline.
A - 02 Performance and Usage of a Remote App-Based Cognitive Assessment among Older Adults with a Range of Technology Experience.

Kimberly Halberstadter, Rachel Rovere, Erin Liebenberg, D. Wolk, and D. Mechanic-Hamilton

Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists, Oct 2023

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OBJECTIVE The mobile cognitive app performance platform (mCAPP), an app-based cognitive assessment, includes memory and executive functioning tasks to remotely detect cognitive changes associated with aging and preclinical Alzheimer’s disease. This study examines the relationship between prior experience and comfort with mobile technology and subjective experiences with mCAPP. METHOD 60 older adults (73% female; age = 74 ± 4.8; education = 17 ± 2.4 years; 48% Black/African American) with normal cognition enrolled in the Penn Alzheimer’s Disease Research Center cohort completed one baseline session and two weeks of at-home mCAPP use. This study included measures of prior experience with mobile technology and games, at-home mCAPP performance and usage levels, and feedback on mCAPP usability. RESULTS 62% of participants reported using mobile devices to play games ("game-players"), and they did not differ from non-users in age or global cognitive status. Game-players self-reported significantly higher proficiency with specific mobile technology features (p = 0.028), but not perceived independence or confidence with technology. mCAPP performance differences were present at baseline but not by the 8th at-home session. Usability and enjoyment of mCAPP were high and increased for both groups. Non-players reported lower likelihood to play mCAPP games at baseline (p < 0.05), but in practice increased play frequency throughout at-home use and reported higher likelihood to play mCAPP games afterwards (p ≤ 0.001). CONCLUSION (S) Participants with varying mobile game experience-levels were willing and able to use mCAPP at-home. Both groups found mCAPP easy and enjoyable to use, and non-players particularly showed increased adoption of mCAPP. This pilot study shows preliminary feasibility of mobile app-based assessment regardless of prior experience with mobile games.
Circular-SWAT for deep learning based diagnostic classification of Alzheimer’s disease: application to metabolome data

T. Jo, Junpyo Kim, Paula Bice, K. Huynh, Tingting Wang, M. Arnold, Peter J. Meikle, C. Giles, R. Kaddurah-Daouk, A. Saykin, K. Nho, Alexandra Kueider-Paisley, P. Doraiswamy, C. Blach, Arthur Moseley, W. Thompson, L. St. John-Williams, Siamak Mahmoudiandehkhordi, Jessica D. Tenenbaum, Kathleen Welsh-Balmer, Brenda L. Plassman, S. Risacher, G. Kastenmüller, M. Arnold, Xianlin Han, R. Baillie, Rob Knight, P. Dorrestein, J. Brewer, E. Mayer, J. Labus, Pierre Baldi, Arpana Gupta, O. Fiehn, D. Barupal, Peter J. Meikle, S. Mazmanian, Dan Rader, M. Kling, L. Shaw, J. Trojanowski, Cornelia Duijin, A. Nevado-Holgado, David A Bennett, Ranga Krishnan, Ali Keshavarzian, Robin Vogt, A. Ikram, T. Hankemeier, I. Thiele, and 446 more authors

eBioMedicine, Oct 2023

Cited by 14

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Summary Background Deep learning has shown potential in various scientific domains but faces challenges when applied to complex, high-dimensional multi-omics data. Alzheimer’s Disease (AD) is a neurodegenerative disorder that lacks targeted therapeutic options. This study introduces the Circular-Sliding Window Association Test (c-SWAT) to improve the classification accuracy in predicting AD using serum-based metabolomics data, specifically lipidomics. Methods The c-SWAT methodology builds upon the existing Sliding Window Association Test (SWAT) and utilizes a three-step approach: feature correlation analysis, feature selection, and classification. Data from 997 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) served as the basis for model training and validation. Feature correlations were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA), and Convolutional Neural Networks (CNN) were employed for feature selection. Random Forest was used for the final classification. Findings The application of c-SWAT resulted in a classification accuracy of up to 80.8% and an AUC of 0.808 for distinguishing AD from cognitively normal older adults. This marks a 9.4% improvement in accuracy and a 0.169 increase in AUC compared to methods without c-SWAT. These results were statistically significant, with a p-value of 1.04 × 10ˆ-4. The approach also identified key lipids associated with AD, such as Cer(d16:1/22:0) and PI(37:6). Interpretation Our results indicate that c-SWAT is effective in improving classification accuracy and in identifying potential lipid biomarkers for AD. These identified lipids offer new avenues for understanding AD and warrant further investigation. Funding The specific funding of this article is provided in the acknowledgements section.
A - 06 Sensitivity of Remote App-Based Assessment of Cognition among Older Adults to Fatigue-Mediated Differences in Cognitive Functioning.

Erin Liebenberg, Rachel Rovere, Kimberly Halberstadter, D. Wolk, and D. Mechanic-Hamilton

Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists, Oct 2023

Cited by 1

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OBJECTIVE This study assesses the sensitivity of the mobile cognitive app performance platform (mCAPP), a mobile and engaging cognitive assessment tool, to participant reported fatigue. METHOD The mCAPP includes three gamified tasks: a memory task ("Concentration"), a stroop-like task ("Brick Drop"), and a digit-symbol coding-like task ("Space Imposters"). For all games, shorter reaction times and fewer guesses indicate better performance. The cohort included 55 participants (72.73% female; age = 71.60 ± 4.48; education = 16.71 ± 2.30; 49.1% white; 49.1% Black/African American, 1.8% Multiracial) without cognitive impairment who are enrolled in the Penn ADRC cohort. Performance was analyzed as a whole and grouped into days of high (7+) and low (0-3) fatigue (range 0-10). RESULTS The average fatigue rating was 2.61 ± 2.51. Overall, higher reported fatigue was weakly correlated with more time spent (ρ = 0.22) and a higher number of guesses on Concentration (ρ = 0.12; p-values<0.01). There was a significant difference in speed for those with high fatigue (M = 2.825) and low fatigue (M = 2.592; p = 0.018) on Space Imposters, but not on Brick Drop (p = 0.15). On Concentration, those with high fatigue needed a higher number of guesses (M = 5.356) compared to low fatigue (M = 5.095; p = 0.003) and more time was spent on individual guesses for those with high fatigue (M = 17.587) compared to low fatigue (M = 13.357; p < 0.001). CONCLUSION The mCAPP can remotely detect differences in cognitive performance in self-reported high and low fatigue states. Future studies will include looking at sleep data to determine objective measures of fatigue-related behavior and in-depth analysis of performance within-subject.
Neuroanatomical and cellular degeneration associated with a social disorder characterized by new ritualistic belief systems in a TDP-C patient vs. a Pick patient

Daniel T. Ohm, E. Rhodes, A. Bahena, N. Capp, MaKayla Lowe, Philip Sabatini, W. Trotman, Christopher A. Olm, J. Phillips, K. Prabhakaran, K. Rascovsky, L. Massimo, C. McMillan, James C. Gee, M. Tisdall, Paul Yushkevich, Edward B. Lee, M. Grossman, and D. Irwin

Frontiers in Neurology, Oct 2023

Cited by 2

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Frontotemporal dementia (FTD) is a spectrum of clinically and pathologically heterogenous neurodegenerative dementias. Clinical and anatomical variants of FTD have been described and associated with underlying frontotemporal lobar degeneration (FTLD) pathology, including tauopathies (FTLD-tau) or TDP-43 proteinopathies (FTLD-TDP). FTD patients with predominant degeneration of anterior temporal cortices often develop a language disorder of semantic knowledge loss and/or a social disorder often characterized by compulsive rituals and belief systems corresponding to predominant left or right hemisphere involvement, respectively. The neural substrates of these complex social disorders remain unclear. Here, we present a comparative imaging and postmortem study of two patients, one with FTLD-TDP (subtype C) and one with FTLD-tau (subtype Pick disease), who both developed new rigid belief systems. The FTLD-TDP patient developed a complex set of values centered on positivity and associated with specific physical and behavioral features of pigs, while the FTLD-tau patient developed compulsive, goal-directed behaviors related to general themes of positivity and spirituality. Neuroimaging showed left-predominant temporal atrophy in the FTLD-TDP patient and right-predominant frontotemporal atrophy in the FTLD-tau patient. Consistent with antemortem cortical atrophy, histopathologic examinations revealed severe loss of neurons and myelin predominantly in the anterior temporal lobes of both patients, but the FTLD-tau patient showed more bilateral, dorsolateral involvement featuring greater pathology and loss of projection neurons and deep white matter. These findings highlight that the regions within and connected to anterior temporal lobes may have differential vulnerability to distinct FTLD proteinopathies and serve important roles in human belief systems.
Aging and Alzheimer’s disease have dissociable effects on local and regional medial temporal lobe connectivity

S. Hrybouski, Sandhitsu R. Das, Long Xie, L. Wisse, M. Kelley, J. Lane, Monica Sherin, Michael Dicalogero, I. Nasrallah, John A. Detre, Paul Yushkevich, and D. Wolk

Brain Communications, Sep 2023

Cited by 24

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The extent to which pathological processes in aging and Alzheimer’s disease (AD) relate to functional disruption of the medial temporal lobe (MTL)‐dependent brain networks is poorly understood. To address this knowledge gap, we examined functional connectivity (FC) alterations between anterior and posterior regions of the MTL and in MTL‐associated functional communities – the Anterior‐Temporal (AT) and Posterior‐Medial (PM) networks – in normal agers, individuals with preclinical AD, and patients with Mild Cognitive Impairment or mild dementia due to AD.
Hippocampal volume loss in individuals with a history of non-fatal opioid overdose

Dustin R Todaro, Xin-Yi Li, L. S. Pereira-Rufino, Peter Manza, I. Nasrallah, Sandhitsu R. Das, A. Childress, Henry R. Kranzler, Nora D. Volkow, D. Langleben, Zhen-Hao Shi, and C. Wiers

Addiction biology, Sep 2023

Cited by 12

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Incidence of opioid‐related overdoses in the United States has increased dramatically over the past two decades. Despite public emphasis on overdose fatalities, most overdose cases are not fatal. Although there are case reports of amnestic syndromes and acute injury to the hippocampus following non‐fatal opioid overdose, the effects of such overdoses on brain structure are poorly understood. Here, we investigated the neuroanatomical correlates of non‐fatal opioid overdoses by comparing hippocampal volume in opioid use disorder (OUD) patients who had experienced an opioid overdose (OD; N = 17) with those who had not (NOD; N = 32). Voxel‐based morphometry showed lower hippocampal volume in the OD group than in the NOD group, which on post hoc analysis was evident in the left but not the right hippocampus. These findings strengthen the evidence that hippocampal injury is associated with non‐fatal opioid overdose, which is hypothesized to underlie overdose‐related amnestic syndrome.
Hippocampal volume loss in individuals with a history of non‐fatal opioid overdose

Dustin R Todaro, Xinyi Li, Lais S. Pereira-Rufino, P. Manza, Ilya M. Nasrallah, Sandhitsu R. Das, A. Childress, H. Kranzler, Nora D. Volkow, D. Langleben, Zhenhao Shi, and C. Wiers

Addiction Biology, Sep 2023

Cited by 7

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Incidence of opioid‐related overdoses in the United States has increased dramatically over the past two decades. Despite public emphasis on overdose fatalities, most overdose cases are not fatal. Although there are case reports of amnestic syndromes and acute injury to the hippocampus following non‐fatal opioid overdose, the effects of such overdoses on brain structure are poorly understood. Here, we investigated the neuroanatomical correlates of non‐fatal opioid overdoses by comparing hippocampal volume in opioid use disorder (OUD) patients who had experienced an opioid overdose (OD; N = 17) with those who had not (NOD; N = 32). Voxel‐based morphometry showed lower hippocampal volume in the OD group than in the NOD group, which on post hoc analysis was evident in the left but not the right hippocampus. These findings strengthen the evidence that hippocampal injury is associated with non‐fatal opioid overdose, which is hypothesized to underlie overdose‐related amnestic syndrome.
Antiamyloid Monoclonal Antibody Therapy for Alzheimer Disease

V. Ramanan, M. Armstrong, Parichita Choudhury, K. Coerver, R. Hamilton, Brad C. Klein, D. Wolk, Scott R Wessels, and Lyell K. Jones

Neurology, Jul 2023

Cited by 74

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With recent data demonstrating that lecanemab treatment can slow cognitive and functional decline in early symptomatic Alzheimer disease (AD), it is widely anticipated that this drug and potentially other monoclonal antibody infusions targeting β-amyloid protein will imminently be realistic options for some patients with AD. Given that these new antiamyloid monoclonal antibodies (mAbs) are associated with nontrivial risks and burdens of treatment that are radically different from current mainstays of AD management, effectively and equitably translating their use to real-world clinical care will require systematic and practice-specific modifications to existing workflows and infrastructure. In this Emerging Issues in Neurology article, we provide practical guidance for a wide audience of neurology clinicians on logistic adaptations and decision making around emerging antiamyloid mAbs. Specifically, we briefly summarize the rationale and available evidence supporting antiamyloid mAb use in AD to facilitate appropriate communication with patients and care partners on potential benefits. We also discuss pragmatic approaches to optimizing patient selection and treatment monitoring, with a particular focus on the value of incorporating shared decision making and multidisciplinary collaboration. In addition, we review some of the recognized limitations of current knowledge and highlight areas of future evolution to guide the development of sustainable and flexible models for treatment and follow-up. As the field enters a new era with disease-modifying treatment options for AD, it will be critical for neurology practices to prepare and continually innovate to ensure optimal outcomes for patients.
iEEG-recon: A Fast and Scalable Pipeline for Accurate Reconstruction of Intracranial Electrodes and Implantable Devices

A. Lucas, Brittany H. Scheid, A. Pattnaik, Ryan S. Gallagher, Marissa Mojena, Ashley Tranquille, Brian Prager, E. Gleichgerrcht, Ruxue Gong, B. Litt, Kathryn A. Davis, Sandhitsu R. Das, J. Stein, and Nishant Sinha

medRxiv, Jun 2023

Cited by 18

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Background: Collaboration between epilepsy centers is essential to integrate multimodal data for epilepsy research. Scalable tools for rapid and reproducible data analysis facilitate multicenter data integration and harmonization. Clinicians use intracranial EEG (iEEG) in conjunction with non-invasive brain imaging to identify epileptic networks and target therapy for drug-resistant epilepsy cases. Our goal was to promote ongoing and future collaboration by automating the process of electrode reconstruction, which involves the labeling, registration, and assignment of iEEG electrode coordinates on neuroimaging. These tasks are still performed manually in many epilepsy centers. We developed a standalone, modular pipeline that performs electrode reconstruction. We demonstrate our tool’s compatibility with clinical and research workflows and its scalability on cloud platforms. Methods: We created iEEG-recon, a scalable electrode reconstruction pipeline for semi-automatic iEEG annotation, rapid image registration, and electrode assignment on brain MRIs. Its modular architecture includes three modules: a clinical module for electrode labeling and localization, and a research module for automated data processing and electrode contact assignment. To ensure accessibility for users with limited programming and imaging expertise, we packaged iEEG-recon in a containerized format that allows integration into clinical workflows. We propose a cloud-based implementation of iEEG-recon, and test our pipeline on data from 132 patients at two epilepsy centers using retrospective and prospective cohorts. Results: We used iEEG-recon to accurately reconstruct electrodes in both electrocorticography (ECoG) and stereoelectroencephalography (SEEG) cases with a 10 minute running time per case, and 20 min for semi-automatic electrode labeling. iEEG-recon generates quality assurance reports and visualizations to support epilepsy surgery discussions. Reconstruction outputs from the clinical module were radiologically validated through pre- and post-implant T1-MRI visual inspections. Our use of ANTsPyNet deep learning approach for brain segmentation and electrode classification was consistent with the widely-used Freesurfer segmentation. Discussion: iEEG-recon is a valuable tool for automating reconstruction of iEEG electrodes and implantable devices on brain MRI, promoting efficient data analysis, and integration into clinical workflows. The tool’s accuracy, speed, and compatibility with cloud platforms make it a useful resource for epilepsy centers worldwide. Comprehensive documentation is available at https://ieeg-recon.readthedocs.io/en/latest/
Improved Seizure Onset-Zone Lateralization in Temporal Lobe Epilepsy using 7T Resting-State fMRI: A Direct Comparison with 3T

A. Lucas, E. Cornblath, Nishant Sinha, L. Caciagli, P. Hadar, Ashley Tranquille, J. Stein, Sandhitsu R. Das, and Kathryn A. Davis

medRxiv, Jun 2023

Cited by 6

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Objective: Resting-state functional magnetic resonance imaging (rs-fMRI) at ultra high- field strengths ([≥]7T) is known to provide superior signal-to-noise and statistical power than comparable acquisitions at lower field strengths. In this study, we aim to provide a direct comparison of the seizure onset-zone (SOZ) lateralizing ability of 7T rs-fMRI and 3T rs-fMRI. Methods: We investigated a cohort of 70 temporal lobe epilepsy (TLE) patients. A paired cohort of 19 patients had 3T and 7T rs-fMRI acquisitions for direct comparison between the two field strengths. Forty-three patients had only 3T, and 8 patients had only 7T rs- fMRI acquisitions. We quantified the functional connectivity between the hippocampus and other nodes within the default mode network (DMN) using seed-to-voxel connectivity, and measured how hippocampo-DMN connectivity could inform SOZ lateralization at 7T and 3T field strengths. Results: Differences between hippocampo-DMN connectivity ipsilateral and contralateral to the SOZ were significantly higher at 7T (pFDR=0.008) than at 3T (pFDR=0.80) when measured in the same subjects. We found that our ability to lateralize the SOZ, by distinguishing subjects with left TLE from subjects with right TLE, was superior at 7T (AUC = 0.97) than 3T (AUC = 0.68). Our findings were reproduced in extended cohorts of subjects scanned at either 3T or 7T. Our rs-fMRI findings at 7T, but not 3T, are consistent and highly correlated (Spearman Rho=0.65) with clinical FDG-PET lateralizing hypometabolism. Significance: We show superior SOZ lateralization in TLE patients when using 7T relative to 3T rs-fMRI, supporting the adoption of high-field strength functional imaging in the epilepsy presurgical evaluation.
Tau burden is associated with cross‐sectional and longitudinal neurodegeneration in the medial temporal lobe in cognitively normal individuals

Long Xie, L. Wisse, Sandhitsu R. Das, Xueying Lyu, R. Flores, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jun 2023

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Neurofibrillary tangle pathology is thought to drive neurodegeneration in beta‐amyloid positive (A+) cognitively normal (CN) individuals, i.e., preclinical Alzheimer’s disease (AD). However, in beta‐amyloid negative (A‐) CN, the contribution of tau pathology [primary age‐related tauopathy (PART)] to neurodegeneration remains uncertain. We investigate the correlation between tau burden measured by PET in the medial temporal lobe (MTL) and MRI‐derived cross‐sectional and longitudinal structural atrophy in these cohorts.
Association of Sleep-Disordered Breathing and Medial Temporal Lobe Atrophy in Cognitively Unimpaired Amyloid-Positive Older Adults

Claire André, Elizabeth Kuhn, S. Réhel, Valentin Ourry, S. Demeilliez-Servouin, Cassandre Palix, Francesca Felisatti, P. Champetier, S. Dautricourt, Paul Yushkevich, D. Vivien, V. Sayette, G. Chételat, R. Flores, and G. Rauchs

Neurology, May 2023

Cited by 21

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Background and Objectives Sleep disordered breathing (SDB) has been related to amyloid deposition and an increased dementia risk. However, how SDB relates to medial temporal lobe neurodegeneration and subsequent episodic memory impairment is unclear. Our objective was to investigate the impact of amyloid positivity on the associations between SDB severity, medial temporal lobe subregions, and episodic memory performance in cognitively unimpaired older adults. Methods Data were acquired between 2016 and 2020 in the context of the Age-Well randomized controlled trial of the Medit-Aging European project. Participants older than 65 years who were free of neurologic, psychiatric, or chronic medical diseases were recruited from the community. They completed a neuropsychological evaluation, in-home polysomnography, a Florbetapir PET, and an MRI, including a specific high-resolution assessment of the medial temporal lobe and hippocampal subfields. Multiple linear regressions were conducted to test interactions between amyloid status and SDB severity on the volume of MTL subregions, controlling for age, sex, education, and the ApoE4 status. Secondary analyses aimed at investigating the links between SDB, MTL subregional atrophy, and episodic memory performance at baseline and at a mean follow-up of 20.66 months in the whole cohort and in subgroups stratified according to amyloid status. Results We included 122 cognitively intact community-dwelling older adults (mean age ± SD: 69.40 ± 3.85 years, 77 women, 26 Aβ+ individuals) in baseline analyses and 111 at follow-up. The apnea-hypopnea index interacted with entorhinal (β = −0.81, p < 0.001, pη2 = 0.19), whole hippocampal (β = −0.61, p < 0.001, pη2 = 0.10), subiculum (β = −0.56, p = 0.002, pη2 = 0.08), CA1 (β = −0.55, p = 0.002, pη2 = 0.08), and DG (β = −0.53, p = 0.003, pη2 = 0.08) volumes such that a higher sleep apnea severity was related to lower MTL subregion volumes in amyloid-positive individuals, but not in those who were amyloid negative. In the whole cohort, lower whole hippocampal (r = 0.27, p = 0.005) and CA1 (r = 0.28, p = 0.003) volumes at baseline were associated with worse episodic memory performance at follow-up. Discussion Overall, we showed that SDB was associated with MTL atrophy in cognitively asymptomatic older adults engaged in the Alzheimer continuum, which may increase the risk of developing memory impairment over time. Trial Registration Information ClinicalTrials.gov Identifier: NCT02977819.
Young versus older subject diffusion magnetic resonance imaging data for virtual white matter lesion tractography

M. Taghvaei, Philip A Cook, S. Sadaghiani, Banafsheh Shakibajahromi, William Tackett, S. Dolui, Debarun De, Christopher Brown, Pulkit Khandelwal, Paul Yushkevich, Sandhitsu R. Das, D. Wolk, and J. Detre

Human Brain Mapping, May 2023

Cited by 8

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White matter hyperintensity (WMH) lesions on T2 fluid‐attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) and changes in adjacent normal‐appearing white matter can disrupt computerized tract reconstruction and result in inaccurate measures of structural brain connectivity. The virtual lesion approach provides an alternative strategy for estimating structural connectivity changes due to WMH. To assess the impact of using young versus older subject diffusion MRI data for virtual lesion tractography, we leveraged recently available diffusion MRI data from the Human Connectome Project (HCP) Lifespan database. Neuroimaging data from 50 healthy young (39.2 ± 1.6 years) and 46 healthy older (74.2 ± 2.5 years) subjects were obtained from the publicly available HCP‐Aging database. Three WMH masks with low, moderate, and high lesion burdens were extracted from the WMH lesion frequency map of locally acquired FLAIR MRI data. Deterministic tractography was conducted to extract streamlines in 21 WM bundles with and without the WMH masks as regions of avoidance in both young and older cohorts. For intact tractography without virtual lesion masks, 7 out of 21 WM pathways showed a significantly lower number of streamlines in older subjects compared to young subjects. A decrease in streamline count with higher native lesion burden was found in corpus callosum, corticostriatal tract, and fornix pathways. Comparable percentages of affected streamlines were obtained in young and older groups with virtual lesion tractography using the three WMH lesion masks of increasing severity. We conclude that using normative diffusion MRI data from young subjects for virtual lesion tractography of WMH is, in most cases, preferable to using age‐matched normative data.
Prediction of Regional Tau Spread Using Individualized Tau Epicenters and Structural Connectomes (S39.002)

Christopher Brown, Sandhitsu R. Das, I. Nasrallah, J. Detre, Paul Yushkevich, C. McMillan, and David Wolk

Wednesday, April 26, Apr 2023

DOI
Regional Deep Atrophy: a Self-Supervised Learning Method to Automatically Identify Regions Associated With Alzheimer’s Disease Progression From Longitudinal MRI

M. Dong, Long Xie, Sandhitsu R. Das, Jiancong Wang, L. Wisse, R. Flores, D. Wolk, and Paul Yushkevich

ArXiv, Apr 2023

Cited by 2

Abs DOI arXiv

Longitudinal assessment of brain atrophy, particularly in the hippocampus, is a well-studied biomarker for neurodegenerative diseases, such as Alzheimer’s disease (AD). In clinical trials, estimation of brain progressive rates can be applied to track therapeutic efficacy of disease modifying treatments. However, most state-of-the-art measurements calculate changes directly by segmentation and/or deformable registration of MRI images, and may misreport head motion or MRI artifacts as neurodegeneration, impacting their accuracy. In our previous study, we developed a deep learning method DeepAtrophy that uses a convolutional neural network to quantify differences between longitudinal MRI scan pairs that are associated with time. DeepAtrophy has high accuracy in inferring temporal information from longitudinal MRI scans, such as temporal order or relative inter-scan interval. DeepAtrophy also provides an overall atrophy score that was shown to perform well as a potential biomarker of disease progression and treatment efficacy. However, DeepAtrophy is not interpretable, and it is unclear what changes in the MRI contribute to progression measurements. In this paper, we propose Regional Deep Atrophy (RDA), which combines the temporal inference approach from DeepAtrophy with a deformable registration neural network and attention mechanism that highlights regions in the MRI image where longitudinal changes are contributing to temporal inference. RDA has similar prediction accuracy as DeepAtrophy, but its additional interpretability makes it more acceptable for use in clinical settings, and may lead to more sensitive biomarkers for disease monitoring in clinical trials of early AD.
Integrating color deconvolution thresholding and weakly supervised learning for automated segmentation of neurofibrillary tangle and neuropil threads

H. Roh, D. Irwin, Mónica Muñoz-López, María Mercedes Iñiguez Onzoño Martin, R. Ittyerah, Sydney A. Lim, M. Bedard, John L. Robinson, T. Schuck, E. Artacho-Pérula, Marı’a Mar Arroyo Jiménez, María Del Pilar Marcos Rabal, F. J. Molina Romero, S. Cebada Sánchez, J. C. Delgado González, C. Rosa-Prieto, M. Córcoles Parada, Edward B. Lee, Daniel T. Ohm, L. Wisse, D. Wolk, J. Gee, R. Insausti, Paul Yushkevich, and Min Chen

Medical Imaging, Apr 2023

Abs DOI

Abnormally phosphorylated tau proteins are known to be a major indicator of Alzheimer’s Disease (AD) with strong association with memory loss and cognitive decline. Automated generation of pixel-wise accurate neurofibrillary tangles (NFTs) and neuropil threads (NTs) segmentation is a challenging task, due to lack of ground truth segmentation data of these abnormal tau pathology. This problem is most prominent in the case of segmenting NTs, where the small threadlike morphology makes pixel-wise labeling a laborious task and unrealistic for large-scale studies. Lack of ground truth data poses a significant limitation for many learning-based methods to generate accurate segmentations of NFTs and NTs. This work presents an automated pipeline for pixel level segmentation of NFTs and NTs that does not rely on ground truth segmentation data. The pipeline is composed of four main steps: (1) color deconvolution is used to separate histopathology images into staining channels (DAB, Hematoxylin, and Eosin), (2) Otsu’s thresholding is used on the DAB stain channel to generate pixel level segmentation of abnormal tau proteins staining, (3) a weakly-supervised learning paradigm (WildCat), using only global descriptors of images, is used to generate density maps of potential regions of NFTs and NTs, and (4) density maps and segmentations are then integrated using connected component analysis to localize NFTs and NTs in the detected tau segmentations. Our results show high global classification accuracy for NFTs (Acc:0.96) and NTs (Acc:0.91), and statistically significant distinctions when evaluating the percent area occupied of the detected NTs relative to expert ratings of NTs severity. Qualitative assessment of the NFTs and NTs results showed accurate pixel-level segmentations of the NFTs, while modest performance for NTs.
Periventricular White Matter Fractional Anisotropy as a Biomarker of Cerebral Small Vessel Disease (P11-6.007)

Banafsheh Shakibajahromi, S. Dolui, Christopher Brown, William Tackett, Pulkit Khandelwal, S. Sadaghiani, M. Taghvaei, Paul Yushkevich, David Wolk, and J. Detre

Wednesday, April 26, Apr 2023

DOI
Craniofacial Soft-Tissue Anthropomorphic Database with Magnetic Resonance Imaging and Unbiased Diffeomorphic Registration

D. Villavisanis, Pulkit Khandelwal, Zachary D. Zapatero, Connor S. Wagner, J. Blum, D. Cho, J. Swanson, Jesse A. Taylor, Paul Yushkevich, and S. Bartlett

Plastic and Reconstructive Surgery, Apr 2023

Cited by 7

Abs DOI

Background: Objective assessment of craniofacial surgery outcomes in a pediatric population is challenging because of the complexity of patient presentations, diversity of procedures performed, and rapid craniofacial growth. There is a paucity of robust methods to quantify anatomical measurements by age and objectively compare craniofacial dysmorphology and postoperative outcomes. Here, the authors present data in developing a racially and ethnically sensitive anthropomorphic database, providing plastic and craniofacial surgeons with “normal” three-dimensional anatomical parameters with which to appraise and optimize aesthetic and reconstructive outcomes. Methods: Patients with normal craniofacial anatomy undergoing head magnetic resonance imaging (MRI) scans from 2008 to 2021 were included in this retrospective study. Images were used to construct composite (template) images with diffeomorphic image registration method using the Advanced Normalization Tools package. Composites were thresholded to generate binary three-dimensional segmentations used for anatomical measurements in Materalise Mimics. Results: High-resolution MRI scans from 130 patients generated 12 composites from an average of 10 MRI sequences each: four 3-year-olds, four 4-year-olds, and four 5-year-olds (two male, two female, two Black, and two White). The average head circumference of 3-, 4-, and 5-year-old composites was 50.3, 51.5, and 51.7 cm, respectively, comparable to normative data published by the World Health Organization. Conclusions: Application of diffeomorphic registration-based image template algorithm to MRI is effective in creating composite templates to represent “normal” three-dimensional craniofacial and soft-tissue anatomy. Future research will focus on development of automated computational tools to characterize anatomical normality, generation of indices to grade preoperative severity, and quantification of postoperative results to reduce subjectivity bias.
Baseline structural MRI and plasma biomarkers predict longitudinal structural atrophy and cognitive decline in early Alzheimer’s disease

Long Xie, Sandhitsu R. Das, L. Wisse, R. Ittyerah, R. Flores, L. Shaw, Paul Yushkevich, and D. Wolk

Alzheimer’s Research & Therapy, Apr 2023

Cited by 45

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Background Crucial to the success of clinical trials targeting early Alzheimer’s disease (AD) is recruiting participants who are more likely to progress over the course of the trials. We hypothesize that a combination of plasma and structural MRI biomarkers, which are less costly and non-invasive, is predictive of longitudinal progression measured by atrophy and cognitive decline in early AD, providing a practical alternative to PET or cerebrospinal fluid biomarkers. Methods Longitudinal T1-weighted MRI, cognitive (memory-related test scores and clinical dementia rating scale), and plasma measurements of 245 cognitively normal (CN) and 361 mild cognitive impairment (MCI) patients from ADNI were included. Subjects were further divided into β-amyloid positive/negative (Aβ+/Aβ−)] subgroups. Baseline plasma (p-tau_181 and neurofilament light chain) and MRI-based structural medial temporal lobe subregional measurements and their association with longitudinal measures of atrophy and cognitive decline were tested using stepwise linear mixed effect modeling in CN and MCI, as well as separately in the Aβ+/Aβ− subgroups. Receiver operating characteristic (ROC) analyses were performed to investigate the discriminative power of each model in separating fast and slow progressors (first and last terciles) of each longitudinal measurement. Results A total of 245 CN (35.0% Aβ+) and 361 MCI (53.2% Aβ+) participants were included. In the CN and MCI groups, both baseline plasma and structural MRI biomarkers were included in most models. These relationships were maintained when limited to the Aβ+ and Aβ− subgroups, including Aβ− CN (normal aging). ROC analyses demonstrated reliable discriminative power in identifying fast from slow progressors in MCI [area under the curve (AUC): 0.78–0.93] and more modestly in CN (0.65–0.73). Conclusions The present data support the notion that plasma and MRI biomarkers, which are relatively easy to obtain, provide a prediction for the rate of future cognitive and neurodegenerative progression that may be particularly useful in clinical trial stratification and prognosis. Additionally, the effect in Aβ− CN indicates the potential use of these biomarkers in predicting a normal age-related decline.
Ex vivo, in situ perfusion protocol for human brain fixation compatible with microscopy, MRI techniques, and anatomical studies

R. Insausti, A. Insausti, Mónica Muñoz-López, Isidro Medina Lorenzo, M. Arroyo-Jiménez, María Del Pilar Marcos Rabal, C. Rosa-Prieto, J. Delgado-González, Javier Montón Etxeberria, S. Cebada-Sánchez, Juan Francisco Raspeño-García, María Mercedes Iñiguez Onzoño, F. J. Molina Romero, R. Benavides-Piccione, S. Tapia-González, L. Wisse, S. Ravikumar, D. Wolk, J. DeFelipe, Paul Yushkevich, and E. Artacho-Pérula

Frontiers in Neuroanatomy, Mar 2023

Cited by 30

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We present a method for human brain fixation based on simultaneous perfusion of 4% paraformaldehyde through carotids after a flush with saline. The left carotid cannula is used to perfuse the body with 10% formalin, to allow further use of the body for anatomical research or teaching. The aim of our method is to develop a vascular fixation protocol for the human brain, by adapting protocols that are commonly used in experimental animal studies. We show that a variety of histological procedures can be carried out (cyto- and myeloarchitectonics, histochemistry, immunohistochemistry, intracellular cell injection, and electron microscopy). In addition, ex vivo, ex situ high-resolution MRI (9.4T) can be obtained in the same specimens. This procedure resulted in similar morphological features to those obtained by intravascular perfusion in experimental animals, provided that the postmortem interval was under 10 h for several of the techniques used and under 4 h in the case of intracellular injections and electron microscopy. The use of intravascular fixation of the brain inside the skull provides a fixed whole human brain, perfectly fitted to the skull, with negligible deformation compared to conventional techniques. Given this characteristic of ex vivo, in situ fixation, this procedure can probably be considered the most suitable one available for ex vivo MRI scans of the brain. We describe the compatibility of the method proposed for intravascular fixation of the human brain and fixation of the donor’s body for anatomical purposes. Thus, body donor programs can provide human brain tissue, while the remainder of the body can also be fixed for anatomical studies. Therefore, this method of human brain fixation through the carotid system optimizes the procurement of human brain tissue, allowing a greater understanding of human neurological diseases, while benefiting anatomy departments by making the remainder of the body available for teaching purposes.
Automated deep learning segmentation of high-resolution 7 T postmortem MRI for quantitative analysis of structure-pathology correlations in neurodegenerative diseases

Pulkit Khandelwal, M. T. Duong, S. Sadaghiani, Sydney A. Lim, Amanda E. Denning, E. Chung, S. Ravikumar, Sanaz Arezoumandan, Claire S. Peterson, M. Bedard, N. Capp, R. Ittyerah, Elyse Migdal, Grace Choi, Emily Kopp, Bridget Loja, Eusha Hasan, Jiacheng Li, A. Bahena, K. Prabhakaran, G. Mizsei, M. Gabrielyan, T. Schuck, W. Trotman, J. Robinson, Daniel T. Ohm, Edward B. Lee, J. Trojanowski, C. McMillan, M. Grossman, David J. Irwin, John A. Detre, M. Tisdall, Sandhitsu R. Das, L. Wisse, D. Wolk, and Paul Yushkevich

Mar 2023

Abs arXiv

Postmortem MRI allows brain anatomy to be examined at high resolution and to link pathology measures with morphometric measurements. However, automated segmentation methods for brain mapping in postmortem MRI are not well developed, primarily due to limited availability of labeled datasets, and heterogeneity in scanner hardware and acquisition protocols. In this work, we present a high resolution of 135 postmortem human brain tissue specimens imaged at 0.3 mm^3 isotropic using a T2w sequence on a 7T whole-body MRI scanner. We developed a deep learning pipeline to segment the cortical mantle by benchmarking the performance of nine deep neural architectures, followed by post-hoc topological correction. We then segment four subcortical structures (caudate, putamen, globus pallidus, and thalamus), white matter hyperintensities, and the normal appearing white matter. We show generalizing capabilities across whole brain hemispheres in different specimens, and also on unseen images acquired at 0.28 mm^3 and 0.16 mm^3 isotropic T2*w FLASH sequence at 7T. We then compute localized cortical thickness and volumetric measurements across key regions, and link them with semi-quantitative neuropathological ratings. Our code, Jupyter notebooks, and the containerized executables are publicly available at: https://pulkit-khandelwal.github.io/exvivo-brain-upenn
Improved Segmentation of Deep Sulci in Cortical Gray Matter Using a Deep Learning Framework Incorporating Laplace’s Equation

S. Ravikumar, Ranjit Ittyerah, Sydney A. Lim, Long Xie, Sandhitsu R. Das, Pulkit Khandelwal, L. Wisse, M. Bedard, J. Robinson, Terry K. Schuck, M. Grossman, J. Trojanowski, Edward B. Lee, M. Tisdall, K. Prabhakaran, J. Detre, D. Irwin, W. Trotman, G. Mizsei, E. Artacho-Pérula, Maria Mercedes Iñiguez Onzoño Martin, María Mar Arroyo Jiménez, M. M. López, Francisco Javier Molina Romero, Maria Pilar Marcos Rabal, S. C. Sánchez, J. Gonz’alez, Carlos Rosa-Prieto, Marta Córcoles Parada, D. Wolk, R. Insausti, and Paul Yushkevich

ArXiv, Mar 2023

Cited by 1

Abs DOI arXiv PDF

When developing tools for automated cortical segmentation, the ability to produce topologically correct segmentations is important in order to compute geometrically valid morphometry measures. In practice, accurate cortical segmentation is challenged by image artifacts and the highly convoluted anatomy of the cortex itself. To address this, we propose a novel deep learning-based cortical segmentation method in which prior knowledge about the geometry of the cortex is incorporated into the network during the training process. We design a loss function which uses the theory of Laplace’s equation applied to the cortex to locally penalize unresolved boundaries between tightly folded sulci. Using an ex vivo MRI dataset of human medial temporal lobe specimens, we demonstrate that our approach outperforms baseline segmentation networks, both quantitatively and qualitatively.
Stress-related reduction of hippocampal subfield volumes in major depressive disorder: A 7-Tesla study

Judy Alper, Rui Feng, G. Verma, S. Rutter, Kuang-han Huang, Long Xie, Paul Yushkevich, Yael Jacob, S. Brown, Marin M. Kautz, Molly Schneider, Hung-Mo Lin, L. Fleysher, B. Delman, P. Hof, J. Murrough, and P. Balchandani

Frontiers in Psychiatry, Feb 2023

Cited by 13

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Background Major depressive disorder (MDD) is a prevalent health problem with complex pathophysiology that is not clearly understood. Prior work has implicated the hippocampus in MDD, but how hippocampal subfields influence or are affected by MDD requires further characterization with high-resolution data. This will help ascertain the accuracy and reproducibility of previous subfield findings in depression as well as correlate subfield volumes with MDD symptom scores. The objective of this study was to assess volumetric differences in hippocampal subfields between MDD patients globally and healthy controls (HC) as well as between a subset of treatment-resistant depression (TRD) patients and HC using automatic segmentation of hippocampal subfields (ASHS) software and ultra-high field MRI. Methods Thirty-five MDD patients and 28 HC underwent imaging using 7-Tesla MRI. ASHS software was applied to the imaging data to perform automated hippocampal segmentation and provide volumetrics for analysis. An exploratory analysis was also performed on associations between symptom scores for diagnostic testing and hippocampal subfield volumes. Results Compared to HC, MDD and TRD patients showed reduced right-hemisphere CA2/3 subfield volume (p = 0.01, η2 = 0.31 and p = 0.3, η2 = 0.44, respectively). Additionally, negative associations were found between subfield volumes and life-stressor checklist scores, including left CA1 (p = 0.041, f2 = 0.419), left CA4/DG (p = 0.010, f2 = 0.584), right subiculum total (p = 0.038, f2 = 0.354), left hippocampus total (p = 0.015, f2 = 0.134), and right hippocampus total (p = 0.034, f2 = 0.110). Caution should be exercised in interpreting these results due to the small sample size and low power. Conclusion Determining biomarkers for MDD and TRD pathophysiology through segmentation on high-resolution MRI data and understanding the effects of stress on these regions can enable better assessment of biological response to treatment selection and may elucidate the underlying mechanisms of depression.
Tau-Neurodegeneration mismatch reveals vulnerability and resilience to comorbidities in Alzheimer’s continuum

Xueying Lyu, M. T. Duong, Long Xie, R. Flores, Hayley M. Richardson, Gyujoon Hwang, L. Wisse, Michael Dicalogero, Corey T. McMillan, John L. Robinson, Sharon X. Xie, M. Grossman, Edward B. Lee, David J. Irwin, B. Dickerson, Christos Davatzikos, I. Nasrallah, Paul Yushkevich, D. Wolk, and Sandhitsu R. Das

medRxiv : the preprint server for health sciences, Feb 2023

Cited by 10

DOI PDF
Aging and Alzheimer’s Disease Have Dissociable Effects on Medial Temporal Lobe Connectivity

S. Hrybouski, Sandhitsu Das, L. Xie, L. Wisse, M. Kelley, J. Lane, M. Sherin, Michael Dicalogero, I. Nasrallah, J. Detre, Paul Yushkevich, and D. Wolk

medRxiv : the preprint server for health sciences, Jan 2023

Cited by 8

DOI PDF
Subcortical functional connectivity gradients in temporal lobe epilepsy

A. Lucas, Sofia Mouchtaris, E. Cornblath, Nishant Sinha, Lorenzo Caciagli, P. Hadar, James J. Gugger, Sandhitsu R. Das, J. Stein, and Kathryn A. Davis

NeuroImage : Clinical, Jan 2023

Cited by 18

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Background and Motivation: Functional gradients have been used to study differences in connectivity between healthy and diseased brain states, however this work has largely focused on the cortex. Because the subcortex plays a key role in seizure initiation in temporal lobe epilepsy (TLE), subcortical functional-connectivity gradients may help further elucidate differences between healthy brains and TLE, as well as differences between left (L)-TLE and right (R)-TLE. Methods: In this work, we calculated subcortical functional-connectivity gradients (SFGs) from resting-state functional MRI (rs-fMRI) by measuring the similarity in connectivity profiles of subcortical voxels to cortical gray matter voxels. We performed this analysis in 23 R-TLE patients and 32 L-TLE patients (who were otherwise matched for age, gender, disease specific characteristics, and other clinical variables), and 16 controls. To measure differences in SFGs between L-TLE and R-TLE, we quantified deviations in the average functional gradient distributions, as well as their variance, across subcortical structures. Results: We found an expansion, measured by increased variance, in the principal SFG of TLE relative to controls. When comparing the gradient across subcortical structures between L-TLE and R-TLE, we found that abnormalities in the ipsilateral hippocampal gradient distributions were significantly different between L-TLE and R-TLE. Conclusion: Our results suggest that expansion of the SFG is characteristic of TLE. Subcortical functional gradient differences exist between left and right TLE and are driven by connectivity changes in the hippocampus ipsilateral to the seizure onset zone.
Image-to-Image Translation Between Tau Pathology and Neuronal Metabolism PET in Alzheimer Disease with Multi-domain Contrastive Learning

M. T. Duong, Sandhitsu R. Das, Pulkit Khandelwal, Xueying Lyu, Long Xie, Paul Yushkevich, D. Wolk, and I. Nasrallah

In MLCN@MICCAI, Jan 2023

Cited by 1

DOI
Automated deep learning segmentation of high-resolution 7 T ex vivo MRI for quantitative analysis of structure-pathology correlations in neurodegenerative diseases

Pulkit Khandelwal, M. T. Duong, S. Sadaghiani, Sydney A. Lim, Amanda E. Denning, E. Chung, S. Ravikumar, Sanaz Arezoumandan, Claire S. Peterson, M. Bedard, N. Capp, R. Ittyerah, Elyse Migdal, Grace Choi, Emily Kopp, Bridget Loja, Eusha Hasan, Jiacheng Li, K. Prabhakaran, G. Mizsei, M. Gabrielyan, T. Schuck, W. Trotman, J. Robinson, Daniel T. Ohm, Edward B. Lee, J. Trojanowski, C. McMillan, M. Grossman, D. Irwin, J. Detre, M. Tisdall, Sandhitsu R. Das, L. Wisse, D. Wolk, and Paul Yushkevich

ArXiv, Jan 2023

Cited by 4

DOI PDF

2022

Association between recollection and familiarity‐based memory measures and plasma biomarkers for Alzheimer’s disease

Michael Dicalogero, J. Lane, M. Kelley, T. Tropea, Leslie M. Shaw, A. Chen-Plotkin, and D. Wolk

Alzheimer’s & Dementia, Dec 2022

Abs DOI

Normal aging and preclinical Alzheimer’s Disease (AD) share common features, such as structural changes to medial temporal lobe regions and declining episodic memory. However, prior work suggests qualitative differences between AD‐related memory changes and those due to aging. Specifically, recollection‐based, or contextual, memory declines with both normal aging and AD. Alternatively, familiarity‐based, or item, memory is more specific to preclinical AD and atrophy in the perirhinal cortex. In the current analysis, we examined the relationship between these forms of memory with plasma biomarkers associated with AD and neurodegeneration.
Deep Learning Registration with Scan‐temporal Consistency May Improve Detection of Alzheimer’s Disease Progression

M. Dong, Long Xie, Jiancong Wang, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2022

Abs DOI

Structural changes in Alzheimer’s disease (AD) can be detected as atrophy in the medial temporal lobe (MTL), which is normally studied by applying volumetric or deformation‐based morphometry (DBM) to longitudinal scans. However, conventional DMB methods are computationally intensive and may not estimate the atrophy accurately due to the noise in the longitudinal images, e.g., head motion or MRI artifacts. We hypothesize that deep learning models can be trained to estimate atrophy from longitudinal MRI scans and are more sensitive to biological changes rather than artifactual.
Targeting the Correct Population for Trials: A Post‐hoc Analysis of Trial of Solanezumab for Mild Dementia Due to Alzheimer’s disease.

A. Ezzati, Kellen K. Petersen, Bhargav Teja Nallapu, C. Davatzikos, D. Wolk, L. Rabin, C. Habeck, Charles B. Hall, and R. Lipton

Alzheimer’s & Dementia, Dec 2022

Cited by 1

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Up to 50% of placebo treated participants in AD clinical trials do not show clinically meaningful cognitive decline (CMCD) over the course of study. Inclusion of these individuals makes it more difficult to demonstrate the benefits of treatments intended to slow cognitive decline. Here, we used data from the trial of solanezumab for mild AD (EXPEDITION3) to investigate effectiveness of predictive models for enrichment of trials.
Deep Learning for Ultra High Resolution T2‐weighted 7 Tesla Ex vivo Magnetic Resonance Imaging Reveals Differential Subcortical Atrophy across Neurodegenerative Diseases

Pulkit Khandelwal, M. T. Duong, E. Chung, S. Sadaghiani, Sydney A. Lim, S. Ravikumar, Sanaz Arezoumandan, Claire S. Peterson, M. Bedard, N. Capp, R. Ittyerah, Elyse Migdal, Grace Choi, Emily Kopp, Bridget Loja Patino, Eusha Hasan, Jiacheng Li, K. Prabhakaran, G. Mizsei, M. Gabrielyan, T. Schuck, John L. Robinson, Daniel T. Ohm, I. Nasrallah, Edward B. Lee, J. Trojanowski, C. McMillan, M. Grossman, D. Irwin, D. Tisdall, Sandhitsu R. Das, L. Wisse, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2022

Cited by 2

Abs DOI

Ex vivo magnetic resonance imaging (MRI) of the brain provides remarkable advantages over in vivo MRI for linking neuroanatomy and morphometry to underlying pathology (Yushkevich et al. 2021, Ravikumar et al. 2021). Subcortical structures show atrophy in certain neurodegenerative diseases, especially Frontotemporal Lobar Degeneration with TDP‐43 (FTLD‐TDP) and four‐repeat (4R) tauopathies (i.e., Corticobasal Degeneration, Progressive Supranuclear Palsy) (Miletić et al. 2022), yet few methods exist to measure subcortical atrophy in ex vivo MRI. We present a framework to quantify subcortical morphometry using 7 Tesla ex vivo MRI and distinguish atrophy patterns across neurodegenerative spectrums.
Deep learning pipeline for cortical gray matter segmentation and thickness analysis in Ultra High Resolution T2w 7 Tesla Ex vivo MRI across neurodegenerative diseases reveals associations with underlying neuropathology

Pulkit Khandelwal, S. Sadaghiani, E. Chung, Sydney A. Lim, M. T. Duong, S. Ravikumar, Sanaz Arezoumandan, Claire S. Peterson, M. Bedard, N. Capp, R. Ittyerah, Elyse Migdal, Grace Choi, Emily Kopp, Bridget Loja Patino, Eusha Hasan, Jiacheng Li, K. Prabhakaran, G. Mizsei, M. Gabrielyan, T. Schuck, J. Robinson, Daniel T. Ohm, Edward B. Lee, J. Trojanowski, C. McMillan, M. Grossman, D. Irwin, D. Tisdall, Sandhitsu R. Das, L. Wisse, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2022

Cited by 3

Abs DOI

Ex vivo magnetic resonance imaging (MRI) enables detailed characterization of neuroanatomy (Augustinack et al. 2013), such as hippocampal subfields in the medial temporal lobe (MTL) (Yushkevich et al. 2021, Ravikumar et al. 2021). However, automated cortical segmentation methods in ex vivo MRI are not well developed due to limited data availability and heterogeneity in scanners and acquisition. Here, we investigate a deep learning framework to parcellate the cortical mantle, compute thickness and link them with neuropathology ratings across 16 cortical regions in 7 Tesla MRIs of 38 ex vivo brain specimens spanning Alzheimer Disease and Related Dementias.
Tau‐Neurodegeneration mismatch reveals vulnerability and resilience in Alzheimer’s continuum and Non‐Alzheimer’s pathophysiology

Xueying Lyu, M. T. Duong, Long Xie, Hayley M. Richardson, R. Flores, Michael Dicalogero, C. McMillan, John L. Robinson, J. Trojanowski, M. Grossman, Edward B. Lee, D. Irwin, B. Dickerson, Sharon X. Xie, I. Nasrallah, Paul Yushkevich, D. Wolk, and Sandhitsu R. Das

Alzheimer’s & Dementia, Dec 2022

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In previous work (Das et al., 2021), we exploited the non‐specific nature of neurodegeneration by investigating the amount and spatial pattern of deviation from the level of neurodegeneration (N) expected for a given level of tau (T). Using a data‐driven clustering approach based on T‐N mismatch, we found phenotypes that had greater N than expected for T (“vulnerable”) and phenotypes with less N than expected for T (“resilient”) in specific patterns. Here we extend this work to include amyloid positive (A+) and negative (A‐) participants. The logic of inclusion of A‐ individuals is that areas of mismatch in A+ individuals is likely driven by factors outside of AD pathology, which can be present in the absence of AD pathology.
At‐Home Data Collection with an App‐Based Cognitive Assessment for Detecting Memory and Executive Functioning Changes in Aging and Pre‐Clinical AD

D. Mechanic-Hamilton, Kimberly Halberstadter, Sean Lydon, Erin Liebenberg, and D. Wolk

Alzheimer’s & Dementia, Dec 2022

Abs DOI

Mobile, valid and engaging cognitive assessments are essential for detecting and tracking change in research participants and patients at risk for Alzheimer’s Disease and Related Dementias (ADRDs). This pilot study aims to determine the feasibility of at‐home, app‐based memory and executive functioning tasks included in the mobile cognitive app performance platform (mCAPP), to detect cognitive changes associated with aging and preclinical AD.
Combining high‐resolution ex vivo MRI and histopathology to identify medial temporal lobe atrophy patterns specific to tau pathology in Alzheimer’s Disease

S. Ravikumar, Amanda E. Denning, Sydney A. Lim, E. Chung, R. Ittyerah, L. Wisse, Long Xie, Sandhitsu R. Das, John L. Robinson, T. Schuck, M. Grossman, Edward B. Lee, D. Tisdall, G. Mizsei, E. Artacho-Pérula, Maria Mercedes Iniguez Onzono Martin, María Mar Arroyo Jiménez, M. Muñoz, Francisco Javier Molina Romero, P. M. Rabal, S. C. Sánchez, José Carlos Delgado González, R. Prieto, Marta Córcoles Parada, D. Irwin, J. Trojanowski, D. Wolk, R. Insausti, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2022

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Tau pathology in the medial temporal lobe (MTL) is closely linked to neurodegeneration, and is an early pathological change associated with Alzheimer’s disease (AD). MRI measures of MTL neurodegeneration have proven to be sensitive to change during preclinical AD. Current measures are confounded by the presence of non‐AD pathologies (e.g., TDP‐43, ageing). Here, we combine ex vivo imaging with histopathological ratings of tau and TDP‐43 to identify fine‐grained MTL atrophy patterns specific to tau. Such an analysis could be used to define MTL “hotspots” where in vivo measures of neurodegeneration are expected to be strongly associated with tau, potentially enabling the development of biomarkers that are more effective during early AD clinical trials.
Associations of phosphorylated tau pathology with whole-hemisphere ex-vivo morphometry in 7 tesla MRI

S. Sadaghiani, W. Trotman, Sydney A. Lim, E. Chung, R. Ittyerah, S. Ravikumar, Pulkit Khandelwal, K. Prabhakaran, Madigan Lavery, Daniel T. Ohm, M. Gabrielyan, Sandhitsu R. Das, T. Schuck, N. Capp, Claire S. Peterson, Elyse Migdal, E. Artacho-Pérula, María Mar Arroyo Jiménez, M. Rabal, S. C. Sánchez, Carlos Rosa Prieto, Marta Córcoles Parada, R. Insausti, John L. Robinson, C. McMillan, M. Grossman, Edward B. Lee, J. Detre, S. Xie, J. Trojanowski, M. Tisdall, L. Wisse, D. Irwin, D. Wolk, and Paul Yushkevich

Alzheimer’s & dementia : the journal of the Alzheimer’s Association, Dec 2022

Cited by 13

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Neurodegenerative disorders are associated with different pathologies that often co‐occur but cannot be measured specifically with in vivo methods.
Associations between cortical microinfarcts, hippocampal atrophy, and cerebral small vessel disease

S. Sadaghiani, S. Dolui, Pulkit Khandelwal, M. Taghvaei, Banafsheh Shakibajahromi, Sandhitsu R. Das, Paul Yushkevich, D. Wolk, and J. Detre

Alzheimer’s & Dementia, Dec 2022

Abs DOI

Brain cortical microinfarcts (CMI) are negatively correlated with cognitive function in both normal aging and Alzheimer’s disease (AD). High‐field structural magnetic resonance imaging (MRI) has facilitated in vivo detection of CMIs but their significance and underlying pathological mechanism remain uncertain. Here we assessed correlations between CMIs and medial temporal lobe (MTL) cortical thickness, white matter hyperintensity (WMH) volume, and relative periventricular white matter cerebral blood flow (PVWM CBF) in healthy individuals. PVWM CBF is thought to provide a measure of cerebral small vessel function.
Linking histology to post‐mortem 7T MRI measures of neurodegeneration

S. Sadaghiani, S. Ravikumar, R. Ittyerah, Sydney A. Lim, E. Chung, M. Bedard, Long Xie, Sandhitsu R. Das, T. Schuck, M. Grossman, Edward B. Lee, D. Tisdall, K. Prabhakaran, J. Detre, G. Mizsei, J. Trojanowski, D. Irwin, L. Wisse, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2022

Abs DOI

Neurodegenerative disorders are associated with different pathologies that often co‐occur and have differential contribution to the pattern of cognitive impairment. The majority of these pathologies cannot be detected or measured by in‐vivo methods; therefore, recognition of the topographic patterns of them and association with MRI findings may provide probabilistic non‐invasive biomarkers. We investigated the association of cortical and medial temporal lobe subregional thickness measured from postmortem MRI and semi‐quantitative pathologic measures in order to provide a methodological approach for linking pathological and radiological measures.
Associations of phosphorylated tau pathology with whole‐hemisphere ex vivo morphometry in 7 tesla MRI

S. Sadaghiani, W. Trotman, Sydney A. Lim, E. Chung, R. Ittyerah, S. Ravikumar, Pulkit Khandelwal, K. Prabhakaran, Madigan Lavery, Daniel T. Ohm, M. Gabrielyan, Sandhitsu R. Das, T. Schuck, Noah Capp, Claire S. Peterson, Elyse Migdal, E. Artacho-Pérula, María Mar Arroyo Jiménez, M. Rabal, Sandra Cebada Sanchez, Carlos Rosa Prieto, Marta Córcoles Parada, R. Insausti, J. Robinson, C. Mcmillan, M. Grossman, Eddie B. Lee, J. Detre, S. Xie, J. Trojanowski, M. Tisdall, L. Wisse, D. Irwin, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2022

Cited by 11

Abs DOI

Neurodegenerative disorders are associated with different pathologies that often co‐occur but cannot be measured specifically with in vivo methods.
Modules of genotypic variance reflect heterogeneity across TDP‐43 proteinopathies

Barbara E. Spencer, David J. Irwin, V. Van Deerlin, Eddie B. Lee, L. Elman, C. Quinn, M. Grossman, D. Wolk, and C. Mcmillan

Alzheimer’s & Dementia, Dec 2022

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TAR DNA‐binding protein (TDP‐43) proteinopathies yield a variety of neurodegenerative conditions including amyotrophic lateral sclerosis (ALS), frontotemporal lobar degeneration (FTLD), and hippocampal sclerosis of aging (HS‐Aging). However, the contribution of both shared and disparate single nucleotide polymorphisms (SNPs) to phenotypic presentations is unclear. We hypothesize that shared genetic variation may drive susceptibility across diseases while disparate genetic variation may contribute to our understanding of disease‐specific drivers.
Mechanisms of Cognitive Decline due to White Matter Lesions in Cognitively Intact Older Adults

M. Taghvaei, Philip A Cook, Pulkit Khandelwal, Banafsheh Shakibajahromi, S. Sadaghiani, Sandhitsu R. Das, Christopher A. Brown, William Tackett, S. Dolui, R. Shinohara, D. Wolk, and J. Detre

Alzheimer’s & Dementia, Dec 2022

Abs DOI

White matter hyperintensities (WMH) on FLAIR MRI are highly prevalent in older adults and are linked to cognitive deficits as well as dementia. Likely mechanisms underlying associations between WMH and cognitive deficits include widespread partial disconnection due to the diffuse nature of progressive WMH and/or tract‐specific disconnection syndromes. We used a virtual lesion approach to evaluate cognitive deficits in domains associated with three tracts: left arcuate fasciculus (LAF; verbal working memory), inferior longitudinal fasciculus (ILF; visual processing), and fornix (memory).
An autopsy‐validated, easily deployable MRI predictor of Alzheimer’s disease tau pathology

J. Vogel, O. Strandberg, Chris Gaiteri, M. Cieslak, S. Covitz, D. Wolk, C. Davatzikos, O. Hansson, and Theodore Satterthwaite

Alzheimer’s & Dementia, Dec 2022

Cited by 2

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Tau pathology is a hallmark of Alzheimer’s disease, but measuring this pathology in vivo with PET is expensive. MRI represents a low‐cost alternative for measuring in vivo disease progression, but is non‐specific. We present an MR‐based marker of tau‐specific pathology using machine learning (ML).
PART is part of SNAP‐MCI

L. Wisse, Long Xie, Xueying Lyu, Sandhitsu R. Das, R. Flores, J. Lane, Paul Yushkevich, D. Wolk, and Disease Neuroimaging Initiative

Alzheimer’s & Dementia, Dec 2022

Abs DOI

Mild Cognitive Impairment with Suspected non‐Alzheimer’s Pathophysiology (SNAP‐MCI) represents a group of patients with Alzheimer’s disease (AD) like neurodegeneration without beta‐amyloid pathology. While this group likely has a heterogeneous etiology, tau pathology, as in Primary Age‐Related Tauopathy (PART), has been hypothesized to play a major role. We investigate tau positron emission tomography (PET) uptake in the medial temporal lobe (MTL) in SNAP‐MCI and the association of MTL Tau‐PET uptake with structural measures and delayed recall in beta‐amyloid negative (A‐) MCI patients.
Empirical pathological staging and subtyping of TDP‐43 proteinopathies

Alexandra L. Young, Jacob W. Vogel, John L. Robinson, C. Mcmillan, R. Ossenkoppele, D. Wolk, David J. Irwin, L. Elman, M. Grossman, V. Lee, Eddie B. Lee, J. Trojanowski, and O. Hansson

Alzheimer’s & Dementia, Dec 2022

Cited by 1

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Pathological aggregation of tar DNA‐binding protein 43 (TDP‐43) in the brain is the primary cause of many cases of frontotemporal lobar degeneration (FTLD), amyotrophic lateral sclerosis (ALS) and limbic‐predominant age‐related TDP‐43 encephalopathy (LATE). It is therefore imperative to establish empirical staging systems to characterize and distinguish stereotypical patterns and commonplace deviations of different TDP‐43 proteinopathies.
Deep Label Fusion: A Generalizable Hybrid Multi-Atlas and Deep Convolutional Neural Network for Medical Image Segmentation

Long Xie, L. Wisse, Jiancong Wang, S. Ravikumar, Pulkit Khandelwal, T. Glenn, A. Luther, Sydney A. Lim, D. Wolk, and Paul Yushkevich

Medical image analysis, Nov 2022

Cited by 65

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Deep convolutional neural networks (DCNN) achieve very high accuracy in segmenting various anatomical structures in medical images but often suffer from relatively poor generalizability. Multi-atlas segmentation (MAS), while less accurate than DCNN in many applications, tends to generalize well to unseen datasets with different characteristics from the training dataset. Several groups have attempted to integrate the power of DCNN to learn complex data representations and the robustness of MAS to changes in image characteristics. However, these studies primarily focused on replacing individual components of MAS with DCNN models and reported marginal improvements in accuracy. In this study we describe and evaluate a 3D end-to-end hybrid MAS and DCNN segmentation pipeline, called Deep Label Fusion (DLF). The DLF pipeline consists of two main components with learnable weights, including a weighted voting subnet that mimics the MAS algorithm and a fine-tuning subnet that corrects residual segmentation errors to improve final segmentation accuracy. We evaluate DLF on five datasets that represent a diversity of anatomical structures (medial temporal lobe subregions and lumbar vertebrae) and imaging modalities (multi-modality, multi-field-strength MRI and Computational Tomography). These experiments show that DLF achieves comparable segmentation accuracy to nnU-Net (Isensee et al., 2020), the state-of-the-art DCNN pipeline, when evaluated on a dataset with similar characteristics to the training datasets, while outperforming nnU-Net on tasks that involve generalization to datasets with different characteristics (different MRI field strength or different patient population). DLF is also shown to consistently improve upon conventional MAS methods. In addition, a modality augmentation strategy tailored for multimodal imaging is proposed and demonstrated to be beneficial in improving the segmentation accuracy of learning-based methods, including DLF and DCNN, in missing data scenarios in test time as well as increasing the interpretability of the contribution of each individual modality.
Aging is associated with maladaptive episodic memory-guided social decision-making

Karolina M. Lempert, Michael S. Cohen, Kameron A MacNear, Frances M. Reckers, Laura Zaneski, D. Wolk, and Joseph W. Kable

In Proceedings of the National Academy of Sciences of the United States of America, Oct 2022

Cited by 13

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Significance Older adults are frequently targets of financial fraud. Therefore, understanding how cognitive changes across adulthood impact social decisions with economic stakes is critical. We investigated, in adults aged 18 to 92, how memory for previous interactions influences social decisions and how those decisions differ from analogous, nonsocial choices. While their memory deficits led to poorer decisions in both domains, older adults had biases that made their social decisions especially maladaptive: they tended to remember that others were generous, they interacted with familiar others regardless of what they remembered about them, and they chose partners who appeared generous, even when they were not. Thus, older adults may make financially costly social decisions when those decisions depend on recalling specific past experiences.
A Taxonomy of Seizure Spread Patterns, Speed of Spread, and Associations With Structural Connectivity

A. Revell, A. Pattnaik, E. Conrad, Nishant Sinha, Brittany H. Scheid, A. Lucas, John M. Bernabei, J. Beckerle, J. Stein, Sandhitsu R. Das, B. Litt, and K. Davis

bioRxiv, Oct 2022

Cited by 5

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Although seizure detection algorithms are widely used to localize seizure onset on intracranial EEG in epilepsy patients, relatively few studies focus on seizure activity beyond the seizure onset zone to direct treatment of surgical patients with epilepsy. To address this gap, we develop and compare fully automated deep learning algorithms to detect seizure activity on single channels, effectively quantifying spread when deployed across multiple channels. Across 275 seizures in 71 patients, we discover that the extent of seizure spread across the brain and the timing of seizure spread between temporal lobe regions is associated with both surgical outcomes and the brain’s structural connectivity between temporal lobes. Finally, we uncover a hierarchical structure of seizure spread patterns highlighting the relationship between clusters of seizures. Collectively, these findings underscore the broad utility in quantifying seizure activity past seizure onset to identify novel mechanisms of seizure evolution and its relationship to potential seizure freedom.
Mapping hippocampal glutamate in mesial temporal lobe epilepsy with glutamate weighted CEST (GluCEST) imaging

A. Lucas, R. Nanga, P. Hadar, Stephanie H. Chen, A. Gibson, Kelly F. Oechsel, M. Elliott, J. Stein, Sandhitsu R. Das, Ravinder Reddy, J. Detre, and K. Davis

Human Brain Mapping, Sep 2022

Cited by 24

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Temporal lobe epilepsy (TLE) is one of the most common subtypes of focal epilepsy, with mesial temporal sclerosis (MTS) being a common radiological and histopathological finding. Accurate identification of MTS during presurgical evaluation confers an increased chance of good surgical outcome. Here we propose the use of glutamate‐weighted chemical exchange saturation transfer (GluCEST) magnetic resonance imaging (MRI) at 7 Tesla for mapping hippocampal glutamate distribution in epilepsy, allowing to differentiate lesional from non‐lesional mesial TLE. We demonstrate that a directional asymmetry index, which quantifies the relative difference between GluCEST contrast in hippocampi ipsilateral and contralateral to the seizure onset zone, can differentiate between sclerotic and non‐sclerotic hippocampi, even in instances where traditional presurgical MRI assessments did not provide evidence of sclerosis. Overall, our results suggest that hippocampal glutamate mapping through GluCEST imaging is a valuable addition to the presurgical epilepsy evaluation toolbox.
The Polygenic Risk Score Knowledge Base offers a centralized online repository for calculating and contextualizing polygenic risk scores

Madeline L. Page, Elizabeth L Vance, Matthew E Cloward, Ed Ringger, Louisa Dayton, M. Ebbert, M. W. P. R. C. R. W. J. Q. A. W. L. R. C. A. J. J. C. Weiner Aisen Petersen Jack Jagust Trojanowki Toga, M. Weiner, P. R. Aisen Petersen, P. Aisen, R. Petersen, C. R. W. J. Q. A. W. L. R. C. A. J. J. C. R. J. L. M. Jack Jagust Trojanowki Toga Beckett Green Saykin M, C. Jack, W. Jagust, J. Trojanowki, A. W. Toga, L. Beckett, R. C. Green, A. Saykin, J. Morris, R. Perrin, L. Shaw, Z. M. W. L. M. H. C. J. K. J. E. D. O. R. L. N. Khachaturian Carrillo Potter Barnes Bernard Gonzál, Z. Khachaturian, M. Carrillo, W. Potter, L. Barnes, M. Bernard, H. González, C. Ho, J. Hsiao, J. Jackson, E. Masliah, D. Masterman, O. Okonkwo, R. Perrin, L. Ryan, N. Silverberg, A. Fleisher, D. T. J. C. D. J. C. R. M. D. A. Sacrey Fockler Conti Veitch Neuhaus Jin Nosheny As, D. Sacrey, J. Fockler, C. Conti, D. Veitch, J. Neuhaus, C. Jin, R. Nosheny, M. Ashford, D. Flenniken, A. Kormos, and 428 more authors

Communications Biology, Sep 2022

Cited by 9

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The process of identifying suitable genome-wide association (GWA) studies and formatting the data to calculate multiple polygenic risk scores on a single genome can be laborious. Here, we present a centralized polygenic risk score calculator currently containing over 250,000 genetic variant associations from the NHGRI-EBI GWAS Catalog for users to easily calculate sample-specific polygenic risk scores with comparable results to other available tools. Polygenic risk scores are calculated either online through the Polygenic Risk Score Knowledge Base (PRSKB; https://prs.byu.edu) or via a command-line interface. We report study-specific polygenic risk scores across the UK Biobank, 1000 Genomes, and the Alzheimer’s Disease Neuroimaging Initiative (ADNI), contextualize computed scores, and identify potentially confounding genetic risk factors in ADNI. We introduce a streamlined analysis tool and web interface to calculate and contextualize polygenic risk scores across various studies, which we anticipate will facilitate a wider adaptation of polygenic risk scores in future disease research. The Polygenic Risk Score Knowledge Base (PRSKB) is a web-based interface that stores data from >2,300 distinct genome-wide association studies, and can estimate polygenic risk scores for general use.
Deep learning-based automated segmentation of resection cavities on postsurgical epilepsy MRI

T. Arnold, Ramya Muthukrishnan, A. Pattnaik, Nishant Sinha, Adam D. Gibson, Hannah Gonzalez, Sandhitsu R. Das, B. Litt, D. J. Englot, V. Morgan, K. Davis, and J. Stein

NeuroImage : Clinical, Aug 2022

Cited by 18

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Highlights • We developed an open-source algorithm for resection cavity segmentation.• Algorithm performance (0.76–0.84 DSC) approached interrater reliability (0.84 DSC).• This tool can be used to estimate postoperative remnant volumes (e.g. hippocampus).• All code and model weights are available: https://github.com/penn-cnt/DeepResection.
Repeatability of B1+ Inhomogeneity Correction of Volumetric (3D) Glutamate CEST via High-Permittivity Dielectric Padding at 7T

Paul S. Jacobs, Blake Benyard, Abigail T. J. Cember, R. Nanga, Q. Cao, M. Tisdall, N. Wilson, Sandhitsu R. Das, K. Davis, J. Detre, D. Roalf, and Ravinder Reddy

Magnetic resonance in medicine, Aug 2022

Cited by 15

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Ultra‐high field MR imaging lacks B1+ inhomogeneity due to shorter RF wavelengths used at higher field strengths compared to human anatomy. CEST techniques tend to be highly susceptible to B1+ inhomogeneities due to a high and uniform B1+ field being necessary to create the endogenous contrast. High‐permittivity dielectric pads have seen increasing usage in MR imaging due to their ability to tailor the spatial distribution of the B1+ field produced. The purpose of this work is to demonstrate that dielectric materials can be used to improve glutamate weighted CEST (gluCEST) at 7T.
Repeatability of B1+ inhomogeneity correction of volumetric (3D) glutamate CEST via High‐permittivity dielectric padding at 7T

Paul S Jacobs, Blake Benyard, Abigail T. J. Cember, R. Nanga, Q. Cao, M. Tisdall, N. Wilson, Sandhitsu R. Das, K. Davis, J. Detre, D. Roalf, and Ravinder Reddy

Magnetic Resonance in Medicine, Aug 2022

Cited by 11

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Ultra‐high field MR imaging lacks B1+ inhomogeneity due to shorter RF wavelengths used at higher field strengths compared to human anatomy. CEST techniques tend to be highly susceptible to B1+ inhomogeneities due to a high and uniform B1+ field being necessary to create the endogenous contrast. High‐permittivity dielectric pads have seen increasing usage in MR imaging due to their ability to tailor the spatial distribution of the B1+ field produced. The purpose of this work is to demonstrate that dielectric materials can be used to improve glutamate weighted CEST (gluCEST) at 7T.
Resting state functional connectivity demonstrates increased segregation in bilateral temporal lobe epilepsy

A. Lucas, E. Cornblath, Nishant Sinha, P. Hadar, Lorenzo Caciagli, S. Keller, L. Bonilha, R. Shinohara, J. Stein, Sandhitsu R. Das, E. Gleichgerrcht, and Kathryn A. Davis

Epilepsia, Aug 2022

Cited by 25

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Temporal lobe epilepsy (TLE) is the most common type of focal epilepsy. An increasingly identified subset of patients with TLE consists of those who show bilaterally independent temporal lobe seizures. The purpose of this study was to leverage network neuroscience to better understand the interictal whole brain network of bilateral TLE (BiTLE).
Neuropsychological and Neuroanatomical Features of Patients with Behavioral/Dysexecutive Variant Alzheimer’s Disease (AD): A Comparison to Behavioral Variant Frontotemporal Dementia and Amnestic AD Groups

Sophia Dominguez Perez, Jeffrey S. Phillips, C. Norise, Nikolas G. Kinney, Prerana Vaddi, A. Halpin, K. Rascovsky, D. Irwin, C. McMillan, Long Xie, L. Wisse, Paul Yushkevich, D. Kallogjeri, M. Grossman, and K. Cousins

Journal of Alzheimer’s disease : JAD, Aug 2022

Cited by 14

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Background: An understudied variant of Alzheimer’s disease (AD), the behavioral/dysexecutive variant of AD (bvAD), is associated with progressive personality, behavior, and/or executive dysfunction and frontal atrophy. Objective: This study characterizes the neuropsychological and neuroanatomical features associated with bvAD by comparing it to behavioral variant frontotemporal dementia (bvFTD), amnestic AD (aAD), and subjects with normal cognition. Methods: Subjects included 16 bvAD, 67 bvFTD, 18 aAD patients, and 26 healthy controls. Neuropsychological assessment and MRI data were compared between these groups. Results: Compared to bvFTD, bvAD showed more significant visuospatial impairments (Rey Figure copy and recall), more irritability (Neuropsychological Inventory), and equivalent verbal memory (Philadelphia Verbal Learning Test). Compared to aAD, bvAD indicated more executive dysfunction (F-letter fluency) and better visuospatial performance. Neuroimaging analysis found that bvAD showed cortical thinning relative to bvFTD posteriorly in left temporal-occipital regions; bvFTD had cortical thinning relative to bvAD in left inferior frontal cortex. bvAD had cortical thinning relative to aAD in prefrontal and anterior temporal regions. All patient groups had lower volumes than controls in both anterior and posterior hippocampus. However, bvAD patients had higher average volume than aAD patients in posterior hippocampus and higher volume than bvFTD patients in anterior hippocampus after adjustment for age and intracranial volume. Conclusion: Findings demonstrated that underlying pathology mediates disease presentation in bvAD and bvFTD.
Regional distribution and maturation of tau pathology among phenotypic variants of Alzheimer’s disease

Sanaz Arezoumandan, Sharon X. Xie, K. Cousins, D. Mechanic-Hamilton, Claire S. Peterson, Camille Y. Huang, Daniel T. Ohm, R. Ittyerah, C. McMillan, D. Wolk, Paul Yushkevich, J. Trojanowski, Edward B. Lee, M. Grossman, Jeffrey S. Phillips, and D. Irwin

Acta neuropathologica, Jul 2022

Cited by 24

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Alzheimer’s disease neuropathologic change (ADNC) is clinically heterogenous and can present with a classic multidomain amnestic syndrome or focal non-amnestic syndromes. Here, we investigated the distribution and burden of phosphorylated and C-terminally cleaved tau pathologies across hippocampal subfields and cortical regions among phenotypic variants of Alzheimer’s disease (AD). In this study, autopsy-confirmed patients with ADNC, were classified into amnestic (aAD, N = 40) and non-amnestic (naAD, N = 39) groups based on clinical criteria. We performed digital assessment of tissue sections immunostained for phosphorylated-tau (AT8 detects pretangles and mature tangles), D421-truncated tau (TauC3, a marker for mature tangles and ghost tangles), and E391-truncated tau (MN423, a marker that primarily detects ghost tangles), in hippocampal subfields and three cortical regions. Linear mixed-effect models were used to test regional and group differences while adjusting for demographics. Both groups showed AT8-reactivity across hippocampal subfields that mirrored traditional Braak staging with higher burden of phosphorylated-tau in subregions implicated as affected early in Braak staging. The burden of phosphorylated-tau and TauC3-immunoreactive tau in the hippocampus was largely similar between the aAD and naAD groups. In contrast, the naAD group had lower relative distribution of MN423-reactive tangles in CA1 (β = − 0.2, SE = 0.09, p = 0.001) and CA2 (β = − 0.25, SE = 0.09, p = 0.005) compared to the aAD. While the two groups had similar levels of phosphorylated-tau pathology in cortical regions, there was higher burden of TauC3 reactivity in sup/mid temporal cortex (β = 0.16, SE = 0.07, p = 0.02) and MN423 reactivity in all cortical regions (β = 0.4–0.43, SE = 0.09, p < 0.001) in the naAD compared to aAD. In conclusion, AD clinical variants may have a signature distribution of overall phosphorylated-tau pathology within the hippocampus reflecting traditional Braak staging; however, non-amnestic AD has greater relative mature tangle pathology in the neocortex compared to patients with clinical amnestic AD, where the hippocampus had greatest relative burden of C-terminally cleaved tau reactivity. Thus, varying neuronal susceptibility to tau-mediated neurodegeneration may influence the clinical expression of ADNC.
Self- and Partner-Reported Subjective Memory Complaints: Association with Objective Cognitive Impairment and Risk of Decline

Leah Zuroff, L. Wisse, T. Glenn, Sharon X. Xie, I. Nasrallah, M. Habes, J. Dubroff, R. Flores, Long Xie, Paul Yushkevich, J. Doshi, Christos Davatsikos, L. Shaw, T. Tropea, A. Chen-Plotkin, D. Wolk, Sandhitsu R. Das, and D. Mechanic-Hamilton

Journal of Alzheimer’s Disease Reports, Jul 2022

Cited by 14

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Background: Episodic memory decline is a hallmark of Alzheimer’s disease (AD). Subjective memory complaints (SMCs) may represent one of the earliest signs of impending cognitive decline. The degree to which self- or partner-reported SMCs predict cognitive change remains unclear. Objective: We aimed to evaluate the relationship between self- and partner-reported SMCs, objective cognitive performance, AD biomarkers, and risk of future decline in a well-characterized longitudinal memory center cohort. We also evaluated whether study partner characteristics influence reports of SMCs. Methods: 758 participants and 690 study partners were recruited from the Penn Alzheimer’s Disease Research Center Clinical Core. Participants included those with Normal Cognition, Mild Cognitive Impairment, and AD. SMCs were measured using the Prospective and Retrospective Memory Questionnaire (PRMQ), and were evaluated for their association with cognition, genetic, plasma, and neuroimaging biomarkers of AD, cognitive and functional decline, and diagnostic progression over an average of four years. Results: We found that partner-reported SMCs were more consistent with cognitive test performance and increasing symptom severity than self-reported SMCs. Partner-reported SMCs showed stronger correlations with AD-associated brain atrophy, plasma biomarkers of neurodegeneration, and longitudinal cognitive and functional decline. A 10-point increase on baseline PRMQ increased the annual risk of diagnostic progression by approximately 70%. Study partner demographics and relationship to participants influenced reports of SMCs in AD participants only. Conclusion: Partner-reported SMCs, using the PRMQ, have a stronger relationship with the neuroanatomic and cognitive changes associated with AD than patient-reported SMCs. Further work is needed to evaluate whether SMCs could be used to screen for future decline.
Fully Automated 3D Segmentation and Diffeomorphic Medial Modeling of the Left Ventricle Mitral Valve Complex in Ischemic Mitral Regurgitation

A. H. Aly, Pulkit Khandelwal, Abdullah H. Aly, Takayuki Kawashima, Kazuki Mori, Yoshiaki Saito, J. Hung, J. Gorman, A. Pouch, R. Gorman, and Paul Yushkevich

Medical image analysis, Jun 2022

Cited by 17

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There is an urgent unmet need to develop a fully-automated image-based left ventricle mitral valve analysis tool to support surgical decision making for ischemic mitral regurgitation patients. This requires an automated tool for segmentation and modeling of the left ventricle and mitral valve from immediate pre-operative 3D transesophageal echocardiography. Previous works have presented methods for semi-automatically segmenting and modeling the mitral valve, but do not include the left ventricle and do not avoid self-intersection of the mitral valve leaflets during shape modeling. In this study, we develop and validate a fully automated algorithm for segmentation and shape modeling of the left ventricular mitral valve complex from pre-operative 3D transesophageal echocardiography. We performed a 3-fold nested cross validation study on two datasets from separate institutions to evaluate automated segmentations generated by nnU-net with the expert manual segmentation which yielded average overall Dice scores of 0.82±0.03 (set A), 0.87±0.08 (set B) respectively. A deformable medial template was subsequently fitted to the segmentation to generate shape models. Comparison of shape models to the manual and automatically generated segmentations resulted in an average Dice score of 0.93-0.94 and 0.75-0.81 for the left ventricle and mitral valve, respectively. This is a substantial step towards automatically analyzing the left ventricle mitral valve complex in the operating room.
Implanting intracranial electrodes does not affect spikes or network connectivity in nearby or connected brain regions

E. Conrad, R. Shinohara, James J. Gugger, A. Revell, Sandhitsu R. Das, J. Stein, E. Marsh, K. Davis, and B. Litt

Network Neuroscience, Apr 2022

Cited by 4

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Abstract To determine the effect of implanting electrodes on electrographic features of nearby and connected brain regions in patients with drug-resistant epilepsy, we analyzed intracranial EEG recordings from 10 patients with drug-resistant epilepsy who underwent implant revision (placement of additional electrodes) during their hospitalization. We performed automated spike detection and measured EEG functional networks. We analyzed the original electrodes that remained in place throughout the full EEG recording, and we measured the change in spike rates and network connectivity in these original electrodes in response to implanting new electrodes. There was no change in overall spike rate pre- to post-implant revision (t(9) = 0.1, p = 0.95). The peri-revision change in the distribution of spike rate and connectivity across electrodes was no greater than chance (Monte Carlo method, spikes: p = 0.40, connectivity: p = 0.42). Electrodes closer to or more functionally connected to the revision site had no greater change in spike rate or connectivity than more distant or less connected electrodes. Changes in electrographic features surrounding electrode implantation are no greater than baseline fluctuations occurring throughout the intracranial recording. These findings argue against an implant effect on spikes or network connectivity in nearby or connected brain regions.
P67. DEVELOPMENT OF A CRANIOFACIAL SOFT TISSUE ANTHROPOMORPHIC DATABASE: APPLICATION OF DIFFEOMORPHIC ALGORITHMS TO MRI

D. Villavisanis, Pulkit Khandelwal, Zachary D. Zapatero, Connor S. Wagner, D. Cho, J. Blum, Liana Cheung, J. Swanson, Jesse A. Taylor, Paul Yushkevich, and S. Bartlett

Plastic and Reconstructive Surgery - Global Open, Apr 2022

Cited by 4

DOI PDF
Dissociation of tau pathology and neuronal hypometabolism within the ATN framework of Alzheimer’s disease

M. T. Duong, Sandhitsu R. Das, Xueying Lyu, Long Xie, Hayley M. Richardson, Sharon X. Xie, Paul Yushkevich, Michael W. Weiner, P. Aisen, Ronald C. Petersen, C. Jack, W. Jagust, J. Trojanowki, A. Toga, Laurel A. Beckett, R. Green, A. Saykin, J. Morris, L. Shaw, E. Liu, T. Montine, R. Thomas, M. Donohue, Sarah Walter, Devon Gessert, T. Sather, G. Jimenez-Maggiora, D. Harvey, M. Bernstein, Nick N. Fox, Paul M. Thompson, N. Schuff, C. Decarli, Bret J. Borowski, J. Gunter, Matthew Senjem, P. Vemuri, David Jones, K. Kantarci, Chadwick P. Ward, R. Koeppe, Normal L. Foster, E. Reiman, Ke-Wei Chen, Chet Mathis, S. Landau, N. Cairns, E. Householder, Lisa taylor-Reinwald, Virginia Lee, and 240 more authors

Nature Communications, Mar 2022

Cited by 44

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Alzheimer’s disease (AD) is defined by amyloid (A) and tau (T) pathologies, with T better correlated to neurodegeneration (N). However, T and N have complex regional relationships in part related to non-AD factors that influence N. With machine learning, we assessed heterogeneity in 18F-flortaucipir vs. 18F-fluorodeoxyglucose positron emission tomography as markers of T and neuronal hypometabolism (NM) in 289 symptomatic patients from the Alzheimer’s Disease Neuroimaging Initiative. We identified six T/NM clusters with differing limbic and cortical patterns. The canonical group was defined as the T/NM pattern with lowest regression residuals. Groups resilient to T had less hypometabolism than expected relative to T and displayed better cognition than the canonical group. Groups susceptible to T had more hypometabolism than expected given T and exhibited worse cognitive decline, with imaging and clinical measures concordant with non-AD copathologies. Together, T/NM mismatch reveals distinct imaging signatures with pathobiological and prognostic implications for AD. In Alzheimer’s disease (AD) tau and neurodegeneration have complex regional relationships. Here, the authors show neuronal hypometabolism discordant with tau burden defines functional resilience or susceptibility to Alzheimer’s pathology via limbic/cortical axes. Susceptible groups have faster cognitive decline and evidence of non-Alzheimer’s pathologies.
Medial Temporal Lobe Networks in Alzheimer’s Disease: Structural and Molecular Vulnerabilities

R. Flores, Sandhitsu R. Das, Long Xie, L. Wisse, Xueying Lyu, Preya Shah, Paul Yushkevich, and D. Wolk

The Journal of Neuroscience, Jan 2022

Cited by 62

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The medial temporal lobe (MTL) is connected to the rest of the brain through two main networks: the anterior-temporal (AT) and the posterior-medial (PM) systems. Given the crucial role of the MTL and networks in the physiopathology of Alzheimer’s disease (AD), the present study aimed at (1) investigating whether MTL atrophy propagates specifically within the AT and PM networks, and (2) evaluating the vulnerability of these networks to AD proteinopathies. To do that, we used neuroimaging data acquired in human male and female in three distinct cohorts: (1) resting-state functional MRI (rs-fMRI) from the aging brain cohort (ABC) to define the AT and PM networks (n = 68); (2) longitudinal structural MRI from Alzheimer’s disease neuroimaging initiative (ADNI)GO/2 to highlight structural covariance patterns (n = 349); and (3) positron emission tomography (PET) data from ADNI3 to evaluate the networks’ vulnerability to amyloid and tau (n = 186). Our results suggest that the atrophy of distinct MTL subregions propagates within the AT and PM networks in a dissociable manner. Brodmann area (BA)35 structurally covaried within the AT network while the parahippocampal cortex (PHC) covaried within the PM network. In addition, these networks are differentially associated with relative tau and amyloid burden, with higher tau levels in AT than in PM and higher amyloid levels in PM than in AT. Our results also suggest differences in the relative burden of tau species. The current results provide further support for the notion that two distinct MTL networks display differential alterations in the context of AD. These findings have important implications for disease spread and the cognitive manifestations of AD. SIGNIFICANCE STATEMENT The current study provides further support for the notion that two distinct medial temporal lobe (MTL) networks, i.e., anterior-temporal (AT) and the posterior-medial (PM), display differential alterations in the context of Alzheimer’s disease (AD). Importantly, neurodegeneration appears to occur within these networks in a dissociable manner marked by their covariance patterns. In addition, the AT and PM networks are also differentially associated with relative tau and amyloid burden, and perhaps differences in the relative burden of tau species [e.g., neurofibriliary tangles (NFTs) vs tau in neuritic plaques]. These findings, in the context of a growing literature consistent with the present results, have important implications for disease spread and the cognitive manifestations of AD in light of the differential cognitive processes ascribed to them.
Neuropsychological and neuroanatomical features of patients with behavioral variant Alzheimer’s disease (AD): a comparison to behavioral variant frontotemporal dementia and amnestic AD groups

Sophia Dominguez Perez, Jeffrey S. Phillips, C. Norise, Nikolas G. Kinney, Prerana Vaddi, A. Halpin, K. Rascovsky, D. Irwin, C. McMillan, Long Xie, L. Wisse, Paul Yushkevich, D. Kallogjeri, M. Grossman, and K. Cousins

medRxiv, Jan 2022

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An understudied non-amnestic variant of Alzheimer’s disease (AD), behavioral variant AD (bvAD) is associated with progressive personality, behavior, or executive dysfunction and frontal atrophy. This study characterizes the neuropsychological and neuroanatomical features associated with bvAD by comparing it to behavioral variant frontotemporal dementia (bvFTD), amnestic AD (aAD), and subjects with normal cognition. Subjects included 16 bvAD, 67 bvFTD, and 18 aAD patients, and 26 healthy controls. Compared to bvFTD, bvAD showed more significant visuospatial impairments (Rey Figure copy and recall), more irritability (Neuropsychological Inventory), and equivalent verbal memory (Philadelphia Verbal Learning Test). Compared to aAD, bvAD indicated more executive dysfunction (F-letter fluency) and better visuospatial performance. Neuroimaging analysis found that bvAD showed cortical thinning relative to bvFTD posteriorly in left temporal-occipital regions; bvFTD had cortical thinning relative to bvAD in left inferior frontal cortex. bvAD had cortical thinning relative to aAD in prefrontal and anterior temporal regions. All patient groups had lower volumes than controls in both anterior and posterior hippocampus. However, bvAD patients had higher average volume than aAD patients in posterior hippocampus and higher volume than bvFTD patients in anterior hippocampus after adjustment for age and intracranial volume. Findings demonstrated that underlying pathology mediates disease presentation in bvAD and bvFTD.

2021

Regional distribution of tau pathology in subfields of hippocampus among phenotypic variants of AD and FTLD‐tau

Sanaz Arezoumandan, K. Cousins, Jeffrey S. Phillips, Daniel T. Ohm, Claire S. Peterson, R. Ittyerah, C. McMillan, D. Wolk, Paul Yushkevich, J. Trojanowski, Edward B. Lee, M. Grossman, and D. Irwin

Alzheimer’s & Dementia, Dec 2021

DOI
Application of histopathologically derived 3D tau burden map as in‐vivo region of interest for biomarker analysis

Sandhitsu R. Das, Long Xie, R. Flores, M. Muñoz, Maria Mercedes Iñiguez Onzoño Martin, R. Ittyerah, Sydney A. Lim, S. Ravikumar, Madigan Lavery, S. Pickup, Wei-Xia Liu, Jiancong Wang, Ling-Yu Hung, Jade Lasserve, Nicolas Vergnet, M. Dong, Salena Cui, Lauren McCollum, J. Robinson, T. Schuck, M. Grossman, D. Tisdall, K. Prabhakaran, G. Mizsei, E. Artacho-Pérula, María Mar Arroyo Jiménez, Maria Pilar Marcos Rabal, Francisco Javier Molina Romero, S. C. Sánchez, José Carlos Delgado González, C. Rosa Prieto, Marta Córcoles Parada, Edward B. Lee, J. Trojanowski, Daniel T. Ohm, I. Nasrallah, M. Kelley, J. Lane, Michael Dicalogero, L. Wisse, D. Irwin, R. Insausti, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Dec 2021

Cited by 1

Abs DOI

Quantitative three‐dimensional maps of tau neurofibrillary tangles (NFT) burden derived from dense serial histology have potential application for in‐vivo biomarker studies. We constructed a group‐level NFT burden map from 15 medial temporal lobe (MTL) specimens, majority with Primary Age‐Related Tauopathy (PART) or low‐level Alzheimer’s disease neuropathologic change, and showed relatively greater NFT burden in the anterior vs. posterior MTL. We investigated whether in‐vivo MRI and PET measures in ROIs derived from this map show meaningful biological relationships.
Remote neuropsychological assessment using the UDS v3.0 T‐Cog: Preliminary data among participants at the Penn ADRC

K. Hackett, Matthew J. Ferrara, S. Newman, M. Kelley, Laura Schankel, Hannah McCoubrey, Sharon Best, Sara Manning Peskin, K. O’Brien, Sharon X. Xie, D. Wolk, and D. Mechanic-Hamilton

Alzheimer’s & Dementia, Dec 2021

Cited by 2

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Due to the COVID‐19 pandemic, collection of the Uniform Data Set (UDS) at Alzheimer’s Disease Research Centers (ADRCs) transitioned to remote administration via the T‐Cog. Feasibility of data collection and dissemination of normative data in individuals across the cognitive spectrum will be necessary for accurate utilization of remotely‐captured neurocognitive performance and classification of cognitive function.
Development and pilot data for an app‐based cognitive assessment for detecting memory and executive functioning changes in aging and pre‐clinical AD

D. Mechanic-Hamilton, Sean Lydon, Alexander Miller, Kimberly Halberstadter, Michael Dicalogero, and D. Wolk

Alzheimer’s & Dementia, Dec 2021

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Mobile, valid and engaging cognitive assessments are essential for detecting and tracking change in research participants and patients at risk for Alzheimer’s Disease and Related Dementias (ADRDs). This pilot study aims to determine the feasibility and psychometric properties of app‐based memory and executive functioning tasks included in the mobile cognitive app performance platform (mCAPP), to detect cognitive changes associated with aging and preclinical Alzheimer’s Disease (AD).
A pilot study of social and structural determinants of health (SSDOH) measures in an Alzheimer’s Disease Research Center (ADRC) cohort

Sharnita Midgett, D. Mechanic-Hamilton, J. Karlawish, D. Wolk, and S. Stites

Alzheimer’s & Dementia, Dec 2021

Abs DOI

Research shows that people have different experiences, opportunities, and challenges depending on their background and life circumstances. These circumstances can be important social and structural determinants of health (SSDoH) that may help explain heterogeneity in cognitive, functional, and interventional outcomes in Alzheimer’s disease and related dementias (ADRDs). The National Institute on Aging has set as a priority understanding the effects of SSDoH. This information may help elucidate disease mechanisms and modifiers as well as aid discovery of disease modifying treatments that are effective across diverse populations.
Peer Review #1 of "Utility of olfactory identification test for screening of cognitive dysfunction in community-dwelling older adults (v0.3)"

S. Nogi, Kentaroh Uchida, J. Maruta, H. Kurozumi, S. Akada, M. Shiba, K. Inoue, C. Callahan, H. Hendrie, W. Tierney, J. Alves, A. Petrosyan, R. Magalhães, R. Wilson, J. Schneider, S. Arnold, Y. Tang, P. Boyle, D. Bennett, D. Roalf, M. Moberg, B. Turetsky, L. Brennan, S. Kabadi, D. Wolk, P. Moberg, M. Windon, S. Kim, E. Oh, Lin Sy, M. Makizako, H. Makizako, T. Doi, K. Uemura, K. Tsutsumimoto, H. Miyaguchi, H. Shimada, K. Yaffe, D. Freimer, H. Chen, K. Asao, A. Rosso, S. Rubin, G. Tranah, S. Cummings, E. Simonsick, X. Liang, D. Ding, Q. Zhao, Q. Guo, and 128 more authors

Dec 2021

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Background. There is a need for a large-scale screening test that can be used to detect dementia in older individuals at an early stage. Olfactory identification deficits have been shown to occur in the early stages of dementia, indicating their usefulness in screening tests. This study investigated the utility of an olfactory identification test as a screening test for mild cognitive dysfunction in community-dwelling older people.
Unfolding the medial temporal lobe to characterize neurodegeneration due to Alzheimer’s disease pathology

S. Ravikumar, L. Wisse, Sydney A. Lim, R. Ittyerah, Long Xie, M. Bedard, Sandhitsu R. Das, D. Irwin, Edward B. Lee, D. Tisdall, K. Prabhakaran, J. Detre, J. Trojanowski, J. Robinson, T. Schuck, M. Grossman, G. Mizsei, E. Artacho-Pérula, Maria Mercedes Iniguez Onzono Martin, María Mar Arroyo Jiménez, M. Muñoz, Francisco Javier Molina Romero, Maria Pilar Marcos Rabal, S. C. Sánchez, José Carlos Delgado González, C. Rosa Prieto, Marta Córcoles Parada, D. Wolk, R. Insausti, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2021

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Measurements of medial temporal lobe (MTL) neurodegeneration derived using MRI have been shown to be sensitive to changes during the early stages of AD. The specificity of these measurements to tau neurofibrillary tangle (NFT) pathology is limited by other frequently comorbid non‐AD factors which also cause structural changes in the MTL. Here, we directly link changes in MTL structure to underlying NFT pathology by combining ex vivo MRI with ratings of NFT severity derived from serial histology using a dataset of 18 human MTL specimens. We hypothesize that such an analysis can be used to define MTL “hotspots” where in vivo measures will be more sensitive to disease progression in preclinical AD than current state of the art biomarkers.
Associations between cortical microinfarcts and MRI markers of neurodegeneration and cerebrovascular disease in aging

S. Sadaghiani, S. Dolui, Dylan M. Tisdall, William Tackett, D. Wolk, and John A. Detre

Alzheimer’s & Dementia, Dec 2021

Abs DOI

Cortical microinfarcts (CMI) are associated with cognitive impairment in both healthy aging and dementia, though the mechanisms underlying CMIs remain uncertain. Here we assessed correlations between CMIs and medial temporal lobe (MTL) cortical thickness, white matter hyperintensity (WMH) volume, and cerebral blood flow (CBF) in older subjects.
Ex vivo MRI and histopathology detect novel iron-rich cortical inflammation in frontotemporal lobar degeneration with tau versus TDP-43 pathology

M. Tisdall, Daniel T. Ohm, Rebecca Lobrovich, Sandhitsu R. Das, G. Mizsei, K. Prabhakaran, R. Ittyerah, Sydney A. Lim, C. McMillan, D. Wolk, James Gee, J. Trojanowski, Edward B. Lee, J. Detre, Paul Yushkevich, M. Grossman, and D. Irwin

NeuroImage : Clinical, Dec 2021

Cited by 41

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Graphical abstract
Baseline structural MRI and plasma biomarkers predict longitudinal structural atrophy and cognitive decline in early AD

Long Xie, Sandhitsu R. Das, L. Wisse, R. Ittyerah, R. Flores, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Dec 2021

Cited by 3

Abs DOI

In clinical trials targeting early Alzheimer’s disease (AD), recruiting participants that are more likely to progress over the course of the trials is crucial to success. Molecular and neurodegenerative markers obtained through PET or in cerebrospinal fluid have significant prognostic value, but they are costly or invasive. In this study, we hypothesize that a combination of plasma and structural MRI biomarkers, which overcome these limitations, are predictive of longitudinal progression measured by atrophy and cognitive decline in early AD, providing a more feasible solution.
Diagnosing Mild Cognitive Impairment Among Racially Diverse Older Adults: Comparison of Consensus, Actuarial, and Statistical Methods

Kathryn Devlin, L. Brennan, Laura Saad, T. Giovannetti, R. Hamilton, D. Wolk, Sharon X. Xie, and D. Mechanic-Hamilton

Journal of Alzheimer’s disease : JAD, Nov 2021

Cited by 15

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Background: Actuarial and statistical methods have been proposed as alternatives to conventional methods of diagnosing mild cognitive impairment (MCI), with the aim of enhancing diagnostic and prognostic validity, but have not been compared in racially diverse samples. Objective: We compared the agreement of consensus, actuarial, and statistical MCI diagnostic methods, and their relationship to race and prognostic indicators, among diverse older adults. Methods: Participants (N = 354; M age = 71; 68% White, 29% Black) were diagnosed with MCI or normal cognition (NC) according to clinical consensus, actuarial neuropsychological criteria (Jak/Bondi), and latent class analysis (LCA). We examined associations with race/ethnicity, longitudinal cognitive and functional change, and incident dementia. Results: MCI rates by consensus, actuarial criteria, and LCA were 44%, 53%, and 41%, respectively. LCA identified three MCI subtypes (memory; memory/language; memory/executive) and two NC classes (low normal; high normal). Diagnostic agreement was substantial, but agreement of the actuarial method with consensus and LCA was weaker than the agreement between consensus and LCA. Among cases classified as MCI by actuarial criteria only, Black participants were over-represented, and outcomes were generally similar to those of NC participants. Consensus diagnoses best predicted longitudinal outcomes overall, whereas actuarial diagnoses best predicted longitudinal functional change among Black participants. Conclusion: Consensus diagnoses optimize specificity in predicting dementia, but among Black older adults, actuarial diagnoses may be more sensitive to early signs of decline. Results highlight the need for cross-cultural validity in MCI diagnosis and should be explored in community- and population-based samples.
Accuracy of high-frequency oscillations recorded intraoperatively for classification of epileptogenic regions

S. Weiss, R. Staba, A. Sharan, Chengyuan Wu, D. Rubinstein, Sandhitsu R. Das, Zachary Waldman, I. Orosz, G. Worrell, J. Engel, and M. Sperling

Scientific Reports, Nov 2021

Cited by 27

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To see whether acute intraoperative recordings using stereo EEG (SEEG) electrodes can replace prolonged interictal intracranial EEG (iEEG) recording, making the process more efficient and safer, 10 min of iEEG were recorded following electrode implantation in 16 anesthetized patients, and 1–2 days later during non-rapid eye movement (REM) sleep. Ripples on oscillations (RonO, 80–250 Hz), ripples on spikes (RonS), sharp-spikes, fast RonO (fRonO, 250–600 Hz), and fast RonS (fRonS) were semi-automatically detected. HFO power and frequency were compared between the conditions using a generalized linear mixed-effects model. HFO rates were compared using a two-way repeated measures ANOVA with anesthesia type and SOZ as factors. A receiver-operating characteristic (ROC) curve analysis quantified seizure onset zone (SOZ) classification accuracy, and the scalar product was used to assess spatial reliability. Resection of contacts with the highest rate of events was compared with outcome. During sleep, all HFOs, except fRonO, were larger in amplitude compared to intraoperatively (p < 0.01). HFO frequency was also affected (p < 0.01). Anesthesia selection affected HFO and sharp-spike rates. In both conditions combined, sharp-spikes and all HFO subtypes were increased in the SOZ (p < 0.01). However, the increases were larger during the sleep recordings (p < 0.05). The area under the ROC curves for SOZ classification were significantly smaller for intraoperative sharp-spikes, fRonO, and fRonS rates (p < 0.05). HFOs and spikes were only significantly spatially reliable for a subset of the patients (p < 0.05). A failure to resect fRonO areas in the sleep recordings trended the most sensitive and accurate for predicting failure. In summary, HFO morphology is altered by anesthesia. Intraoperative SEEG recordings exhibit increased rates of HFOs in the SOZ, but their spatial distribution can differ from sleep recordings. Recording these biomarkers during non-REM sleep offers a more accurate delineation of the SOZ and possibly the epileptogenic zone.
Tau-atrophy variability reveals phenotypic heterogeneity in Alzheimer’s disease

Sandhitsu R. Das, Xueying Lyu, M. T. Duong, Long Xie, Lauren McCollum, R. Flores, Michael Dicalogero, D. Irwin, B. Dickerson, I. Nasrallah, Paul Yushkevich, and D. Wolk

Annals of neurology, Oct 2021

Cited by 41

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Tau neurofibrillary tangles (T) are the primary driver of downstream neurodegeneration (N) and subsequent cognitive impairment in Alzheimer’s disease (AD). However, there is substantial variability in the T‐N relationship – manifested in higher or lower atrophy than expected for level of tau in a given brain region. The goal of this study was to determine if region‐based quantitation of this variability allows for identification of underlying modulatory factors, including polypathology.
Tau‐Atrophy Variability Reveals Phenotypic Heterogeneity in Alzheimer’s Disease

Sandhitsu R. Das, Xueying Lyu, M. Duong, L. Xie, Lauren McCollum, R. Flores, M. Dicalogero, D. Irwin, B. Dickerson, I. Nasrallah, Paul Yushkevich, and D. Wolk

Annals of Neurology, Oct 2021

Cited by 40

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Tau neurofibrillary tangles (T) are the primary driver of downstream neurodegeneration (N) and subsequent cognitive impairment in Alzheimer’s disease (AD). However, there is substantial variability in the T‐N relationship – manifested in higher or lower atrophy than expected for level of tau in a given brain region. The goal of this study was to determine if region‐based quantitation of this variability allows for identification of underlying modulatory factors, including polypathology.
Gray Matter Segmentation in Ultra High Resolution 7 Tesla ex vivo T2w MRI of Human Brain Hemispheres

Pulkit Khandelwal, S. Sadaghiani, M. T. Duong, S. Ravikumar, Sydney A. Lim, Sanaz Arezoumandan, Claire S. Peterson, E. Chung, M. Bedard, N. Capp, R. Ittyerah, Elyse Migdal, G. Choi, Emily Kopp, Bridget Loja, Eusha Hasan, Jiacheng Li, K. Prabhakaran, G. Mizsei, M. Gabrielyan, T. Schuck, J. Robinson, Daniel T. Ohm, Edward B. Lee, J. Trojanowski, C. McMillan, M. Grossman, D. Irwin, M. Tisdall, Sandhitsu R. Das, L. Wisse, D. Wolk, and Paul Yushkevich

ArXiv, Oct 2021

Cited by 4

Abs arXiv

Ex vivo MRI of the brain provides remarkable advantages over in vivo MRI for visualizing and characterizing detailed neuroanatomy. However, automated cortical segmentation methods in ex vivo MRI are not well developed, primarily due to limited availability of labeled datasets, and heterogeneity in scanner hardware and acquisition protocols. In this work, we present a high resolution 7 Tesla dataset of 32 ex vivo human brain specimens. We benchmark the cortical mantle segmentation performance of nine neural network architectures, trained and evaluated using manually-segmented 3D patches sampled from specific cortical regions, and show excellent generalizing capabilities across whole brain hemispheres in different specimens, and also on unseen images acquired at different magnetic field strength and imaging sequences. Finally, we provide cortical thickness measurements across key regions in 3D ex vivo human brain images. Our code and processed datasets are publicly available at https://github.com/Pulkit-Khandelwal/picsl-ex-vivo-segmentation.
Ex vivo MRI atlas of the human medial temporal lobe: characterizing neurodegeneration due to tau pathology

S. Ravikumar, L. Wisse, Sydney A. Lim, R. Ittyerah, Long Xie, M. Bedard, Sandhitsu R. Das, Edward B. Lee, M. Tisdall, K. Prabhakaran, J. Lane, J. Detre, G. Mizsei, J. Trojanowski, J. Robinson, T. Schuck, M. Grossman, E. Artacho-Pérula, Maria Mercedes Iñiguez Onzoño Martin, María Mar Arroyo Jiménez, M. Muñoz, Francisco Javier Molina Romero, Maria Pilar Marcos Rabal, S. C. Sánchez, José Carlos Delgado González, C. Rosa Prieto, Marta Córcoles Parada, D. Irwin, D. Wolk, R. Insausti, and Paul Yushkevich

Acta Neuropathologica Communications, Oct 2021

Cited by 51

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Tau neurofibrillary tangle (NFT) pathology in the medial temporal lobe (MTL) is closely linked to neurodegeneration, and is the early pathological change associated with Alzheimer’s disease (AD). To elucidate patterns of structural change in the MTL specifically associated with tau pathology, we compared high-resolution ex vivo MRI scans of human postmortem MTL specimens with histology-based pathological assessments of the MTL. MTL specimens were obtained from twenty-nine brain donors, including patients with AD, other dementias, and individuals with no known history of neurological disease. Ex vivo MRI scans were combined using a customized groupwise diffeomorphic registration approach to construct a 3D probabilistic atlas that captures the anatomical variability of the MTL. Using serial histology imaging in eleven specimens, we labelled the MTL subregions in the atlas based on cytoarchitecture. Leveraging the atlas and neuropathological ratings of tau and TAR DNA-binding protein 43 (TDP-43) pathology severity, morphometric analysis was performed to correlate regional MTL thickness with the severity of tau pathology, after correcting for age and TDP-43 pathology. We found significant correlations between tau pathology and thickness in the entorhinal cortex (ERC) and stratum radiatum lacunosum moleculare (SRLM). When focusing on cases with low levels of TDP-43 pathology, we found strong associations between tau pathology and thickness in the ERC, SRLM and the subiculum/cornu ammonis 1 (CA1) subfields of the hippocampus, consistent with early Braak stages.
Staging tau pathology with tau PET in Alzheimer’s disease: a longitudinal study

Shi‐Dong Chen, Jiaying Lu, Hong-Qi Li, Yu‐Xiang Yang, Jie-Hui Jiang, Mei Cui, C. Zuo, L. Tan, Q. Dong, Jin-Tai Yu, Michael W. Paul Ronald Clifford R. William John Q. Arthur Weiner Aisen Petersen Jack Jagust Trojanowki Toga, M. Weiner, P. Aisen, Ron Petersen, C. Jack, W. Jagust, J. Trojanowki, A. Toga, L. Beckett, R. Green, A. Saykin, J. Morris, R. Perrin, L. Shaw, M. Carrillo, W. Potter, L. Barnes, M. Bernard, Hector A. Gonzalez, C. Ho, John K. Hsiao, Jonathan D. Jackson, E. Masliah, D. Masterman, Ozioma Okonkwo, R. Perrin, Laurie M. Ryan, N. Silverberg, A. Fleisher, D. Sacrey, J. Fockler, C. Conti, D. Veitch, J. Neuhaus, Chengshi Jin, R. Nosheny, M. Ashford, D. Flenniken, A. Kormos, M. Rafii, and 424 more authors

Translational Psychiatry, Sep 2021

Cited by 60

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A biological research framework to define Alzheimer’ disease with dichotomized biomarker measurement was proposed by National Institute on Aging–Alzheimer’s Association (NIA–AA). However, it cannot characterize the hierarchy spreading pattern of tau pathology. To reflect in vivo tau progression using biomarker, we constructed a refined topographic 18 F-AV-1451 tau PET staging scheme with longitudinal clinical validation. Seven hundred and thirty-four participants with baseline 18 F-AV-1451 tau PET (baseline age 73.9 ± 7.7 years, 375 female) were stratified into five stages by a topographic PET staging scheme. Cognitive trajectories and clinical progression were compared across stages with or without further dichotomy of amyloid status, using linear mixed-effect models and Cox proportional hazard models. Significant cognitive decline was first observed in stage 1 when tau levels only increased in transentorhinal regions. Rates of cognitive decline and clinical progression accelerated from stage 2 to stage 3 and stage 4. Higher stages were also associated with greater CSF phosphorylated tau and total tau concentrations from stage 1. Abnormal tau accumulation did not appear with normal β-amyloid in neocortical regions but prompt cognitive decline by interacting with β-amyloid in temporal regions. Highly accumulated tau in temporal regions independently led to cognitive deterioration. Topographic PET staging scheme have potentials in early diagnosis, predicting disease progression, and studying disease mechanism. Characteristic tau spreading pattern in Alzheimer’s disease could be illustrated with biomarker measurement under NIA–AA framework. Clinical–neuroimaging–neuropathological studies in other cohorts are needed to validate these findings.
White matter signals reflect information transmission between brain regions during seizures

A. Revell, Marc Jaskir, A. Lucas, Alexander B. Silva, Dhanya Mahesh, Lena Armstrong, T. Arnold, John M. Bernabei, E. Gleichgerrcht, L. Bonilha, J. Stein, Sandhitsu R. Das, R. Shinohara, D. Bassett, B. Litt, and K. Davis

Brain, Sep 2021

Cited by 20

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White matter supports critical brain functions such as learning and memory, modulates the distribution of action potentials, and transmits neural information between brain regions. Notably, neuronal cell bodies exist in deeper white matter tissue, neurotransmitter vesicles are released directly in white matter, and white matter blood-oxygenation level dependent (BOLD) signals are detectable across a range of different tasks—all appearing to reflect a dynamic, active tissue from which recorded signals can reveal meaningful information about the brain. Yet, the signals within white matter have largely been ignored. Here, we elucidate the properties of white matter signals using intracranial EEG in a bipolar montage. We show that such signals capture the communication between brain regions and differentiate pathophysiologies of epilepsy. In direct contradiction to past assumptions that white matter functional signals provide little value, we show that white matter recordings can elucidate brain function and pathophysiology. Broadly, white matter functional recordings acquired through implantable devices may provide a wealth of currently untapped knowledge about the neurobiology of disease.
Fully automated placental volume quantification from 3DUS for prediction of small-for-gestational-age infants

N. Schwartz, I. Oguz, Jiancong Wang, A. Pouch, N. Yushkevich, Shobhana Parameshwaran, J. Gee, Paul Yushkevich, and Baris U. Oguz

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine, Sep 2021

Cited by 15

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Early placental volume (PV) has been associated with small‐for‐gestational‐age infants born under the 10th/5th centiles (SGA10/SGA5). Manual or semiautomated PV quantification from 3D ultrasound (3DUS) is time intensive, limiting its incorporation into clinical care. We devised a novel convolutional neural network (CNN) pipeline for fully automated placenta segmentation from 3DUS images, exploring the association between the calculated PV and SGA.
Fully Automated Placental Volume Quantification From 3D Ultrasound for Prediction of Small‐for‐Gestational‐Age Infants

N. Schwartz, I. Oguz, Jiancong Wang, A. Pouch, N. Yushkevich, S. Parameshwaran, J. Gee, Paul Yushkevich, and Baris U. Oguz

Journal of Ultrasound in Medicine, Sep 2021

Cited by 11

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Early placental volume (PV) has been associated with small‐for‐gestational‐age infants born under the 10th/5th centiles (SGA10/SGA5). Manual or semiautomated PV quantification from 3D ultrasound (3DUS) is time intensive, limiting its incorporation into clinical care. We devised a novel convolutional neural network (CNN) pipeline for fully automated placenta segmentation from 3DUS images, exploring the association between the calculated PV and SGA.
Tau pathology mediates age effects on medial temporal lobe structure

L. Wisse, Long Xie, Sandhitsu R. Das, R. Flores, O. Hansson, M. Habes, J. Doshi, C. Davatzikos, Paul A. Yushkevich, and D. Wolk

Neurobiology of aging, Sep 2021

Cited by 21

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Hippocampal atrophy is endemic in ‘normal aging’ but it is unclear what factors drive age-related changes in medial temporal lobe (MTL) structural measures. We investigated cross-sectional (n=191) and longitudinal (n=164) MTL atrophy patterns in cognitively normal older adults from ADNI-GO/2 with no to low cerebral β-amyloid and assessed whether white matter hyperintensities (WMHs) and cerebrospinal fluid (CSF) phospho tau (p-tau) levels can explain age-related changes in the MTL. Age was significantly associated with hippocampal volumes and Brodmann Area (BA) 35 thickness, regions affected early by neurofibrillary tangle pathology, in the cross-sectional analysis and with anterior/posterior hippocampus, entorhinal cortex and BA35 in the longitudinal analysis. CSF p-tau was significantly associated with hippocampal volumes and atrophy rates. Mediation analyses showed that CSF p-tau levels partially mediated age effects on hippocampal atrophy rates. No significant associations were observed for WMHs. These findings point towards a role of tau pathology, potentially reflecting Primary Age-Related Tauopathy, in age-related MTL structural changes and suggests a potential role for tau-targeted interventions in age-associated neurodegeneration and memory decline.
Tau pathology mediates age effects on medial temporal lobe structure.

L. Wisse, L. Xie, S.R. Das, R. Flores, O. Hansson, M. Habes, J. Doshi, C. Davatzikos, Paul Yushkevich, D. Wolk, and Alzheimers Disease Neuroimaging I

Neurobiology of aging, Sep 2021

Cited by 19

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Hippocampal atrophy is endemic in ’normal aging’ but it is unclear what factors drive age-related changes in medial temporal lobe (MTL) structural measures. We investigated cross-sectional (n = 191) and longitudinal (n = 164) MTL atrophy patterns in cognitively normal older adults from ADNI-GO/2 with no to low cerebral β-amyloid and assessed whether white matter hyperintensities (WMHs) and cerebrospinal fluid (CSF) phospho tau (p-tau) levels can explain age-related changes in the MTL. Age was significantly associated with hippocampal volumes and Brodmann Area (BA) 35 thickness, regions affected early by neurofibrillary tangle pathology, in the cross-sectional analysis and with anterior and/or posterior hippocampus, entorhinal cortex and BA35 in the longitudinal analysis. CSF p-tau was significantly associated with hippocampal volumes and atrophy rates. Mediation analyses showed that CSF p-tau levels partially mediated age effects on hippocampal atrophy rates. No significant associations were observed for WMHs. These findings point toward a role of tau pathology, potentially reflecting Primary Age-Related Tauopathy, in age-related MTL structural changes and suggests a potential role for tau-targeted interventions in age-associated neurodegeneration and memory decline.
DeepAtrophy: Teaching a neural network to detect progressive changes in longitudinal MRI of the hippocampal region in Alzheimer’s disease

M. Dong, Long Xie, Sandhitsu R. Das, Jiancong Wang, L. Wisse, R. Flores, D. Wolk, and Paul Yushkevich

NeuroImage, Aug 2021

Cited by 24

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Measures of change in hippocampal volume derived from longitudinal MRI are a well-studied biomarker of disease progression in Alzheimer’s disease (AD) and are used in clinical trials to track therapeutic efficacy of disease-modifying treatments. However, longitudinal MRI change measures based on deformable registration can be confounded by MRI artifacts, resulting in over-estimation or underestimation of hippocampal atrophy. For example, the deformation-based-morphometry method ALOHA (Das et al., 2012) finds an increase in hippocampal volume in a substantial proportion of longitudinal scan pairs from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) study, unexpected, given that the hippocampal gray matter is lost with age and disease progression. We propose an alternative approach to quantify disease progression in the hippocampal region: to train a deep learning network (called DeepAtrophy) to infer temporal information from longitudinal scan pairs. The underlying assumption is that by learning to derive time-related information from scan pairs, the network implicitly learns to detect progressive changes that are related to aging and disease progression. Our network is trained using two categorical loss functions: one that measures the network’s ability to correctly order two scans from the same subject, input in arbitrary order; and another that measures the ability to correctly infer the ratio of inter-scan intervals between two pairs of same-subject input scans. When applied to longitudinal MRI scan pairs from subjects unseen during training, DeepAtrophy achieves greater accuracy in scan temporal ordering and interscan interval inference tasks than ALOHA (88.5% vs. 75.5% and 81.1% vs. 75.0%, respectively). A scalar measure of time-related change in a subject level derived from DeepAtrophy is then examined as a biomarker of disease progression in the context of AD clinical trials. We find that this measure performs on par with ALOHA in discriminating groups of individuals at different stages of the AD continuum. Overall, our results suggest that using deep learning to infer temporal information from longitudinal MRI of the hippocampal region has good potential as a biomarker of disease progression, and hints that combining this approach with conventional deformation-based morphometry algorithms may lead to improved biomarkers in the future.
NODEO: A Neural Ordinary Differential Equation Based Optimization Framework for Deformable Image Registration

Yifan Wu, Tom Z. Jiahao, Jiancong Wang, Paul Yushkevich, M. Hsieh, and J. Gee

In Computer Vision and Pattern Recognition, Aug 2021

Cited by 48

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Deformable image registration (DIR), aiming to find spatial correspondence between images, is one of the most critical problems in the domain of medical image analysis. In this paper, we present a novel, generic, and accurate diffeomorphic image registration framework that utilizes neural ordinary differential equations (NODEs). We model each voxel as a moving particle and consider the set of all voxels in a 3D image as a high-dimensional dynamical system whose trajectory determines the targeted deformation field. Our method leverages deep neural networks for their expressive power in modeling dynamical systems, and simultaneously optimizes for a dynamical system between the image pairs and the corresponding transformation. Our formulation allows various constraints to be imposed along the transformation to maintain desired regularities. Our experiment results show that our method outperforms the benchmarks under various metrics. Additionally, we demonstrate the feasibility to expand our framework to register multiple image sets using a unified form of transformation, which could possibly serve a wider range of applications.
The what and when of olfactory working memory in humans

Andrew I. Yang, G. N. Dikecligil, Heidi Jiang, Sandhitsu R. Das, J. Stein, S. Schuele, J. Rosenow, K. Davis, Timothy H. Lucas, and J. Gottfried

Current biology : CB, Aug 2021

Cited by 28

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Encoding and retaining novel sequences of sensory stimuli in working memory is crucial for adaptive behavior. A fundamental challenge for the central nervous system is to maintain each sequence item in an active and discriminable state, while also preserving their temporal context. Nested neural oscillations have been postulated to disambiguate the “what” and “when” of sequences, but the mechanisms by which these multiple streams of information are coordinated in the human brain remain unclear. Drawing from foundational animal studies1,2, we recorded local field potentials from the human piriform cortex and hippocampus during a working memory task in which subjects experienced sequences of three distinct odors. Our data revealed a unique organization of odor memories across multiple timescales of the theta rhythm. During encoding, odors elicited greater gamma at distinct theta phases in both regions, time-stamping their positions in the sequence, whereby the robustness of this effect was predictive of temporal order memory. During maintenance, stimulus-driven patterns of theta-coupled gamma were spontaneously reinstated in piriform cortex, recapitulating the order of the initial sequence. Replay events were time-compressed across contiguous theta cycles, coinciding with periods of enhanced piriform-hippocampal theta phase synchrony, and their prevalence forecasted subsequent recall accuracy on a trial-by-trial basis. Our data provide a novel link between endogenous replay orchestrated by the theta rhythm and short-term retention of sequential memories in the human brain.
The what and when of olfactory working memory in humans.

Andrew I Yang, G. N. Dikecligil, Heidi Jiang, Sandhitsu R. Das, J. Stein, S. Schuele, J. Rosenow, K. Davis, T. Lucas, and J. Gottfried

Current biology : CB, Aug 2021

Cited by 22

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Downstream effects of polypathology on neurodegeneration of medial temporal lobe subregions

L. Wisse, S. Ravikumar, R. Ittyerah, S. Lim, J. Lane, M. Bedard, L. Xie, S. Das, T. Schuck, M. Grossman, E. B. Lee, M. Tisdall, K. Prabhakaran, J. Detre, G. Mizsei, J. Trojanowski, E. Artacho-Pérula, M. M. Onzono Martin, M. M. Arroyo-Jiménez, M. Muñoz López, F. J. Molina Romero, M. P. Marcos Rabal, S. Cebada Sánchez, J. C. Delgado González, C. Rosa Prieto, M. Córcoles Parada, D. Wolk, D. Irwin, R. Insausti, and Paul Yushkevich

Acta Neuropathologica Communications, Jul 2021

Cited by 3

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The medial temporal lobe (MTL) is a nidus for neurodegenerative pathologies and therefore an important region in which to study polypathology. We investigated associations between neurodegenerative pathologies and the thickness of different MTL subregions measured using high-resolution post-mortem MRI. Tau, TAR DNA-binding protein 43 (TDP-43), amyloid-β and α-synuclein pathology were rated on a scale of 0 (absent)—3 (severe) in the hippocampus and entorhinal cortex (ERC) of 58 individuals with and without neurodegenerative diseases (median age 75.0 years, 60.3% male). Thickness measurements in ERC, Brodmann Area (BA) 35 and 36, parahippocampal cortex, subiculum, cornu ammonis (CA)1 and the stratum radiatum lacunosum moleculare (SRLM) were derived from 0.2 × 0.2 × 0.2 mm3 post-mortem MRI scans of excised MTL specimens from the contralateral hemisphere using a semi-automated approach. Spearman’s rank correlations were performed between neurodegenerative pathologies and thickness, correcting for age, sex and hemisphere, including all four proteinopathies in the model. We found significant associations of (1) TDP-43 with thickness in all subregions (r = − 0.27 to r = − 0.46), and (2) tau with BA35 (r = − 0.31) and SRLM thickness (r = − 0.33). In amyloid-β and TDP-43 negative cases, we found strong significant associations of tau with ERC (r = − 0.40), BA35 (r = − 0.55), subiculum (r = − 0.42) and CA1 thickness (r = − 0.47). This unique dataset shows widespread MTL atrophy in relation to TDP-43 pathology and atrophy in regions affected early in Braak stageing and tau pathology. Moreover, the strong association of tau with thickness in early Braak regions in the absence of amyloid-β suggests a role of Primary Age-Related Tauopathy in neurodegeneration.
Three-dimensional mapping of neurofibrillary tangle burden in the human medial temporal lobe.

Paul Yushkevich, M. M. López, Maria Mercedes Iñiguez Onzoño Martin, R. Ittyerah, Sydney A. Lim, S. Ravikumar, M. Bedard, S. Pickup, Wei-Xia Liu, Jiancong Wang, Ling-Yu Hung, Jade Lasserve, Nicolas Vergnet, Long Xie, M. Dong, Salena Cui, Lauren McCollum, J. Robinson, T. Schuck, R. Flores, M. Grossman, M. Tisdall, K. Prabhakaran, G. Mizsei, Sandhitsu R. Das, E. Artacho-Pérula, Marı A. Del Mar Arroyo Jiménez, Marı A. Pilar Marcos Rabal, Francisco Javier Molina Romero, S. C. Sánchez, José Carlos Delgado González, C. Rosa-Prieto, Marta Córcoles Parada, Edward B. Lee, J. Trojanowski, Daniel T. Ohm, L. Wisse, D. Wolk, D. Irwin, and R. Insausti

Brain : a journal of neurology, Jul 2021

Cited by 80

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Tau protein neurofibrillary tangles are closely linked to neuronal/synaptic loss and cognitive decline in Alzheimer’s disease and related dementias. Our knowledge of the pattern of neurofibrillary tangle progression in the human brain, critical to the development of imaging biomarkers and interpretation of in vivo imaging studies in Alzheimer’s disease, is based on conventional two-dimensional histology studies that only sample the brain sparsely. To address this limitation, ex vivo MRI and dense serial histological imaging in 18 human medial temporal lobe specimens (age 75.3 ± 11.4 years, 45 to 93) were used to construct three-dimensional quantitative maps of neurofibrillary tangle burden in the medial temporal lobe at individual and group levels. Group-level maps were obtained in the space of an in vivo brain template, and neurofibrillary tangle was measured in specific anatomical regions defined in this template. Three-dimensional maps of neurofibrillary tangle burden reveal significant variation along the anterior-posterior axis. While early neurofibrillary tangle pathology is thought to be confined to the transentorhinal region, we find similar levels of burden in this region and other medial temporal lobe subregions, including amygdala, temporopolar cortex, and subiculum/cornu Ammonis 1 hippocampal subfields. Overall, the three-dimensional maps of neurofibrillary tangle burden presented here provide more complete information about the distribution of this neurodegenerative pathology in the region of the cortex where it first emerges in Alzheimer’s disease, and may help inform the field about the patterns of pathology spread, as well as support development and validation of neuroimaging biomarkers.
Oh brother, where art tau? Amyloid, neurodegeneration, and cognitive decline without elevated tau

Lauren McCollum, Sandhitsu R. Das, Long Xie, R. Flores, Jieqiong Wang, Sharon X. Xie, L. Wisse, Paul Yushkevich, and D. Wolk

NeuroImage : Clinical, Jun 2021

Cited by 16

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Highlights • Amyloid, tau and neurodegeneration are Alzheimer’s disease (AD) biomarkers.• Mild cognitive impairment (MCI) cases were grouped using the “A/T/(N)” model.• A+T-N+ MCI had less episodic memory loss and slower decline than A+T+N+ MCI.• A+T-N+ MCI was more like A-T-N+ than A+T+N+ MCI on whole brain cortical thickness.• A+T-N+ MCI’s less “AD-like” profile suggests that non-AD pathologies drive symptoms.
A framework For brain atlases: Lessons from seizure dynamics

A. Revell, Alexander B. Silva, T. Arnold, J. Stein, Sandhitsu R. Das, R. Shinohara, Dani S. Bassett, B. Litt, and K. Davis

NeuroImage, Jun 2021

Cited by 48

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Brain maps, or atlases, are essential tools for studying brain function and organization. The abundance of available atlases used across the neuroscience literature, however, creates an implicit challenge that may alter the hypotheses and predictions we make about neurological function and pathophysiology. Here, we demonstrate how parcellation scale, shape, anatomical coverage, and other atlas features may impact our prediction of the brain’s function from its underlying structure. We show how network topology, structure-function correlation (SFC), and the power to test specific hypotheses about epilepsy pathophysiology may change as a result of atlas choice and atlas features. Through the lens of our disease system, we propose a general framework and algorithm for atlas selection. This framework aims to maximize the descriptive, explanatory, and predictive validity of an atlas. Broadly, our framework strives to provide empirical guidance to neuroscience research utilizing the various atlases published over the last century.
Pathological drivers of neurodegeneration in suspected non-Alzheimer’s disease pathophysiology

L. Wisse, R. Flores, L. Xie, S. Das, C. McMillan, J. Trojanowski, M. Grossman, E. B. Lee, D. Irwin, Paul Yushkevich, and D. Wolk

Alzheimer’s Research & Therapy, May 2021

Cited by 35

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Little is known about the heterogeneous etiology of suspected non-Alzheimer’s pathophysiology (SNAP), a group of subjects with neurodegeneration in the absence of β-amyloid. Using antemortem MRI and pathological data, we investigated the etiology of SNAP and the association of neurodegenerative pathologies with structural medial temporal lobe (MTL) measures in β-amyloid-negative subjects. Subjects with antemortem MRI and autopsy data were selected from ADNI (n=63) and the University of Pennsylvania (n=156). Pathological diagnoses and semi-quantitative scores of MTL tau, neuritic plaques, α-synuclein, and TDP-43 pathology and MTL structural MRI measures from antemortem T1-weighted MRI scans were obtained. β-amyloid status (A+/A−) was determined by CERAD score and neurodegeneration status (N+/N−) by hippocampal volume. SNAP reflects a heterogeneous group of pathological diagnoses. In ADNI, SNAP (A−N+) had significantly more neuropathological diagnoses than A+N+. In the A− group, tau pathology was associated with hippocampal, entorhinal cortex, and Brodmann area 35 volume/thickness and TDP-43 pathology with hippocampal volume. SNAP had a heterogeneous profile with more mixed pathologies than A+N+. Moreover, a role for TDP-43 and tau pathology in driving MTL neurodegeneration in the absence of β-amyloid was supported.
Automatic Segmentation of Bone Selective MR Images for Visualization and Craniometry of the Cranial Vault

Pulkit Khandelwal, C. Zimmerman, Long Xie, Hyunyeol Lee, H. K. Song, Paul Yushkevich, A. Vossough, S. Bartlett, and F. Wehrli

Academic radiology, Apr 2021

Cited by 7

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STRUCTURED ABSTRACT Rationale and Objectives: Solid-state MRI has been shown to provide a radiation-free alternative imaging strategy to CT. However, manual image segmentation to produce bone-selective MR-based 3D renderings is time and labor intensive, thereby acting as a bottleneck in clinical practice. The objective of this study was to evaluate an automatic multi-atlas segmentation pipeline for use on cranial vault images entirely circumventing prior manual intervention and to assess concordance of craniometric measurements between pipeline produced MRI and CT-based 3D skull renderings. Materials and Methods: Dual-RF, dual-echo, 3D UTE pulse sequence MR data were obtained at 3T on 30 healthy subjects along with low-dose CT images between December 2018 to January 2020 for this prospective study. The four-point MRI datasets (two RF pulse widths and two echo times) were combined to produce bone-specific images. CT images were thresholded and manually corrected to segment the cranial vault. CT images were then rigidly registered to MRI using mutual information. The corresponding cranial vault segmentations were then transformed to MRI. The “ground truth” segmentations served as reference for the MR images. Subsequently, an automated multi-atlas pipeline was used to segment the bone-selective images. To compare manually and automatically segmented MR images, the Dice similarity coefficient (DSC) and Hausdorff distance (HD) were computed, and craniometric measurements between CT and automated-pipeline MRI-based segmentations was examined via Lin’s concordance coefficient (LCC). Results: Automated segmentation reduced the need for an expert to obtain segmentation. Average DSC was 90.86±1.94%, and average 95th percentile HD was 1.65±0.44 mm between ground truth and automated segmentations. MR-based measurements differed from CT-based measurements by 0.73–1.2 mm on key craniometric measurements. LCCfor distances between CT and MR-based landmarks were vertex-basion: 0.906, left-right frontozygomatic suture: 0.780, and glabella-opisthocranium: 0.956 for the three measurements. Conclusion: Good agreement between CT and automated MR-based 3D cranial vault renderings has been achieved, thereby eliminating the laborious manual segmentation process. Target applications comprise craniofacial surgery as well as imaging of traumatic injuries and masses involving both bone and soft tissue.
Joint ex vivo MRI and histology detect iron-rich cortical gliosis in Tau and TDP-43 proteinopathies

M. Tisdall, Daniel T. Ohm, Rebecca Lobrovich, Sandhitsu R. Das, G. Mizsei, K. Prabhakaran, R. Ittyerah, Sydney A. Lim, C. McMillan, D. Wolk, J. Gee, J. Trojanowski, Edward B. Lee, J. Detre, Paul Yushkevich, M. Grossman, and D. Irwin

bioRxiv, Apr 2021

Cited by 3

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Frontotemporal lobar degeneration (FTLD) is a heterogeneous spectrum of age-associated neurodegenerative diseases that include two main pathologic categories of tau (FTLD-Tau) and TDP-43 (FTLD-TDP) proteinopathies. These distinct proteinopathies are often clinically indistinguishable during life, posing a major obstacle for diagnosis and emerging therapeutic trials tailored to disease-specific mechanisms. Moreover, MRI-derived measures have had limited success to date discriminating between FTLD-Tau or FTLD-TDP. T2*-weighted (T2*w) ex vivo MRI has previously been shown to be sensitive to non-heme iron in healthy intracortical lamination and myelin, and to pathological iron deposits in amyloid-beta plaques and activated microglia in Alzheimer’s disease (AD). However, an integrated, ex vivo MRI and histopathology approach is understudied in FTLD. We apply joint, whole-hemisphere ex vivo MRI at 7T and histopathology to the study autopsy-confirmed FTLD-Tau (n=3) and FTLD-TDP (n=2), relative to an AD disease-control brain with antemortem clinical symptoms of frontotemporal dementia and an age-matched healthy control. We detect distinct laminar patterns of novel iron-laden glial pathology in both FTLD-Tau and FTLD-TDP brains. We find iron-positive ameboid and hypertrophic microglia and astrocytes largely in deeper GM and adjacent WM in FTLD-Tau. In contrast, FTLD-TDP presents prominent superficial cortical layer iron reactivity in astrocytic processes enveloping small blood vessels with limited involvement of adjacent WM, as well as more diffuse distribution of punctate iron-rich dystrophic microglial processes across all GM lamina. This integrated MRI/histopathology approach reveals ex vivo MRI features that are consistent with these pathological observations distinguishing FTLD-Tau and FTLD-TDP, including prominent irregular hypointense signal in deeper cortex in FTLD-Tau whereas FTLD-TDP showed upper cortical layer hypointense bands and diffuse cortical speckling. Moreover, differences in adjacent WM degeneration and iron-rich gliosis on histology between FTLD-Tau and FTLD-TDP were also readily apparent on MRI as hyperintense signal and irregular areas of hypointensity, respectively that were more prominent in FTLD-Tau compared to FTLD-TDP. These unique histopathological and radiographic features were distinct from HC and AD brains, suggesting that iron-sensitive T2*w MRI, adapted to in vivo application at sufficient resolution, may offer an opportunity to improve antemortem diagnosis of FTLD proteinopathies using tissue-validated methods.
The ANTsX ecosystem for quantitative biological and medical imaging

N. Tustison, Philip A Cook, A. Holbrook, H. Johnson, J. Muschelli, Gabriel A. Devenyi, J. Duda, Sandhitsu R. Das, Nicholas C. Cullen, D. Gillen, M. Yassa, J. Stone, J. Gee, and B. Avants

Scientific Reports, Apr 2021

Cited by 491

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The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of multiple open-source software libraries which house top-performing algorithms used worldwide by scientific and research communities for processing and analyzing biological and medical imaging data. The base software library, ANTs, is built upon, and contributes to, the NIH-sponsored Insight Toolkit. Founded in 2008 with the highly regarded Symmetric Normalization image registration framework, the ANTs library has since grown to include additional functionality. Recent enhancements include statistical, visualization, and deep learning capabilities through interfacing with both the R statistical project (ANTsR) and Python (ANTsPy). Additionally, the corresponding deep learning extensions ANTsRNet and ANTsPyNet (built on the popular TensorFlow/Keras libraries) contain several popular network architectures and trained models for specific applications. One such comprehensive application is a deep learning analog for generating cortical thickness data from structural T1-weighted brain MRI, both cross-sectionally and longitudinally. These pipelines significantly improve computational efficiency and provide comparable-to-superior accuracy over multiple criteria relative to the existing ANTs workflows and simultaneously illustrate the importance of the comprehensive ANTsX approach as a framework for medical image analysis.
Automatic Segmentation of Bone Selective MR Images for Visualization and Craniometry of the Cranial Vault.

C. Zimmerman, Pulkit Khandelwal, L. Xie, Hyunyeol Lee, H. K. Song, Paul Yushkevich, A. Vossough, S. Bartlett, and F. Wehrli

Academic radiology, Apr 2021

Cited by 6

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RATIONALE AND OBJECTIVES Solid-state MRI has been shown to provide a radiation-free alternative imaging strategy to CT. However, manual image segmentation to produce bone-selective MR-based 3D renderings is time and labor intensive, thereby acting as a bottleneck in clinical practice. The objective of this study was to evaluate an automatic multi-atlas segmentation pipeline for use on cranial vault images entirely circumventing prior manual intervention, and to assess concordance of craniometric measurements between pipeline produced MRI and CT-based 3D skull renderings. MATERIALS AND METHODS Dual-RF, dual-echo, 3D UTE pulse sequence MR data were obtained at 3T on 30 healthy subjects along with low-dose CT images between December 2018 to January 2020 for this prospective study. The four-point MRI datasets (two RF pulse widths and two echo times) were combined to produce bone-specific images. CT images were thresholded and manually corrected to segment the cranial vault. CT images were then rigidly registered to MRI using mutual information. The corresponding cranial vault segmentations were then transformed to MRI. The "ground truth" segmentations served as reference for the MR images. Subsequently, an automated multi-atlas pipeline was used to segment the bone-selective images. To compare manually and automatically segmented MR images, the Dice similarity coefficient (DSC) and Hausdorff distance (HD) were computed, and craniometric measurements between CT and automated-pipeline MRI-based segmentations were examined via Lin’s concordance coefficient (LCC). RESULTS Automated segmentation reduced the need for an expert to obtain segmentation. Average DSC was 90.86 ± 1.94%, and average 95th percentile HD was 1.65 ± 0.44 mm between ground truth and automated segmentations. MR-based measurements differed from CT-based measurements by 0.73-1.2 mm on key craniometric measurements. LCC for distances between CT and MR-based landmarks were vertex-basion: 0.906, left-right frontozygomatic suture: 0.780, and glabella-opisthocranium: 0.956 for the three measurements. CONCLUSION Good agreement between CT and automated MR-based 3D cranial vault renderings has been achieved, thereby eliminating the laborious manual segmentation process. Target applications comprise craniofacial surgery as well as imaging of traumatic injuries and masses involving both bone and soft tissue.
Early stages of tau pathology and its associations with functional connectivity, atrophy and memory

D. Berron, Jacob W. Vogel, P. Insel, J. Pereira, Long Xie, L. Wisse, Paul Yushkevich, S. Palmqvist, N. Mattsson-Carlgren, E. Stomrud, Ruben Smith, O. Strandberg, and O. Hansson

Brain, Mar 2021

Cited by 217

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In Alzheimer’s disease, postmortem studies have shown that the first cortical site where neurofibrillary tangles appear is the transentorhinal region, a subregion within the medial temporal lobe that largely overlaps with area 35, and the entorhinal cortex. Here we used tau‐PET imaging to investigate the sequence of tau pathology progression within the human medial temporal lobe and across regions in the posterior‐medial system. Our objective was to study how medial temporal tau is related to functional connectivity, regional atrophy, and memory performance.
Deep Label Fusion: A 3D End-to-End Hybrid Multi-Atlas Segmentation and Deep Learning Pipeline

Long Xie, L. Wisse, Jiancong Wang, S. Ravikumar, T. Glenn, A. Luther, Sydney A. Lim, D. Wolk, and Paul Yushkevich

Information Processing in Medical Imaging, Mar 2021

Cited by 2

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Deep learning (DL) is the state-of-the-art methodology in various medical image segmentation tasks. However, it requires relatively large amounts of manually labeled training data, which may be infeasible to generate in some applications. In addition, DL methods have relatively poor generalizability to out-of-sample data. Multi-atlas segmentation (MAS), on the other hand, has promising performance using limited amounts of training data and good generalizability. A hybrid method that integrates the high accuracy of DL and good generalizability of MAS is highly desired and could play an important role in segmentation problems where manually labeled data is hard to generate. Most of the prior work focuses on improving single components of MAS using DL rather than directly optimizing the final segmentation accuracy via an end-to-end pipeline. Only one study explored this idea in binary segmentation of 2D images, but it remains unknown whether it generalizes well to multi-class 3D segmentation problems. In this study, we propose a 3D end-to-end hybrid pipeline, named deep label fusion (DLF), that takes advantage of the strengths of MAS and DL. Experimental results demonstrate that DLF yields significant improvements over conventional label fusion methods and U-Net, a direct DL approach, in the context of segmenting medial temporal lobe subregions using 3T T1-weighted and T2-weighted MRI. Further, when applied to an unseen similar dataset acquired in 7T, DLF maintains its superior performance, which demonstrates its good generalizability.
Accurate and Robust Alignment of Differently Stained Histologic Images Based on Greedy Diffeomorphic Registration

Ludovic Venet, Sarthak Pati, Michal Feldman, MacLean D. Nasrallah, Paul Yushkevich, and S. Bakas

Applied sciences (Basel, Switzerland), Feb 2021

Cited by 26

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Histopathologic assessment routinely provides rich microscopic information about tissue structure and disease process. However, the sections used are very thin, and essentially capture only 2D representations of a certain tissue sample. Accurate and robust alignment of sequentially cut 2D slices should contribute to more comprehensive assessment accounting for surrounding 3D information. Towards this end, we here propose a two-step diffeomorphic registration approach that aligns differently stained histology slides to each other, starting with an initial affine step followed by estimating a deformation field. It was quantitatively evaluated on ample (n = 481) and diverse data from the automatic non-rigid histological image registration challenge, where it was awarded the second rank. The obtained results demonstrate the ability of the proposed approach to robustly (average robustness = 0.9898) and accurately (average relative target registration error = 0.2%) align differently stained histology slices of various anatomical sites while maintaining reasonable computational efficiency (<1 min per registration). The method was developed by adapting a general-purpose registration algorithm designed for 3D radiographic scans and achieved consistently accurate results for aligning high-resolution 2D histologic images. Accurate alignment of histologic images can contribute to a better understanding of the spatial arrangement and growth patterns of cells, vessels, matrix, nerves, and immune cell interactions.
3D Mapping of Neurofibrillary Tangle Burden in the Human Medial Temporal Lobe

Paul Yushkevich, M. M. López, Maria Mercedes Iñiguez Onzoño Martin, R. Ittyerah, Sydney A. Lim, S. Ravikumar, M. Bedard, S. Pickup, Wei-Xia Liu, Jiancong Wang, Ling-Yu Hung, Jade Lasserve, Nicolas Vergnet, Long Xie, M. Dong, Salena Cui, Lauren McCollum, J. Robinson, T. Schuck, R. Flores, M. Grossman, M. Tisdall, K. Prabhakaran, G. Mizsei, Sandhitsu R. Das, E. Artacho-Pérula, María Mar Arroyo Jiménez, M. Rabal, Francisco Javier Molina Romero, S. C. Sánchez, José Carlos Delgado González, C. Rosa-Prieto, Marta Córcoles Parada, Edward B. Lee, J. Trojanowski, Daniel T. Ohm, L. Wisse, D. Wolk, D. Irwin, and R. Insausti

bioRxiv, Jan 2021

Cited by 6

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Tau protein neurofibrillary tangles (NFT) are closely linked to neuronal/synaptic loss and cognitive decline in Alzheimer’s disease (AD) and related dementias. Our knowledge of the pattern of NFT progression in the human brain, critical to the development of imaging biomarkers and interpretation of in vivo imaging studies in AD, is based on conventional 2D histology studies that only sample the brain sparsely. To address this limitation, ex vivo MRI and dense serial histological imaging in 18 human medial temporal lobe (MTL) specimens were used to construct 3D quantitative maps of NFT burden in the MTL at individual and group levels. These maps reveal significant variation in NFT burden along the anterior-posterior axis. While early NFT pathology is thought to be confined to the transentorhinal region, we find similar levels of NFT burden in this region and other MTL subregions, including amygdala, temporopolar cortex, and subiculum/CA1.
Unfolding the Medial Temporal Lobe Cortex to Characterize Neurodegeneration Due to Alzheimer’s Disease Pathology Using Ex vivo Imaging

S. Ravikumar, L. Wisse, Sydney A. Lim, D. Irwin, R. Ittyerah, Long Xie, Sandhitsu R. Das, Edward B. Lee, M. Tisdall, K. Prabhakaran, J. Detre, G. Mizsei, J. Trojanowski, J. Robinson, T. Schuck, M. Grossman, E. Artacho-Pérula, Maria Mercedes Iniguez Onzono Martin, María Mar Arroyo Jiménez, M. M. López, Francisco Javier Molina Romero, M. Rabal, S. C. Sánchez, José Carlos Delgado González, Carlos Rosa Prieto, Marta Córcoles Parada, D. Wolk, R. Insausti, and Paul Yushkevich

In MLCN@MICCAI, Jan 2021

Cited by 3

DOI
Deformable Image Registration using Neural ODEs

Yifan Wu, Tom Z. Jiahao, Jiancong Wang, Paul Yushkevich, J. Gee, and M. A. Hsieh

ArXiv, Jan 2021

Cited by 1

2020

Neurodegeneration in the Longitudinal Evaluation of Early Onset Alzheimer’s Disease Study (LEADS) sample: Results from the MRI core

Jessica A. Collins, Rania Ezzo, P. Vemuri, Bret J. Borowski, L. Iaccarino, R. La Joie, Orit H. Lesman-Segev, Viktoriya Bourakova, A. Eloyan, P. Aisen, A. Fagan, T. Foroud, C. Gatsonis, C. Jack, J. Kramer, R. Koeppe, Andrew J. Saykin, A. Toga, Gregory S. Day, N. Graff-Radford, Lawrence S. Honig, David T. Jones, Joseph C. Masdeu, Mario F. Mendez, C. Onyike, E. Rogalski, S. Salloway, D. Wolk, Thomas S. Wingo, Maria C. Carrillo, Liana G. Apostolova, G. Rabinovici, and B. Dickerson

Alzheimer’s & Dementia, Dec 2020

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Approximately 5% of the 5.6 million (∼280,000) Americans with Alzheimer’s disease (AD) develop symptoms at age 65 or younger and are classified as having early‐onset AD (EOAD). Although EOAD and late‐onset AD (LOAD) share the same pathologic substrate, there are notable differences in their clinical and biological phenotypes. The Longitudinal Early‐onset AD study (LEADS) is a multi‐site, observational clinical and biomarker study of EOAD. In the present study we utilized the currently available LEADS imaging data to explore the spatial extent and magnitude of neurodegeneration EOAD
ATN classifications in a mixed cohort of frontotemporal lobar degeneration (FTLD) and Alzheimer’s disease (AD) pathology using cerebrospinal fluid neurofilament light chain (NFL)

K. Cousins, J. Phillips, David J. Irwin, Eddie B. Lee, D. Wolk, L. M. Shaw, Garrett S. Gibbons, C. Mcmillan, J. Trojanowski, and M. Grossman

Alzheimer’s & Dementia, Dec 2020

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The ATN framework combines cerebrospinal fluid (CSF) amyloidβ 1‐42 (Aβ1‐42), phosphorylated tau (p‐tau), and total tau (t‐tau) to diagnose individuals along the continuum of Alzheimer’s disease (AD). While ATN profiles indicative of AD are highly accurate, profiles indicating normal, non‐AD pathology, or concurrent AD and non‐AD pathology are inconsistent, due in part to the insensitivity of t‐tau to non‐AD pathologies, such as frontotemporal lobar degeneration (FTLD). We test a modified framework that replaces t‐tau with neurofilament light chain (NFL), a CSF marker of axonal degeneration.
Variability in tau‐atrophy relationships reveals underlying phenotypes in individuals on the Alzheimer’s disease continuum

Sandhitsu R. Das, Long Xie, Lauren McCollum, R. Flores, D. Irwin, I. Nasrallah, B. Dickerson, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Dec 2020

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Tau neurofibrillary tangles (T) are thought to be the primary driver of downstream neurodegeneration (N) and subsequent cognitive impairment in AD. However, there is substantial variability in the T‐N relationship – manifested in higher or lower atrophy than expected for the level of tau in a given brain region. We quantitatively describe and categorize source(s) of variability using region‐based measures of T and N to gain insight into underlying modulatory factors, including polypathology.
Detecting biological changes in longitudinal MRI scans of Alzheimer’s disease patients in the hippocampus region with deep learning

M. Dong, Long Xie, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2020

Cited by 1

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Alzheimer’s Disease (AD) is characterized by gradual loss of gray matter, particularly in the medial temporal lobe (MTL) and hippocampus. Longitudinal change in hippocampal volume on MRI is an effective biomarker to monitor disease progression in AD. However, neurodegenerative changes in the hippocampus on longitudinal MRI can be obscured by differences in MRI signal that are unrelated to disease progression, such as different amounts of head motion, noise, or MRI artifact. We hypothesize that a deep learning model can be trained to distinguish true biological changes from nonsystematic factors, leading to a more sensitive biomarker of disease progression.
Sensitive biomarkers to Alzheimer’s disease progression in longitudinal MRI from deep learning

M. Dong, Long Xie, Jiancong Wang, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2020

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In clinical trials of disease‐modifying treatments of Alzheimer’s disease (AD), the measure of hippocampus volume change from longitudinal MRI is a well‐studied biomarker of disease progression. However, even the most sensitive longitudinal MRI measures can be confounded by the presence of motion and susceptibility artifacts. We hypothesize that deep learning can be used to differentiate MRI changes due to biological factors (tissue loss) from changes due to artifact and other non‐biological factors, leading to novel biomarkers that are more sensitive to longitudinal change that can accurately evaluate disease progression.
Is it time to use predictive models to boost power of Alzheimer’s disease clinical trials? A post‐hoc analysis of phase 3 solanezumab trials

A. Ezzati, C. Davatzikos, D. Wolk, P. Aisen, and R. Lipton

Alzheimer’s & Dementia, Dec 2020

Cited by 2

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The ideal participants for Alzheimer’s disease (AD) clinical trials would show cognitive decline in the absence of treatment (i.e. placebo arm) and would also respond to the therapeutic intervention. However, up to 50% of placebo treated participants enrolled in the AD clinical trials do not show cognitive or functional decline during the timeframe of trials. One strategy to boost the power of trials is to exclude individuals who are not likely to progress using data‐driven predictive models. In this study, we aimed to investigate if using machine learning (ML) predictive models can be an effective tool for enriching enrollment in AD trials.
Increased white matter MRI T1 hypointensity volume in young‐onset Alzheimer’s disease patients is not accounted for by age or cardiovascular risk factors

Ryn Flaherty, Rania Ezzo, Jessica A. Collins, Samantha Krivensky, Ryan Eckbo, P. Vemuri, Bret J. Borowski, L. Iaccarino, R. La Joie, Orit H. Lesman-Segev, Viktoriya Bourakova, A. Eloyan, P. Aisen, A. Fagan, T. Foroud, C. Gatsonis, C. Jack, J. Kramer, R. Koeppe, Andrew J. Saykin, A. Toga, Gregory S. Day, N. Graff-Radford, Lawrence S. Honig, David T. Jones, Joseph C. Masdeu, Mario F. Mendez, C. Onyike, E. Rogalski, Stephen P. Salloway, D. Wolk, Thomas S. Wingo, Maria C. Carrillo, L. Apostolova, G. Rabinovici, and B. Dickerson

Alzheimer’s & Dementia, Dec 2020

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White matter (WM) hypointensity volume in T1 MRI correlates strongly with T2 hyperintensities and both are typically associated with advancing age and vascular brain injury (VBI). Recent research has suggested that Alzheimer’s Disease (AD) neuropathologic changes (ADNC) also increases WM hypointensity volume. Sporadic early onset AD (EOAD) patients provide a unique model to examine the relationship between ADNC biomarkers and WM hypointensity volume in the absence of advanced age, cardiovascular injury, or autosomal dominant genetic mutations.
Neurodegeneration in medial temporal lobe subregions propagates within distinct functional networks in the AD continuum

R. Flores, Sandhitsu R. Das, Long Xie, L. Wisse, Preya Shah, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Dec 2020

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The medial temporal lobe (MTL) is extensively connected to the rest of the brain through two specific networks: the anterior‐temporal (AT) and the posterior‐medial (PM) systems. As neurodegeneration is thought to occur along specific networks, our aim was to evaluate whether atrophy in perirhinal (PRC) vs parahippocampal cortices (PHC) ‐ two MTL nodes of the AT vs PM systems, respectively ‐ covary over time with distinct brain regions reflecting the AT vs PM networks.
The development of a valid, reliable, harmonized segmentation protocol for hippocampal subfields and medial temporal lobe cortices: A progress update

R. La Joie, R. Olsen, D. Berron, K. Amunts, Jean C. Augustinack, A. Bakker, Andrew R. Bender, M. Boccardi, M. Bocchetta, M. Chakravarty, G. Chételat, R. Flores, Jordan DeKraker, Song-Lin Ding, R. Insausti, O. Kedo, S. Mueller, N. Ofen, D. Palombo, N. Raz, Craig E. L. Stark, Lei Wang, Paul Yushkevich, Qi-Jing Yu, Valerie A. Carr, L. Wisse, and Ana M. Daugherty

Alzheimer’s & Dementia, Dec 2020

Cited by 2

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The medial temporal lobe (MTL, i.e. hippocampus and adjacent cortices) is particularly vulnerable to age‐related diseases: Alzheimer’s disease, other age‐related proteinothies (TDP‐43, AGD, etc) and vascular injury. Yet, the subregional pattern of vulnerability is thought to differ across etiologies; characterizing these differences using high‐resolution MRI may provide more insight in disease processes and better biomarkers. However, substantial differences in subfield definition has hindered the ability to compare results across laboratories or draw robust conclusions (Figure 1). The Hippocampal Subfields Group (HSG) is an international group seeking to remedy this problem by developing a histologically‐valid, reliable, and freely available segmentation protocol for high‐resolution T2‐weighted 3T MRI (http://www.hippocampalsubfields.com)
Longitudinal network connectivity measurements in medial temporal lobe subregions discriminate preclinical Alzheimer’s from amyloid‐β negative controls

Pulkit Khandelwal, Long Xie, D. Bassett, R. Flores, D. Wolk, Paul Yushkevich, and Sandhitsu R. Das

Alzheimer’s & Dementia, Dec 2020

Abs DOI

Finding sensitive outcome measures for disease progression in clinical trials of preclinical Alzheimer’s disease (AD) remains challenging. We hypothesize that longitudinal network connectivity measurements of the medial temporal lobe (MTL) subregions, sites of earliest tau pathology, are more sensitive to progression at early stages than annualized subregional atrophy rates, thus, increasing power to detect a significant effect in a shorter timeframe.
Optimized extraction of the medial temporal lobe for postmortem MRI based on custom 3D printed molds

Jade Lasserve, Sydney A. Lim, L. Wisse, R. Ittyerah, S. Ravikumar, Madigan Lavery, J. Robinson, T. Schuck, M. Grossman, Edward B. Lee, Paul Yushkevich, D. Tisdall, K. Prabhakaran, G. Mizsei, E. Artacho-Pérula, Maria Mercedes Iniguez Onzono Martin, María Mar Arroyo Jiménez, M. Muñoz, Francisco Javier Molina Romero, M. Rabal, D. Irwin, J. Trojanowski, D. Wolk, and R. Insausti

Alzheimer’s & Dementia, Dec 2020

Cited by 3

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Structural magnetic resonance imaging (MRI) biomarkers are important for early detection of Alzheimer’s Disease (AD). However, atrophy measures can be confounded by changes due to aging and comorbid non‐AD neurodegenerative pathologies. Linking postmortem MRI of the medial temporal lobe (MTL) to histopathology may identify focal patterns of change associated specifically with early AD. We implemented a pipeline of high‐resolution MRI of MTL specimens and serial histopathology imaging [REF]. However, the task of extracting the intact MTL specimen such that it fits into the MRI coil requires anatomical expertise and has proven error prone. Here we present an algorithm to automatically create 3D printed molds guiding MTL extraction.
Epigenetic measurement of biological age associates with tau load in normal brain aging

Marissa J. Maroni, D. Wolk, Sandhitsu R. Das, R. Flores, L. Wisse, Long Xie, Paul Yushkevich, Edward B. Lee, and C. McMillan

Alzheimer’s & Dementia, Dec 2020

Cited by 4

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Aging is the most established risk factor for sporadic Alzheimer’s Disease (AD). However, relative risk of AD varies greatly across individuals. One potential explanation for this heterogeneity is that chronological age may not reflect differences in biological aging. One measure of biological age is the “epigenetic clock” which utilizes a weighted statistical model from >350 CpG sites that captures the cumulative work of an individual’s epigenetic maintenance system and has been demonstrated to relate to age, mortality, and survival. In this study, we test the hypothesis that the epigenetic clock will be related to two regional brain aging signatures associated with AD, including neurofibrillary tau tangle (NFTs) load and reduced cortical thickness.
Cognitive and neurodegenerative profile differences between “mismatch MCI” (A+T‐N+ MCI) And “prodromal AD” (A+T+N+ MCI) increase with time

Lauren McCollum, Sandhitsu R. Das, Jieqiong Wang, Long Xie, R. Flores, L. Wisse, Sharon X. Xie, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Dec 2020

Abs DOI

Per the Amyloid/Tau/Neurodegeneration (A/T/N) framework, beta‐amyloid accumulates during preclinical Alzheimer’s Disease (AD), followed by tau, then neurodegeneration. As AD symptoms are most linked to tau and neurodegeneration, both are expected by the MCI stage of disease. Thus, A+T‐N+ MCI (“mismatch MCI”) is thought to have both AD pathophysiology and non‐AD pathology, with the latter (given absence of tau) driving neurodegeneration and symptoms. We investigate the cognitive and neurodegenerative profile of mismatch MCI compared to “standard” A+T+N+ MCI (“prodromal AD”).
Detection of Alzheimer’s Disease-Related Cognitive Change With the Mobile Cognitive App Performance Platform

D. Mechanic-Hamilton, Sean Lydon, Alexander Miller, Kimberly Halberstadter, J. Lane, Sandhitsu R. Das, and D. Wolk

Innovation in Aging, Dec 2020

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Abstract This study investigates the psychometric properties of the mobile cognitive app performance platform (mCAPP), designed to detect memory changes associated with preclinical Alzheimer’s Disease (AD). The mCAPP memory task includes learning and matching hidden card pairs and incorporates increasing memory load, pattern separation features, and spatial memory. Participants included 30 older adults with normal cognition. They completed the mCAPP, paper and pencil neuropsychological tests and a subset completed a high-resolution structural MRI. The majority of participants found the difficulty level of the mCAPP game to be “just right”. Accuracy on the mCAPP correlated with performance on memory and executive measures, while speed of performance on the mCAPP correlated with performance on attention and executive function measures. Longer trial duration correlated with measures of the parahippocampal cortex. The relationship of mCAPP variables with molecular biomarkers, at-home and burst testing, and development of additional cognitive measures will also be discussed.
Development of the mobile cognitive app performance platform for detection of AD‐related cognitive change

D. Mechanic-Hamilton, Sean Lydon, Kimberly Halberstadter, J. Lane, Sandhitsu R. Das, and D. Wolk

Alzheimer’s & Dementia, Dec 2020

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This pilot study investigates the psychometric properties of a mobile app‐based memory task, the mobile cognitive app performance platform (mCAPP), to detect memory changes associated with preclinical Alzheimer’s Disease (AD). A mobile, reliable, valid, short, and engaging cognitive assessment is necessary for early detection and tracking change in individuals at risk for AD.
7T Epilepsy Task Force Consensus Recommendations on the use of 7T in Clinical Practice.

Giske Opheim, A. G. Kolk, K. M. Bloch, A. Colon, K. A. Davis, T. Henry, J. Jansen, Stephen E. Jones, Jullie W. Pan, K. Rössler, J. Stein, M. Strandberg, S. Trattnig, P. Moortele, Maria Isabel Vargas, I. Wang, F. Bartolomei, N. Bernasconi, A. Bernasconi, B. Bernhardt, I. Björkman-Burtscher, M. Cosottini, Sandhitsu R. Das, L. Hertz-Pannier, S. Inati, M. Jurkiewicz, Ali R. Khan, Shuli Liang, R. Ma, S. Mukundan, H. Pardoe, L. Pinborg, J. Polimeni, J. Ranjeva, E. Steijvers, S. Stufflebeam, T. Veersema, A. Vignaud, N. Voets, S. Vulliémoz, C. Wiggins, Rongli Xue, R. Guerrini, and M. Guye

Neurology, Dec 2020

Cited by 62

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Identifying a structural brain lesion on MRI has important implications in epilepsy and is the most important correlate to seizure freedom after surgery in patients with drug-resistant focal onset epilepsy. However, at conventional magnetic field strengths (1.5 and 3T) only around 60-85% of MRI examinations reveal such lesions. Over the last decade, studies have demonstrated the added value of 7T MRI in patients with and without known epileptogenic lesions from 1.5 and/or 3T. However, translation of 7T MRI to clinical practice is still challenging, particularly in centers new to 7T, and there is a need for practical recommendations on targeted use of 7T MRI in the clinical management of patients with epilepsy. The 7T Epilepsy Task Force - an international group representing 21 7T MRI centers with experience from scanning over 2000 patients with epilepsy - would hereby like to share its experience with the neurology community regarding the appropriate clinical indications, patient selection and preparation, acquisition protocols and setup, technical challenges, and radiological guidelines for 7T MRI in epilepsy patients. This article mainly addresses structural imaging, but also presents multiple non-structural MRI techniques that benefit from 7T and hold promise as future directions in epilepsy. Answering to the increased availability of 7T MRI as an approved tool for diagnostic purposes, this article aims to give guidance on clinical 7T MRI epilepsy management by giving recommendations on referral, suitable 7T MRI protocols and image interpretation.
Amyloid and tau PET in sporadic early‐onset Alzheimer’s disease: Preliminary results from LEADS

G. Rabinovici, L. Iaccarino, R. La Joie, Orit H. Lesman-Segev, D. Soleimani-Meigooni, K. Provost, Jessica A. Collins, P. Aisen, Bret J. Borowski, A. Eloyan, A. Fagan, T. Foroud, C. Gatsonis, C. Jack, J. Kramer, Andrew J. Saykin, A. Toga, P. Vemuri, Gregory S. Day, N. Graff-Radford, Lawrence S. Honig, David T. Jones, Joseph C. Masdeu, Mario F. Mendez, C. Onyike, E. Rogalski, S. Salloway, D. Wolk, Thomas S. Wingo, R. Koeppe, B. Dickerson, Maria C. Carrillo, and L. Apostolova

Alzheimer’s & Dementia, Dec 2020

Cited by 2

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Previous studies have reported that age modifies the distribution and burden of tau (and, to a lesser extent, amyloid) pathology in sporadic Alzheimer’s disease (AD). Here we present preliminary baseline amyloid and tau PET results from the Longitudinal Early‐Onset Alzheimer’s Disease Study (LEADS), a multi‐site longitudinal study of sporadic early‐onset AD.
Multi-institutional noninvasive in vivo characterization of IDH, 1p/19q, and EGFRvIII in glioma using neuro-Cancer Imaging Phenomics Toolkit (neuro-CaPTk)

Saima Rathore, S. Mohan, S. Bakas, Chiharu Sako, C. Badve, Sarthak Pati, Ashutosh Kumar Singh, D. Bounias, Phuc Ngo, H. Akbari, A. Gastounioti, M. Bergman, M. Bilello, R. Shinohara, Paul Yushkevich, D. O’Rourke, A. Sloan, D. Kontos, M. Nasrallah, J. Barnholtz-Sloan, and C. Davatzikos

Neuro-oncology Advances, Dec 2020

Cited by 31

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Abstract Background Gliomas represent a biologically heterogeneous group of primary brain tumors with uncontrolled cellular proliferation and diffuse infiltration that renders them almost incurable, thereby leading to a grim prognosis. Recent comprehensive genomic profiling has greatly elucidated the molecular hallmarks of gliomas, including the mutations in isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2), loss of chromosomes 1p and 19q (1p/19q), and epidermal growth factor receptor variant III (EGFRvIII). Detection of these molecular alterations is based on ex vivo analysis of surgically resected tissue specimen that sometimes is not adequate for testing and/or does not capture the spatial tumor heterogeneity of the neoplasm. Methods We developed a method for noninvasive detection of radiogenomic markers of IDH both in lower-grade gliomas (WHO grade II and III tumors) and glioblastoma (WHO grade IV), 1p/19q in IDH-mutant lower-grade gliomas, and EGFRvIII in glioblastoma. Preoperative MRIs of 473 glioma patients from 3 of the studies participating in the ReSPOND consortium (collection I: Hospital of the University of Pennsylvania [HUP: n = 248], collection II: The Cancer Imaging Archive [TCIA; n = 192], and collection III: Ohio Brain Tumor Study [OBTS, n = 33]) were collected. Neuro-Cancer Imaging Phenomics Toolkit (neuro-CaPTk), a modular platform available for cancer imaging analytics and machine learning, was leveraged to extract histogram, shape, anatomical, and texture features from delineated tumor subregions and to integrate these features using support vector machine to generate models predictive of IDH, 1p/19q, and EGFRvIII. The models were validated using 3 configurations: (1) 70–30% training–testing splits or 10-fold cross-validation within individual collections, (2) 70–30% training–testing splits within merged collections, and (3) training on one collection and testing on another. Results These models achieved a classification accuracy of 86.74% (HUP), 85.45% (TCIA), and 75.15% (TCIA) in identifying EGFRvIII, IDH, and 1p/19q, respectively, in configuration I. The model, when applied on combined data in configuration II, yielded a classification success rate of 82.50% in predicting IDH mutation (HUP + TCIA + OBTS). The model when trained on TCIA dataset yielded classification accuracy of 84.88% in predicting IDH in HUP dataset. Conclusions Using machine learning algorithms, high accuracy was achieved in the prediction of IDH, 1p/19q, and EGFRvIII mutation. Neuro-CaPTk encompasses all the pipelines required to replicate these analyses in multi-institutional settings and could also be used for other radio(geno)mic analyses.
Novel ex vivo MRI atlas of the medial temporal lobe can be used to characterize structural changes due to Alzheimer’s disease pathology

S. Ravikumar, L. Wisse, Long Xie, R. Ittyerah, Sandhitsu R. Das, J. Detre, M. Grossman, Madigan Lavery, Sydney A. Lim, D. Irwin, T. Schuck, J. Trojanowski, E. Artacho-Pérula, Maria Mercedes Iniguez Onzono Martin, Edward B. Lee, G. Mizsei, D. Tisdall, María Mar Arroyo Jiménez, M. Muñoz, José Carlos Delgado González, Marta Córcoles Parada, C. Rosa Prieto, S. C. Sánchez, K. Prabhakaran, Maria Pilar Marcos Rabal, Francisco Javier Molina Romero, J. Robinson, D. Wolk, R. Insausti, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2020

Cited by 1

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Finding effective biomarkers that can support early‐stage clinical trials is a major challenge in Alzheimer’s Disease (AD). MRI measures of structural change in the medial temporal lobe (MTL) have proven to be sensitive to change in the early stages of AD. However, other frequently comorbid non‐AD factors (e.g. cerebrovascular disease, TDP‐43 pathology) also cause changes in the MTL. For MRI biomarkers to detect changes specifically linked to AD pathology, patterns of structural change must be linked to the underlying neuropathology. To provide this linkage, we use ex vivo imaging with pathologically derived ratings of AD and non‐AD pathology to study the localized effects of the disease on MTL structure. We hypothesize that such an analysis can be used to define MTL “hotspots” where in vivo measures will be more sensitive to disease progression in preclinical AD than current state of the art biomarkers.
A predictive, modeling‐based screening tool to enrich amyloid beta positivity in a cognitively normal sample

M. Truelove‐Hill, G. Erus, Raymond Pomponio, V. Bashyam, J. Doshi, M. Habes, A. Ezzati, Murat Bilgel, S. Resnick, I. Nasrallah, D. Wolk, and C. Davatzikos

Alzheimer’s & Dementia, Dec 2020

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As β‐amyloid (Aβ) targeted clinical trials have had questionable benefit in treating patients with early symptomatic Alzheimer’s disease, treatment would presumably be most effective if administered during the disease’s preclinical phase. PET scans, while highly sensitive to AD pathology, are less practical for screening a large, cognitively normal population for evidence of preclinical AD. Recruitment methods that produce an Aβ enriched sample before PET data collection would decrease participant burden and potentially lower costs. Here, we develop a simple predictive model using subject demographics, structural MRI, and APOE4 status. Using the model’s estimates of one’s probability of Aβ positivity, we significantly increase the proportion of Aβ+ subjects in a cognitively normal sample.
Automated Analysis of Low-Field Brain MRI in Cerebral Malaria

Danni Tu, M. Goyal, Jordan D Dworkin, S. Kampondeni, L. Vidal, Eric Biondo-Savin, Sandeep Juvvadi, P. Raghavan, Jennifer M. Nicholas, K. Chetcuti, Kelly A. Clark, T. Robert-Fitzgerald, T. Satterthwaite, Paul Yushkevich, C. Davatzikos, G. Erus, N. Tustison, D. Postels, T. Taylor, Dylan S. Small, and R. Shinohara

Biometrics, Dec 2020

Cited by 8

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A central challenge of medical imaging studies is to extract biomarkers that characterize pathology or predict disease outcomes. State-of-the-art automated approaches to identify these biomarkers in high-resolution, high-quality magnetic resonance images have performed well. However, such methods may not translate to low resolution, lower quality images acquired on MRI scanners with lower magnetic field strength. In low-resource settings where low-field scanners are more common and there is a shortage of available radiologists to manually interpret MRI scans, it is therefore essential to develop automated methods that can augment or replace manual interpretation while accommodating reduced image quality. Motivated by a project in which a cohort of children with cerebral malaria were imaged using 0.35 Tesla MRI to evaluate the degree of diffuse brain swelling, we introduce a fully automated framework to translate radiological diagnostic criteria into image-based biomarkers. We integrate multi-atlas label fusion, which leverages high-resolution images from another sample as prior spatial information, with parametric Gaussian hidden Markov models based on image intensities, to create a robust method for determining ventricular cerebrospinal fluid volume. We further propose normalized image intensity and texture measurements to determine the loss of gray-to-white matter tissue differentiation and sulcal effacement. These integrated biomarkers are found to have excellent classification performance for determining severe cerebral edema due to cerebral malaria.
High‐resolution postmortem MRI reveals TDP‐43 association with medial temporal lobe subregional atrophy

L. Wisse, S. Ravikumar, R. Ittyerah, Sydney A. Lim, J. Lane, Madigan Lavery, Long Xie, J. Robinson, T. Schuck, M. Grossman, Edward B. Lee, D. Tisdall, K. Prabhakaran, J. Detre, Sandhitsu R. Das, G. Mizsei, E. Artacho-Pérula, Maria Mercedes Iniguez Onzono Martin, María Mar Arroyo Jiménez, M. Muñoz, Francisco Javier Molina Romero, M. Rabal, S. C. Sánchez, José Carlos Delgado González, Carlos Rosa Prieto, Marta Córcoles Parada, D. Irwin, J. Trojanowski, D. Wolk, R. Insausti, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2020

Cited by 3

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The medial temporal lobe (MTL) is a hotspot of different neurodegenerative pathologies, and recent studies have shown associations of severity of pathology with atrophy measured on antemortem MRI. However, these studies are limited by the interval between time of scan and death and the relatively low resolution of the commonly acquired in vivo MRI scans, limiting the granularity of the regions being measured. We investigate the association of different neurodegenerative pathologies, particularly TDP‐43, and the thickness of different MTL subregions measured on high‐resolution postmortem MRI. As prior work suggests an anterior‐to‐posterior gradient of atrophy for TDP‐43 in frontotemporal dementia spectrum disorders and Limbic‐predominant Age‐related TDP‐43 Encephalopathy (LATE), we also examined differences along the long axis of the MTL.
Tau pathology mediates age effects on medial temporal lobe atrophy

L. Wisse, Long Xie, Sandhitsu R. Das, R. Flores, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Dec 2020

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Age effects on the hippocampus are well established, but age‐effects on adjacent cortical regions less so. Moreover, aging has often been investigated using cross‐sectional designs, seldomly separating aging effects from the effects of β‐amyloid. We investigate the effect of aging on medial temporal lobe (MTL) subregions cross‐sectionally and longitudinally in β‐amyloid‐negative (A‐) cognitively normal (CN) older adults and the role of tau pathology, a potential mediator.
Subtle differences in the appearance of hippocampal layers differentiate preclinical AD from healthy aging

Long Xie, Sandhitsu R. Das, L. Wisse, R. Ittyerah, Nicolas Vergnet, R. Flores, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Dec 2020

Cited by 1

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Degeneration of the stratum radiatum lacunosum moleculare (SRLM), located between the cornu ammonis (CA)/subiculum and dentate gyrus (DG) subfields of the hippocampus (Figure 1) and containing apical dendrites of CA pyramidal cells, may be an early feature of AD and can be observed in postmortem studies (Adler et al, 2018). The pathological change in SRLM may produce subtle alteration of image signal on high‐resolution in vivo MRI. We hypothesize that convolutional neural networks (CNNs) can detect such alterations in preclinical AD, yielding a more sensitive biomarker than conventional morphological measurements.
Remote effects of temporal lobe epilepsy surgery: Long‐term morphological changes after surgical resection

T. Arnold, Lohith G. Kini, John M. Bernabei, A. Revell, Sandhitsu R. Das, J. Stein, Timothy H. Lucas, D. Englot, V. Morgan, B. Litt, and K. Davis

Epilepsia Open, Nov 2020

Cited by 10

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Epilepsy surgery is an effective treatment for drug‐resistant patients. However, how different surgical approaches affect long‐term brain structure remains poorly characterized. Here, we present a semiautomated method for quantifying structural changes after epilepsy surgery and compare the remote structural effects of two approaches, anterior temporal lobectomy (ATL), and selective amygdalohippocampectomy (SAH).
Cross-sectional and longitudinal Medial Temporal Lobe Subregional Atrophy Patterns in Semantic Variant Primary Progressive Aphasia

L. Wisse, Molly B. Ungrady, R. Ittyerah, Sydney A. Lim, Paul Yushkevich, D. Wolk, D. Irwin, Sandhitsu R. Das, and M. Grossman

Neurobiology of aging, Nov 2020

Cited by 9

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Introduction: T1-MRI studies report early atrophy in the left anterior temporal lobe, especially the perirhinal cortex (PRC), in semantic variant Primary Progressive Aphasia (svPPA). Improved segmentation protocols using high-resolution T2-MRI have enabled fine-grained medial temporal lobe (MTL) subregional measurements, which may provide novel information on the atrophy pattern and disease progression in svPPA. We aimed to investigate the MTL subregional atrophy pattern cross-sectionally and longitudinally in patients with svPPA as compared to controls and patients with Alzheimer’s disease (AD). Methods: MTL subregional volumes were obtained using the Automated Segmentation for Hippocampal Subfields (ASHS) software from high-resolution T2-MRIs in 15 svPPA, 37 AD and 23 healthy controls. All MTL volumes were corrected for intracranial volume and parahippocampal cortices for slice number. Longitudinal atrophy rates of all subregions were obtained using an unbiased deformation-based morphometry pipeline in 6 svPPA patients, 9 controls and 12 AD patients. Results: Cross-sectionally, significant volume loss was observed in svPPA compared to controls in the left MTL, right cornu ammonis (CA)1, Brodmann Area (BA)35 and BA36 (subdivisions of the PRC). Compared to AD patients, svPPA patients had significantly smaller left CA1, BA35 and left and right BA36 volumes. Longitudinally, svPPA patients had significantly greater atrophy rates of left and right BA36 compared to controls, but not relative to AD patients. Discussion: Fine-grained analysis of MTL atrophy patterns provides information about the evolution of atrophy in svPPA. These results indicate that MTL subregional measures might be useful markers to track disease progression or for clinical trials in svPPA.
Cross-sectional and longitudinal medial temporal lobe subregional atrophy patterns in semantic variant primary progressive aphasia.

L. Wisse, Molly B. Ungrady, R. Ittyerah, Sydney A. Lim, Paul Yushkevich, D. Wolk, D. Irwin, Sandhitsu R. Das, and M. Grossman

Neurobiology of aging, Nov 2020

Cited by 8

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T1-magnetic resonance imaging (MRI) studies report early atrophy in the left anterior temporal lobe, especially the perirhinal cortex, in semantic variant primary progressive aphasia (svPPA). Improved segmentation protocols using high-resolution T2-MRI have enabled fine-grained medial temporal lobe (MTL) subregional measurements, which may provide novel information on the atrophy pattern and disease progression in svPPA. We aimed to investigate the MTL subregional atrophy pattern cross-sectionally and longitudinally in patients with svPPA as compared with controls and patients with Alzheimer’s disease (AD). MTL subregional volumes were obtained using the Automated Segmentation for Hippocampal Subfields software from high-resolution T2-MRIs in 15 svPPA, 37 AD, and 23 healthy controls. All MTL volumes were corrected for intracranial volume and parahippocampal cortices for slice number. Longitudinal atrophy rates of all subregions were obtained using an unbiased deformation-based morphometry pipeline in 6 svPPA patients, 9 controls, and 12 AD patients. Cross-sectionally, significant volume loss was observed in svPPA compared with controls in the left MTL, right cornu ammonis 1 (CA1), Brodmann area (BA)35, and BA36 (subdivisions of the perirhinal cortex). Compared with AD patients, svPPA patients had significantly smaller left CA1, BA35, and left and right BA36 volumes. Longitudinally, svPPA patients had significantly greater atrophy rates of left and right BA36 than controls but not relative to AD patients. Fine-grained analysis of MTL atrophy patterns provides information about the evolution of atrophy in svPPA. These results indicate that MTL subregional measures might be useful markers to track disease progression or for clinical trials in svPPA.
Multimodal image analysis and subvalvular dynamics in ischemic mitral regurgitation

A. H. Aly, Yoshiaki Saito, W. Bouma, J. Pilla, A. Pouch, Paul Yushkevich, Matthew J. Gillespie, J. Gorman, and R. Gorman

JTCVS Open, Oct 2020

Cited by 2

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Background The exact geometric pathogenesis of leaflet tethering in ischemic mitral regurgitation (IMR) and the relative contribution of each component of the mitral valve complex (MVC) remain largely unknown. In this study, we sought to further elucidate mitral valve (MV) leaflet remodeling and papillary muscle dynamics in an ovine model of IMR with magnetic resonance imaging (MRI) and 3-dimensional echocardiography (3DE). Methods Multimodal imaging combining 3DE and MRI was used to analyze the MVC at baseline, 30 minutes post–myocardial infarction (MI), and 12 weeks post-MI in ovine IMR models. Advanced 3D imaging software was used to trace the MVC from each modality, and the tracings were verified against resected specimens. Results 3DE MV remodeling was regionally heterogenous and observed primarily in the anterior leaflet, with significant increases in surface area, especially in A2 and A3. The posterior leaflet was significantly shortened in P2 and P3. Mean posteromedial papillary muscle (PMPM) volume was decreased from 1.9 ± 0.2 cm3 at baseline to 0.9 ± 0.3 cm3 at 12 weeks post-MI (P < .05). At 12 weeks post-MI, the PMPM was predominately displaced horizontally and outward along the intercommissural axis with minor apical displacement. The subvalvular contribution to tethering is a combination of unilateral movement, outward displacement, and degeneration of the PMPM. These findings have led to a proposed new framework for characterizing PMPM dynamics in IMR. Conclusions This study provides new insights into the complex interrelated and regionally heterogenous valvular and subvalvular mechanisms involved in the geometric pathogenesis of IMR tethering.
DeepAtrophy: Teaching a Neural Network to Differentiate Progressive Changes from Noise on Longitudinal MRI in Alzheimer’s Disease

M. Dong, Long Xie, Sandhitsu R. Das, Jiancong Wang, L. Wisse, R. Flores, D. Wolk, and Paul Yushkevich

ArXiv, Oct 2020

Cited by 1

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Volume change measures derived from longitudinal MRI (e.g. hippocampal atrophy) are a well-studied biomarker of disease progression in Alzheimer’s Disease (AD) and are used in clinical trials to track the therapeutic efficacy of disease-modifying treatments. However, longitudinal MRI change measures can be confounded by non-biological factors, such as different degrees of head motion and susceptibility artifact between pairs of MRI scans. We hypothesize that deep learning methods applied directly to pairs of longitudinal MRI scans can be trained to differentiate between biological changes and non-biological factors better than conventional approaches based on deformable image registration. To achieve this, we make a simplifying assumption that biological factors are associated with time (i.e. the hippocampus shrinks overtime in the aging population) whereas non-biological factors are independent of time. We then formulate deep learning networks to infer the temporal order of same-subject MRI scans input to the network in arbitrary order; as well as to infer ratios between interscan intervals for two pairs of same-subject MRI scans. In the test dataset, these networks perform better in tasks of temporal ordering (89.3%) and interscan interval inference (86.1%) than a state-of-the-art deformation-based morphometry method ALOHA (76.6% and 76.1% respectively) (Das et al., 2012). Furthermore, we derive a disease progression score from the network that is able to detect a group difference between 58 preclinical AD and 75 beta-amyloid-negative cognitively normal individuals within one year, compared to two years for ALOHA. This suggests that deep learning can be trained to differentiate MRI changes due to biological factors (tissue loss) from changes due to non-biological factors, leading to novel biomarkers that are more sensitive to longitudinal changes at the earliest stages of AD.
Feed-forward, feed-back, and distributed feature representation during visual word recognition revealed by human intracranial neurophysiology

L. Long, Min-Da Yang, N. Kriegeskorte, J. Jacobs, R. Remez, M. Sperling, A. Sharan, B. Lega, Alexis Burks, G. Worrell, R. Gross, B. Jobst, K. Davis, K. Zaghloul, S. Sheth, J. Stein, Sandhitsu R. Das, R. Gorniak, Paul A. Wanda, M. Kahana, and N. Mesgarani

Oct 2020

Cited by 3

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Scientists debate where, when, and how different visual, orthographic, lexical, and semantic features are involved in visual word recognition. In this study, we investigate intracranial neurophysiology data from 151 patients engaged in reading single words. Using representational similarity analysis, we characterize the neural representation of a hierarchy of word features across the entire cerebral cortex. We find evidence of both feed-forward and feedback processing, with early representation of visual and lexical information in lingual gyrus followed by lexical representation in fusiform gyrus and semantic sensitivity in inferior frontal gyrus, with letter representation emerging later in fusiform gyrus. Furthermore, we observed a variety of anatomically heterogeneous temporal response shapes, and these functional populations had significant feature sensitivity. Taken together, our results demonstrate the early influence of lexical, phonological, and semantic features in visual word recognition and reveal feed-forward, feed-back, and anatomically distributed processing mechanisms that contribute to visual word recognition.
ANTsX: A dynamic ecosystem for quantitative biological and medical imaging

N. Tustison, Philip A Cook, A. Holbrook, H. Johnson, J. Muschelli, Gabriel A. Devanyi, J. Duda, Sandhitsu R. Das, Nicholas C. Cullen, D. Gillen, M. Yassa, J. Stone, J. Gee, and B. Avants

medRxiv, Oct 2020

Cited by 14

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The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of multiple open- source software libraries which house top-performing algorithms used worldwide by scientific and research communities for processing and analyzing biological and medical imaging data. The base software library, ANTs, is built upon, and contributes to, the NIH-sponsored Insight Toolkit. Founded in 2008 with the highly regarded Symmetric Normalization image registration framework, the ANTs library has since grown to include additional functionality. Recent enhancements include statistical, visualization, and deep learning capabilities through interfacing with both the R statistical project (ANTsR) and Python (ANTsPy). Additionally, the corresponding deep learning extensions ANTsRNet and ANTsPyNet (built on the popular TensorFlow/Keras libraries) contain several popular network architectures and trained models for specific applications. One such comprehensive application is a deep learning analog for generating cortical thickness data from structural T1-weighted brain MRI. Not only does this significantly improve computational efficiency and provide comparable-to-superior accuracy over the existing ANTs pipeline but it also illustrates the importance of the comprehensive ANTsX approach as a framework for medical image analysis.
Hippocampal subfield volumetry from structural isotropic 1 mm3 MRI scans: A note of caution

L. Wisse, G. Chételat, Ana M. Daugherty, R. Flores, R. La Joie, S. Mueller, Craig E. L. Stark, Lei Wang, Paul Yushkevich, D. Berron, N. Raz, A. Bakker, R. Olsen, and Valerie A. Carr

Human Brain Mapping, Oct 2020

Cited by 137

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Spurred by availability of automatic segmentation software, in vivo MRI investigations of human hippocampal subfield volumes have proliferated in the recent years. However, a majority of these studies apply automatic segmentation to MRI scans with approximately 1 × 1 × 1 mm3 resolution, a resolution at which the internal structure of the hippocampus can rarely be visualized. Many of these studies have reported contradictory and often neurobiologically surprising results pertaining to the involvement of hippocampal subfields in normal brain function, aging, and disease. In this commentary, we first outline our concerns regarding the utility and validity of subfield segmentation on 1 × 1 × 1 mm3 MRI for volumetric studies, regardless of how images are segmented (i.e., manually or automatically). This image resolution is generally insufficient for visualizing the internal structure of the hippocampus, particularly the stratum radiatum lacunosum moleculare, which is crucial for valid and reliable subfield segmentation. Second, we discuss the fact that automatic methods that are employed most frequently to obtain hippocampal subfield volumes from 1 × 1 × 1 mm3 MRI have not been validated against manual segmentation on such images. For these reasons, we caution against using volumetric measurements of hippocampal subfields obtained from 1 × 1 × 1 mm3 images.
Hippocampal Subfield Pathologic Burden in Lewy Body Diseases versus Alzheimer’s Disease

D. Coughlin, R. Ittyerah, Claire S. Peterson, Jeffrey S. Phillips, Simon Miller, K. Rascovsky, D. Weintraub, A. Siderowf, J. Duda, H. Hurtig, D. Wolk, C. McMillan, Paul Yushkevich, M. Grossman, Edward B. Lee, J. Trojanowski, and D. Irwin

Neuropathology and applied neurobiology, Sep 2020

Cited by 32

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Lewy body diseases (LBD) are characterized by alpha‐synuclein (SYN) pathology, but comorbid Alzheimer’s disease (AD) pathology is common and the relationship between these pathologies in microanatomic hippocampal subfields is understudied. Here we use digital histological methods to test the association between hippocampal SYN pathology and the distribution of tau and amyloid‐beta (Aβ) pathology in LBD and contrast with AD subjects. We also correlate pathologic burden with antemortem episodic memory testing.
Hippocampal subfield pathologic burden in Lewy body diseases vs. Alzheimer’s disease

D. Coughlin, R. Ittyerah, Claire S. Peterson, J. Phillips, Simon Miller, K. Rascovsky, D. Weintraub, A. Siderowf, J. Duda, H. Hurtig, D. Wolk, C. Mcmillan, Paul Yushkevich, M. Grossman, Eddie B. Lee, J. Trojanowski, and D. Irwin

Neuropathology and Applied Neurobiology, Sep 2020

Cited by 31

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Lewy body diseases (LBD) are characterized by alpha‐synuclein (SYN) pathology, but comorbid Alzheimer’s disease (AD) pathology is common and the relationship between these pathologies in microanatomic hippocampal subfields is understudied. Here we use digital histological methods to test the association between hippocampal SYN pathology and the distribution of tau and amyloid‐beta (Aβ) pathology in LBD and contrast with AD subjects. We also correlate pathologic burden with antemortem episodic memory testing.
Volumetric glutamate imaging (GluCEST) using 7T MRI can lateralize nonlesional temporal lobe epilepsy: A preliminary study

P. Hadar, Lohith G. Kini, R. Nanga, R. Shinohara, Stephanie H. Chen, Preya Shah, L. Wisse, M. Elliott, H. Hariharan, R. Reddy, J. Detre, J. Stein, Sandhitsu R. Das, and K. Davis

Brain and Behavior, Sep 2020

Cited by 19

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Drug‐resistant epilepsy patients show worse outcomes after resection when standard neuroimaging is nonlesional, which occurs in one‐third of patients. In prior work, we employed 2‐D glutamate imaging, Glutamate Chemical Exchange Saturation Transfer (GluCEST), to lateralize seizure onset in nonlesional temporal lobe epilepsy (TLE) based on increased ipsilateral GluCEST signal in the total hippocampus and hippocampal head. We present a significant advancement to single‐slice GluCEST imaging, allowing for three‐dimensional analysis of brain glutamate networks.
Bone-Selective Magnetic Resonance Imaging as a Nonradiative Alternative to Computed Tomography for Cranial Vault Imaging: Concordance and Implementation of an Automated Segmentation Pipeline for Timely Image Processing

C. Zimmerman, Pulkit Khandelwal, Rosaline S. Zhang, Long Xie, Hyunyeol Lee, Jesse A. Taylor, J. Swanson, Paul Yushkevich, F. Wehrli, and S. Bartlett

Plastic and Reconstructive Surgery Global Open, Sep 2020

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METHODS: Eight Yucatan miniature pigs, 4 donors and 4 recipients, were used. Right forelimbs of donor animals were amputated at mid-humeral level, to maintain integrity of forearm fascial compartments, and preserved with EVNLP until replantation. The right forelimb of the recipient animal was amputated, and a central venous line was placed in the contralateral neck. Perfusate electrolytes, gases, O 2 saturation, muscle contractility, surface temperature (infrared thermography), and peripheral perfusion (indocyanine green agiography) were assessed during EVNLP. The humerus was fixed with a single 3.5 mm LC-DCP plate; microsurgical anastomosis of the brachial artery, cephalic vein, and repair of radial, ulnar, and median nerves were performed under an operative microscope. Tendons of the biceps and triceps were repaired with pulvertaft weave technique. The first animal did not receive systemic immunosuppression. Systemic immunosuppression for the remaining 3 pigs included induction with antithymoglobulin, followed by daily cyclosporine (CSA), mycophenolate mofetil, and methylprednisolone. CSA trough levels were measured daily. Limbs were monitored clinically and histologically for signs of rejection. Bone healing was confirmed with CT scan at euthanasia. The endpoint of the study was 90 days.
In Vivo Image-Based 4D Modeling of Competent and Regurgitant Mitral Valve Dynamics

A. H. Aly, Eric K. Lai, Natalie Yushkevich, R. H. Stoffers, J. Gorman, A. Cheung, Robert C. Gorman, Paul Yushkevich, and A. Pouch

Experimental mechanics, Aug 2020

Cited by 9

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In vivo characterization of mitral valve dynamics relies on image analysis algorithms that accurately reconstruct valve morphology and motion from clinical images. The goal of such algorithms is to provide patient-specific descriptions of both competent and regurgitant mitral valves, which can be used as input to biomechanical analyses and provide insights into the pathophysiology of diseases like ischemic mitral regurgitation (IMR). The goal is to generate accurate image-based representations of valve dynamics that visually and quantitatively capture normal and pathological valve function. We present a novel framework for 4D segmentation and geometric modeling of the mitral valve in real-time 3D echocardiography (rt-3DE), an imaging modality used for pre-operative surgical planning of mitral interventions. The framework integrates groupwise multi-atlas label fusion and template-based medial modeling with Kalman filtering to generate quantitatively descriptive and temporally consistent models of valve dynamics. The algorithm is evaluated on rt-3DE data series from 28 patients: 14 with normal mitral valve morphology and 14 with severe IMR. In these 28 data series that total 613 individual 3DE images, each 3D mitral valve segmentation is validated against manual tracing, and temporal consistency between segmentations is demonstrated. Automated 4D image analysis allows for reliable non-invasive modeling of the mitral valve over the cardiac cycle for comparison of annular and leaflet dynamics in pathological and normal mitral valves. Future studies can apply this algorithm to cardiovascular mechanics applications, including patient-specific strain estimation, fluid dynamics simulation, inverse finite element analysis, and risk stratification for surgical treatment.
Domain Generalizer: A Few-shot Meta Learning Framework for Domain Generalization in Medical Imaging

Pulkit Khandelwal, and Paul Yushkevich

In DART/DCL@MICCAI, Aug 2020

Cited by 49

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Deep learning models perform best when tested on target (test) data domains whose distribution is similar to the set of source (train) domains. However, model generalization can be hindered when there is significant difference in the underlying statistics between the target and source domains. In this work, we adapt a domain generalization method based on a model-agnostic meta-learning framework [1] to biomedical imaging. The method learns a domain-agnostic feature representation to improve generalization of models to the unseen test distribution. The method can be used for any imaging task, as it does not depend on the underlying model architecture. We validate the approach through a computed tomography (CT) vertebrae segmentation task across healthy and pathological cases on three datasets. Next, we employ few-shot learning, i.e. training the generalized model using very few examples from the unseen domain, to quickly adapt the model to new unseen data distribution. Our results suggest that the method could help generalize models across different medical centers, image acquisition protocols, anatomies, different regions in a given scan, healthy and diseased populations across varied imaging modalities.
Longitudinal atrophy in early Braak regions in preclinical Alzheimer’s disease

Long Xie, L. Wisse, Sandhitsu R. Das, Nicolas Vergnet, M. Dong, R. Ittyerah, R. Flores, Paul Yushkevich, and D. Wolk

Human Brain Mapping, Aug 2020

Cited by 57

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A major focus of Alzheimer’s disease (AD) research has been finding sensitive outcome measures to disease progression in preclinical AD, as intervention studies begin to target this population. We hypothesize that tailored measures of longitudinal change of the medial temporal lobe (MTL) subregions (the sites of earliest cortical tangle pathology) are more sensitive to disease progression in preclinical AD compared to standard cognitive and plasma NfL measures. Longitudinal T1‐weighted MRI of 337 participants were included, divided into amyloid‐β negative (Aβ−) controls, cerebral spinal fluid p‐tau positive (T+) and negative (T−) preclinical AD (Aβ+ controls), and early prodromal AD. Anterior/posterior hippocampus, entorhinal cortex, Brodmann areas (BA) 35 and 36, and parahippocampal cortex were segmented in baseline MRI using a novel pipeline. Unbiased change rates of subregions were estimated using MRI scans within a 2‐year‐follow‐up period. Experimental results showed that longitudinal atrophy rates of all MTL subregions were significantly higher for T+ preclinical AD and early prodromal AD than controls, but not for T− preclinical AD. Posterior hippocampus and BA35 demonstrated the largest group differences among hippocampus and MTL cortex respectively. None of the cross‐sectional MTL measures, longitudinal cognitive measures (PACC, ADAS‐Cog) and cross‐sectional or longitudinal plasma NfL reached significance in preclinical AD. In conclusion, longitudinal atrophy measurements reflect active neurodegeneration and thus are more directly linked to active disease progression than cross‐sectional measurements. Moreover, accelerated atrophy in preclinical AD seems to occur only in the presence of concomitant tau pathology. The proposed longitudinal measurements may serve as efficient outcome measures in clinical trials.
Sensitive measures of cognition in Mild Cognitive Impairment

Nathaniel Klooster, S. Humphries, E. Cardillo, Franziska Hartung, Long Xie, Sandhitsu R. Das, Paul Yushkevich, Arun Pilania, Jieqiong Wang, D. Wolk, and A. Chatterjee

Journal of Alzheimer’s disease : JAD, Jul 2020

Cited by 6

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Background: Sensitive measures of cognition are needed in preclinical and prodromal Alzheimer’s disease (AD) to track cognitive change and evaluate potential interventions. Neurofibrillary tangle pathology in AD is first observed in Brodmann Area 35 (BA35), the medial portion of the perirhinal cortex. The importance of the perirhinal cortex for semantic memory may explain early impairments of semantics in preclinical AD. Additionally, our research has tied figurative language impairment to neurodegenerative disease. Objective: We aim to identify tasks that are sensitive to cognitive impairment in individuals with mild cognitive impairment (MCI), and that are sensitive to atrophy in BA35. Methods: Individuals with MCI and cognitively normal participants (CN) were tested on productive and receptive experimental measures of semantic memory and experimental tests of figurative language comprehension (including metaphor and verbal analogy). Performance was related to structural imaging and standard neuropsychological assessment. Results: On the experimental tests of semantics and figurative language, people with MCI performed worse than CN participants. The experimental semantic memory tasks are sensitive and specific; performance on the experimental semantic memory tasks related to medial temporal lobe structural integrity, including BA35, while standard neuropsychological assessments of semantic memory did not, demonstrating the sensitivity of these experimental measures. A visuo-spatial analogy task did not differentiate groups, confirming the specificity of semantic and figurative language tasks. Conclusion: These experimental measures appear sensitive to cognitive change and neurodegeneration early in the AD trajectory and may prove useful in tracking cognitive change in clinical trials aimed at early intervention.
Neural and behavioral correlates of episodic memory are associated with temporal discounting in older adults

K. Lempert, D. Mechanic-Hamilton, Long Xie, L. Wisse, R. Flores, Jieqiong Wang, Sandhitsu R. Das, Paul Yushkevich, D. Wolk, and Joseph W. Kable

Neuropsychologia, Jul 2020

Cited by 27

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When facing decisions involving trade-offs between smaller, sooner and larger, delayed rewards, people tend to discount the value of future rewards. There are substantial individual differences in this tendency toward temporal discounting, however. One neurocognitive system that may underlie these individual differences is episodic memory, given the overlap in the neural circuitry involved in imagining the future and remembering the past. Here we tested this hypothesis in older adults, including both those that were cognitively normal and those with amnestic mild cognitive impairment (MCI). We found that performance on neuropsychological measures of episodic memory retrieval was associated with temporal discounting, such that people with better memory discounted delayed rewards less. This relationship was specific to episodic memory and temporal discounting, since executive function (another cognitive ability) was unrelated to temporal discounting, and episodic memory was unrelated to risk tolerance (another decision-making preference). We also examined cortical thickness and volume in medial temporal lobe regions critical for episodic memory. Entorhinal cortical thickness was associated with reduced temporal discounting, with episodic memory performance partially mediating this association. The inclusion of MCI participants was critical to revealing these associations between episodic memory and entorhinal cortical thickness and temporal discounting. These effects were larger in the MCI group, reduced after controlling for MCI status, and statistically significant only when including MCI participants in analyses. Overall, these findings suggest that individual differences in temporal discounting are driven by episodic memory function, and that a decline in medial temporal lobe structural integrity may impact temporal discounting.
Neural and behavioral correlates of episodic memory are associated with temporal discounting in older adults.

Karolina M. Lempert, D. Mechanic-Hamilton, L. Xie, L. Wisse, R. Flores, Jieqiong Wang, Sandhitsu R. Das, Paul Yushkevich, D. Wolk, and J. Kable

Neuropsychologia, Jul 2020

Cited by 26

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When facing decisions involving trade-offs between smaller, sooner and larger, delayed rewards, people tend to discount the value of future rewards. There are substantial individual differences in this tendency toward temporal discounting, however. One neurocognitive system that may underlie these individual differences is episodic memory, given the overlap in the neural circuitry involved in imagining the future and remembering the past. Here we tested this hypothesis in older adults, including both those that were cognitively normal and those with amnestic mild cognitive impairment (MCI). We found that performance on neuropsychological measures of episodic memory retrieval was associated with temporal discounting, such that people with better memory discounted delayed rewards less. This relationship was specific to episodic memory and temporal discounting, since executive function (another cognitive ability) was unrelated to temporal discounting, and episodic memory was unrelated to risk tolerance (another decision-making preference). We also examined cortical thickness and volume in medial temporal lobe regions critical for episodic memory. Entorhinal cortical thickness was associated with reduced temporal discounting, with episodic memory performance partially mediating this association. The inclusion of MCI participants was critical to revealing these associations between episodic memory and entorhinal cortical thickness and temporal discounting. These effects were larger in the MCI group, reduced after controlling for MCI status, and statistically significant only when including MCI participants in analyses. Overall, these findings suggest that individual differences in temporal discounting are driven by episodic memory function, and that a decline in medial temporal lobe structural integrity may impact temporal discounting.
Intraoperative post-annuloplasty three-dimensional valve analysis does not predict recurrent ischemic mitral regurgitation

F. Meijerink, Inez J. Wijdh-Den Hamer, W. Bouma, A. Pouch, A. H. Aly, Eric K. Lai, T. Eperjesi, M. Acker, Paul Yushkevich, J. Hung, M. Mariani, K. Khabbaz, Thomas G. Gleason, F. Mahmood, Joseph H. Iii Gorman, and R. Gorman

Journal of Cardiothoracic Surgery, Jul 2020

Cited by 3

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Background High ischemic mitral regurgitation (IMR) recurrence rates continue to plague IMR repair with undersized ring annuloplasty. We have previously shown that pre-repair three-dimensional echocardiography (3DE) analysis is highly predictive of IMR recurrence. The objective of this study was to determine the quantitative change in 3DE annular and leaflet tethering parameters immediately after repair and to determine if intraoperative post-repair 3DE parameters would be able to predict IMR recurrence 6 months after repair. Methods Intraoperative pre- and post-repair transesophageal real-time 3DE was performed in 35 patients undergoing undersized ring annuloplasty for IMR. An advanced modeling algorhythm was used to assess 3D annular geometry and regional leaflet tethering. IMR recurrence (≥ grade 2) was assessed with transthoracic echocardiography 6 months after repair. Results Annuloplasty significantly reduced septolateral diameter, commissural width, annular area, and tethering volume and significantly increased all segmental tethering angles (except A2). Intraoperative post-repair annular geometry and leaflet tethering did not differ significantly between patients with recurrent IMR ( n = 9) and patients with non-recurrent IMR ( n = 26). No intraoperative post-repair predictors of IMR recurrence could be identified. Conclusions Undersized ring annuloplasty changes mitral geometry acutely, exacerbates leaflet tethering, and generally fixes IMR acutely, but it does not always fix the delicate underlying chronic problem of continued left ventricular dilatation and remodeling. This may explain why pre-repair 3D valve geometry (which reflects chronic left ventricular remodeling) is highly predictive of recurrent IMR, whereas immediate post-repair 3D valve geometry (which does not completely reflect chronic left ventricular remodeling anymore) is not.
Contribution of mixed pathology to medial temporal lobe atrophy in Alzheimer’s disease

R. Flores, L. Wisse, Sandhitsu R. Das, Long Xie, Corey T. McMillan, J. Trojanowski, John L. Robinson, M. Grossman, Edward B. Lee, David J. Irwin, Paul Yushkevich, and D. Wolk

Alzheimer’s & dementia : the journal of the Alzheimer’s Association, Apr 2020

Cited by 99

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It is unclear how different proteinopathies (tau, transactive response DNA‐binding protein 43 [TDP‐43], amyloid β [Aβ], and α‐synuclein) contribute to atrophy within medial temporal lobe (MTL) subregions in Alzheimer’s disease (AD).
Contribution of mixed pathology to medial temporal lobe atrophy in Alzheimer’s disease

R. Flores, L. Wisse, Sandhitsu R. Das, L. Xie, C. Mcmillan, J. Trojanowski, John L. Robinson, M. Grossman, Eddie B. Lee, D. Irwin, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Apr 2020

Cited by 90

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It is unclear how different proteinopathies (tau, transactive response DNA‐binding protein 43 [TDP‐43], amyloid β [Aβ], and α‐synuclein) contribute to atrophy within medial temporal lobe (MTL) subregions in Alzheimer’s disease (AD).
Tau Status Portends Different Baseline and Longitudinal Cognitive Performance in Amyloid- and Neurodegeneration-positive Mild Cognitive Impairment (MCI) (4723)

Lauren McCollum, L. Wisse, Salena Cui, R. Flores, Sandhitsu R. Das, Long Xie, Paul Yushkevich, and David Wolk

Neurology, Apr 2020

DOI
Automated Meshing of Anatomical Shapes for Deformable Medial Modeling: Application to the Placenta in 3D Ultrasound

A. Pouch, Paul Yushkevich, Abdullah H. Aly, Alexander H. F. Woltersom, Edidiong Okon, A. H. Aly, N. Yushkevich, Shobhana Parameshwaran, Jiancong Wang, Baris U. Oguz, C. Gee, I. Oguz, and N. Schwartz

In IEEE International Symposium on Biomedical Imaging, Apr 2020

Cited by 6

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Deformable medial modeling is an approach to extracting clinically useful features of the morphological skeleton of anatomical structures in medical images. Similar to any deformable modeling technique, it requires a pre-defined model, or synthetic skeleton, of a class of shapes before modeling new instances of that class. The creation of synthetic skeletons often requires manual interaction, and the deformation of the synthetic skeleton to new target geometries is prone to registration errors if not well initialized. This work presents a fully automated method for creating synthetic skeletons (i.e., 3D boundary meshes with medial links) for flat, oblong shapes that are homeomorphic to a sphere. The method rotationally cross-sections the 3D shape, approximates a 2D medial model in each cross-section, and then defines edges between nodes of neighboring slices to create a regularly sampled 3D boundary mesh. In this study, we demonstrate the method on 62 segmentations of placentas in first-trimester 3D ultrasound images and evaluate its compatibility and representational accuracy with an existing deformable modeling method. The method may lead to extraction of new clinically meaningful features of placenta geometry, as well as facilitate other applications of deformable medial modeling in medical image analysis.
Building an Ex Vivo Atlas of the Earliest Brain Regions Affected by Alzheimer’s Disease Pathology

S. Ravikumar, L. Wisse, R. Ittyerah, Sydney A. Lim, Madigan Lavery, Long Xie, J. Robinson, T. Schuck, M. Grossman, Edward B. Lee, M. Tisdall, K. Prabhakaran, J. Detre, Sandhitsu R. Das, G. Mizsei, E. Artacho-Pérula, Maria Mercedes Iñiguez Onzono Martin, María Mar Arroyo Jiménez, M. Muñoz, Francisco Javier Molina Romero, Maria Pilar Marcos Rabal, D. Irwin, J. Trojanowski, D. Wolk, R. Insausti, and Paul Yushkevich

In IEEE International Symposium on Biomedical Imaging, Apr 2020

Cited by 7

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Earliest neuropathological changes in Alzheimer’s Disease (AD) emerge in the medial temporal lobe (MTL). In order for MRI biomarkers to detect changes linked specifically to AD pathology (as opposed to aging or other pathological factors) macroscopic patterns of structural change in the MTL must be linked to the underlying neuropathology. To provide such a linkage, we are conducting an autopsy imaging study combining ex vivo MRI and serial histopathology. Information from multiple subjects can be studied by creating a “population average” atlas of the MTL. We present a groupwise registration approach for constructing the atlas that is able to successfully capture the complex structure of the MTL, and anatomical variability across subjects. This atlas allows us to generate maps of cortical thickness measurements and identify regions in the MTL where structural changes correlate most strongly with AD progression. We show that using this atlas, we are able to find a significant correlation between atrophy and AD pathology in the MTL sub-regions associated with the earliest stages of AD pathology as described by Braak and Braak [1].
3D Mapping of TAU Neurofibrillary Tangle Pathology in the Human Medial Temporal Lobe

Paul Yushkevich, Maria Mercedes Iñiguez Onzoño Martin, R. Ittyerah, Sydney A. Lim, Madigan Lavery, Jiancong Wang, Ling-Yu Hung, Nicolas Vergnet, S. Ravikumar, Long Xie, M. Dong, R. Flores, Salena Cui, Lauren McCollum, Daniel T. Ohm, J. Robinson, T. Schuck, M. Grossman, M. Tisdall, K. Prabhakaran, G. Mizsei, Sandhitsu R. Das, E. Artacho-Pérula, María Mar Arroyo Jiménez, M. M. López, M. Rabal, Francisco Javier Molina Romero, Edward B. Lee, J. Trojanowski, L. Wisse, D. Wolk, D. Irwin, and R. Insausti

In IEEE International Symposium on Biomedical Imaging, Apr 2020

Cited by 5

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Tau protein neurofibrillary tangles (NFT) are linked to neuronal and synaptic loss and cognitive decline in Alzheimer’s disease (AD) and related dementias. In AD, NFT pathology is known to spread through the cortex in a characteristic pattern, starting in the medial temporal lobe. However, the exact 3D pattern of NFT progression has not been described, and capturing this pattern quantitatively can help inform in vivo AD imaging biomarkers. We present a computational framework for generating 3D maps of NFT load from ex vivo MRI and serial histology. Weakly supervised deep learning is used to detect NFTs on histology slides prepared with an anti-tau immunohistochemistry stain, and a multi-stage registration pipeline that leverages 3D printing is used for histology-MRI alignment. Derived maps of NFT density are strongly concordant with manual NFT counting, as well as categorical NFT severity ratings used for clinical diagnosis.
Issue Information Page

A. Mehdiani, Alexander Albert, H. Dalyanoĝlu, D. Scheiber, Ralf Westenfeld, H. Aubin, A. Lichtenberg, P. Akhyari, M. Levack, G. Mecozzi, Jayant S Jainandunsing, W. Bouma, A. Jassar, and Paul Yushkevich

Journal of Cardiac Surgery, Jan 2020

DOI PDF
Minimally interactive placenta segmentation from three-dimensional ultrasound images

I. Oguz, N. Yushkevich, A. Pouch, Baris U. Oguz, Jiancong Wang, Shobhana Parameshwaran, J. Gee, Paul Yushkevich, and N. Schwartz

Journal of Medical Imaging, Jan 2020

Cited by 15

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Abstract. Purpose: Placental size in early pregnancy has been associated with important clinical outcomes, including fetal growth. However, extraction of placental size from three-dimensional ultrasound (3DUS) requires time-consuming interactive segmentation methods and is prone to user variability. We propose a semiautomated segmentation technique that requires minimal user input to robustly measure placental volume from 3DUS images. Approach: For semiautomated segmentation, a single, central 2D slice was manually annotated to initialize an automated multi-atlas label fusion (MALF) algorithm. The dataset consisted of 47 3DUS volumes obtained at 11 to 14 weeks in singleton pregnancies (28 anterior and 19 posterior). Twenty-six of these subjects were imaged twice within the same session. Dice overlap and surface distance were used to quantify the automated segmentation accuracy compared to expert manual segmentations. The mean placental volume measurements obtained by our method and VOCAL (virtual organ computer-aided analysis), a leading commercial semiautomated method, were compared to the manual reference set. The test–retest reliability was also assessed. Results: The overlap between our automated segmentation and manual (mean Dice: 0.824 ± 0.061, median: 0.831) was within the range reported by other methods requiring extensive manual input. The average surface distance was 1.66 ± 0.96 mm. The correlation coefficient between test–retest volumes was r = 0.88, and the intraclass correlation was ICC ( 1 ) = 0.86. Conclusions: MALF is a promising method that can allow accurate and reliable segmentation of the placenta with minimal user interaction. Further refinement of this technique may allow for placental biometry to be incorporated into clinical pregnancy surveillance.
Journal of cardiac surgery: Issue Information Page

A. Mehdiani, Alexander Albert, Hannan Dalyanoglu, D. Scheiber, Ralf Westenfeld, H. Aubin, A. Lichtenberg, P. Akhyari, M. Levack, G. Mecozzi, Jayant S. Jainandunsing, W. Bouma, A. Jassar, and Paul Yushkevich

Journal of Cardiac Surgery, Jan 2020

DOI
NEW RELIGIOUS MOVEMENTS AND METHODS OF PROTECTION AGAINST THEIR CRIMINAL ACTIVITIES

Paul Yushkevich

Jan 2020

DOI

2019

Quantitative Three-Dimensional Echocardiographic Analysis of the Bicuspid Aortic Valve and Aortic Root: a Single Modality Approach

M. Levack, G. Mecozzi, Jayant S. Jainandunsing, W. Bouma, A. Jassar, A. Pouch, Paul Yushkevich, M. Mariani, B. Jackson, J. Gorman, and R. Gorman

Journal of cardiac surgery, Dec 2019

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Patients with bicuspid aortic valves (BAV) are heterogeneous with regard to patterns of root remodeling and valvular dysfunction. Two‐dimensional echocardiography is the standard surveillance modality for patients with aortic valve dysfunction. However, ancillary computed tomography or magnetic resonance imaging is often necessary to characterize associated patterns of aortic root pathology. Conversely, the pairing of three‐dimensional (3D) echocardiography with novel quantitative modeling techniques allows for a single modality description of the entire root complex. We sought to determine 3D aortic valve and root geometry with this quantitative approach.
Quantitative three‐dimensional echocardiographic analysis of the bicuspid aortic valve and aortic root: A single modality approach

M. Levack, G. Mecozzi, Jayant S Jainandunsing, W. Bouma, A. Jassar, A. Pouch, Paul Yushkevich, M. Mariani, B. Jackson, J. Gorman, and R. Gorman

Journal of Cardiac Surgery, Dec 2019

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Patients with bicuspid aortic valves (BAV) are heterogeneous with regard to patterns of root remodeling and valvular dysfunction. Two‐dimensional echocardiography is the standard surveillance modality for patients with aortic valve dysfunction. However, ancillary computed tomography or magnetic resonance imaging is often necessary to characterize associated patterns of aortic root pathology. Conversely, the pairing of three‐dimensional (3D) echocardiography with novel quantitative modeling techniques allows for a single modality description of the entire root complex. We sought to determine 3D aortic valve and root geometry with this quantitative approach.
Characterization of hippocampal subfields using ex vivo MRI and histology data: lessons for in vivo segmentation

R. Flores, D. Berron, Song-Lin Ding, R. Ittyerah, J. Pluta, Long Xie, D. Adler, J. Robinson, T. Schuck, J. Trojanowski, M. Grossman, Wei-Xia Liu, S. Pickup, Sandhitsu R. Das, D. Wolk, Paul Yushkevich, and L. Wisse

Hippocampus, Nov 2019

Cited by 49

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Hippocampal subfield segmentation on in vivo MRI is of great interest for cognition, aging, and disease research. Extant subfield segmentation protocols have been based on neuroanatomical references, but these references often give limited information on anatomical variability. Moreover, there is generally a mismatch between the orientation of the histological sections and the often anisotropic coronal sections on in vivo MRI. To address these issues, we provide a detailed description of hippocampal anatomy using a postmortem dataset containing nine specimens of subjects with and without dementia, which underwent a 9.4 T MRI and histological processing. Postmortem MRI matched the typical orientation of in vivo images and segmentations were generated in MRI space, based on the registered annotated histological sections. We focus on the following topics: the order of appearance of subfields, the location of subfields relative to macroanatomical features, the location of subfields in the uncus and tail and the composition of the dark band, a hypointense layer visible in T2‐weighted MRI. Our main findings are that: (a) there is a consistent order of appearance of subfields in the hippocampal head, (b) the composition of subfields is not consistent in the anterior uncus, but more consistent in the posterior uncus, (c) the dark band consists only of the CA‐stratum lacunosum moleculare, not the strata moleculare of the dentate gyrus, (d) the subiculum/CA1 border is located at the middle of the width of the hippocampus in the body in coronal plane, but moves in a medial direction from anterior to posterior, and (e) the variable location and composition of subfields in the hippocampal tail can be brought back to a body‐like appearance when reslicing the MRI scan following the curvature of the tail. Our findings and this publicly available dataset will hopefully improve anatomical accuracy of future hippocampal subfield segmentation protocols.
Virtual resection predicts surgical outcome for drug-resistant epilepsy.

Lohith G. Kini, John M. Bernabei, Fadi Mikhail, P. Hadar, Preya Shah, A. Khambhati, Kelly F. Oechsel, Ryan Archer, Jacqueline Boccanfuso, E. Conrad, R. Shinohara, J. Stein, Sandhitsu R. Das, A. Kheder, Timothy H. Lucas, K. Davis, D. Bassett, and B. Litt

Brain : a journal of neurology, Oct 2019

Cited by 124

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Patients with drug-resistant epilepsy often require surgery to become seizure-free. While laser ablation and implantable stimulation devices have lowered the morbidity of these procedures, seizure-free rates have not dramatically improved, particularly for patients without focal lesions. This is in part because it is often unclear where to intervene in these cases. To address this clinical need, several research groups have published methods to map epileptic networks but applying them to improve patient care remains a challenge. In this study we advance clinical translation of these methods by: (i) presenting and sharing a robust pipeline to rigorously quantify the boundaries of the resection zone and determining which intracranial EEG electrodes lie within it; (ii) validating a brain network model on a retrospective cohort of 28 patients with drug-resistant epilepsy implanted with intracranial electrodes prior to surgical resection; and (iii) sharing all neuroimaging, annotated electrophysiology, and clinical metadata to facilitate future collaboration. Our network methods accurately forecast whether patients are likely to benefit from surgical intervention based on synchronizability of intracranial EEG (area under the receiver operating characteristic curve of 0.89) and provide novel information that traditional electrographic features do not. We further report that removing synchronizing brain regions is associated with improved clinical outcome, and postulate that sparing desynchronizing regions may further be beneficial. Our findings suggest that data-driven network-based methods can identify patients likely to benefit from resective or ablative therapy, and perhaps prevent invasive interventions in those unlikely to do so.
The Cancer Imaging Phenomics Toolkit (CaPTk): Technical Overview

Sarthak Pati, Ashish Singh, Saima Rathore, A. Gastounioti, M. Bergman, Phuc Ngo, Min-Ha Sung, D. Bounias, James Minock, Grayson Murphy, Hong-Ming Li, Amita Bhattarai, Adam Wolf, Patmaa Sridaran, Ratheesh Kalarot, H. Akbari, Aristeidis Sotiras, Siddhesh P. Thakur, R. Verma, R. Shinohara, Paul Yushkevich, Yong Fan, D. Kontos, C. Davatzikos, and S. Bakas

Brainlesion : glioma, multiple sclerosis, stroke and traumatic brain injuries. BrainLes (Workshop), Oct 2019

Cited by 109

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The purpose of this manuscript is to provide an overview of the technical specifications and architecture of the Cancer imaging Phenomics Toolkit (CaPTk www.cbica.upenn.edu/captk), a cross-platform, open-source, easy-to-use, and extensible software platform for analyzing 2D and 3D images, currently focusing on radiographic scans of brain, breast, and lung cancer. The primary aim of this platform is to enable swift and efficient translation of cutting-edge academic research into clinically useful tools relating to clinical quantification, analysis, predictive modeling, decision-making, and reporting workflow. CaPTk builds upon established open-source software toolkits, such as the Insight Toolkit (ITK) and OpenCV, to bring together advanced computational functionality. This functionality describes specialized, as well as general-purpose, image analysis algorithms developed during active multi-disciplinary collaborative research studies to address real clinical requirements. The target audience of CaPTk consists of both computational scientists and clinical experts. For the former it provides i) an efficient image viewer offering the ability of integrating new algorithms, and ii) a library of readily-available clinically-relevant algorithms, allowing batch-processing of multiple subjects. For the latter it facilitates the use of complex algorithms for clinically-relevant studies through a user-friendly interface, eliminating the prerequisite of a substantial computational background. CaPTk’s long-term goal is to provide widely-used technology to make use of advanced quantitative imaging analytics in cancer prediction, diagnosis and prognosis, leading toward a better understanding of the biological mechanisms of cancer development.
The Cancer Imaging Phenomics Toolkit (CaPTk): Technical Overview.

Sarthak Pati, Ashish Singh, Saima Rathore, A. Gastounioti, M. Bergman, Phuc Ngo, S. Ha, Dimitrios Bounias, James Minock, Grayson Murphy, Hongming Li, Amita Bhattarai, Adam Wolf, Patmaa Sridaran, Ratheesh Kalarot, H. Akbari, Aristeidis Sotiras, Siddhesh P. Thakur, R. Verma, R. Shinohara, Paul Yushkevich, Yong Fan, D. Kontos, C. Davatzikos, and S. Bakas

Brainlesion : glioma, multiple sclerosis, stroke and traumatic brain injuries. BrainLes, Oct 2019

Cited by 97

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Improving Multi-atlas Segmentation by Convolutional Neural Network Based Patch Error Estimation

Long Xie, Jiancong Wang, M. Dong, D. Wolk, and Paul Yushkevich

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Oct 2019

Cited by 10

DOI
In-vivo Measures of Tau Burden are Associated with Atrophy in Early Braak Stage Medial Temporal Lobe Regions in Amyloid Negative Individuals

Sandhitsu R. Das, Long Xie, L. Wisse, Nicolas Vergnet, R. Ittyerah, Salena Cui, Paul Yushkevich, and D. Wolk

Alzheimer’s & dementia : the journal of the Alzheimer’s Association, Sep 2019

Cited by 43

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It is unclear the degree to which tau pathology in the medial temporal lobe (MTL) measured by 18F‐flortaucipir positron emission tomography relates to MTL subregional atrophy and whether this relationship differs between amyloid‐β–positive and amyloid‐β–negative individuals.
In vivo measures of tau burden are associated with atrophy in early Braak stage medial temporal lobe regions in amyloid‐negative individuals

Sandhitsu R. Das, L. Xie, L. Wisse, Nicolas Vergnet, R. Ittyerah, Salena Cui, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Sep 2019

Cited by 40

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It is unclear the degree to which tau pathology in the medial temporal lobe (MTL) measured by 18F‐flortaucipir positron emission tomography relates to MTL subregional atrophy and whether this relationship differs between amyloid‐β–positive and amyloid‐β–negative individuals.
Longitudinal Changes in Hippocampal Subfield Volume Associated with Collegiate Football

S. Parivash, Maged Goubran, Brian D. Mills, P. Rezaii, C. Thaler, D. Wolman, W. Bian, L. Mitchell, B. Boldt, David Douglas, Eugene W. Wilson, Jay Choi, Long Xie, Paul Yushkevich, P. DiGiacomo, Jitsupa Wongsripuemtet, M. Parekh, J. Fiehler, H. Do, Jaime Lopez, J. Rosenberg, David B. Camarillo, G. Grant, M. Wintermark, and M. Zeineh

Journal of Neurotrauma, Sep 2019

Cited by 25

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Collegiate football athletes are subject to repeated traumatic brain injuriesthat may cause brain injury. The hippocampus is composed of several distinct subfields with possible differential susceptibility to injury. The aim of this study is to determine whether there are longitudinal changes in hippocampal subfield volume in collegiate football. A prospective cohort study was conducted over a 5-year period tracking 63 football and 34 volleyball male collegiate athletes. Athletes underwent high-resolution structural magnetic resonance imaging, and automated segmentation provided hippocampal subfield volumes. At baseline, football (n = 59) athletes demonstrated a smaller subiculum volume than volleyball (n = 32) athletes (−67.77 mm3; p = 0.012). A regression analysis performed within football athletes similarly demonstrated a smaller subiculum volume among those at increased concussion risk based on athlete position (p = 0.001). For the longitudinal analysis, a linear mixed-effects model assessed the interaction between sport and time, revealing a significant decrease in cornu ammonis area 1 (CA1) volume in football (n = 36) athletes without an in-study concussion compared to volleyball (n = 23) athletes (volume difference per year = −35.22 mm3; p = 0.005). This decrease in CA1 volume over time was significant when football athletes were examined in isolation from volleyball athletes (p = 0.011). Thus, this prospective, longitudinal study showed a decrease in CA1 volume over time in football athletes, in addition to baseline differences that were identified in the downstream subiculum. Hippocampal changes may be important to study in high-contact sports.
The effects of direct brain stimulation in humans depend on frequency, amplitude, and white-matter proximity

U. Mohan, Andrew J. Watrous, Jonathan F. Miller, B. Lega, M. Sperling, G. Worrell, R. Gross, K. Zaghloul, B. Jobst, K. Davis, S. Sheth, J. Stein, Sandhitsu R. Das, R. Gorniak, Paul A. Wanda, D. Rizzuto, M. Kahana, and J. Jacobs

Brain stimulation, Aug 2019

Cited by 104

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Researchers have used direct electrical brain stimulation to treat a range of neurological and psychiatric disorders. However, for brain stimulation to be maximally effective, clinicians and researchers should optimize stimulation parameters according to desired outcomes. To examine how different kinds of stimulation affect human brain activity, we compared the changes in neuronal activity that resulted from stimulation at a range of frequencies, amplitudes, and locations with direct human brain recordings. We recorded human brain activity directly with electrodes that were implanted in widespread regions across 106 neurosurgical epilepsy patients while systematically stimulating across a range of parameters and locations. Overall, stimulation most often had an inhibitory effect on neuronal activity, consistent with earlier work. When stimulation excited neuronal activity, it most often occurred from high-frequency stimulation. These effects were modulated by the location of the stimulating electrode, with stimulation sites near white matter more likely to cause excitation and sites near gray matter more likely to inhibit neuronal activity. By characterizing how different stimulation parameters produced specific neuronal activity patterns on a large scale, our results help guide clinicians and researchers when designing stimulation protocols to cause precisely targeted changes in human brain activity.
P1‐349: ADVANCING CLINICAL AND BIOMARKER RESEARCH IN AD: THE LEAD STUDY

Liana G. Apostolova, L. Iaccarino, Jessica A. Collins, Paul Aisen, Bret J. Borowski, A. Eloyan, A. Fagan, T. Foroud, C. Gatsonis, C. Jack, J. Kramer, R. Koeppe, Andrew J. Saykin, A. Toga, P. Vemuri, Gregory S. Day, N. Graff-Radford, Lawrence S. Honig, David T. Jones, Joseph C. Masdeu, Mario F. Mendez, C. Onyike, E. Rogalski, S. Salloway, D. Wolk, Thomas S. Wingo, G. Rabinovici, B. Dickerson, and Maria C. Carrillo

Alzheimer’s & Dementia, Jul 2019

Cited by 1

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discrimination. Visualization of learning process by guided Grad-CAM revealed that CIS became more focused by the CNN as the training progressed. DLB/AD score was signiﬁcantly associated with three core-features of DLB. Conclusions: Deep learning-based imaging classiﬁcation was useful not only for objective and accurate differentiation of DLB from AD but also for predicting clinical features of DLB. The CIS was identiﬁed as a speciﬁc feature during DLB classiﬁcation. The visualization of speciﬁc features and learning process could have important implications for the potential of deep learning to discover new imaging features.
IC‐P‐043: CONTRIBUTION OF TAU, TDP‐43, β‐AMYLOID AND α‐SYNUCLEIN TO MEDIAL TEMPORAL LOBE ATROPHY

R. Flores, L. Wisse, Sandhitsu R. Das, Long Xie, C. McMillan, J. Trojanowski, M. Grossman, Edward B. Lee, D. Irwin, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2019

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Background: The Risk Reduction for Alzheimer’s Disease (rrAD) trial is designed to assess the effects of aerobic exercise and intensive vascular risk reduction on cognitive performance in older adults who are at high risk for AD. About 640 normal adults age 60 to 85 years with family history of dementia or subjective memory complaints, hypertension, and a sedentary life style are being enrolled at four clinical sites. BrainMRI scans are obtained at baseline and 24 months, and are being processed centrally at the trial imaging coordinating center (ICC). We aims to share our experience from our neuroimaging core. Methods: Data Acquisition: 3T MRI scanners (GE, Siemens and Philips) are used. The sequences used include: 3D T1-weighted high-resolution MPRAGE to quantify brain morphometry; T2 FLAIR tomeasurewhite matter lesions; DTI to assess brain white matter microstructural integrity and structural connectivity; resting-state fMRI to assess neural functional connectivity; 3D pCASL to assess regional brain perfusion; T2*weighted imaging to detect hemorrhage; and phase-contrast imaging to measure blood flow into the brain. Quality Control: All images are transferred via the web-based Globus software (https://www.globus.org/) in DICOM format to the ICC within 24 hours after acquisition. The ICC team completes quality control (QC) within three business days. The QC ensures subject anonymity, accuracy and image quality (imaging distortion, artifacts and signal-to-noise ratio) for all scans. The data collection sites are notified immediately if any severe image artifacts and clinically significant lesions are found. Recommendations are provided if a participant should be rescanned and/or if phantom QC scans should be performed (Fig. 1). Data Analysis: All imaging results are aligned to 3D MPRAGE images. MPRAGE images are segmented and standardized to MNI305 space using FreeSurfer. To reduce the impact of atrophy and distortion in older brains for group analyses, imaging results are standardized to MNI space via the FreeSurfer pipeline (Fig. 2). Results: With vigorous subject recruitment, data acquisition, QC and data analysis procedures, we have acquired over 350 high-qualityMRI datasets by January 2019. Scanner hardware issues have been timely detected and resolved to reduce scan delay. Conclusions: Successful procedures of a multicenter neuroimaging trial are demonstrated. IC-P-042 DIFFERENTIATING TAUOPATHIES WITH A NOVEL DIFFUSION TENSOR IMAGING METHOD TO INVESTIGATE CORTICAL ARCHITECTURE
P1‐441: CONTRIBUTION OF TAU, TDP‐43, β‐AMYLOID AND α‐SYNUCLEIN TO MEDIAL TEMPORAL LOBE ATROPHY

R. Flores, L. Wisse, Sandhitsu R. Das, Long Xie, C. McMillan, J. Trojanowski, M. Grossman, Edward B. Lee, D. Irwin, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2019

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Robin de Flores, Laura Wisse, Sandhitsu R. Das, Long Xie, Corey T. McMillan, John Q. Trojanowski, Murray Grossman, Eddie B. Lee, David Irwin, Paul A. Yushkevich, David A. Wolk, Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA; Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA, USA; Penn FTD Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA; Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA, USA; Penn Memory Center, University of Pennsylvania, Philadelphia, PA, USA. Contact e-mail: robindeflores@gmail.com
P2‐462: SEMANTIC RICHNESS IN PEOPLE WITH PRECLINICAL ALZHEIMER’S DISEASE

Nathaniel Klooster, Arun Pilania, L. Wisse, Sandhitsu R. Das, Long Xie, D. Wolk, and A. Chatterjee

Alzheimer’s & Dementia, Jul 2019

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Although there have not been published norms for older adults of this test so far, it has been found that this test is more sensitive than visual naming tests in mixed etiology dementia. The aim of this study was to analyze the performance in the ANT of older adults and generate normative data. Methods: Cross-sectional descriptive-observational study. We evaluated 73 adults (57 women, age range: 55-93, mean age: 68.41 SD: 9.09), without concomitant pathologies that potentially affect cognition. Spanish ANT adaptation was administered. SPSS program was used and Pearson correlations, ANOVA, means and standard deviations were calculated to generate normative data. Results: There were no differences in performance according to gender. A moderate negative significant correlation with age was found (r -.511, p< .001). The sample was divided into five age groups 50-59 years (M 43.94 SD 3.57), 60-69 years (M 43.94 SD 3.56), 70-79 years (M 39.87 SD 4.49), 80-89 years (M 39.25 SD 2.55) and 90-99 years (M 39.00 SD 2.83). A low positive significant correlation was found with education (r .397, p1⁄4 .001). A later analysis revealed that this correlation only occurs in the group of 50-59 years and 70-79 years. Conclusions: In the present study, the performance in the ANT of older adults was analyzed and normative data were generated. It was observed that age and education influence the performance of this test. Future studies should examine these results by expanding the sample.
Neural and behavioral correlates of declarative memory are associated with temporal discounting in older adults

K. Lempert, D. Mechanic-Hamilton, Long Xie, L. Wisse, R. Flores, Jieqiong Wang, Sandhitsu R. Das, Paul Yushkevich, D. Wolk, and Joseph W. Kable

bioRxiv, Jul 2019

Cited by 5

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When facing intertemporal choices, or decisions involving trade-offs between smaller, sooner and larger, delayed rewards, people tend to discount the value of future rewards. There are substantial individual differences in this tendency toward temporal discounting, however. The neurocognitive mechanisms underlying these individual differences remain unclear. One possibility is that individual differences in declarative memory ability underlie individual differences in temporal discounting. Here we tested this hypothesis in older adults (both cognitively normal and with mild cognitive impairment), given that declarative memory declines with age, at rates that vary across individuals. We related temporal discounting to performance on neuropsychological measures of declarative memory, as well as to structural measures of medial temporal lobe regions that are critical for memory. Performance on episodic and semantic memory retrieval tasks was associated with temporal discounting, such that people with better declarative memory discounted delayed rewards less. This relationship held even when controlling for executive function abilities that might influence memory retrieval. Underlining the specificity of this association, performance on measures of executive function (Trail Making Test, Digit Span Backwards, lexical fluency) was unrelated to temporal discounting, and declarative memory ability was unrelated to risk preferences. Finally, cortical thickness in the entorhinal cortex was associated with reduced temporal discounting, with declarative memory ability partially mediating this association. These findings suggest that individual differences in temporal discounting are primarily driven by memory ability, and not executive function, and that a decline in medial temporal lobe structural integrity with aging may impact time preferences. Significance statement Despite the large body of literature supporting the role of both declarative memory and executive function in choices between immediate and delayed rewards (intertemporal choices), no study has examined which of these neurocognitive mechanisms underlies individual differences in the tendency to discount future rewards (temporal discounting). This has been challenging given the limited variability in, and high correlation between, these abilities in young adults. Here we show that older adults with better declarative memory discount delayed rewards less, even when controlling for executive function. Moreover, cortical thickness in entorhinal cortex, a region integral to memory processes, is also associated with temporal discounting. This knowledge will aid in the development of interventions to increase patience, especially as memory declines with aging.
P4‐593: EARLY PREDICTION OF COGNITIVE DECLINE BASED ON BRAIN MRI IMAGES USING A DEEP LEARNING SURVIVAL ANALYSIS MODEL

Hong-Ming Li, D. Wolk, and Yong Fan

Alzheimer’s & Dementia, Jul 2019

Cited by 2

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: Early recognition of cognitive decline could promote timely interventions to slow or halt dementia progression. To achieve this goal
P4-068: AMYLOID-POSITIVE COGNITIVE IMPAIRMENT IS LESS “ALZHEIMER’S-LIKE” IN THE ABSENCE OF TAU

Lauren McCollum, Sandhitsu R. Das, Long Xie, Salena Cui, R. Flores, L. Wisse, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2019

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IC‐P‐143: RELATIVE SPARING OF MEDIAL TEMPORAL SUBREGION VOLUMES IN NON‐AMNESTIC ALZHEIMER’S DISEASE

J. Phillips, Long Xie, L. Wisse, J. Gee, Paul Yushkevich, M. Grossman, and David J. Irwin

Alzheimer’s & Dementia, Jul 2019

Cited by 2

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IC-P-142 [C]MK-6884 PET TRACER FOR M4 MUSCARINIC CHOLINERGIC RECEPTORS IN ALZHEIMER’S DISEASE: COMPARISON WITH [F]FDG PET Belen Pascual, Paolo Zanotti-Fregonara, Meixiang Yu, Quentin Funk, Arbones Victoria, Yuchuan Wang, Wenping Li, Amy Cheng, Matt Anderson, Eric D. Hostetler, Anthony S. Basile, Joseph C.Masdeu, Houston Methodist Neurological Institute, Houston, TX, USA; Merck & Co., Inc., Kenilworth, NJ, USA. Contact e-mail: bpascual@ houstonmethodist.org
Characterizing the role of the structural connectome in seizure dynamics.

Preya Shah, Arian Ashourvan, Fadi Mikhail, A. Pines, Lohith G. Kini, Kelly F. Oechsel, Sandhitsu R. Das, J. Stein, R. Shinohara, D. Bassett, B. Litt, and K. Davis

Brain : a journal of neurology, Jul 2019

Cited by 78

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How does the human brain’s structural scaffold give rise to its intricate functional dynamics? This is a central question in translational neuroscience that is particularly relevant to epilepsy, a disorder affecting over 50 million subjects worldwide. Treatment for medication-resistant focal epilepsy is often structural-through surgery or laser ablation-but structural targets, particularly in patients without clear lesions, are largely based on functional mapping via intracranial EEG. Unfortunately, the relationship between structural and functional connectivity in the seizing brain is poorly understood. In this study, we quantify structure-function coupling, specifically between white matter connections and intracranial EEG, across pre-ictal and ictal periods in 45 seizures from nine patients with unilateral drug-resistant focal epilepsy. We use high angular resolution diffusion imaging (HARDI) tractography to construct structural connectivity networks and correlate these networks with time-varying broadband and frequency-specific functional networks derived from coregistered intracranial EEG. Across all frequency bands, we find significant increases in structure-function coupling from pre-ictal to ictal periods. We demonstrate that short-range structural connections are primarily responsible for this increase in coupling. Finally, we find that spatiotemporal patterns of structure-function coupling are highly stereotyped for each patient. These results suggest that seizures harness the underlying structural connectome as they propagate. Mapping the relationship between structural and functional connectivity in epilepsy may inform new therapies to halt seizure spread, and pave the way for targeted patient-specific interventions.
Barnes-Hut Approximation for Point SetGeodesic Shooting

Jiancong Wang, Long Xie, Paul Yushkevich, and J. Gee

ArXiv, Jul 2019

Abs arXiv

Geodesic shooting has been successfully applied to diffeo-morphic registration of point sets. Exact computation of the geodesicshooting between point sets, however, requiresO(N2) calculations each time step on the number of points in the point set. We proposean approximation approach based on the Barnes-Hut algorithm to speedup point set geodesic shooting. This approximation can reduce the al-gorithm complexity toO(N b+N logN). The evaluation of the proposedmethod in both simulated images and the medial temporal lobe thick-ness analysis demonstrates a comparable accuracy to the exact point set geodesic shooting while offering up to 3-fold speed up. This improvementopens up a range of clinical research studies and practical problems towhich the method can be effectively applied.
IC‐04‐05: CROSS‐SECTIONAL AND LONGITUDINAL MEDIAL TEMPORAL LOBE SUBREGIONAL ATROPHY IN SUSPECTED NON‐ALZHEIMER’S PATHOPHYSIOLOGY

L. Wisse, Long Xie, Sandhitsu R. Das, Flores Robin, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2019

Abs DOI PDF

not available.
O2-08-05: PATHOLOGICAL DRIVERS OF NEURODEGENERATION IN SUSPECTED NON-ALZHEIMER’S PATHOPHYSIOLOGY

L. Wisse, Flores Robin, Sandhitsu R. Das, C. McMillan, J. Trojanowski, M. Grossman, Edward B. Lee, D. Irwin, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2019

DOI
P2‐354: MEDIAL TEMPORAL LOBE CORRELATES OF ANOSAGNOSIA IN PRODROMAL AD

L. Wisse, T. Glenn, Sandhitsu R. Das, Flores Robin, Long Xie, Paul Yushkevich, D. Wolk, and Alzheimer’s Disease Neuroimaging Initiative

Alzheimer’s & Dementia, Jul 2019

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subregional Background: Animal studies have provided strong evidence for the propagation of neuroﬁbrillary tau tangles through connected neurons. Here, we test the theory of tau spreading through communi-cating neurons in humans by placing a seed in the entorhinal cortex and allowing it to diffuse naturally through the human connectome, and comparing the predicted pattern of tau to observed regional tau load in living humans. Methods: AV1451-PET scans from 175 cognitively intact individuals (69 amyloid-positive), 57 amyloid-positive individuals with
P4‐591: THE DEVELOPMENT OF A HARMONIZED SEGMENTATION PROTOCOL FOR HIPPOCAMPAL SUBFIELDS: AN UPDATE

L. Wisse, D. Berron, R. Olsen, Ana M. Daugherty, K. Amunts, Jean C. Augustinack, A. Bakker, Andrew R. Bender, M. Boccardi, M. Bocchetta, M. Chakravarty, G. Chételat, R. Flores, Jordan DeKraker, Song-Lin Ding, R. Insausti, O. Kedo, S. Mueller, N. Ofen, D. Palombo, N. Raz, Craig E. L. Stark, Lei Wang, Paul Yushkevich, Qi-Jing Yu, Valerie A. Carr, and R. La Joie

Alzheimer’s & Dementia, Jul 2019

Abs DOI

[Sudre 2015], and further normalized to global or regional brain volumes, respectively. Global and regional WMH loads were log-transformed due to right-skewed distributions, and then z-transformed. WMH loads were compared between groups using analysis of covariance (ANCOVA), correcting for age and scanners. Linear regression was performed to examine associations between global or regional WMH loads, age and vascular risk factors, assessed with the simple Framingham Risk Score (FRS-CVD). Results: Global (p1⁄40.012), parietal DWMH (p1⁄40.015), parietal PWMH (p1⁄40.019), occipital DWMH (p1⁄40.004) and occipital PWMH (p1⁄40.001) loads were increased in SCD-Ab+ compared to asymptomatic cognitively normal Abcontrols (NC-Ab-). Only occipital DWMH load was significantly higher in MCI-Ab+ compared to MCI-Ab(p1⁄40.004). Only frontal PWMH and DWMH loads were positively associated with FRSCVD without the age component (FRS-CVDwoa), after controlling for age. Conclusions: Global, occipital and parietal WMH loads are increased in SCD-Ab+, suggesting that WMH may be an early biomarker in AD. Occipital DWMH seem to be more specific to AD, with significantly higher load also in MCI-Ab+ compared to MCI-Ab-, while only frontal WMH were associated with vascular risk factors, after correcting for age. esday, July 17, 2019 S1549
IC‐02‐04: NOVEL MEASURES OF LONGITUDINAL CHANGE IN MEDIAL TEMPORAL LOBE SUBREGIONS DISCRIMINATE PRECLINICAL ALZHEIMER’S DISEASE PATIENTS FROM AMYLOID‐β NEGATIVE CONTROLS

Long Xie, L. Wisse, Sandhitsu R. Das, R. Ittyerah, R. Flores, Paul Yushkevich, and David A. Wolk

Alzheimer’s & Dementia, Jul 2019

Abs DOI

not available. SATURDAY, JULY 13, 2019 ALZHEIMER’S IMAGING CONSORTIUM PODIUM PRESENTATIONS IC-04 IMAGING NON-ALZHEIMER’S PATHOLOGIES IC-04-01 THE SEARCH FOR PATHOLOGICALLY VALID IMAGING BIOMARKERS: AD PATHOLOGY COMES NOTALONE Stefan J. Teipel, Michel J. Grothe, Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany; German Center for Neurodegenerative Diseases (DZNE) – Rostock/Greifswald, Rostock, Germany. Contact e-mail: stefan.teipel@med.uni-rostock.de
IC‐P‐134: NOVEL MEASURES OF LONGITUDINAL CHANGE IN MEDIAL TEMPORAL LOBE SUBREGIONS DISCRIMINATE PRECLINICAL ALZHEIMER’S DISEASE PATIENTS FROM AMYLOID‐β NEGATIVE CONTROLS

Long Xie, L. Wisse, Sandhitsu R. Das, R. Ittyerah, Flores Robin, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2019

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IC-P-134 NOVEL MEASURES OF LONGITUDINAL CHANGE IN MEDIALTEMPORAL LOBE SUBREGIONS DISCRIMINATE PRECLINICAL ALZHEIMER’S DISEASE PATIENTS FROM AMYLOID-b NEGATIVE CONTROLS Long Xie, Laura Wisse, Sandhitsu R. Das, Ranjit Ittyerah, de Flores Robin, Paul A. Yushkevich, David A. Wolk, and Alzheimer’s Disease Neuroimaging Initiative, Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA, USA; University of Pennsylvania, Philadelphia, PA, USA. Contact e-mail: darren.xie0625@ gmail.com
P1‐374: NOVEL MEASURES OF LONGITUDINAL CHANGE IN MEDIAL TEMPORAL LOBE SUBREGIONS DISCRIMINATE PRECLINICAL ALZHEIMER’S DISEASE PATIENTS FROM AMYLOID‐β NEGATIVE CONTROLS

Long Xie, L. Wisse, Sandhitsu R. Das, R. Ittyerah, R. Flores, Paul Yushkevich, and David A. Wolk

Alzheimer’s & Dementia, Jul 2019

Cited by 1

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cortices (P<0.001). The significant cortical thinning on the right hemisphere of SD group was found in inferior-parietal cortex and the banks of superior temporal sulcus (P<0.01). Conclusions: We demonstrated a diffused cortical thinning pattern in SD group compared to age-matchedAAMI group. The significant cortical thinning in SD group were profound on the left hemisphere especially in the temporal lobe and less profound on the left hemisphere.
P1‐372: THE DIFFERENCE OF CORTICAL THICKNESS BETWEEN SEMANTIC DEMENTIA PATIENTS AND AGE ASSOCIATED MILD COGNITIVE IMPAIRMENT SUBJECTS

Paul Yushkevich

Alzheimer’s & Dementia, Jul 2019

Abs DOI

degree of accuracy combining structural images with SVM model which may be of potential use in the clinical diagnosis. Our study may also provide information to reveal underlying mechanisms of cognitive impairment in WMLs. References: 1. Yu, D., et al., Soluble Epoxide Hydrolase-Derived Linoleic Acid Oxylipins in Serum Are Associated with Periventricular White Matter Hyperintensities and VascularCognitive Impairment. TranslStrokeRes, 2018. 2.Brickman, A.M., et al., Reconsidering harbingers of dementia: progression of parietal lobe white matter hyperintensities predicts Alzheimer’s disease incidence. Neurobiol Aging, 2015. 36(1): p. 27-32.
Progress update from the hippocampal subfields group

R. Olsen, Valerie A. Carr, Ana M. Daugherty, R. La Joie, R. Amaral, K. Amunts, J. Augustinack, A. Bakker, Andrew R. Bender, D. Berron, M. Boccardi, M. Bocchetta, A. Burggren, M. Chakravarty, G. Chételat, R. Flores, Jordan DeKraker, Song-Lin Ding, M. Geerlings, Yushan Huang, R. Insausti, E. G. Johnson, P. Kanel, O. Kedo, K. Kennedy, A. Keresztes, Joshua K. Lee, U. Lindenberger, S. Mueller, E. Mulligan, N. Ofen, D. Palombo, Lorenzo Pasquini, J. Pluta, N. Raz, K. Rodrigue, M. Schlichting, Yee Lee Shing, C. Stark, T. Steve, N. Suthana, Lei Wang, M. Werkle-Bergner, Paul Yushkevich, Qijing Yu, and L. Wisse

Alzheimer’s & Dementia : Diagnosis, Assessment & Disease Monitoring, Jun 2019

Cited by 73

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Heterogeneity of segmentation protocols for medial temporal lobe regions and hippocampal subfields on in vivo magnetic resonance imaging hinders the ability to integrate findings across studies. We aim to develop a harmonized protocol based on expert consensus and histological evidence.
PC234. Automated Image Analysis to Determine Local Wall Strain of Abdominal Aortic Aneurysms

A. Vrudhula, A. H. Aly, Paul Yushkevich, A. Pouch, Eric K. Shang, R. Gorman, J. Gorman, and B. Jackson

Journal of Vascular Surgery, Jun 2019

DOI PDF
Cerebrospinal Fluid AD Biomarkers and Regional [18F]-Flortaucipir Uptake in Lewy Body Disorders (S10.009)

David Coughlin, Jeffrey Phillips, Emily Roll, David Wolk, Sandhitsu R. Das, I. Nasrallah, S. Vaishnavi, A. Siderowf, Daniel Weintraub, Leslie A. Shaw, John Q. Trojanowski, Murray Grossman, David J. Irwin, and C. McMillan

Neurology, Apr 2019

Cited by 1

DOI
18F-AV-1451 Tau Tracer Uptake Correlates with Medial Temporal Lobe Subregional Atrophy in Amyloid Negative Individuals (P5.1-012)

Sandhitsu R. Das, Long Xie, L. Wisse, R. Ittyerah, Paul Yushkevich, and D. Wolk

Neurology, Apr 2019

DOI
Hippocampal tau pathology burden in Lewy body disorders (P1.1-014)

R. Ittyerah, David Coughlin, Jeffrey Phillips, Simon Miller, Edward B. Lee, John Q. Trojanowski, Daniel Weintraub, A. Siderowf, John E. Duda, H. Hurtig, David Wolk, Paul Yushkevich, Murray Grossman, and David J. Irwin

Neurology, Apr 2019

DOI
Convergent Evidence for a Longevity Genetic Locus Associated with Tau Load in PART (S34.007)

K. Jefferson-George, David Wolk, Edward B. Lee, Sandhitsu R. Das, L. Wisse, P. De Jager, Julie A. Schneider, David Bennett, and C. McMillan

Neurology, Apr 2019

DOI
Cognitive Profiles in Amyloid-Positive Mild Cognitive Impairment and Alzheimer’s Disease with and without Tau (P2.1-030)

Lauren McCollum, L. Wisse, Sandhitsu R. Das, R. Flores, Paul Yushkevich, and D. Wolk

Neurology, Apr 2019

Abs DOI

Objective: To determine differences in cognitive profiles of amyloid-positive individuals (A+) with mild cognitive impairment (MCI) and Alzheimer’s Disease (AD) with and without concomitant pathologic tau (T+/T−). Background: A major source of heterogeneity in AD is mixed pathology (e.g. vascular with AD pathology), posing challenges for research and clinical care. The recently developed ATN framework for AD pathology classifies individuals based on amyloid (A), tau (T), and neurodegeneration (N) status. Tau pathology is directly linked to neurodegeneration and cognitive decline in AD. Thus, cognitive impairment in setting of amyloid without tau suggests an alternate driver of neuronal injury. Design/Methods: Data from ADNI was utilized. Inclusion criteria were amyloid positivity (based on composite SUVR of 1.11 with florbetapir PET) and diagnosis of MCI or AD. A tau cut-off of 1.22 SUVR in bilateral extrahippocampal medial temporal lobe using the novel tau PET tracer AV-1451 was derived from amyloid-negative controls. A+T− and A+T+ groups were compared. Results: 43 amyloid-positive individuals with MCI or AD met inclusion criteria: 13 A+T− and 30 A+T+. The A+T− group was older (75.8 vs 69.9 years, p=0.026), had higher MMSE (27.2 vs. 24.2, p=0.044), and better scores on verbal memory recall (AVTOT6 5.31 vs 2.70, p=0.024). However, the A+T− group performed worse on Trails B, a measure of executive function/sequencing, but this did not reach significance (145.5 vs 131.1, p=0.628). Conclusions: Amongst a cohort of amyloid-positive MCI and AD, tau-negative individuals displayed clinical differences from counterparts with concomitant tau pathology, including somewhat better memory, but, if anything, relatively more affected executive function. The less AD-like pattern of the A+T− group may support the notion that symptomatic patients who are A+T− may have non-AD pathologies driving their clinical symptoms. Further investigation will examine the burden of white matter hyperintensities, a marker of vascular disease, and patterns of cortical thickness in these groups. Disclosure: Dr. McCollum has nothing to disclose. Dr. Wisse has nothing to disclose. Dr. Das has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Rancho Biosciences. Dr. de Flores has nothing to disclose. Dr. Yushkevich has nothing to disclose. Dr. Wolk has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Merck, Jannsen, Eli Lilly and GE.
Distribution of Hippocampal Tau Pathology in Amnestic and Non-Amnestic Forms of Alzheimer’s Disease (S34.009)

Simon Miller, Jeffrey Phillips, R. Ittyerah, Claire S. Peterson, Edward B. Lee, John Q. Trojanowski, David Wolk, Paul Yushkevich, Murray Grossman, and David J. Irwin

Neurology, Apr 2019

DOI
Medial temporal lobe subfield volumes are spared in non-amnestic Alzheimer’s disease (P5.7-001)

Jeffrey Phillips, L. Wisse, Paul Yushkevich, James C. Gee, Murray Grossman, and David J. Irwin

Neurology, Apr 2019

DOI
Facilitating Manual Segmentation of 3D Datasets Using Contour And Intensity Guided Interpolation

S. Ravikumar, L. Wisse, Yang Gao, G. Gerig, and Paul Yushkevich

In IEEE International Symposium on Biomedical Imaging, Apr 2019

Cited by 6

Abs DOI

Manual segmentation of anatomical structures in 3D imaging datasets is a highly time-consuming process. This process can be sped up using interslice interpolation techniques, which require only a small subset of slices to be manually segmented. In this paper, we propose a two-step interpolation approach that utilizes a “binary weighted averaging” algorithm to interpolate contour information, and the random forest framework to perform intensity-based label classification. We present the results of experiments performed in the context of hippocampal segmentations in ex vivo MRI scans. Compared to the random walker algorithm and morphology-based interpolation, the proposed method produces more accurate segmentations and smoother 3D reconstructions.
TAPAS: A Thresholding Approach for Probability Map Automatic Segmentation in Multiple Sclerosis

A. M. Valcarcel, J. Muschelli, D. Pham, M. Martin, Paul Yushkevich, Rachel B. Brandstadter, Kristina Patterson, M. Schindler, P. Calabresi, R. Bakshi, and R. Shinohara

NeuroImage : Clinical, Apr 2019

Cited by 8

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Total brain white matter lesion (WML) volume is the most widely established magnetic resonance imaging (MRI) outcome measure in studies of multiple sclerosis (MS). To estimate WML volume, there are a number of automatic segmentation methods, yet, manual delineation remains the gold standard approach. These approaches often yield a probability map to which a threshold is applied to create lesion segmentation masks. Unfortunately, few approaches systematically determine the threshold employed; many methods use a manually selected threshold, thus introducing human error and bias into the automated procedure. In this study, we propose and validate an automatic thresholding algorithm, Thresholding Approach for Probability Map Automatic Segmentation in Multiple Sclerosis (TAPAS), to obtain subject-specific threshold estimates for probability map automatic segmentation of T2-weighted (T2) hyperintense WMLs. Using multimodal MRI, the proposed method applies an automatic segmentation algorithm to obtain probability maps. We obtain the true subject-specific threshold that maximizes Sørensen-Dice Similarity Coefficient (DSC). Then the subject-specific thresholds are modeled on a naive estimate of volume using a general additive model. Applying this model, we predict a subject-specific threshold in data not used for training. We ran a Monte Carlo-resampled split-sample cross-validation (100 validation sets) using two data sets: the first obtained from the Johns Hopkins Hospital (JHH) on a Philips 3 Tesla (3T) scanner (n = 94) and a second collected at the Brigham and Women’s Hospital (BWH) using a Siemens 3T scanner (n = 40). By means of the proposed automated technique, in the JHH data, we found an average reduction in subject-level absolute error of 0.1 mL per one mL increase in manual volume. Using Bland-Altman analysis, we found that volumetric bias associated with group-level thresholding is mitigated when applying TAPAS. The BWH data showed similar absolute error estimates using group-level thresholding or TAPAS likely since Bland-Altman analyses indicate no systematic biases associated with group or TAPAS volume estimates. The current study presents the first validated fully automated method for subject-specific threshold prediction to segment brain lesions.
Accurate and Robust Alignment of Variable-stained Histologic Images Using a General-purpose Greedy Diffeomorphic Registration Tool

Ludovic Venet, Sarthak Pati, Paul Yushkevich, and S. Bakas

ArXiv, Apr 2019

Cited by 11

Abs arXiv

Variously stained histology slices are routinely used by pathologists to assess extracted tissue samples from various anatomical sites and determine the presence or extent of a disease. Evaluation of sequential slides is expected to enable a better understanding of the spatial arrangement and growth patterns of cells and vessels. In this paper we present a practical two-step approach based on diffeomorphic registration to align digitized sequential histopathology stained slides to each other, starting with an initial affine step followed by the estimation of a detailed deformation field.
Tau and neurodegeneration mismatch is a signature of polypathology in AD continuum (P1.1-011)

David Wolk, John Q. Trojanowski, David J. Irwin, Murray Grossman, Leslie A. Shaw, Jeffrey Phillips, Edward B. Lee, Sandhitsu R. Das, and C. McMillan

Neurology, Apr 2019

DOI
Automated segmentation of medial temporal lobe subregions on in vivo T1-weighted MRI in early stages of Alzheimer’s disease

Long Xie, L. Wisse, J. Pluta, R. Flores, Virgine Piskin, J. Manjón, Hong-Zhi Wang, Sandhitsu R. Das, Song-Lin Ding, D. Wolk, and Paul Yushkevich

Human brain mapping, Apr 2019

Cited by 117

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Medial temporal lobe (MTL) substructures are the earliest regions affected by neurofibrillary tangle pathology—and thus are promising biomarkers for Alzheimer’s disease (AD). However, automatic segmentation of the MTL using only T1‐weighted (T1w) magnetic resonance imaging (MRI) is challenging due to the large anatomical variability of the MTL cortex and the confound of the dura mater, which is commonly segmented as gray matter by state‐of‐the‐art algorithms because they have similar intensity in T1w MRI. To address these challenges, we developed a novel atlas set, consisting of 15 cognitively normal older adults and 14 patients with mild cognitive impairment with a label explicitly assigned to the dura, that can be used by the multiatlas automated pipeline (Automatic Segmentation of Hippocampal Subfields [ASHS‐T1]) for the segmentation of MTL subregions, including anterior/posterior hippocampus, entorhinal cortex (ERC), Brodmann areas (BA) 35 and 36, and parahippocampal cortex on T1w MRI. Cross‐validation experiments indicated good segmentation accuracy of ASHS‐T1 and that the dura can be reliably separated from the cortex (6.5% mislabeled as gray matter). Conversely, FreeSurfer segmented majority of the dura mater (62.4%) as gray matter and the degree of dura mislabeling decreased with increasing disease severity. To evaluate its clinical utility, we applied the pipeline to T1w images of 663 ADNI subjects and significant volume/thickness loss is observed in BA35, ERC, and posterior hippocampus in early prodromal AD and all subregions at later stages. As such, the publicly available new atlas and ASHS‐T1 could have important utility in the early diagnosis and monitoring of AD and enhancing brain‐behavior studies of these regions.
Automated segmentation of medial temporal lobe subregions on in vivo T1‐weighted MRI in early stages of Alzheimer’s disease

L. Xie, L. Wisse, J. Pluta, R. Flores, Virgine Piskin, J. Manjón, Hongzhi Wang, Sandhitsu R. Das, S. Ding, D. Wolk, and Paul Yushkevich

Human Brain Mapping, Apr 2019

Cited by 105

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Medial temporal lobe (MTL) substructures are the earliest regions affected by neurofibrillary tangle pathology—and thus are promising biomarkers for Alzheimer’s disease (AD). However, automatic segmentation of the MTL using only T1‐weighted (T1w) magnetic resonance imaging (MRI) is challenging due to the large anatomical variability of the MTL cortex and the confound of the dura mater, which is commonly segmented as gray matter by state‐of‐the‐art algorithms because they have similar intensity in T1w MRI. To address these challenges, we developed a novel atlas set, consisting of 15 cognitively normal older adults and 14 patients with mild cognitive impairment with a label explicitly assigned to the dura, that can be used by the multiatlas automated pipeline (Automatic Segmentation of Hippocampal Subfields [ASHS‐T1]) for the segmentation of MTL subregions, including anterior/posterior hippocampus, entorhinal cortex (ERC), Brodmann areas (BA) 35 and 36, and parahippocampal cortex on T1w MRI. Cross‐validation experiments indicated good segmentation accuracy of ASHS‐T1 and that the dura can be reliably separated from the cortex (6.5% mislabeled as gray matter). Conversely, FreeSurfer segmented majority of the dura mater (62.4%) as gray matter and the degree of dura mislabeling decreased with increasing disease severity. To evaluate its clinical utility, we applied the pipeline to T1w images of 663 ADNI subjects and significant volume/thickness loss is observed in BA35, ERC, and posterior hippocampus in early prodromal AD and all subregions at later stages. As such, the publicly available new atlas and ASHS‐T1 could have important utility in the early diagnosis and monitoring of AD and enhancing brain‐behavior studies of these regions.
Self- and Informant-Reported Subjective Memory Complaints: Association with Depression, Cognitive Impairment, and Decline (S13.006)

Leah Zuroff, Jessica Bove, D. Wolk, and D. Mechanic-Hamilton

Neurology, Apr 2019

DOI
Erratum: Li et al., “The DNA Repair-Associated Protein Gadd45γ Regulates the Temporal Coding of Immediate Early Gene Expression within the Prelimbic Prefrontal Cortex and Is Required for the Consolidation of Associative Fear Memory”

Xiang Li, Paul R. Marshall, L. Leighton, E. Zajaczkowski, Zi-Qi Wang, Sachithrani U. Madugalle, Jiayu Yin, T. Bredy, Sang-Ah Lee, Jonathan F. Miller, Andrew J. Watrous, M. Sperling, A. Sharan, G. Worrell, Brent M. Berry, Joshua P. Aronson, K. Davis, R. Gross, B. Lega, S. Sheth, Sandhitsu R. Das, J. Stein, R. Gorniak, and D. Rizzuto

The Journal of Neuroscience, Mar 2019

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In the article “The DNA Repair-Associated Protein Gadd45 Regulates the Temporal Coding of Immediate Early Gene Expression within the Prelimbic Prefrontal Cortex and Is Required for the Consolidation of Associative Fear Memory” by Xiang Li, Paul R. Marshall, Laura J. Leighton, Esmi L. Zajaczkowski, Ziqi Wang, Sachithrani U. Madugalle, Jiayu Yin, Timothy W. Bredy, and Wei Wei, which appeared on pages 970 –983 of the February 6, 2019 issue, some of the references on page 971, first full paragraph, appeared incorrectly. Beginning with the third sentence, the references “Baker-Andresen et al., 2013”, “Li et al., 2014”, and “Miller et al., 2010; Baker-Andresen et al., 2013; Li et al., 2014” should appear as “Savell et al., 2016”, “Rudenko et al., 2013”, and “Massart et al., 2015; Wright et al., 2015”, respectively. In addition, the following references should be added to the reference list:
Abstract #117: Changes in high frequency activity depend on frequency of electrical stimulation in the human cortex

U. Mohan, M. Sperling, A. Sharan, G. Worrell, Brent M. Berry, B. Lega, B. Jobst, K. Davis, R. Gross, S. Sheth, Sandhitsu R. Das, and J. Stein

Brain Stimulation, Mar 2019

DOI
Dynamic theta networks in the human medial temporal lobe support episodic memory.

E. Solomon, J. Stein, Sandhitsu R. Das, R. Gorniak, M. Sperling, G. Worrell, Cory S. Inman, R. Tan, B. Jobst, D. Rizzuto, and M. Kahana

Current biology : CB, Mar 2019

Cited by 101

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Summary The medial temporal lobe (MTL) is a locus of episodic memory in the human brain. It is comprised of cytologically distinct subregions that, in concert, give rise to successful encoding and retrieval of context-dependent memories. However, the functional connections between these subregions are poorly understood. To determine functional connectivity among MTL subregions, we had 131 subjects fitted with indwelling electrodes perform a verbal memory task, and asked how encoding or retrieval correlated with interregional synchronization. Using phase-based measures of connectivity, we found that synchronous theta (4-8 Hz) activity underlies successful episodic memory. During encoding, we observed a dynamic pattern of connections converging on the left entorhinal cortex, beginning with the perirhinal cortex and shifting through hippocampal subfields. Retrieval-associated networks demonstrated enhanced involvement of the subiculum and CA1, reflecting a substantial reorganization of the encoding network. We posit that coherent theta activity within the MTL marks periods of successful memory, but distinct patterns of connectivity dissociate key stages of memory processing.
Older Adult Normative Data for the Sniffin’ Sticks Odor Identification Test

K. Vickers, Kathleen A. Breslin, D. Roalf, Vidyulata Kamath, Sharon X. Xie, P. Moberg, D. Wolk, and D. Mechanic-Hamilton

Archives of Clinical Neuropsychology, Mar 2019

Cited by 5

DOI PDF
Diffeomorphic Medial Modeling

Paul Yushkevich, A. H. Aly, Jiancong Wang, Long Xie, R. Gorman, L. Younes, and A. Pouch

Information processing in medical imaging : proceedings of the ... conference, Feb 2019

Cited by 6

Abs DOI arXiv PDF

Deformable shape modeling approaches that describe objects in terms of their medial axis geometry (e.g., m-reps [10]) yield rich geometrical features that can be useful for analyzing the shape of sheet-like biological structures, such as the myocardium. We present a novel shape analysis approach that combines the benefits of medial shape modeling and diffeomorphometry. Our algorithm is formulated as a problem of matching shapes using diffeomorphic flows under constraints that approximately preserve medial axis geometry during deformation. As the result, correspondence between the medial axes of similar shapes is maintained. The approach is evaluated in the context of modeling the shape of the left ventricular wall from 3D echocardiography images.
Functional control of electrophysiological network architecture using direct neurostimulation in humans

A. Khambhati, Ari E. Kahn, J. Costantini, Youssef Ezzyat, E. Solomon, R. Gross, B. Jobst, S. Sheth, K. Zaghloul, G. Worrell, S. Seger, B. Lega, S. Weiss, M. Sperling, R. Gorniak, Sandhitsu R. Das, J. Stein, D. Rizzuto, M. Kahana, Timothy H. Lucas, K. Davis, J. Tracy, and D. Bassett

Network Neuroscience, Jan 2019

Cited by 65

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Chronically implantable neurostimulation devices are becoming a clinically viable option for treating patients with neurological disease and psychiatric disorders. Neurostimulation offers the ability to probe and manipulate distributed networks of interacting brain areas in dysfunctional circuits. Here, we use tools from network control theory to examine the dynamic reconfiguration of functionally interacting neuronal ensembles during targeted neurostimulation of cortical and subcortical brain structures. By integrating multimodal intracranial recordings and diffusion-weighted imaging from patients with drug-resistant epilepsy, we test hypothesized structural and functional rules that predict altered patterns of synchronized local field potentials. We demonstrate the ability to predictably reconfigure functional interactions depending on stimulation strength and location. Stimulation of areas with structurally weak connections largely modulates the functional hubness of downstream areas and concurrently propels the brain towards more difficult-to-reach dynamical states. By using focal perturbations to bridge large-scale structure, function, and markers of behavior, our findings suggest that stimulation may be tuned to influence different scales of network interactions driving cognition.Author SummaryBrain stimulation devices capable of perturbing the physiological state of neural systems are rapidly gaining popularity for their potential to treat neurological and psychiatric disease. A root problem is that underlying dysfunction spans a large-scale network of brain regions, requiring the ability to control the complex interactions between multiple brain areas. Here, we use tools from network control theory to examine the dynamic reconfiguration of functionally interacting neuronal ensembles during targeted neurostimulation of cortical and subcortical brain structures. We demonstrate the ability to predictably reconfigure patterns of interactions between functional brain areas by modulating the strength and location of stimulation. Our findings have high significance for designing stimulation protocols capable of modulating distributed neural circuits in the human brain.
Fully automated placental volume quantification from 3DUS for prediction of small‐for‐gestational age infants: 1049

N. Schwartz, I. Oguz, Jiancong Wang, A. Pouch, N. Yushkevich, Shobhana Parameshwaran, J. Gee, Paul Yushkevich, and Baris U. Oguz

American Journal of Obstetrics and Gynecology, Jan 2019

Cited by 2

Abs DOI

1048 Early-onset isolated fetal growth restriction and perinatal outcomes Moeun Son, Ronald J. Wapner, Robert M. Silver, David M. Haas, Deborah A. Wing, Samuel Parry, Brian M. Mercer, George R. Saade, Uma M. Reddy, William A. Grobman Northwestern University Feinberg School of Medicine, Chicago, IL, Columbia University College of Physicians and Surgeons, New York, NY, University of Utah School of Medicine, Salt Lake City, UT, Indiana University School of Medicine, Indianapolis, IN, University of California, Irvine, School of Medicine, Irvine, CA, University of Pennsylvania School of Medicine, Philadelphia, PA, Case Western Reserve University School of Medicine, Cleveland, OH, University of Texas Medal Branch, Galveston, TX, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD OBJECTIVE: To investigate the relationship between early-onset isolated fetal growth restriction (FGR) and perinatal outcomes. STUDY DESIGN: Secondary analysis of a prospective cohort study of nulliparous women with singleton nonanomalous pregnancies from 8 U.S. clinical sites and excellent gestational dating including first trimester sonogram. Women were included if they had assessment of fetal biometry by ultrasound at study visit 2 (16-21 weeks of gestation). Those with prenatally diagnosed fetal structural or chromosomal abnormalities, or missing exposure or primary outcome data were excluded from this analysis. Women who delivered prior to 20 weeks of gestation were also excluded. The main exposure variable was the presence of FGR on the ultrasound at study visit 2. FGR was defined as estimated fetal weight <10 percentile for gestational age (GA) using the Hadlock growth curve. The primary outcome was small for GA (SGA) at birth, defined as birthweight <10 percentile on the Alexander nomogram. Secondary outcomes were FGR on the ultrasound at study visit 3 (22e29 weeks of gestation and at least 4 weeks after visit 2), preterm birth (PTB) at <37, <32, and <28 weeks of gestation, hypertensive disorders of pregnancy, placental abruption, and stillbirth or neonatal death. Perinatal outcomes were compared between the groups with bivariable and multivariable analyses.
Structural and functional asymmetry of medial temporal subregions in unilateral temporal lobe epilepsy: a 7T MRI study

Preya Shah, D. Bassett, L. Wisse, J. Detre, J. Stein, Paul Yushkevich, R. Shinohara, M. Elliott, Sandhitsu R. Das, and K. Davis

Human brain mapping, Jan 2019

Cited by 50

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Mesial temporal lobe epilepsy (TLE) is a common neurological disorder affecting the hippocampus and surrounding medial temporal lobe (MTL). Although prior studies have analyzed whole‐brain network distortions in TLE patients, the functional network architecture of the MTL at the subregion level has not been examined. In this study, we utilized high‐resolution 7T T2‐weighted magnetic resonance imaging (MRI) and resting‐state BOLD‐fMRI to characterize volumetric asymmetry and functional network asymmetry of MTL subregions in unilateral medically refractory TLE patients and healthy controls. We subdivided the TLE group into mesial temporal sclerosis patients (TLE‐MTS) and MRI‐negative nonlesional patients (TLE‐NL). Using an automated multi‐atlas segmentation pipeline, we delineated 10 MTL subregions per hemisphere for each subject. We found significantly different patterns of volumetric asymmetry between the two groups, with TLE‐MTS exhibiting volumetric asymmetry corresponding to decreased volumes ipsilaterally in all hippocampal subfields, and TLE‐NL exhibiting no significant volumetric asymmetries other than a mild decrease in whole‐hippocampal volume ipsilaterally. We also found significantly different patterns of functional network asymmetry in the CA1 subfield and whole hippocampus, with TLE‐NL patients exhibiting asymmetry corresponding to increased connectivity ipsilaterally and TLE‐MTS patients exhibiting asymmetry corresponding to decreased connectivity ipsilaterally. Our findings provide initial evidence that functional neuroimaging‐based network properties within the MTL can distinguish between TLE subtypes. High‐resolution MRI has potential to improve localization of underlying brain network disruptions in TLE patients who are candidates for surgical resection.
AMYLOID-POSITIVE COGNITIVE IMPAIRMENT IS LESS “ALZHEIMER’S-LIKE” IN THE ABSENCE OF TAU NEUROINFLAMMATION IN AT-CELLTGF- b RECEPTOR DISRUPTED P301S MOUSE

Sandhitsu R. Das, Long Xie, Salena Cui, R. Flores, L. Wisse, Paul Yushkevich, and D. Wolk

Jan 2019
LONG-TERM NSAID THERAPY IN OLDER ADULTS: EFFECTS ON AT(N)V IMAGING BIOMARKERS

R. Grunstein, S. Duffy, J. Shine, L. Wisse, Sandhitsu R. Das, R. Ittyerah, Robin de, Flores, Paul Yushkevich, and David A. Wolk

Jan 2019
OLDER ADULTS: A COMMUNITY-BASED STUDY

Chengxuan Qiu, Arun Pilania, L. Wisse, Sandhitsu R. Das, Long Xie, David A. Wolk, and Anjan Chatterjee

Jan 2019
Spike and-Slab Group LASSOs for Grouped Regression and Sparse Generalized Additive Models

A. M. Valcarcel, J. Muschelli, D. Pham, M. Martin, Paul Yushkevich, P. Calabresi, R. Bakshi, and R. Shinohara

Jan 2019

Cited by 28
NUMERICAL SIMULATION OF REACTION-DIFFUSION PROCESSES IN THE PROBLEM OF STUDYING THE COLLECTIVE BEHAVIOR OF MICROORGANISMS

Paul Yushkevich, D. A. Korshik, and A. Maslovskaya

Messenger AmSU, Jan 2019

DOI PDF
[ 11 C]MK-6884 PET TRACER FOR M4 MUSCARINIC CHOLINERGIC RECEPTORS IN ALZHEIMER’S DISEASE: COMPARISON WITH [ 18 F]FDG PET RELATIVE SPARING OF MEDIAL TEMPORAL SUBREGION VOLUMES IN NON-AMNESTIC ALZHEIMER’S DISEASE

Paolo Zanotti-Fregonara, Mei-Xiang Yu, Quentin Funk, A. Victoria, Yuchuan Wang, Wen-Ping Li, Amy Cheng, Matt Anderson, Eric D. Hostetler, A. Basile, Joseph C. Masdeu, Paul Yushkevich, and M. Grossman

Jan 2019

2018

Associative memory for conceptually unitized word pairs in mild cognitive impairment is related to the volume of the perirhinal cortex

Emma Delhaye, D. Mechanic-Hamilton, Laura Saad, Sandhitsu R. Das, L. Wisse, Paul Yushkevich, D. Wolk, and C. Bastin

Hippocampus, Dec 2018

Cited by 20

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Unitization, that is, the encoding of an association as one integrated entity, has been shown to improve associative memory in populations presenting with associative memory deficit due to hippocampal dysfunction, such as amnesic patients with focal hippocampal lesions and healthy older adults. One reason for this benefit is that encoding of unitized associations would rely on the perirhinal cortex (PrC) and thus minimize the need for hippocampal recruitment. Mild cognitive impairment (MCI) is accompanied by a deficit in associative memory. However, unitization has never been studied to explore the potential benefit in associative memory in MCI, maybe because MCI is characterized by PrC pathology. However, the PrC may potentially still function sufficiently to allow for the successful adoption of unitization. In this study, we aimed at assessing whether unitization could attenuate MCI patients’ associative memory deficit, and whether the ability to remember unitized associations would be modulated by the integrity of the PrC in MCI patients. Unitization was manipulated at a conceptual level, by encouraging participants to encode unrelated word pairs as new compound words. Participants also underwent a structural MRI exam, and measures of PrC were extracted (Brodmann Areas [BA] 35 and 36). Results showed that, contrary to healthy controls, MCI patients did not benefit from unitization. Moreover, their memory performance for unitized associations was related to the measure of PrC integrity (BA35), while it was not the case in controls. This finding thus suggests that unitization does not help to attenuate the associative deficit in MCI patients, and brings support to the literature linking unitization to the PrC function.
Abstract 11933: Extracting Clinical Pearls From Heart Sound Waves: A Deep Learning Approach

A. H. Aly, Yumeng Guo, Jiancong Wang, A. Pouch, J. Gorman, J. Gee, Paul Yushkevich, and R. Gorman

Circulation, Nov 2018
High interictal connectivity within the resection zone is associated with favorable post-surgical outcomes in focal epilepsy patients

Preya Shah, John M. Bernabei, Lohith G. Kini, Arian Ashourvan, Jacqueline Boccanfuso, Ryan Archer, Kelly F. Oechsel, Sandhitsu R. Das, J. Stein, Timothy H. Lucas, D. Bassett, K. Davis, and B. Litt

NeuroImage : Clinical, Nov 2018

Cited by 64

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Objective Patients with drug-resistant focal epilepsy are often candidates for invasive surgical therapies. In these patients, it is necessary to accurately localize seizure-generators to ensure seizure freedom following intervention. While intracranial electroencephalography (iEEG) is the gold standard for mapping networks for surgery, this approach requires inducing and recording seizures, which may cause patient morbidity. The goal of this study is to evaluate the utility of mapping interictal (non-seizure) iEEG networks to identify targets for surgical treatment. Methods We analyze interictal iEEG recordings and neuroimaging from 27 focal epilepsy patients treated via surgical resection. We generate interictal functional networks by calculating pairwise correlation of iEEG signals across different frequency bands. We identify electrodes falling within surgically resected tissue (i.e. the resection zone), and compute node-level and edge-level synchrony in relation to the resection zone. We associate these metrics with post-surgical outcomes. Results Greater overlap between resected electrodes and highly synchronous electrodes is associated with favorable post-surgical outcomes. Additionally, good outcome patients have significantly higher connectivity localized within the resection zone compared to those with poorer postoperative seizure control. This finding persists following normalization by a spatially-constrained null model. Conclusions This study suggests that spatially-informed interictal network synchrony measures can distinguish between good and poor post-surgical outcomes. By capturing clinically relevant information during interictal periods, our method may ultimately reduce the need for prolonged invasive implants and provide insights into the pathophysiology of an epileptic brain. We discuss next steps for translating these findings into a prospectively useful clinical tool.
Task-Enhanced Arterial Spin Labeled Perfusion MRI Predicts Longitudinal Neurodegeneration in Mild Cognitive Impairment

Long Xie, Sandhitsu R. Das, Arun Pilania, Molly Daffner, Grace E Stockbower, S. Dolui, Paul Yushkevich, J. Detre, and D. Wolk

Hippocampus, Nov 2018

Cited by 10

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Mild cognitive impairment (MCI) is considered a prodromal stage of Alzheimer’s disease (AD), but is also recognized to be a heterogeneous condition. Biomarkers that predict AD progression in MCI are of clinical significance because they can be used to better identify appropriate candidates for therapeutic intervention studies. It has been hypothesized that comparing to structural measurements, functional ones may be more sensitive to early disease abnormalities and the sensitivity could be further enhanced when combined with cognitive task, a “brain stress test.” In this study, we investigated the value of regional cerebral blood flow (CBF), measured by arterial spin labeled perfusion MRI (ASL MRI) during a memory‐encoding task, in predicting the estimated rate of hippocampal atrophy, an established marker of AD progression. Thirty‐one amnestic MCI patients (20 male and 11 female; age: 70.9 ± 6.5 years, range from 56 to 83 years; mini mental status examination: 27.8 ± 1.8) and 42 normal control subjects (13 male and 29 female; age: 70.6 ± 8.8 years, range from 55 to 88 years; mini mental status examination: 29.1 ± 1.2) were included in this study. We compared the predictive value of CBF during task to CBF during rest and structural volumetry. Both region‐of‐interest and voxelwise analyses showed that baseline CBF measurements during task (strongest effect in fusiform gyrus, region‐of‐interest analysis statistics: r = 0.56, p = .003), but not resting ASL MRI or structural volumetry, were correlated with the estimated rate of hippocampal atrophy in amnestic MCI patients. Further, stepwise linear regression demonstrated that resting ASL MRI and volumetry did not provide complementary information in prediction. These results support the notion that physiologic measures during a cognitive challenge may increase the ability to detect subtle functional changes that predict progression. As such, ASL MRI could have important utility in stratifying candidates for AD treatment trials.
Task‐enhanced arterial spin labeled perfusion MRI predicts longitudinal neurodegeneration in mild cognitive impairment

L. Xie, Sandhitsu R. Das, Arun Pilania, Molly Daffner, Grace E Stockbower, Sudipto Dolui, Paul Yushkevich, J. Detre, and D. Wolk

Hippocampus, Nov 2018

Cited by 10

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Mild cognitive impairment (MCI) is considered a prodromal stage of Alzheimer’s disease (AD), but is also recognized to be a heterogeneous condition. Biomarkers that predict AD progression in MCI are of clinical significance because they can be used to better identify appropriate candidates for therapeutic intervention studies. It has been hypothesized that comparing to structural measurements, functional ones may be more sensitive to early disease abnormalities and the sensitivity could be further enhanced when combined with cognitive task, a “brain stress test.” In this study, we investigated the value of regional cerebral blood flow (CBF), measured by arterial spin labeled perfusion MRI (ASL MRI) during a memory‐encoding task, in predicting the estimated rate of hippocampal atrophy, an established marker of AD progression. Thirty‐one amnestic MCI patients (20 male and 11 female; age: 70.9 ± 6.5 years, range from 56 to 83 years; mini mental status examination: 27.8 ± 1.8) and 42 normal control subjects (13 male and 29 female; age: 70.6 ± 8.8 years, range from 55 to 88 years; mini mental status examination: 29.1 ± 1.2) were included in this study. We compared the predictive value of CBF during task to CBF during rest and structural volumetry. Both region‐of‐interest and voxelwise analyses showed that baseline CBF measurements during task (strongest effect in fusiform gyrus, region‐of‐interest analysis statistics: r = 0.56, p = .003), but not resting ASL MRI or structural volumetry, were correlated with the estimated rate of hippocampal atrophy in amnestic MCI patients. Further, stepwise linear regression demonstrated that resting ASL MRI and volumetry did not provide complementary information in prediction. These results support the notion that physiologic measures during a cognitive challenge may increase the ability to detect subtle functional changes that predict progression. As such, ASL MRI could have important utility in stratifying candidates for AD treatment trials.
Clinical validation of automated hippocampal segmentation in temporal lobe epilepsy

P. Hadar, Lohith G. Kini, C. Coto, Virginie Piskin, L. Callans, Stephanie H. Chen, J. Stein, Sandhitsu R. Das, Paul Yushkevich, and K. Davis

NeuroImage : Clinical, Oct 2018

Cited by 17

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Objective To provide a multi-atlas framework for automated hippocampus segmentation in temporal lobe epilepsy (TLE) and clinically validate the results with respect to surgical lateralization and post-surgical outcome. Methods We retrospectively identified 47 TLE patients who underwent surgical resection and 12 healthy controls. T1-weighted 3 T MRI scans were acquired for all subjects, and patients were identified by a neuroradiologist with regards to lateralization and degree of hippocampal sclerosis (HS). Automated segmentation was implemented through the Joint Label Fusion/Corrective Learning (JLF/CL) method. Gold standard lateralization was determined from the surgically resected side in Engel I (seizure-free) patients at the two-year timepoint. ROC curves were used to identify appropriate thresholds for hippocampal asymmetry ratios, which were then used to analyze JLF/CL lateralization. Results The optimal template atlas based on subject images with varying appearances, from normal-appearing to severe HS, was demonstrated to be composed entirely of normal-appearing subjects, with good agreement between automated and manual segmentations. In applying this atlas to 26 surgically resected seizure-free patients at a two-year timepoint, JLF/CL lateralized seizure onset 92% of the time. In comparison, neuroradiology reads lateralized 65% of patients, but correctly lateralized seizure onset in these patients 100% of the time. When compared to lateralized neuroradiology reads, JLF/CL was in agreement and correctly lateralized all 17 patients. When compared to nonlateralized radiology reads, JLF/CL correctly lateralized 78% of the nine patients. Significance While a neuroradiologist’s interpretation of MR imaging is a key, albeit imperfect, diagnostic tool for seizure localization in medically-refractory TLE patients, automated hippocampal segmentation may provide more efficient and accurate epileptic foci localization. These promising findings demonstrate the clinical utility of automated segmentation in the TLE MR imaging pipeline prior to surgical resection, and suggest that further investigation into JLF/CL-assisted MRI reading could improve clinical outcomes. Our JLF/CL software is publicly available at https://www.nitrc.org/projects/ashs/.
Semi-automated Image Segmentation of the Midsystolic Left Ventricular Mitral Valve Complex in Ischemic Mitral Regurgitation

A. H. Aly, Abdullah H. Aly, Mahmoud Elrakhawy, Kirlos Haroun, Luis Prieto-Riascos, R. Gorman, N. Yushkevich, Yoshiaki Saito, J. Gorman, Paul Yushkevich, and A. Pouch

In STACOM@MICCAI, Sep 2018

Cited by 2

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Ischemic mitral regurgitation (IMR) is primarily a left ventricular disease in which the mitral valve is dysfunctional due to ventricular remodeling after myocardial infarction. Current automated methods have focused on analyzing the mitral valve and left ventricle independently. While these methods have allowed for valuable insights into mechanisms of IMR, they do not fully integrate pathological features of the left ventricle and mitral valve. Thus, there is an unmet need to develop an automated segmentation algorithm for the left ventricular mitral valve complex, in order to allow for a more comprehensive study of this disease. The objective of this study is to generate and evaluate segmentations of the left ventricular mitral valve complex in pre-operative 3D transesophageal echocardiography using multi-atlas label fusion. These patient-specific segmentations could enable future statistical shape analysis for clinical outcome prediction and surgical risk stratification. In this study, we demonstrate a preliminary segmentation pipeline that achieves an average Dice coefficient of 0.78 ± 0.06.
Combining Deep Learning and Multi-atlas Label Fusion for Automated Placenta Segmentation from 3DUS

Baris U. Oguz, Jiancong Wang, N. Yushkevich, A. Pouch, J. Gee, Paul Yushkevich, N. Schwartz, and I. Oguz

In DATRA/PIPPI@MICCAI, Sep 2018

Cited by 20

DOI
Characterizing Anatomical Variability And Alzheimer’s Disease Related Cortical Thinning in the Medial Temporal Lobe Using Graph-Based Groupwise Registration And Point Set Geodesic Shooting

Long Xie, L. Wisse, Sandhitsu R. Das, R. Ittyerah, Jiancong Wang, D. Wolk, and Paul Yushkevich

In ShapeMI@MICCAI, Sep 2018

Cited by 6

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The perirhinal cortex (PRC) is a site of early neurofibrillary tangle (NFT) pathology in Alzheimer’s disease (AD). Subtle morphological changes in the PRC have been reported in MRI studies of early AD, which has significance for clinical trials targeting preclinical AD. However, the PRC exhibits considerable anatomical variability with multiple discrete variants described in the neuroanatomy literature. We hypothesize that different anatomical variants are associated with different patterns of AD-related effects in the PRC. Single-template approaches conventionally used for automated image-based brain morphometry are ill-equipped to test this hypothesis. This study uses graph-based groupwise registration and diffeomorphic landmark matching with geodesic shooting to build statistical shape models of discrete PRC variants and examine variant-specific effects of AD on PRC shape and thickness. Experimental results demonstrate that the statistical models recover the folding patterns of the known PRC variants and capture the expected shape variability within the population. By applying the proposed pipeline to a large dataset with subjects from different stages in the AD spectrum, we find 1) a pattern of cortical thinning consistent with the NFT pathology progression, 2) different patterns of the initial spatial distribution of cortical thinning between anatomical variants, and 3) an effect of AD on medial temporal lobe shape. As such, the proposed pipeline could have important utility in the early detection and monitoring of AD.
Characterizing Anatomical Variability and Alzheimer’s Disease Related Cortical Thinning in the Medial Temporal Lobe Using Graph-Based Groupwise Registration and Point Set Geodesic Shooting

L. Xie, L. Wisse, Sandhitsu R. Das, R. Ittyerah, Jiancong Wang, D. Wolk, and Paul Yushkevich

In ShapeMI@MICCAI, Sep 2018

Cited by 5

DOI PDF
Quantitative MRI of perivascular spaces (PVS) at 3 Tesla for early diagnosis of mild cognitive impairment (MCI)

M. Niazi, M. Karaman, Sandhitsu Das, X. J. Zhou, Paul Yushkevich, and K. Cai

AJNR. American journal of neuroradiology, Aug 2018

Cited by 33

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The authors automated the identification of enlarged perivascular spaces in brain MR images using a custom quantitative program designed with Matlab. They quantified the densities of enlarged perivascular spaces for patients with mild cognitive impairment (n=14) and age-matched cognitively healthy controls (n=15) and compared them to determine whether the density of enlarged perivascular spaces can serve as an imaging surrogate for mild cognitive impairment diagnosis. The density of enlarged perivascular spaces was found to be significantly higher in those with mild cognitive impairment compared with age-matched healthy control subjects. BACKGROUND AND PURPOSE: The limitations inherent in the current methods of diagnosing mild cognitive impairment have constrained the use of early therapeutic interventions to delay the progression of mild cognitive impairment to dementia. This study evaluated whether quantifying enlarged perivascular spaces observed on MR imaging can help differentiate those with mild cognitive impairment from cognitively healthy controls and, thus, have an application in the diagnosis of mild cognitive impairment. MATERIALS AND METHODS: We automated the identification of enlarged perivascular spaces in brain MR Images using a custom quantitative program designed with Matlab. We then quantified the densities of enlarged perivascular spaces for patients with mild cognitive impairment (n = 14) and age-matched cognitively healthy controls (n = 15) and compared them to determine whether the density of enlarged perivascular spaces can serve as an imaging surrogate for mild cognitive impairment diagnosis. RESULTS: Quantified as a percentage of volume fraction (v/v%), densities of enlarged perivascular spaces were calculated to be 2.82 ± 0.40 v/v% for controls and 4.17 ± 0.57 v/v% for the mild cognitive impairment group in the subcortical brain (P < .001), and 2.74 ± 0.57 v/v% for the controls and 3.90 ± 0.62 v/v% for the mild cognitive impairment cohort in the basal ganglia (P < .001). Maximum intensity projections exhibited a visually conspicuous difference in the distributions of enlarged perivascular spaces for a patient with mild cognitive impairment and a control patient. By means of receiver operating characteristic curve analysis, we determined the sensitivity and specificity of using enlarged perivascular spaces as a differentiating biomarker between mild cognitive impairment and controls to be 92.86% and 93.33%, respectively. CONCLUSIONS: The density of enlarged perivascular spaces was found to be significantly higher in those with mild cognitive impairment compared with age-matched healthy control subjects. The density of enlarged perivascular spaces, therefore, may be a useful imaging biomarker for the diagnosis of mild cognitive impairment.
Quantitative MRI of Perivascular Spaces at 3T for Early Diagnosis of Mild Cognitive Impairment

M. Niazi, M. Karaman, S. Das, X.J. Zhou, Paul Yushkevich, and K. Cai

American Journal of Neuroradiology, Aug 2018

Cited by 32

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The authors automated the identification of enlarged perivascular spaces in brain MR images using a custom quantitative program designed with Matlab. They quantified the densities of enlarged perivascular spaces for patients with mild cognitive impairment (n=14) and age-matched cognitively healthy controls (n=15) and compared them to determine whether the density of enlarged perivascular spaces can serve as an imaging surrogate for mild cognitive impairment diagnosis. The density of enlarged perivascular spaces was found to be significantly higher in those with mild cognitive impairment compared with age-matched healthy control subjects. BACKGROUND AND PURPOSE: The limitations inherent in the current methods of diagnosing mild cognitive impairment have constrained the use of early therapeutic interventions to delay the progression of mild cognitive impairment to dementia. This study evaluated whether quantifying enlarged perivascular spaces observed on MR imaging can help differentiate those with mild cognitive impairment from cognitively healthy controls and, thus, have an application in the diagnosis of mild cognitive impairment. MATERIALS AND METHODS: We automated the identification of enlarged perivascular spaces in brain MR Images using a custom quantitative program designed with Matlab. We then quantified the densities of enlarged perivascular spaces for patients with mild cognitive impairment (n = 14) and age-matched cognitively healthy controls (n = 15) and compared them to determine whether the density of enlarged perivascular spaces can serve as an imaging surrogate for mild cognitive impairment diagnosis. RESULTS: Quantified as a percentage of volume fraction (v/v%), densities of enlarged perivascular spaces were calculated to be 2.82 ± 0.40 v/v% for controls and 4.17 ± 0.57 v/v% for the mild cognitive impairment group in the subcortical brain (P < .001), and 2.74 ± 0.57 v/v% for the controls and 3.90 ± 0.62 v/v% for the mild cognitive impairment cohort in the basal ganglia (P < .001). Maximum intensity projections exhibited a visually conspicuous difference in the distributions of enlarged perivascular spaces for a patient with mild cognitive impairment and a control patient. By means of receiver operating characteristic curve analysis, we determined the sensitivity and specificity of using enlarged perivascular spaces as a differentiating biomarker between mild cognitive impairment and controls to be 92.86% and 93.33%, respectively. CONCLUSIONS: The density of enlarged perivascular spaces was found to be significantly higher in those with mild cognitive impairment compared with age-matched healthy control subjects. The density of enlarged perivascular spaces, therefore, may be a useful imaging biomarker for the diagnosis of mild cognitive impairment.
IC‐P‐202: AV1451 TAU TRACER UPTAKE CORRELATES WITH HIPPOCAMPAL CA1 SUBFIELD ATROPHY IN AMYLOID‐NEGATIVE INDIVIDUALS

Sandhitsu R. Das, R. Ittyerah, L. Wisse, Long Xie, Paul Yushkevich, and David A. Wolk

Alzheimer’s & Dementia, Jul 2018

DOI
P3‐390: IDENTIFYING ALTERED BRAIN NETWORKS USING DIFFUSION TENSOR IMAGING IN ELDERLY SUBJECTS WITH SUBJECTIVE COGNITIVE IMPAIRMENT

Sandhitsu R. Das, R. Ittyerah, L. Wisse, Long Xie, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2018

DOI
P4‐314: A HARMONIZED PROTOCOL FOR IN VIVO HUMAN HIPPOCAMPAL SUBFIELD SEGMENTATION: INITIAL RESULTS OF THE 3 TESLA PROTOCOL

R. La Joie, Ana.M. Daugherty, Laura E. M. Wisse, R. Amaral, K. Amunts, Jean C. Augustinack, A. Bakker, Andrew R. Bender, D. Berron, A. Burggren, M. Chakravarty, Robin Flores, Song-Lin Ding, Arne D. Ekstrom, P. Kanel, O. Kedo, R. Insausti, N. Malykhin, S. Mueller, N. Ofen, D. Palombo, J. Pluta, D. Schoemaker, Craig E. L. Stark, T. Steve, Lei Wang, M. Yassa, Qi-Jing Yu, Paul Yushkevich, Valerie A. Carr, and R. Olsen

Alzheimer’s & Dementia, Jul 2018

DOI
P1‐669: AWARENESS OF MILD COGNITIVE IMPAIRMENT AND MILD ALZHEIMER’S DISEASE DEMENTIA DIAGNOSES IS ASSOCIATED WITH DECREASED SELF‐RATINGS OF QUALITY OF LIFE IN OLDER ADULTS

S. Stites, Jonathan D. Rubright, K. Harkins, David A. Wolk, and J. Karlawish

Alzheimer’s & Dementia, Jul 2018

Cited by 1

DOI
Ripple oscillations in the left temporal neocortex are associated with impaired verbal episodic memory encoding

Zachary Waldman, L. Camarillo-Rodriguez, Inna Chervenova, Brent M. Berry, S. Shimamoto, Bahareh Elahian, Michal T. Kucewicz, C. Ganne, Xiao-Song He, Leon A. Davis, J. Stein, Sandhitsu R. Das, Richard Gorniak, A. Sharan, Robert E. Gross, Cory S. Inman, B. Lega, K. Zaghloul, B. Jobst, K. A. Davis, Paul A. Wanda, Mehraneh Khadjevand, J. Tracy, D. Rizzuto, Gregory A. Worrell, Michael R. Sperling, and S. Weiss

Epilepsy & behavior : E&B, Jul 2018

Cited by 16

Abs DOI arXiv PDF

Summary Background: We sought to determine if ripple oscillations (80–120Hz), detected in intracranial EEG (iEEG) recordings of epilepsy patients, correlate with an enhancement or disruption of verbal episodic memory encoding. Methods: We defined ripple and spike events in depth iEEG recordings during list learning in 107 patients with focal epilepsy. We used logistic regression models (LRMs) to investigate the relationship between the occurrence of ripple and spike events during word presentation and the odds of successful word recall following a distractor epoch, and included the seizure onset zone (SOZ) as a covariate in the LRMs. Results: We detected events during 58,312 word presentation trials from 7,630 unique electrode sites. The probability of ripple on spike (RonS) events was increased in the seizure onset zone (SOZ, p<0.04). In the left temporal neocortex RonS events during word presentation corresponded with a decrease in the odds ratio (OR) of successful recall, however this effect only met significance in the SOZ (OR of word recall 0.71, 95% CI: 0.59–0.85, n=158 events, adaptive Hochberg p<0.01). Ripple on oscillation events (RonO) that occurred in the left temporal neocortex non-SOZ also correlated with decreased odds of successful recall (OR 0.52, 95% CI: 0.34–0.80, n=140, adaptive Hochberg, p<0.01). Spikes and RonS that occurred during word presentation in the left middle temporal gyrus during word presentation correlated with the most significant decrease in the odds of successful recall, irrespective of the location of the SOZ (adaptive Hochberg, p<0.01). Conclusion: Ripples and spikes generated in left temporal neocortex are associated with impaired verbal episodic memory encoding. Although physiological and pathological ripple oscillations were not distinguished during cognitive tasks, our results show an association of undifferentiated ripples with impaired encoding. The effect was sometimes specific to regions outside the SOZ, suggesting that widespread effects of epilepsy outside the SOZ may contribute to cognitive impairment.
IC‐P‐132: AGE AND VASCULAR DISEASE EFFECTS ON MEDIAL TEMPORAL LOBE SUBREGIONS IN COGNITIVELY NORMAL OLDER ADULTS

L. Wisse, Mohamad Habes, Sandhitsu R. Das, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2018

DOI
P2‐405: AGE AND VASCULAR DISEASE EFFECTS ON MEDIAL TEMPORAL LOBE SUBREGIONS IN COGNITIVELY NORMAL OLDER ADULTS

L. Wisse, Mohamad Habes, Sandhitsu R. Das, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2018

DOI
P4‐298: MEDIAL TEMPORAL LOBE SUBREGIONAL ATROPHY PATTERN IN SEMANTIC VARIANT PRIMARY PROGRESSIVE APHASIA AND ASSOCIATIONS WITH COGNITIVE IMPAIRMENTS

L. Wisse, Molly B. Ungrady, D. Wolk, D. Irwin, C. McMillan, R. Ittyerah, Paul Yushkevich, and M. Grossman

Alzheimer’s & Dementia, Jul 2018

Cited by 1

DOI
P3‐407: PATTERN OF CORTICAL THINNING AND SHAPE VARIABILITY RELATED TO ALZHEIMER’S DISEASE IN REGIONS AFFECTED BY EARLIEST NEUROFIBRILLARY TANGLE PATHOLOGY

Long Xie, L. Wisse, Sandhitsu R. Das, R. Ittyerah, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2018

DOI
P4‐320: DURA MATTERS: FAILURE TO ACCOUNT FOR THE DURA MATER CONFOUNDS MEASURES OF ATROPHY IN CORTICAL REGIONS LINKED TO THE EARLIEST NEUROFIBRILLARY TANGLE PATHOLOGY

Long Xie, L. Wisse, Sandhitsu R. Das, R. Ittyerah, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Jul 2018

DOI
S2‐01‐03: LINKING POSTMORTEM MRI AND DENSE HISTOLOGY

Paul Yushkevich

Alzheimer’s & Dementia, Jul 2018

DOI
Determining a Short Form Montreal Cognitive Assessment (s-MoCA) Czech Version: Validity in Mild Cognitive Impairment Parkinson’s Disease and Cross-Cultural Comparison

O. Bezdicek, M. Červenková, Tyler M. Moore, Hana Georgi, Z. Šulc, D. Wolk, D. Weintraub, P. Moberg, R. Jech, M. Kopeček, and D. Roalf

Assessment, Jun 2018

Cited by 24

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The Montreal Cognitive Assessment (MoCA) is one of the most common screening instruments for mild cognitive impairment. However, the standard MoCA is approximately two times longer to administer than the Mini-Mental State Examination. A total of 699 Czech and 175 American participants received the standard MoCA Czech and English versions and in the clinical part, a sample of 102 nondemented patients with Parkinson’s disease (PD). We created a validated Czech short version (s-MoCA-CZ) from the original using item response theory. As expected, s-MoCA-CZ scores were highly correlated with the standard version (Pearson r = .94, p < .001). s-MoCA-CZ also had 80% classification accuracy in the differentiation of PD mild cognitive impairment from PD without impairment. The s-MoCA-CZ, a brief screening tool, is shorter to administer than the standard MoCA. It provides high-classification accuracy for PD mild cognitive impairment and is equivalent to that of the standard MoCA-CZ.
Longitudinal and cross-sectional structural magnetic resonance imaging correlates of AV-1451 uptake.

Sandhitsu R. Das, L. Xie, L. Wisse, R. Ittyerah, N. Tustison, B. Dickerson, Paul Yushkevich, and D. Wolk

Neurobiology of aging, Jun 2018

Cited by 68

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We examined the relationship between in vivo estimates of tau deposition as measured by 18F-AV-1451 tau positron emission tomography imaging and cross-sectional cortical thickness, as well as rates of antecedent cortical thinning measured from magnetic resonance imaging in individuals with and without evidence of cerebral amyloid in 63 participants from the Alzheimer’s Disease Neuroimaging Initiative study, including 32 cognitively normal individuals (mean age 74 years), 27 patients with mild cognitive impairment (mean age 76.8 years), and 4 patients diagnosed with Alzheimer’s disease (mean age 80 years). We hypothesized that structural measures would correlate with 18F-AV-1451 in a spatially local manner and that this correlation would be stronger for longitudinal compared to cross-sectional measures of cortical thickness and in those with cerebral amyloid versus those without. Cross-sectional and longitudinal estimates of voxelwise atrophy were made from whole brain maps of cortical thickness and rates of thickness change. In amyloid-β-positive individuals, the correlation of voxelwise atrophy across the whole brain with a summary measure of medial temporal lobe (MTL) 18F-AV-1451 uptake demonstrated strong local correlations in the MTL with longitudinal atrophy that was weaker in cross-sectional analysis. Similar effects were seen in correlations between 31 bilateral cortical regions of interest. In addition, several nonlocal correlations between atrophy and 18F-AV-1451 uptake were observed, including association between MTL atrophy and 18F-AV-1451 uptake in parietal lobe regions of interest such as the precuneus. Amyloid-β-negative individuals only showed weaker correlations in data uncorrected for multiple comparisons. While these data replicate previous reports of associations between 18F-AV-1451 uptake and cross-sectional structural measures, the current results demonstrate a strong relationship with longitudinal measures of atrophy. These data support the notion that in vivo measures of tau pathology are tightly linked to the rate of neurodegenerative change.
Lateralized hippocampal oscillations underlie distinct aspects of human spatial memory and navigation

Jonathan F. Miller, Andrew J. Watrous, Melina Tsitsiklis, Sang Wan Lee, S. Sheth, C. Schevon, Elliot H. Smith, M. Sperling, A. Sharan, A. Asadi-Pooya, G. Worrell, S. Meisenhelter, Cory S. Inman, K. Davis, B. Lega, Paul A. Wanda, Sandhitsu R. Das, J. Stein, R. Gorniak, and J. Jacobs

Nature Communications, Jun 2018

Cited by 162

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The hippocampus plays a vital role in various aspects of cognition including both memory and spatial navigation. To understand electrophysiologically how the hippocampus supports these processes, we recorded intracranial electroencephalographic activity from 46 neurosurgical patients as they performed a spatial memory task. We measure signals from multiple brain regions, including both left and right hippocampi, and we use spectral analysis to identify oscillatory patterns related to memory encoding and navigation. We show that in the left but not right hippocampus, the amplitude of oscillations in the 1–3-Hz “low theta” band increases when viewing subsequently remembered object–location pairs. In contrast, in the right but not left hippocampus, low-theta activity increases during periods of navigation. The frequencies of these hippocampal signals are slower than task-related signals in the neocortex. These results suggest that the human brain includes multiple lateralized oscillatory networks that support different aspects of cognition. Theta oscillations are implicated in memory formation. Here, the authors show that low-theta oscillations in the hippocampus are differentially modulated between each hemisphere, with oscillations in the left increasing when successfully learning object–location pairs and in the right during spatial navigation.
User-Guided Segmentation of Multi-Modality Medical Imaging Datasets with ITK-SNAP

Paul Yushkevich, Artem Pashchinskiy, I. Oguz, S. Mohan, J. Schmitt, J. Stein, Dženan Zukić, Jared Vicory, M. McCormick, N. Yushkevich, N. Schwartz, Yang Gao, and G. Gerig

Neuroinformatics, Jun 2018

Cited by 175

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ITK-SNAP is an interactive software tool for manual and semi-automatic segmentation of 3D medical images. This paper summarizes major new features added to ITK-SNAP over the last decade. The main focus of the paper is on new features that support semi-automatic segmentation of multi-modality imaging datasets, such as MRI scans acquired using different contrast mechanisms (e.g., T1, T2, FLAIR). The new functionality uses decision forest classifiers trained interactively by the user to transform multiple input image volumes into a foreground/background probability map; this map is then input as the data term to the active contour evolution algorithm, which yields regularized surface representations of the segmented objects of interest. The new functionality is evaluated in the context of high-grade and low-grade glioma segmentation by three expert neuroradiogists and a non-expert on a reference dataset from the MICCAI 2013 Multi-Modal Brain Tumor Segmentation Challenge (BRATS). The accuracy of semi-automatic segmentation is competitive with the top specialized brain tumor segmentation methods evaluated in the BRATS challenge, with most results obtained in ITK-SNAP being more accurate, relative to the BRATS reference manual segmentation, than the second-best performer in the BRATS challenge; and all results being more accurate than the fourth-best performer. Segmentation time is reduced over manual segmentation by 2.5 and 5 times, depending on the rater. Additional experiments in interactive placenta segmentation in 3D fetal ultrasound illustrate the generalizability of the new functionality to a different problem domain.
Electrical Stimulation in Hippocampus and Entorhinal Cortex Impairs Spatial and Temporal Memory

A. Goyal, Jonathan F. Miller, Andrew J. Watrous, Sang-Ah Lee, Tom Coffey, M. Sperling, A. Sharan, G. Worrell, Brent M. Berry, B. Lega, B. Jobst, K. Davis, Cory S. Inman, S. Sheth, Paul A. Wanda, Youssef Ezzyat, Sandhitsu R. Das, J. Stein, R. Gorniak, and J. Jacobs

The Journal of Neuroscience, May 2018

Cited by 74

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The medial temporal lobe (MTL) is widely implicated in supporting episodic memory and navigation, but its precise functional role in organizing memory across time and space remains elusive. Here we examine the specific cognitive processes implemented by MTL structures (hippocampus and entorhinal cortex) to organize memory by using electrical brain stimulation, leveraging its ability to establish causal links between brain regions and features of behavior. We studied neurosurgical patients of both sexes who performed spatial-navigation and verbal-episodic memory tasks while brain stimulation was applied in various regions during learning. During the verbal memory task, stimulation in the MTL disrupted the temporal organization of encoded memories such that items learned with stimulation tended to be recalled in a more randomized order. During the spatial task, MTL stimulation impaired subjects’ abilities to remember items located far away from boundaries. These stimulation effects were specific to the MTL. Our findings thus provide the first causal demonstration in humans of the specific memory processes that are performed by the MTL to encode when and where events occurred. SIGNIFICANCE STATEMENT Numerous studies have implicated the medial temporal lobe (MTL) in encoding spatial and temporal memories, but they have not been able to causally demonstrate the nature of the cognitive processes by which this occurs in real-time. Electrical brain stimulation is able to demonstrate causal links between a brain region and a given function with high temporal precision. By examining behavior in a memory task as subjects received MTL stimulation, we provide the first causal evidence demonstrating the role of the MTL in organizing the spatial and temporal aspects of episodic memory.
MTL functional connectivity predicts stimulation-induced theta power

E. Solomon, R. Gross, B. Lega, M. Sperling, G. Worrell, S. Sheth, K. Zaghloul, B. Jobst, J. Stein, Sandhitsu R. Das, R. Gorniak, Cory S. Inman, S. Seger, J. Kragel, D. Rizzuto, and M. Kahana

bioRxiv, May 2018

Cited by 2

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Focal electrical stimulation of the brain incites a cascade of neural activity that propagates from the stimulated region to both nearby and remote areas, offering the potential to control the activity of brain networks. Understanding how exogenous electrical signals perturb such networks in humans is key to its clinical translation. To investigate this, we applied electrical stimulation to subregions of the medial temporal lobe in 26 neurosurgical patients fitted with indwelling electrodes. Networks of low-frequency (5-13 Hz) spectral coherence predicted stimulation-evoked changes in theta (5-8 Hz) power, but only when stimulation was applied in or adjacent to white matter. Furthermore, these power changes aligned with control-theoretic predictions of how exogenous stimulation flows through complex networks, such as a dispersal of induced activity when functional hubs are targeted. Our results demonstrate that functional connectivity is predictive of causal changes in the brain, but that access to structural connections is necessary to observe such effects.
Quantitative assessment of finger tapping characteristics in mild cognitive impairment, Alzheimer’s disease, and Parkinson’s disease

D. Roalf, Petra E. Rupert, D. Mechanic-Hamilton, L. Brennan, J. Duda, D. Weintraub, J. Trojanowski, D. Wolk, and P. Moberg

Journal of neurology, Apr 2018

Cited by 116

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BackgroundFine motor impairments are common in neurodegenerative disorders, yet standardized, quantitative measurements of motor abilities are uncommonly used in neurological practice. Thus, understanding and comparing fine motor abilities across disorders have been limited.ObjectivesThe current study compared differences in finger tapping, inter-tap interval, and variability in Alzheimer’s disease (AD), Parkinson’s disease (PD), mild cognitive impairment (MCI), and healthy older adults (HOA).MethodsFinger tapping was measured using a highly sensitive light-diode finger tapper. Total number of finger taps, inter-tap interval, and intra-individual variability (IIV) of finger tapping was measured and compared in AD (n = 131), PD (n = 63), MCI (n = 46), and HOA (n = 62), controlling for age and sex.ResultsAll patient groups had fine motor impairments relative to HOA. AD and MCI groups produced fewer taps with longer inter-tap interval and higher IIV compared to HOA. The PD group, however, produced more taps with shorter inter-tap interval and higher IIV compared to HOA.ConclusionsDisease-specific changes in fine motor function occur in the most common neurodegenerative diseases. The findings suggest that alterations in finger tapping patterns are common in AD, MCI, and PD. In addition, the present results underscore the importance of motor dysfunction even in neurodegenerative disorders without primary motor symptoms.
Characterizing the human hippocampus in aging and Alzheimer’s disease using a computational atlas derived from ex vivo MRI and histology

D. Adler, L. Wisse, R. Ittyerah, J. Pluta, Song-Lin Ding, Long Xie, Jiancong Wang, Salmon Kadivar, J. Robinson, T. Schuck, J. Trojanowski, M. Grossman, J. Detre, M. Elliott, J. Toledo, Wei-Xia Liu, S. Pickup, Michael I. Miller, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

In Proceedings of the National Academy of Sciences of the United States of America, Mar 2018

Cited by 178

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Predictive control of electrophysiological network architecture using direct, single-node neurostimulation in humans

A. Khambhati, Ari E. Kahn, J. Costantini, Youssef Ezzyat, E. Solomon, R. Gross, B. Jobst, S. Sheth, K. Zaghloul, G. Worrell, S. Seger, B. Lega, S. Weiss, M. Sperling, R. Gorniak, Sandhitsu R. Das, J. Stein, D. Rizzuto, M. Kahana, Timothy H. Lucas, K. Davis, J. Tracy, and D. Bassett

bioRxiv, Mar 2018

Cited by 8

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Chronically implantable neurostimulation devices are becoming a clinically viable option for treating patients with neurological disease and psychiatric disorders. Neurostimulation offers the ability to probe and manipulate distributed networks of interacting brain areas in dysfunctional circuits. Here, we use tools from network control theory to examine the dynamic reconfiguration of functionally interacting neuronal ensembles during targeted neurostimulation of cortical and subcortical brain structures. By integrating multi-modal intracranial recordings and diffusion tensor imaging from patients with drug-resistant epilepsy, we test hypothesized structural and functional rules that predict altered patterns of synchronized local field potentials. We demonstrate the ability to predictably reconfigure functional interactions depending on stimulation strength and location. Stimulation of areas with structurally weak connections largely modulates the functional hubness of downstream areas and concurrently propels the brain towards more difficult-to-reach dynamical states. By using focal perturbations to bridge large-scale structure, function, and markers of behavior, our findings suggest that stimulation may be tuned to influence different scales of network interactions driving cognition.
Automated Multi-Atlas Segmentation of Hippocampal and Extrahippocampal Subregions in Alzheimer’s Disease at 3T and 7T: What Atlas Composition Works Best?

Long Xie, R. Shinohara, R. Ittyerah, H. Kuijf, J. Pluta, K. Blom, M. Kooistra, Y. Reijmer, H. Koek, J. Zwanenburg, Hong-Zhi Wang, P. Luijten, M. Geerlings, Sandhitsu R. Das, G. Biessels, D. Wolk, Paul Yushkevich, and L. Wisse

Journal of Alzheimer’s disease : JAD, Mar 2018

Cited by 12

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Background: Multi-atlas segmentation, a popular technique implemented in the Automated Segmentation of Hippocampal Subfields (ASHS) software, utilizes multiple expert-labelled images (“atlases”) to delineate medial temporal lobe substructures. This multi-atlas method is increasingly being employed in early Alzheimer’s disease (AD) research, it is therefore becoming important to know how the construction of the atlas set in terms of proportions of controls and patients with mild cognitive impairment (MCI) and/or AD affects segmentation accuracy. Objective: To evaluate whether the proportion of controls in the training sets affects the segmentation accuracy of both controls and patients with MCI and/or early AD at 3T and 7T. Methods: We performed cross-validation experiments varying the proportion of control subjects in the training set, ranging from a patient-only to a control-only set. Segmentation accuracy of the test set was evaluated by the Dice similarity coeffiecient (DSC). A two-stage statistical analysis was applied to determine whether atlas composition is linked to segmentation accuracy in control subjects and patients, for 3T and 7T. Results: The different atlas compositions did not significantly affect segmentation accuracy at 3T and for patients at 7T. For controls at 7T, including more control subjects in the training set significantly improves the segmentation accuracy, but only marginally, with the maximum of 0.0003 DSC improvement per percent increment of control subject in the training set. Conclusion: ASHS is robust in this study, and the results indicate that future studies investigating hippocampal subfields in early AD populations can be flexible in the selection of their atlas compositions.
Closed-loop stimulation of temporal cortex rescues functional networks and improves memory

Youssef Ezzyat, Paul A. Wanda, Deborah F. Levy, Allison Kadel, Ada Aka, Isaac Pedisich, M. Sperling, A. Sharan, B. Lega, Alexis Burks, R. Gross, Cory S. Inman, B. Jobst, Mark A. Gorenstein, K. Davis, G. Worrell, M. Kucewicz, J. Stein, R. Gorniak, Sandhitsu R. Das, D. Rizzuto, and M. Kahana

Nature Communications, Feb 2018

Cited by 306

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Memory failures are frustrating and often the result of ineffective encoding. One approach to improving memory outcomes is through direct modulation of brain activity with electrical stimulation. Previous efforts, however, have reported inconsistent effects when using open-loop stimulation and often target the hippocampus and medial temporal lobes. Here we use a closed-loop system to monitor and decode neural activity from direct brain recordings in humans. We apply targeted stimulation to lateral temporal cortex and report that this stimulation rescues periods of poor memory encoding. This system also improves later recall, revealing that the lateral temporal cortex is a reliable target for memory enhancement. Taken together, our results suggest that such systems may provide a therapeutic approach for treating memory dysfunction. Memory lapses can occur due to ineffective encoding, but it is unclear if targeted brain stimulation can improve memory performance. Here, authors use a closed-loop system to decode and stimulate periods of ineffective encoding, showing that stimulation of lateral temporal cortex can enhance memory.
Tau PET imaging predicts cognition in atypical variants of Alzheimer’s disease

J. Phillips, Sandhitsu R. Das, C. Mcmillan, D. Irwin, Emily Roll, Fulvio Da Re, I. Nasrallah, D. Wolk, and M. Grossman

Human Brain Mapping, Feb 2018

Cited by 61

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Defining SNAP by cross-sectional and longitudinal definitions of neurodegeneration

L. Wisse, Sandhitsu R. Das, C. Davatzikos, B. Dickerson, Sharon X. Xie, Paul Yushkevich, and D. Wolk

NeuroImage : Clinical, Feb 2018

Cited by 18

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Introduction Suspected non-Alzheimer’s pathophysiology (SNAP) is a biomarker driven designation that represents a heterogeneous group in terms of etiology and prognosis. SNAP has only been identified by cross-sectional neurodegeneration measures, whereas longitudinal measures might better reflect “active” neurodegeneration and might be more tightly linked to prognosis. We compare neurodegeneration defined by cross-sectional ‘hippocampal volume’ only (SNAP/L−) versus both cross-sectional and longitudinal ‘hippocampal atrophy rate’ (SNAP/L+) and investigate how these definitions impact prevalence and the clinical and biomarker profile of SNAP in Mild Cognitive Impairment (MCI). Methods 276 MCI patients from ADNI-GO/2 were designated amyloid “positive” (A+) or “negative” (A−) based on their florbetapir scan and neurodegeneration ‘positive’ or ‘negative’ based on cross-sectional hippocampal volume and longitudinal hippocampal atrophy rate. Results 74.1% of all SNAP participants defined by the cross-sectional definition of neurodegeneration also met the longitudinal definition of neurodegeneration, whereas 25.9% did not. SNAP/L+ displayed larger white matter hyperintensity volume, a higher conversion rate to dementia over 5 years and a steeper decline on cognitive tasks compared to SNAP/L− and the A- CN group. SNAP/L− had more abnormal values on neuroimaging markers and worse performance on cognitive tasks than the A- CN group, but did not show a difference in dementia conversion rate or longitudinal cognition. Discussion Using a longitudinal definition of neurodegeneration in addition to a cross-sectional one identifies SNAP participants with significant cognitive decline and a worse clinical prognosis for which cerebrovascular disease may be an important driver.
Early Tau Burden Correlates with Higher Rate of Atrophy in Transentorhinal Cortex

Long Xie, Sandhitsu R. Das, L. Wisse, R. Ittyerah, Paul Yushkevich, and D. Wolk

Journal of Alzheimer’s disease : JAD, Feb 2018

Cited by 36

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Neurofibrillary tangle (NFT) pathology is linked to neurodegeneration in the medial temporal lobe (MTL). Using a tailored pipeline, we correlated atrophy rate, as measured from retrospective longitudinal MRI, with NFT burden, measured from 18F-AV-1451 PET, within MTL regions of earliest NFT pathology. In amyloid-β positive but not amyloid-β negative individuals, we found significant correlation between 18F-AV-1451 uptake and atrophy rate that was strongest in the transentorhinal cortex, the first region with NFT pathology. This supports the role of NFTs in driving neurodegeneration and the utility of 18F-AV-1451 PET and structural measurement of transentorhinal cortex in tracking early tau-mediated disease progression.
Longitudinal and cross-sectional structural MRI correlates of AV-1451 uptake

Sandhitsu R. Das, Long Xie, L. Wisse, R. Ittyerah, N. Tustison, B. Dickerson, Paul Yushkevich, A. David, and Wolk

Feb 2018
Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome

C. Davatzikos, Saima Rathore, S. Bakas, Sarthak Pati, M. Bergman, Ratheesh Kalarot, P. Sridharan, A. Gastounioti, Nariman Jahani, E. Cohen, H. Akbari, B. Tunç, J. Doshi, D. Parker, Michael H. Hsieh, Aristeidis Sotiras, Hong-Ming Li, Y. Ou, R. Doot, M. Bilello, Yong Fan, R. Shinohara, Paul Yushkevich, R. Verma, and D. Kontos

Journal of Medical Imaging, Feb 2018

Cited by 202

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Quantifying effects of Alzheimer ’ s disease on the human hippocampus using an ex vivo atlas combining MRI and histology

L. Wisse, D. Adler, R. Ittyerah, J. Pluta, Song-Lin Ding, Long Xie, Jiancong, Wang, Salmon Kadivar, J. Robinson, T. Schuck, J. Trojanowski, M. Grossman, J. Detre, M. Elliott, J. Toledo, Wei-Xia Liu, S. Pickup, Michael I. Miller, Sandhitsu, R. Das, D. Wolk, and Paul Yushkevich

Feb 2018
IC-P-173 PATTERN OF CORTICALTHINNING AND SHAPE VARIABILITY RELATED TO ALZHEIMER’S DISEASE IN REGIONS AFFECTED BY EARLIEST NEUROFIBRILLARY TANGLE PATHOLOGY

Long Xie, L. Wisse, Sandhitsu R. Das, R. Ittyerah, Paul Yushkevich, and D. Wolk

Feb 2018

2017

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

A. Young, Razvan V. Marinescu, N. Oxtoby, M. Bocchetta, K. Yong, Nicholas C. Firth, D. Cash, David L. Thomas, K. Dick, Jorge Cardoso, J. V. Swieten, B. Borroni, D. Galimberti, Mario Masellis, M. Tartaglia, James B. Rowe, C. Graff, F. Tagliavini, G. Frisoni, R. Laforce, E. Finger, Alexandre Mendonça, S. Sorbi, J. Warren, Sebastian J Crutch, Nick C. Fox, S. Ourselin, Jonathan M. Schott, J. Rohrer, Daniel C Alexander, Christin Silvana Andrea Luisa Giuliano Sandra Maura Marie C Andersson Archetti Arighi Benussi Binetti Black Co, Christin Andersson, S. Archetti, A. Arighi, L. Benussi, G. Binetti, Sandra E. Black, M. Cosseddu, Marie Fallström, C. Ferreira, C. Fenoglio, Morris Freedman, G. Fumagalli, S. Gazzina, Roberta Ghidoni, M. Grisoli, Vesna Jelic, L. Jiskoot, Ron Keren, G. Lombardi, and 330 more authors

Nature Communications, Dec 2017

Cited by 95

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The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique—Subtype and Stage Inference (SuStaIn)—able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer’s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 × 10−4) or temporal stage (p = 3.96 × 10−5). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine. Progressive diseases tend to be heterogeneous in their underlying aetiology mechanism, disease manifestation, and disease time course. Here, Young and colleagues devise a computational method to account for both phenotypic heterogeneity and temporal heterogeneity, and demonstrate it using two neurodegenerative disease cohorts.
The medial temporal lobe organizes memory across time and space: Causal evidence from brain stimulation

A. Goyal, Jonathan F. Miller, Andrew J. Watrous, Sang-Ah Lee, Tom Coffey, M. Sperling, A. Sharan, G. Worrell, Berry Brent, B. Lega, B. Jobst, K. Davis, R. Gross, S. Sheth, Youssef Ezzyat, Sandhitsu R. Das, J. Stein, R. Gorniak, M. Kahana, D. Rizzuto, and J. Jacobs

bioRxiv, Nov 2017

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The medial temporal lobe (MTL) is widely implicated in supporting episodic memory and navigation, but its precise functional role in organizing memory across time and space remains elusive. Here we examine the specific cognitive processes implemented by MTL structures (hippocampus and entorhinal cortex) to organize memory by using electrical brain stimulation, leveraging its ability to establish causal links between brain regions and features of behavior. We studied neurosurgical patients who performed spatial-navigation and verbal-episodic memory tasks while brain stimulation was applied in various regions during learning. During the verbal memory task, stimulation in the MTL disrupted the temporal organization of encoded memories such that items learned with stimulation tended to be recalled in a more randomized order. During the spatial task, MTL stimulation impaired subjects’ abilities to remember items using view-independent (allocentric) navigation strategies. These stimulation effects were specific to the MTL. Our findings thus provide the first causal demonstration in humans of the specific memory processes that are performed by the MTL to encode when and where events occurred. Significance Statement Numerous studies have implicated the medial temporal lobe (MTL) in encoding spatial and temporal memories, but they have not been able to causally demonstrate the nature of the cognitive processes by which this occurs in real-time. Electrical brain stimulation is able to demonstrate causal links between a brain region and a given function with high temporal precision. By examining behavior in a memory task as subjects received MTL stimulation, we provide the first causal evidence demonstrating the role of the MTL in organizing the spatial and temporal aspects of episodic memory.
Electrophysiological Signatures of Spatial Boundaries in the Human Subiculum

Sang-Ah Lee, Jonathan F. Miller, Andrew J. Watrous, M. Sperling, A. Sharan, G. Worrell, Brent M. Berry, Joshua P. Aronson, K. Davis, R. Gross, B. Lega, S. Sheth, Sandhitsu R. Das, J. Stein, R. Gorniak, D. Rizzuto, and J. Jacobs

The Journal of Neuroscience, Nov 2017

Cited by 63

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Environmental boundaries play a crucial role in spatial navigation and memory across a wide range of distantly related species. In rodents, boundary representations have been identified at the single-cell level in the subiculum and entorhinal cortex of the hippocampal formation. Although studies of hippocampal function and spatial behavior suggest that similar representations might exist in humans, boundary-related neural activity has not been identified electrophysiologically in humans until now. To address this gap in the literature, we analyzed intracranial recordings from the hippocampal formation of surgical epilepsy patients (of both sexes) while they performed a virtual spatial navigation task and compared the power in three frequency bands (1–4, 4–10, and 30–90 Hz) for target locations near and far from the environmental boundaries. Our results suggest that encoding locations near boundaries elicited stronger theta oscillations than for target locations near the center of the environment and that this difference cannot be explained by variables such as trial length, speed, movement, or performance. These findings provide direct evidence of boundary-dependent neural activity localized in humans to the subiculum, the homolog of the hippocampal subregion in which most boundary cells are found in rodents, and indicate that this system can represent attended locations that rather than the position of one’s own body. SIGNIFICANCE STATEMENT Spatial computations using environmental boundaries are an integral part of the brain’s spatial mapping system. In rodents, border/boundary cells in the subiculum and entorhinal cortex reveal boundary coding at the single-neuron level. Although there is good reason to believe that such representations also exist in humans, the evidence has thus far been limited to functional neuroimaging studies that broadly implicate the hippocampus in boundary-based navigation. By combining intracranial recordings with high-resolution imaging of hippocampal subregions, we identified a neural marker of boundary representation in the human subiculum.
Tau PET Imaging Predicts Cognition in Atypical Variants of Alzheimer’s Disease

Jeffrey S. Phillips, Sandhitsu R. Das, C. McMillan, D. Irwin, Emily Roll, F. Da Re, I. Nasrallah, D. Wolk, and M. Grossman

Human brain mapping, Nov 2017

Cited by 63

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Accumulation of paired helical filament tau contributes to neurodegeneration in Alzheimer’s disease (AD). 18F‐flortaucipir is a positron emission tomography (PET) radioligand sensitive to tau in AD, but its clinical utility will depend in part on its ability to predict cognitive symptoms in diverse dementia phenotypes associated with selective, regional uptake. We examined associations between 18F‐flortaucipir and cognition in 14 mildly‐impaired patients (12 with cerebrospinal fluid analytes consistent with AD pathology) who had amnestic (n = 5) and non‐amnestic AD syndromes, including posterior cortical atrophy (PCA, n = 5) and logopenic‐variant primary progressive aphasia (lvPPA, n = 4). Amnestic AD patients had deficits in memory; lvPPA in language; and both amnestic AD and PCA patients in visuospatial function. Associations with cognition were tested using sparse regression and compared to associations in anatomical regions‐of‐interest (ROIs). 18F‐flortaucipir uptake was expected to show regionally‐specific correlations with each domain. In multivariate analyses, uptake was elevated in neocortical areas specifically associated with amnestic and non‐amnestic syndromes. Uptake in left anterior superior temporal gyrus accounted for 67% of the variance in language performance. Uptake in right lingual gyrus predicted 85% of the variance in visuospatial performance. Memory was predicted by uptake in right fusiform gyrus and cuneus as well as a cluster comprising right anterior hippocampus and amygdala; this eigenvector explained 57% of the variance in patients’ scores. These results provide converging evidence for associations between 18F‐flortaucipir uptake, tau pathology, and patients’ cognitive symptoms.
Hippocampal gamma‐slow oscillation coupling in macaques during sedation and sleep

A. Richardson, Xilin Liu, Pauline K. Weigand, Eric Hudgins, J. Stein, Sandhitsu R. Das, A. Proekt, M. Kelz, Milin Zhang, J. Spiegel, and T. Lucas

Hippocampus, Nov 2017

Cited by 9

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Mapping the structural and functional network architecture of the medial temporal lobe using 7T MRI

Preya Shah, D. Bassett, L. Wisse, J. Detre, J. Stein, Paul Yushkevich, R. Shinohara, J. Pluta, Elijah Valenciano, Molly Daffner, D. Wolk, M. Elliott, B. Litt, K. Davis, and Sandhitsu R. Das

Human brain mapping, Nov 2017

Cited by 65

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Medial temporal lobe (MTL) subregions play integral roles in memory function and are differentially affected in various neurological and psychiatric disorders. The ability to structurally and functionally characterize these subregions may be important to understanding MTL physiology and diagnosing diseases involving the MTL. In this study, we characterized network architecture of the MTL in healthy subjects (n = 31) using both resting state functional MRI and MTL‐focused T2‐weighted structural MRI at 7 tesla. Ten MTL subregions per hemisphere, including hippocampal subfields and cortical regions of the parahippocampal gyrus, were segmented for each subject using a multi‐atlas algorithm. Both structural covariance matrices from correlations of subregion volumes across subjects, and functional connectivity matrices from correlations between subregion BOLD time series were generated. We found a moderate structural and strong functional inter‐hemispheric symmetry. Several bilateral hippocampal subregions (CA1, dentate gyrus, and subiculum) emerged as functional network hubs. We also observed that the structural and functional networks naturally separated into two modules closely corresponding to (a) bilateral hippocampal formations, and (b) bilateral extra‐hippocampal structures. Finally, we found a significant correlation in structural and functional connectivity (r = 0.25). Our findings represent a comprehensive analysis of network topology of the MTL at the subregion level. We share our data, methods, and findings as a reference for imaging methods and disease‐based research.
Joint Intensity Fusion Image Synthesis Applied to Multiple Sclerosis Lesion Segmentation

G. Fleishman, A. M. Valcarcel, D. Pham, Snehashis Roy, P. Calabresi, Paul Yushkevich, R. Shinohara, and I. Oguz

In BrainLes@MICCAI, Sep 2017

Cited by 9

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We propose a new approach to Multiple Sclerosis lesion segmentation that utilizes synthesized images. A new method of image synthesis is considered: joint intensity fusion (JIF). JIF synthesizes an image from a library of deformably registered and intensity normalized atlases. Each location in the synthesized image is a weighted average of the registered atlases; atlas weights vary spatially. The weights are determined using the joint label fusion (JLF) framework. The primary methodological contribution is the application of JLF to MRI signal directly rather than labels. Synthesized images are then used as additional features in a lesion segmentation task using the OASIS classifier, a logistic regression model on intensities from multiple modalities. The addition of JIF synthesized images improved the Dice-Sorensen coefficient (relative to manually drawn gold standards) of lesion segmentations over the standard model segmentations by 0.0462 ± 0.0050 (mean ± standard deviation) at optimal threshold over all subjects and 10 separate training/testing folds.
Dice Overlap Measures for Objects of Unknown Number: Application to Lesion Segmentation

I. Oguz, A. Carass, D. Pham, Snehashis Roy, Nagesh Subbana, P. Calabresi, Paul Yushkevich, R. Shinohara, and Jerry L Prince

In BrainLes@MICCAI, Sep 2017

Cited by 11

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The Dice overlap ratio is commonly used to evaluate the performance of image segmentation algorithms. While Dice overlap is very useful as a standardized quantitative measure of segmentation accuracy in many applications, it offers a very limited picture of segmentation quality in complex segmentation tasks where the number of target objects is not known a priori, such as the segmentation of white matter lesions or lung nodules. While Dice overlap can still be used in these applications, segmentation algorithms may perform quite differently in ways not reflected by differences in their Dice score. Here we propose a new set of evaluation techniques that offer new insights into the behavior of segmentation algorithms. We illustrate these techniques with a case study comparing two popular multiple sclerosis (MS) lesion segmentation algorithms: OASIS and LesionTOADS.
Gradient Boosted Trees for Corrective Learning

Baris U. Oguz, R. Shinohara, Paul Yushkevich, and I. Oguz

In MLMI@MICCAI, Sep 2017

Cited by 12

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Random forests (RF) have long been a widely popular method in medical image analysis. Meanwhile, the closely related gradient boosted trees (GBT) have not become a mainstream tool in medical imaging despite their attractive performance, perhaps due to their computational cost. In this paper, we leverage the recent availability of an efficient open-source GBT implementation to illustrate the GBT method in a corrective learning framework, in application to the segmentation of the caudate nucleus, putamen and hippocampus. The size and shape of these structures are used to derive important biomarkers in many neurological and psychiatric conditions. However, the large variability in deep gray matter appearance makes their automated segmentation from MRI scans a challenging task. We propose using GBT to improve existing segmentation methods. We begin with an existing ‘host’ segmentation method to create an estimate surface. Based on this estimate, a surface-based sampling scheme is used to construct a set of candidate locations. GBT models are trained on features derived from the candidate locations, including spatial coordinates, image intensity, texture, and gradient magnitude. The classification probabilities from the GBT models are used to calculate a final surface estimate. The method is evaluated on a public dataset, with a 2-fold cross-validation. We use a multi-atlas approach and FreeSurfer as host segmentation methods. The mean reduction in surface distance error metric for FreeSurfer was 0.2 – 0.3 mm, whereas for multi-atlas segmentation, it was 0.1mm for each of caudate, putamen and hippocampus. Importantly, our approach outperformed an RF model trained on the same features (p < 0.05 on all measures). Our method is readily generalizable and can be applied to a wide range of medical image segmentation problems and allows any segmentation method to be used as input.
Spatiotemporal Segmentation and Modeling of the Mitral Valve in Real-Time 3D Echocardiographic Images

A. Pouch, A. H. Aly, Eric K. Lai, N. Yushkevich, R. H. Stoffers, J. Gorman, A. Cheung, R. Gorman, and Paul Yushkevich

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Sep 2017

Cited by 9

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Transesophageal echocardiography is the primary imaging modality for preoperative assessment of mitral valves with ischemic mitral regurgitation (IMR). While there are well known echocardiographic insights into the 3D morphology of mitral valves with IMR, such as annular dilation and leaflet tethering, less is understood about how quantification of valve dynamics can inform surgical treatment of IMR or predict short-term recurrence of the disease. As a step towards filling this knowledge gap, we present a novel framework for 4D segmentation and geometric modeling of the mitral valve in real-time 3D echocardiography (rt-3DE). The framework integrates multi-atlas label fusion and template-based medial modeling to generate quantitatively descriptive models of valve dynamics. The novelty of this work is that temporal consistency in the rt-3DE segmentations is enforced during both the segmentation and modeling stages with the use of groupwise label fusion and Kalman filtering. The algorithm is evaluated on rt-3DE data series from 10 patients: five with normal mitral valve morphology and five with severe IMR. In these 10 data series that total 207 individual 3DE images, each 3DE segmentation is validated against manual tracing and temporal consistency between segmentations is demonstrated. The ultimate goal is to generate accurate and consistent representations of valve dynamics that can both visually and quantitatively provide insight into normal and pathological valve function.
Self‐gated MRI of multiple beat morphologies in the presence of arrhythmias

F. Contijoch, Srikanth K. Iyer, J. Pilla, Paul Yushkevich, J. Gorman, R. Gorman, H. Litt, Yuchi Han, and W. Witschey

Magnetic Resonance in Medicine, Aug 2017

Cited by 32

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Multiple Sclerosis Lesion Segmentation Using Joint Label Fusion

M. Dong, I. Oguz, Nagesh Subbana, P. Calabresi, R. Shinohara, and Paul Yushkevich

In Patch-MI@MICCAI, Aug 2017

Cited by 4

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This paper adapts the joint label fusion (JLF) multi-atlas image segmentation algorithm to the problem of multiple sclerosis (MS) lesion segmentation in multi-modal MRI. Conventionally, JLF requires a set of atlas images to be co-registered to the target image using deformable registration. However, given the variable spatial distribution of lesions in the brain, whole-brain deformable registration is unlikely to line up lesions between atlases and the target image. As a solution, we propose to first pre-segment the target image using an intensity regression based technique, yielding a set of “candidate” lesions. Each “candidate” lesion is then matched to a set of similar lesions in the atlas based on location and size; and deformable registration and JLF are applied at the level of the “candidate” lesion. The approach is evaluated on a dataset of 74 subjects with MS and shown to improve Dice similarity coefficient with reference manual segmentation by 12% over intensity regression technique.
A tract-specific approach to assessing white matter in preterm infants

D. Pecheva, Paul Yushkevich, D. Batalle, E. Hughes, P. Aljabar, J. Wurie, J. Hajnal, A. Edwards, D. Alexander, S. Counsell, and Hui Zhang

Neuroimage, Aug 2017

Cited by 34

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&NA; Diffusion‐weighted imaging (DWI) is becoming an increasingly important tool for studying brain development. DWI analyses relying on manually‐drawn regions of interest and tractography using manually‐placed waypoints are considered to provide the most accurate characterisation of the underlying brain structure. However, these methods are labour‐intensive and become impractical for studies with large cohorts and numerous white matter (WM) tracts. Tract‐specific analysis (TSA) is an alternative WM analysis method applicable to large‐scale studies that offers potential benefits. TSA produces a skeleton representation of WM tracts and projects the group’s diffusion data onto the skeleton for statistical analysis. In this work we evaluate the performance of TSA in analysing preterm infant data against results obtained from native space tractography and tract‐based spatial statistics. We evaluate TSA’s registration accuracy of WM tracts and assess the agreement between native space data and template space data projected onto WM skeletons, in 12 tracts across 48 preterm neonates. We show that TSA registration provides better WM tract alignment than a previous protocol optimised for neonatal spatial normalisation, and that TSA projects FA values that match well with values derived from native space tractography. We apply TSA for the first time to a preterm neonatal population to study the effects of age at scan on WM tracts around term equivalent age. We demonstrate the effects of age at scan on DTI metrics in commissural, projection and association fibres. We demonstrate the potential of TSA for WM analysis and its suitability for infant studies involving multiple tracts. Graphical abstract Figure. No caption available. HighlightsEvaluation of tract‐specific analysis (TSA) for white matter studies in infants.TSA improves white matter tract alignment over scalar‐based registration.TSA closely approximates native space tractography DTI values.The first application of TSA to a neonatal population.
[P3–294]: CROSS‐SECTIONAL AND LONGITUDINAL BRAIN NETWORK ATROPHY IN DIFFERENT STAGES OF ALZHEIMER’s DISEASE AND IN RELATION TO COGNITIVE MEASURES

J. Arendonk, L. Wisse, Sandhitsu R. Das, N. Tustison, and D. Wolk

Alzheimer’s & Dementia, Jul 2017

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[O1–12–06]: RELATIONSHIP BETWEEN LONGITUDINAL STRUCTURAL ATROPHY AND AV1451 TAU UPTAKE IN AMYLOID‐POSITIVE INDIVIDUALS

Sandhitsu R. Das, Long Xie, L. Wisse, R. Ittyerah, N. Tustison, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2017

DOI
Hippocampal gamma-slow oscillation coupling in macaques during sedation and sleep

Andrew G. Richardson, Xilin Liu, Pauline K. Weigand, Eric Hudgins, J. Stein, Sandhitsu R. Das, A. Proekt, M. Kelz, Milin Zhang, J. Spiegel, and Timothy H. Lucas

Hippocampus, Jul 2017

Cited by 9

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Behavioral and neurophysiological evidence suggests that the slow (≤1 Hz) oscillation (SO) during sleep plays a role in consolidating hippocampal (HIPP)‐dependent memories. The effects of the SO on HIPP activity have been studied in rodents and cats both during natural sleep and during anesthetic administration titrated to mimic sleep‐like slow rhythms. In this study, we sought to document these effects in primates. First, HIPP field potentials were recorded during ketamine‐dexmedetomidine sedation and during natural sleep in three rhesus macaques. Sedation produced regionally‐specific slow and gamma (∼40 Hz) oscillations with strong coupling between the SO phase and gamma amplitude. These same features were seen in slow‐wave sleep (SWS), but the coupling was weaker and the coupled gamma oscillation had a higher frequency (∼70 Hz) during SWS. Second, electrical stimuli were delivered to HIPP afferents in the parahippocampal gyrus (PHG) during sedation to assess the effects of sleep‐like SO on excitability. Gamma bursts after the peak of SO cycles corresponded to periods of increased gain of monosynaptic connections between the PHG and HIPP. However, the two PHG‐HIPP connectivity gains during sedation were both substantially lower than when the animal was awake. We conclude that the SO is correlated with rhythmic excitation and inhibition of the PHG‐HIPP network, modulating connectivity and gamma generators intrinsic to this network. Ketamine‐dexmedetomidine sedation produces a similar effect, but with a decreased contribution of the PHG to HIPP activity and gamma generation.
[IC‐P‐109]: REGIONAL AV1451 UPTAKE AND CORTICAL THICKNESS IN RELATION TO MEMORY, LANGUAGE AND EXECUTIVE FUNCTIONING IN AMYLOID‐POSITIVE SUBJECTS

L. Wisse, Sandhitsu R. Das, Long Xie, R. Ittyerah, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2017

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[O1–06–01]: REGIONAL AV1451 UPTAKE AND CORTICAL THICKNESS IN RELATION TO MEMORY, LANGUAGE AND EXECUTIVE FUNCTIONING IN AMYLOID‐POSITIVE SUBJECTS

L. Wisse, Sandhitsu R. Das, Long Xie, R. Ittyerah, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2017

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[P4–507]: ALZHEIMER’s DISEASE AND THE HIPPOCAMPUS: NOVEL INSIGHTS FROM AN EX VIVO COMPUTATIONAL ATLAS COMBINING MRI AND HISTOLOGY

L. Wisse, D. Adler, R. Ittyerah, J. Pluta, Song-Lin Ding, Long Xie, Jiancong Wang, Salmon Kadivar, J. Robinson, T. Schuck, J. Trojanowski, M. Grossman, J. Detre, M. Elliott, J. Toledo, Wei-Xia Liu, S. Pickup, Sandhitsu R. Das, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Jul 2017

DOI
[IC‐P‐153]: TAU BURDEN CORRELATES WITH LONGITUDINAL STRUCTURAL CHANGE IN REGIONS AFFECTED BY EARLIEST NEUROFIBRILLARY TANGLE PATHOLOGY IN AMYLOID‐β POSITIVE ADNI SUBJECTS

Long Xie, Sandhitsu R. Das, L. Wisse, R. Ittyerah, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2017

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[P4–249]: TAU BURDEN CORRELATES WITH LONGITUDINAL STRUCTURAL CHANGE IN REGIONS AFFECTED BY EARLIEST NEUROFIBRILLARY TANGLE PATHOLOGY IN AMYLOID‐β‐POSITIVE ADNI SUBJECTS

Long Xie, Sandhitsu R. Das, L. Wisse, R. Ittyerah, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2017

DOI PDF
ITK-SNAP: An Intractive Medical Image Segmentation Tool to Meet the Need for Expert-Guided Segmentation of Complex Medical Images

Paul Yushkevich, and G. Gerig

IEEE Pulse, Jul 2017

Cited by 137

DOI
Theta band power increases in the posterior hippocampus predict successful episodic memory encoding in humans

Jui-Jui Lin, M. Rugg, Sandhitsu R. Das, J. Stein, D. Rizzuto, M. Kahana, and B. Lega

Hippocampus, Jun 2017

Cited by 103

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Functional differences in the anterior and posterior hippocampus during episodic memory processing have not been examined in human electrophysiological data. This is in spite of strong evidence for such differences in rodent data, including greater place cell specificity in the dorsal hippocampus, greater sensitivity to the aversive or motivational content of memories in ventral regions, connectivity analyses identifying preferential ventral hippocampal connections with the amygdala, and gene expression analyses identifying a dorsal–ventral gradient. We asked if memory‐related oscillatory patterns observed in human hippocampal recordings, including the gamma band and slow‐theta (2.5–5 Hz) subsequent memory effects, would exhibit differences along the longitudinal axis and between hemispheres. We took advantage of a new dataset of stereo electroencephalography patients with simultaneous, robotically targeted anterior, and posterior hippocampal electrodes to directly compare oscillatory subsequent memory effects during item encoding. This same data set allowed us to examine left–right connectivity and hemispheric differences in hippocampal oscillatory patterns. Our data suggest that a power increase during successful item encoding in the 2.5–5 Hz slow‐theta frequency range preferentially occurs in the posterior hippocampus during the first 1,000 ms after item presentation, while a gamma band power increase is stronger in the dominant hemisphere. This dominant–nondominant pattern in the gamma range appears to reverse during item retrieval, however. Intrahippocampal phase coherence was found to be stronger during successful item encoding. Our phase coherence data are also consistent with existing reports of a traveling wave for theta oscillations propagating along the septotemporal (longitudinal) axis of the human hippocampus. We examine how our findings fit with theories of functional specialization along the hippocampal axis.
Mapping of pain circuitry in early post-natal development using manganese-enhanced MRI in rats.

M. Sperry, Benjamin M. Kandel, S. Wehrli, K. Bass, Sandhitsu R. Das, Paramveer S. Dhillon, James C. Gee, and Gordon A Barr

Neuroscience, Jun 2017

Cited by 14

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Neural Correlates of Verbal Episodic Memory and Lexical Retrieval in Logopenic Variant Primary Progressive Aphasia

Khaing T. Win, J. Pluta, Paul Yushkevich, D. Irwin, C. McMillan, K. Rascovsky, D. Wolk, and M. Grossman

Frontiers in Neuroscience, Jun 2017

Cited by 49

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Objective: Logopenic variant primary progressive aphasia (lvPPA) is commonly associated with Alzheimer’s disease (AD) pathology. But lvPPA patients display different cognitive and anatomical profile from the common clinical AD patients, whose verbal episodic memory is primarily affected. Reports of verbal episodic memory difficulty in lvPPA are inconsistent, and we hypothesized that their lexical retrieval impairment contributes to verbal episodic memory performance and is associated with left middle temporal gyrus atrophy. Methods: We evaluated patients with lvPPA (n = 12) displaying prominent word-finding and repetition difficulties, and a demographically-matched cohort of clinical Alzheimer’s disease (AD, n = 26), and healthy seniors (n = 16). We assessed lexical retrieval with confrontation naming and verbal episodic memory with delayed free recall. Whole-brain regressions related naming and delayed free recall to gray matter atrophy. Medial temporal lobe (MTL) subfields were examined using high in-plane resolution imaging. Results: lvPPA patients had naming and delayed free recall impairments, but intact recognition memory. In lvPPA, delayed free recall was related to naming; both were associated with left middle temporal gyrus atrophy but not MTL atrophy. Despite cerebrospinal fluid evidence consistent with AD pathology, examination of MTL subfields revealed no atrophy in lvPPA. While AD patients displayed impaired delayed free recall, this deficit did not correlate with naming. Regression analyses related delayed free recall deficits in clinical AD patients to MTL subfield atrophy, and naming to left middle temporal gyrus atrophy. Conclusion: Unlike amnestic AD patients, MTL subfields were not affected in lvPPA patients. Verbal episodic memory deficit observed in lvPPA was unlikely to be due to a hippocampal-mediated mechanism but appeared to be due to poor lexical retrieval. Relative sparing of MTL volume and intact recognition memory are consistent with previous reports of hippocampal-sparing variant cases of AD pathology, where neurofibrillary tangles are disproportionately distributed in cortical areas with relative sparing of the hippocampus. This suggests that AD neuropathology in lvPPA may originate in neuronal networks outside of the MTL, which deviates from the typical Braak staging pattern of spreading pathology in clinical AD.
A protocol for manual segmentation of medial temporal lobe subregions in 7 Tesla MRI

D. Berron, P. Vieweg, A. Hochkeppler, J. Pluta, Song-Lin Ding, A. Maass, A. Luther, L. Xie, S. Das, D. Wolk, T. Wolbers, Paul Yushkevich, E. Düzel, and L. Wisse

NeuroImage : Clinical, May 2017

Cited by 145

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Recent advances in MRI and increasing knowledge on the characterization and anatomical variability of medial temporal lobe (MTL) anatomy have paved the way for more specific subdivisions of the MTL in humans. In addition, recent studies suggest that early changes in many neurodegenerative and neuropsychiatric diseases are better detected in smaller subregions of the MTL rather than with whole structure analyses. Here, we developed a new protocol using 7 Tesla (T) MRI incorporating novel anatomical findings for the manual segmentation of entorhinal cortex (ErC), perirhinal cortex (PrC; divided into area 35 and 36), parahippocampal cortex (PhC), and hippocampus; which includes the subfields subiculum (Sub), CA1, CA2, as well as CA3 and dentate gyrus (DG) which are separated by the endfolial pathway covering most of the long axis of the hippocampus. We provide detailed instructions alongside slice-by-slice segmentations to ease learning for the untrained but also more experienced raters. Twenty-two subjects were scanned (19–32 yrs, mean age = 26 years, 12 females) with a turbo spin echo (TSE) T2-weighted MRI sequence with high-resolution oblique coronal slices oriented orthogonal to the long axis of the hippocampus (in-plane resolution 0.44 × 0.44 mm2) and 1.0 mm slice thickness. The scans were manually delineated by two experienced raters, to assess intra- and inter-rater reliability. The Dice Similarity Index (DSI) was above 0.78 for all regions and the Intraclass Correlation Coefficients (ICC) were between 0.76 to 0.99 both for intra- and inter-rater reliability. In conclusion, this study presents a fine-grained and comprehensive segmentation protocol for MTL structures at 7 T MRI that closely follows recent knowledge from anatomical studies. More specific subdivisions (e.g. area 35 and 36 in PrC, and the separation of DG and CA3) may pave the way for more precise delineations thereby enabling the detection of early volumetric changes in dementia and neuropsychiatric diseases.
Direct Brain Stimulation Modulates Encoding States and Memory Performance in Humans.

Youssef Ezzyat, J. Kragel, John F. Burke, Deborah F. Levy, Anastasia Lyalenko, P. Wanda, Logan O’Sullivan, Katherine B. Hurley, S. Busygin, Isaac Pedisich, M. Sperling, G. Worrell, M. Kucewicz, K. Davis, T. Lucas, Cory S. Inman, B. Lega, B. Jobst, S. Sheth, K. Zaghloul, Michael J. Jutras, J. Stein, Sandhitsu R. Das, R. Gorniak, D. Rizzuto, and M. Kahana

Current biology : CB, May 2017

Cited by 220

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Image Segmentation and Modeling of the Pediatric Tricuspid Valve in Hypoplastic Left Heart Syndrome

A. Pouch, A. H. Aly, A. Lasso, Alexander V. Nguyen, Adam B. Scanlan, F. McGowan, G. Fichtinger, R. Gorman, J. Gorman, Paul Yushkevich, and Matthew A. Jolley

Functional imaging and modeling of the heart : ... International Workshop, FIMH ..., proceedings. FIMH, May 2017

Cited by 17

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Hypoplastic left heart syndrome (HLHS) is a single-ventricle congenital heart disease that is fatal if left unpalliated. In HLHS patients, the tricuspid valve is the only functioning atrioventricular valve, and its competence is therefore critical. This work demonstrates the first automated strategy for segmentation, modeling, and morphometry of the tricuspid valve in transthoracic 3D echocardiographic (3DE) images of pediatric patients with HLHS. After initial landmark placement, the automated segmentation step uses multi-atlas label fusion and the modeling approach uses deformable modeling with medial axis representation to produce patient-specific models of the tricuspid valve that can be comprehensively and quantitatively assessed. In a group of 16 pediatric patients, valve segmentation and modeling attains an accuracy (mean boundary displacement) of 0.8 ± 0.2 mm relative to manual tracing and shows consistency in annular and leaflet measurements. In the future, such image-based tools have the potential to improve understanding and evaluation of tricuspid valve morphology in HLHS and guide strategies for patient care.
Direct Brain Stimulation Modulates Encoding States and Memory Performance in Humans

Youssef Ezzyat, J. Kragel, J. Burke, Deborah F. Levy, Anastasia Lyalenko, Paul A. Wanda, Logan O’Sullivan, Katherine B. Hurley, S. Busygin, Isaac Pedisich, M. Sperling, G. Worrell, M. Kucewicz, K. Davis, Timothy H. Lucas, Cory S. Inman, B. Lega, B. Jobst, S. Sheth, K. Zaghloul, Michael J. Jutras, J. Stein, Sandhitsu R. Das, R. Gorniak, D. Rizzuto, and M. Kahana

Current biology : CB, Apr 2017

Cited by 225

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SUMMARY People often forget information because they fail to effectively encode it. Here, we test the hypothesis that targeted electrical stimulation can modulate neural encoding states and subsequent memory outcomes. Using recordings from neurosurgical epilepsy patients with intracranially implanted electrodes, we trained multivariate classifiers to discriminate spectral activity during learning that predicted remembering from forgetting, then decoded neural activity in later sessions in which we applied stimulation during learning. Stimulation increased encoding-state estimates and recall if delivered when the classifier indicated low encoding efficiency but had the reverse effect if stimulation was delivered when the classifier indicated high encoding efficiency. Higher encoding-state estimates from stimulation were associated with greater evidence of neural activity linked to contextual memory encoding. In identifying the conditions under which stimulation modulates memory, the data suggest strategies for therapeutically treating memory dysfunction.
Effects of the Insulin Sensitizer Metformin in Alzheimer’s Disease: Pilot Data from a Randomized Placebo-Controlled Crossover Study

A. Koenig, D. Mechanic-Hamilton, Sharon X. Xie, Martha F. Combs, A. Cappola, Long Xie, J. Detre, D. Wolk, and S. Arnold

Alzheimer disease and associated disorders, Apr 2017

Cited by 303

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Epidemiological studies have identified a robust association between type II diabetes mellitus and Alzheimer disease (AD), and neurobiological studies have suggested the presence of central nervous system insulin resistance in individuals with AD. Given this association, we hypothesized that the central nervous system–penetrant insulin-sensitizing medication metformin would be beneficial as a disease-modifying and/or symptomatic therapy for AD, and conducted a placebo-controlled crossover study of its effects on cerebrospinal fluid (CSF), neuroimaging, and cognitive biomarkers. Twenty nondiabetic subjects with mild cognitive impairment or mild dementia due to AD were randomized to receive metformin then placebo for 8 weeks each or vice versa. CSF and neuroimaging (Arterial Spin Label MRI) data were collected for biomarker analyses, and cognitive testing was performed. Metformin was found to be safe, well-tolerated, and measureable in CSF at an average steady-state concentration of 95.6 ng/mL. Metformin was associated with improved executive functioning, and trends suggested improvement in learning/memory and attention. No significant changes in cerebral blood flow were observed, though post hoc completer analyses suggested an increase in orbitofrontal cerebral blood flow with metformin exposure. Further study of these findings is warranted.
Effects of the Insulin Sensitizer Metformin in Alzheimer Disease: Pilot Data From a Randomized Placebo-controlled Crossover Study

A. Koenig, Dawn J. Mechanic-Hamilton, S. Xie, Martha F. Combs, A. Cappola, L. Xie, J. Detre, David A. Wolk, and S. Arnold

Alzheimer Disease & Associated Disorders, Apr 2017

Cited by 286

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Similar patterns of neural activity predict memory function during encoding and retrieval

J. Kragel, Youssef Ezzyat, M. Sperling, R. Gorniak, G. Worrell, Brent M. Berry, Cory S. Inman, Jui-Jui Lin, K. Davis, Sandhitsu R. Das, J. Stein, B. Jobst, K. Zaghloul, S. Sheth, D. Rizzuto, and M. Kahana

NeuroImage, Apr 2017

Cited by 72

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ABSTRACT Neural networks that span the medial temporal lobe (MTL), prefrontal cortex, and posterior cortical regions are essential to episodic memory function in humans. Encoding and retrieval are supported by the engagement of both distinct neural pathways across the cortex and common structures within the medial temporal lobes. However, the degree to which memory performance can be determined by neural processing that is common to encoding and retrieval remains to be determined. To identify neural signatures of successful memory function, we administered a delayed free‐recall task to 187 neurosurgical patients implanted with subdural or intraparenchymal depth electrodes. We developed multivariate classifiers to identify patterns of spectral power across the brain that independently predicted successful episodic encoding and retrieval. During encoding and retrieval, patterns of increased high frequency activity in prefrontal, MTL, and inferior parietal cortices, accompanied by widespread decreases in low frequency power across the brain predicted successful memory function. Using a cross‐decoding approach, we demonstrate the ability to predict memory function across distinct phases of the free‐recall task. Furthermore, we demonstrate that classifiers that combine information from both encoding and retrieval states can outperform task‐independent models. These findings suggest that the engagement of a core memory network during either encoding or retrieval shapes the ability to remember the past, despite distinct neural interactions that facilitate encoding and retrieval. HIGHLIGHTSMultivariate decoding of iEEG data identified successful memory encoding and recall.Neural dynamics during retrieval enhanced classification of encoding states.Increased HFA and decreased LFA in overlapping neural systems signal memory success.
Tau PET Imaging Predicts Cognition in Atypical Variants of Alzheimer’s Disease (P6.077)

Jeffrey Phillips, Sandhitsu R. Das, C. McMillan, David J. Irwin, I. Nasrallah, David Wolk, and Murray Grossman

Neurology, Apr 2017

Cited by 1

DOI
213: Novel 3D morphologic analysis of the early placenta using deformable medial modeling

A. Pouch, I. Oguz, N. Yushkevich, J. Gee, Paul Yushkevich, and N. Schwartz

American Journal of Obstetrics and Gynecology, Apr 2017

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Mapping of pain circuitry in early post-natal development using manganese-enhanced MRI in rats

M. Sperry, Benjamin M. Kandel, S. Wehrli, K. Bass, Sandhitsu R. Das, Paramveer S. Dhillon, James C. Gee, and Gordon A. Barr

Neuroscience, Apr 2017

Cited by 17

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Premature or ill full-term infants are subject to a number of noxious procedures as part of their necessary medical care. Although we know that human infants show neural changes in response to such procedures, we know little of the sensory or affective brain circuitry activated by pain. In rodent models, the focus has been on spinal cord and, more recently, midbrain and medulla. The present study assesses activation of brain circuits using manganese-enhanced magnetic resonance imaging (MEMRI). Uptake of manganese, a paramagnetic contrast agent that is transported across active synapses and along axons, was measured in response to a hindpaw injection of dilute formalin in 12-day-old rat pups, the age at which rats begin to show aversion learning and which is roughly the equivalent of full-term human infants. Formalin induced the well-reported biphasic response at this age and induced a conditioned aversion to cues associated with its injection, thus demonstrating the aversiveness of the stimulation. Morphometric analyses, structural equation modeling and co-expression analysis showed that limbic and sensory paths were activated, the most prominent of which were the prefrontal and anterior cingulate cortices, nucleus accumbens, amygdala, hypothalamus, several brainstem structures, and the cerebellum. Therefore, both sensory and affective circuits, which are activated by pain in the adult, can also be activated by noxious stimulation in 12-day-old rat pups.
A patch-based framework for new ITK functionality: Joint fusion, denoising, and non-local super-resolution

N. Tustison, B. Avants, Hong-Zhi Wang, Long Xie, P. Coupé, Paul Yushkevich, and J. Manjón

The Insight Journal, Mar 2017

Cited by 2

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In an earlier Insight Journal article, we introduced an ITK implementation of the adaptive patch-based image denoising algorithm described in [3]. We follow-up up that offering with a generalized non-local, patch-based ITK class framework and a refactored denoising class. In addition, we provide two ITK implementations of related, well-known algorithms. The first is a non-local super resolution method described in [1, 2]. The second is the multivariate joint label fusion algorithm of [4, 5] with additional extensions, denoted as “joint intensity fusion”, which will be described in a forthcoming manuscript. Accompanying these ITK classes are documented programming interfaces which use our previously introduced unique command line interface routines. Several 2-D examples on brain imaging data are provided to qualitatively demonstrate performance.
Medial temporal lobe subregional morphometry using high resolution MRI in Alzheimer’s disease.

D. Wolk, Sandhitsu R. Das, S. Mueller, M. Weiner, and Paul Yushkevich

Neurobiology of aging, Mar 2017

Cited by 87

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Multi‐template analysis of human perirhinal cortex in brain MRI: Explicitly accounting for anatomical variability

L. Xie, J. Pluta, Sandhitsu R. Das, L. Wisse, Hongzhi Wang, L. Mancuso, Dasha Kliot, B. Avants, S. Ding, J. Manjón, D. Wolk, and Paul Yushkevich

Neuroimage, Mar 2017

Cited by 40

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2016

Interictal Epileptiform Discharges Impair Word Recall in Multiple Brain Areas

Peter C. Horak, S. Meisenhelter, Yin-Chen Song, M. Testorf, M. Kahana, Weston D Viles, K. Bujarski, Andrew C. Connolly, Ashlee A Robbins, M. Sperling, A. Sharan, G. Worrell, Laura R. Miller, R. Gross, K. Davis, D. Roberts, B. Lega, S. Sheth, K. Zaghloul, J. Stein, Sandhitsu R. Das, D. Rizzuto, and B. Jobst

Epilepsia, Dec 2016

Cited by 96

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Interictal epileptiform discharges (IEDs) have been linked to memory impairment, but the spatial and temporal dynamics of this relationship remain elusive. In the present study, we aim to systematically characterize the brain areas and times at which IEDs affect memory.
Direct Electrical Stimulation of the Human Entorhinal Region and Hippocampus Impairs Memory.

J. Jacobs, Jonathan F. Miller, Sang-Ah Lee, Tom Coffey, Andrew J. Watrous, M. Sperling, A. Sharan, G. Worrell, Brent M. Berry, B. Lega, B. Jobst, K. Davis, R. Gross, S. Sheth, Youssef Ezzyat, Sandhitsu R. Das, J. Stein, R. Gorniak, M. Kahana, and D. Rizzuto

Neuron, Dec 2016

Cited by 229

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A quantitative meta-analysis of olfactory dysfunction in mild cognitive impairment

D. Roalf, M. Moberg, B. Turetsky, L. Brennan, S. Kabadi, D. Wolk, and P. Moberg

Journal of neurology, neurosurgery, and psychiatry, Dec 2016

Cited by 113

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Background The connection between Alzheimer’s disease (AD) and olfactory deficits is well documented and further, alterations in olfactory functioning may signal declines in functions associated with dementia. The aim of the present comprehensive meta-analysis was to investigate the nature of olfactory deficits in mild cognitive impairment (MCI). Methods Articles were identified through computerised literature search from inception to 30 June 2016 using PubMed, MEDLINE and PsychInfo databases. In order to control for differences in sample size during effect size computation, studies were weighted according to their inverse variance estimates. Results 31 articles (62 effects) were identified, which included 1993 MCI patients and 2861 healthy older adults (HOA). Included studies contrasted odour identification, discrimination, detection threshold and/or memory between cases and controls. Moderate to large and heterogeneous effects were seen for olfactory deficits in MCI relative to HOA (d=−0.76, 95% CI −0.87<δ<−0.64). Moderator analysis revealed that tests of odour identification yielded larger effect sizes than those of odour detection threshold or memory. In addition, a potential interaction between age and sex was observed, with male patients carrying a larger burden of olfactory deficit and older female patients performing better on olfactory tests. Conclusions and relevance Olfactory deficits are present and robust in MCI. Odour identification is most impaired in MCI, which parallels the most prominent sensory deficit seen in AD. As such, a simple-to-administer test of odour identification warrants inclusion in the screening of individuals at risk for developing AD.
Odor Identification Screening Improves Diagnostic Classification in Incipient Alzheimer’s Disease

M. Quarmley, P. Moberg, D. Mechanic-Hamilton, S. Kabadi, Steve Arnold, D. Wolk, and D. Roalf

Journal of Alzheimer’s disease : JAD, Nov 2016

Cited by 64

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Background: Measurements of olfaction may serve as useful biomarkers of incipient dementia. Here we examine the improvement in diagnostic accuracy of Alzheimer’s disease (AD) and mild cognitive impairment (MCI) when assessing both cognitive functioning and odor identification. Objective: To determine the utility of odor identification as a supplementary screening test in incipient AD. Methods: Sniffin’ Sticks Odor Identification Test (SS-OIT) and the Montreal Cognitive Assessment (MoCA) were administered in 262 AD, 174 MCI [150 amnestic (aMCI), and 24 non-amnestic (naMCI)], and 292 healthy older adults (HOA). Results: Odor identification scores were higher in HOA relative to MCI or AD groups, and MCI outperformed AD. Odor identification scores were higher in aMCI single domain than aMCI multiple domain. Complementing MoCA scores with the SS-OIT significantly improved diagnostic accuracy of individuals with AD and MCI, including within MCI subgroups. Discussion: Odor identification is a useful supplementary screening tool that provides additional information relevant for clinical categorization of AD and MCI, including those who are at highest risk to convert to AD.
A harmonized segmentation protocol for hippocampal and parahippocampal subregions: why do we need one and what are the key goals?

L. Wisse, Ana M. Daugherty, R. Olsen, D. Berron, Valerie A. Carr, Craig E. L. Stark, R. Amaral, K. Amunts, Jean C. Augustinack, Andrew R. Bender, Jeffrey D. Bernstein, M. Boccardi, M. Bocchetta, A. Burggren, M. Chakravarty, M. Chupin, Arne D. Ekstrom, R. Flores, R. Insausti, P. Kanel, O. Kedo, Kristen M. Kennedy, G. Kerchner, Karen F. Larocque, Xiu-Wen Liu, A. Maass, N. Malykhin, S. Mueller, N. Ofen, D. Palombo, M. Parekh, J. Pluta, J. Pruessner, N. Raz, K. Rodrigue, D. Schoemaker, Andrea T. Shafer, T. Steve, N. Suthana, Lei Wang, Julie L. Winterburn, M. Yassa, Paul Yushkevich, and R. La Joie

Hippocampus, Nov 2016

Cited by 158

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The advent of high‐resolution magnetic resonance imaging (MRI) has enabled in vivo research in a variety of populations and diseases on the structure and function of hippocampal subfields and subdivisions of the parahippocampal gyrus. Because of the many extant and highly discrepant segmentation protocols, comparing results across studies is difficult. To overcome this barrier, the Hippocampal Subfields Group was formed as an international collaboration with the aim of developing a harmonized protocol for manual segmentation of hippocampal and parahippocampal subregions on high‐resolution MRI. In this commentary we discuss the goals for this protocol and the associated key challenges involved in its development. These include differences among existing anatomical reference materials, striking the right balance between reliability of measurements and anatomical validity, and the development of a versatile protocol that can be adopted for the study of populations varying in age and health. The commentary outlines these key challenges, as well as the proposed solution of each, with concrete examples from our working plan. Finally, with two examples, we illustrate how the harmonized protocol, once completed, is expected to impact the field by producing measurements that are quantitatively comparable across labs and by facilitating the synthesis of findings across different studies. © 2016 Wiley Periodicals, Inc.
Probabilistic Atlas of the Human Hippocampus Combining Ex Vivo MRI and Histology

D. Adler, R. Ittyerah, J. Pluta, S. Pickup, Wei-Xia Liu, D. Wolk, and Paul Yushkevich

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Oct 2016

Cited by 7

DOI
Globally Optimal Label Fusion with Shape Priors

I. Oguz, Satyananda Kashyap, Hong-Zhi Wang, Paul Yushkevich, and M. Sonka

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Oct 2016

Cited by 10

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Multi-atlas label fusion methods have gained popularity in a variety of segmentation tasks given their attractive performance. Graph-based segmentation methods are widely used given their global optimality guarantee. We propose a novel approach, GOLF, that combines the strengths of these two approaches. GOLF incorporates shape priors to the label-fusion problem and provides a globally optimal solution even for the multi-label scenario, while also leveraging the highly accurate posterior maps from a multi-atlas label fusion approach. We demonstrate GOLF for the joint segmentation of the left and right pairs of caudate, putamen, globus pallidus and nucleus accumbens. Compared to the FreeSurfer and FIRST approaches, GOLF is significantly more accurate on all reported indices for all 8 structures. We also present comparisons to a multi-atlas approach, which reveals further insights on the contributions of the different components of the proposed framework.
Accounting for the Confound of Meninges in Segmenting Entorhinal and Perirhinal Cortices in T1-Weighted MRI

Long Xie, L. Wisse, Sandhitsu R. Das, Hong-Zhi Wang, D. Wolk, J. Manjón, and Paul Yushkevich

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Oct 2016

Cited by 47

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Quantification of medial temporal lobe (MTL) cortices, including entorhinal cortex (ERC) and perirhinal cortex (PRC), from in vivo MRI is desirable for studying the human memory system as well as in early diagnosis and monitoring of Alzheimer’s disease. However, ERC and PRC are commonly over-segmented in T1-weighted (T1w) MRI because of the adjacent meninges that have similar intensity to gray matter in T1 contrast. This introduces errors in the quantification and could potentially confound imaging studies of ERC/PRC. In this paper, we propose to segment MTL cortices along with the adjacent meninges in T1w MRI using an established multi-atlas segmentation framework together with super-resolution technique. Experimental results comparing the proposed pipeline with existing pipelines support the notion that a large portion of meninges is segmented as gray matter by existing algorithms but not by our algorithm. Cross-validation experiments demonstrate promising segmentation accuracy. Further, agreement between the volume and thickness measures from the proposed pipeline and those from the manual segmentations increase dramatically as a result of accounting for the confound of meninges. Evaluated in the context of group discrimination between patients with amnestic mild cognitive impairment and normal controls, the proposed pipeline generates more biologically plausible results and improves the statistical power in discriminating groups in absolute terms comparing to other techniques using T1w MRI. Although the performance of the proposed pipeline is inferior to that using T2-weighted MRI, which is optimized to image MTL sub-structures, the proposed pipeline could still provide important utilities in analyzing many existing large datasets that only have T1w MRI available.
Multi-template analysis of human perirhinal cortex in brain MRI: Explicitly accounting for anatomical variability

Long Xie, J. Pluta, Sandhitsu R. Das, L. Wisse, Hong-Zhi Wang, L. Mancuso, Dasha Kliot, B. Avants, Song-Lin Ding, J. Manjón, D. Wolk, and Paul Yushkevich

NeuroImage, Oct 2016

Cited by 41

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Rational: The human perirhinal cortex (PRC) plays critical roles in episodic and semantic memory and visual perception. The PRC consists of Brodmann areas 35 and 36 (BA35, BA36). In Alzheimer’s disease (AD), BA35 is the first cortical site affected by neurofibrillary tangle pathology, which is closely linked to neural injury in AD. Large anatomical variability, manifested in the form of different cortical folding and branching patterns, makes it difficult to segment the PRC in MRI scans. Pathology studies have found that in ˜97% of specimens, the PRC falls into one of three discrete anatomical variants. However, current methods for PRC segmentation and morphometry in MRI are based on single‐template approaches, which may not be able to accurately model these discrete variants Methods: A multi‐template analysis pipeline that explicitly accounts for anatomical variability is used to automatically label the PRC and measure its thickness in T2‐weighted MRI scans. The pipeline uses multi‐atlas segmentation to automatically label medial temporal lobe cortices including entorhinal cortex, PRC and the parahippocampal cortex. Pairwise registration between label maps and clustering based on residual dissimilarity after registration are used to construct separate templates for the anatomical variants of the PRC. An optimal path of deformations linking these templates is used to establish correspondences between all the subjects. Experimental evaluation focuses on the ability of single‐template and multi‐template analyses to detect differences in the thickness of medial temporal lobe cortices between patients with amnestic mild cognitive impairment (aMCI, n=41) and age‐matched controls (n=44). Results: The proposed technique is able to generate templates that recover the three dominant discrete variants of PRC and establish more meaningful correspondences between subjects than a single‐template approach. The largest reduction in thickness associated with aMCI, in absolute terms, was found in left BA35 using both regional and summary thickness measures. Further, statistical maps of regional thickness difference between aMCI and controls revealed different patterns for the three anatomical variants. HIGHLIGHTSA multi‐template framework is proposed to quantify perirhinal cortex (PRC) using MRI.The framework explicitly models the 3 discrete anatomical variants of PRC.Better correspondences are established between subject’s PRC anatomies.Regional and summary measures yield stronger power in discriminating aMCI.Spatial distributions of early AD pathology may vary among anatomical variants.
Supervoxel-Based Hierarchical Markov Random Field Framework for Multi-atlas Segmentation

Ning Yu, Hong-Zhi Wang, and Paul Yushkevich

In Patch-MI@MICCAI, Oct 2016

Cited by 3

DOI
The value of preoperative 3-dimensional over 2-dimensional valve analysis in predicting recurrent ischemic mitral regurgitation after mitral annuloplasty.

Inez J Wijdh-Den Hamer, W. Bouma, E. Lai, M. Levack, E. Shang, A. Pouch, T. Eperjesi, T. Plappert, Paul Yushkevich, J. Hung, M. Mariani, K. Khabbaz, T. Gleason, Feroze Mahmood, M. Acker, Y. Woo, A. Cheung, Matthew J. Gillespie, B. Jackson, J. Gorman, and R. Gorman

The Journal of thoracic and cardiovascular surgery, Sep 2016

Cited by 30

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Modeling the Myxomatous Mitral Valve With Three-Dimensional Echocardiography.

A. Pouch, B. Jackson, E. Lai, Manabu Takebe, Sijie Tian, A. Cheung, Y. Woo, Prakash A. Patel, Hongzhi Wang, Paul Yushkevich, R. Gorman, and J. Gorman

The Annals of thoracic surgery, Sep 2016

Cited by 8

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Comparison of In Vivo and Ex Vivo MRI of the Human Hippocampal Formation in the Same Subjects

L. Wisse, D. Adler, R. Ittyerah, J. Pluta, John L. Robinson, T. Schuck, J. Trojanowski, M. Grossman, J. Detre, M. Elliott, J. Toledo, Wei-Xia Liu, S. Pickup, Sandhitsu Das, D. Wolk, and Paul Yushkevich

Cerebral Cortex, Sep 2016

Cited by 33

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Medial temporal lobe subregional morphometry using high resolution MRI in Alzheimer’s Disease

D. Wolk, Sandhitsu R. Das, S. Mueller, M. Weiner, and Paul Yushkevich

Neurobiology of aging, Sep 2016

Cited by 92

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Autopsy studies of Alzheimer’s Disease (AD) have found that neurofibrillary tangle (NFT) pathology of the medial temporal lobe (MTL) demonstrates selective topography with relatively stereotyped subregional involvement at early disease stages, prompting interest in more granular measurement of these structures with in vivo MRI. We applied a novel, automated method for measurement of hippocampal subfields and extrahippocampal MTL cortical regions. The cohort included cognitively normal (CN) adults (n=86), early Mild Cognitive Impairment (EMCI; n=43), late MCI (LMCI; n=22), and mild AD (n=40) patients from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). For pseudolongitudinal analysis of the continuum from preclinical to mild AD dementia, the groups were further divided according to amyloid status based on PET. Specific subregions associated with the early NFT pathology of AD were more sensitive to preclinical and early prodromal AD than whole hippocampal volume while more diffuse involvement was found in later stages. In particular, BA35, the first region associated with NFT deposition, was the only region to discriminate preclinical AD from amyloid negative CN adults (“normal aging”). In general, patterns of atrophy in the pseudolongitudinal analysis largely recapitulated Braak staging of NFTs within the MTL.
In-vivo heterogeneous functional and residual strains in human aortic valve leaflets.

A. Aggarwal, A. Pouch, E. Lai, John Lesicko, Paul Yushkevich, Joseph H Gorman Iii, R. Gorman, and M. Sacks

Journal of biomechanics, Aug 2016

Cited by 41

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Self-gated MRI of multiple beat morphologies in the presence of arrhythmias

F. Contijoch, Srikanth K. Iyer, J. Pilla, Paul Yushkevich, J. Gorman, R. Gorman, H. Litt, Yu-Chi Han, and W. Witschey

Magnetic resonance in medicine, Aug 2016

Cited by 33

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Develop self‐gated MRI for distinct heartbeat morphologies in subjects with arrhythmias.
Clinical Application of Automatic Segmentation of Medial Temporal Lobe Subregions in Prodromal and Dementia-Level Alzheimer’s Disease

E. Gertje, J. Pluta, Sandhitsu R. Das, L. Mancuso, Dasha Kliot, Paul Yushkevich, and D. Wolk

Journal of Alzheimer’s disease : JAD, Aug 2016

Cited by 12

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Background: Volumetry of medial temporal lobe (MTL) structures to diagnose Alzheimer’s disease (AD) in its earliest symptomatic stage could be of great importance for interventions or disease modifying pharmacotherapy. Objective: This study aimed to demonstrate the first application of an automatic segmentation method of MTL subregions in a clinical population. Automatic segmentation of magnetic resonance images (MRIs) in a research population has previously been shown to detect evidence of neurodegeneration in MTL subregions and to help discriminate AD and mild cognitive impairment (MCI) from a healthy comparison group. Methods: Clinical patients were selected and T2-weighted MRI scan quality was checked. An automatic segmentation method of hippocampal subfields (ASHS) was applied to scans of 67 AD patients, 38 amnestic MCI patients, and 57 healthy controls. Hippocampal subfields, entorhinal cortex (ERC), and perirhinal cortex were automatically labeled and subregion volumes were compared between groups. Results: One fourth of all scans were excluded due to bad scan quality. There were significant volume reductions in all subregions, except BA36, in aMCIs (p < 0.001), most prominently in Cornu Ammonis 1 (CA1) and ERC, and in all subregions in AD. However, sensitivity of CA1 and ERC hardly differed from sensitivity of WH in aMCI and AD. Conclusion: Applying automatic segmentation of MTL subregions in a clinical setting as a potential biomarker for prodromal AD is feasible, but issues of image quality due to motion remain to be addressed. CA1 and ERC provided strongest group discrimination in differentiating aMCIs from controls, but discriminatory power of different subfields was low overall.
Modeling the Myxomatous Mitral Valve With Three-Dimensional Echocardiography

A. Pouch, B. Jackson, Eric K. Lai, Manabu Takebe, Sijie Tian, A. Cheung, Y. Woo, Prakash A. Patel, Hong-Zhi Wang, Paul Yushkevich, R. Gorman, and J. Gorman

The Annals of thoracic surgery, Aug 2016

Cited by 8

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Background Degenerative mitral valve disease is associated with variable and complex defects in valve morphology. Three-dimensional echocardiography (3DE) has shown promise in aiding preoperative planning for patients with this disease but to date has not been as transformative as initially predicted. The clinical usefulness of 3DE has been limited by the laborious methods currently required to extract quantitative data from the images. Methods To maximize the utility of 3DE for preoperative valve evaluation, this work describes an automated 3DE image analysis method for generating models of the mitral valve that are well suited for both qualitative and quantitative assessment. The method is unique in that it captures detailed alterations in mitral leaflet and annular morphology and produces image-derived models with locally varying leaflet thickness. The method is evaluated on midsystolic transesophageal 3DE images acquired from 22 subjects with myxomatous degeneration and from 22 subjects with normal mitral valve morphology. Results Relative to manual image analysis, the automated method accurately represents both normal and complex leaflet geometries with a mean boundary displacement error on the order of one image voxel. A detailed quantitative analysis of the valves is presented and reveals statistically significant differences between normal and myxomatous valves with respect to numerous aspects of annular and leaflet geometry. Conclusions This work demonstrates a successful methodology for the relatively rapid quantitative description of the complex mitral valve distortions associated with myxomatous degeneration. The methodology has the potential to significantly improve surgical planning for patients with complex mitral valve disease.
Within-Individual Variability: An Index for Subtle Change in Neurocognition in Mild Cognitive Impairment

D. Roalf, M. Quarmley, D. Mechanic-Hamilton, D. Wolk, S. Arnold, and P. Moberg

Journal of Alzheimer’s disease : JAD, Aug 2016

Cited by 32

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Background: The transition from mild cognitive impairment (MCI) to Alzheimer’s disease is characterized by a decline in cognitive performance in many domains. Cognitive performance profiles in MCI are heterogeneous, however, and additional insights into markers of incipient dementia are needed. Typically, studies focus on average or mean performance, but ignore consistency of performance across domains. WIV (within-individual variability) provides an index of this consistency and is a potential marker of cognitive decline. Objective: To use neurocognitive data from the Alzheimer’s Disease Neuroimaging Initiative cohort to measure neurocognitive variability. Methods: The utility of WIV was measured, in addition to global neurocognitive performance (GNP), for identifying AD and MCI. In addition, the association between changes in neurocognitive variability and diagnostic transition over 12 months was measured. Results: As expected, variability was higher in AD and MCI as compared to healthy controls; GNP was lower in both groups as compared to healthy subjects. Global neurocognitive performance alone best distinguished those with dementia from healthy older adults. Yet, for individuals with MCI, including variability along with GNP improved diagnostic classification. Variability was higher at baseline in individuals transitioning from MCI to AD over a 12-month period. Conclusion: We conclude that variability offers complementary information about neurocognitive performance in dementia, particularly in individuals with MCI, and may provide beneficial information about disease transition.
Neural signatures of experience-based improvements in deterministic decision-making

Joshua J. Tremel, Patryk A. Laurent, D. Wolk, Mark E. Wheeler, and J. Fiez

Behavioural brain research, Aug 2016

Cited by 3

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Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions.
A framework for informing segmentation of in vivo MRI with information derived from ex vivo imaging: Application in the medial temporal lobe

Paul Yushkevich, L. Wisse, D. Adler, R. Ittyerah, J. Pluta, J. Robinson, T. Schuck, J. Trojanowski, M. Grossman, J. Detre, M. Elliott, J. Toledo, Wei-Xia Liu, S. Pickup, Sandhitsu R. Das, D. Wolk, and Wei-Xia Liu

In Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Aug 2016

Cited by 6

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Automatic segmentation of cortical and subcortical structures is commonplace in brain MRI literature and is frequently used as the first step towards quantitative analysis of structural and functional neuroimaging. Most approaches to brain structure segmentation are based on propagation of anatomical information from example MRI datasets, called atlases or templates, that are manually labeled by experts. The accuracy of automatic segmentation is usually validated against the “bronze” standard of manual segmentation of test MRI datasets. However, good performance vis-a-vis manual segmentation does not imply accuracy relative to the underlying true anatomical boundaries. In the context of segmentation of hippocampal subfields and functionally related medial temporal lobe cortical subregions, we explore the challenges associated with validating existing automatic segmentation techniques against underlying histologically-derived anatomical “gold” standard; and, further, developing automatic in vivo MRI segmentation techniques informed by histological imaging.
ITK-SNAP: an interactive tool for semi-automatic segmentation of multi-modality biomedical images

Paul Yushkevich, Yang Gao, G. Gerig, and Yang Gao

In Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Aug 2016

Cited by 663

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Obtaining quantitative measures from biomedical images often requires segmentation, i.e., finding and outlining the structures of interest. Multi-modality imaging datasets, in which multiple imaging measures are available at each spatial location, are increasingly common, particularly in MRI. In applications where fully automatic segmentation algorithms are unavailable or fail to perform at desired levels of accuracy, semi-automatic segmentation can be a time-saving alternative to manual segmentation, allowing the human expert to guide segmentation, while minimizing the effort expended by the expert on repetitive tasks that can be automated. However, few existing 3D image analysis tools support semi-automatic segmentation of multi-modality imaging data. This paper describes new extensions to the ITK-SNAP interactive image visualization and segmentation tool that support semi-automatic segmentation of multi-modality imaging datasets in a way that utilizes information from all available modalities simultaneously. The approach combines Random Forest classifiers, trained by the user by placing several brushstrokes in the image, with the active contour segmentation algorithm. The new multi-modality semi-automatic segmentation approach is evaluated in the context of high-grade glioblastoma segmentation.
ND morphological contour interpolation

Dženan Zukić, Jared Vicory, Matthew Mccormick, L. Wisse, G. Gerig, Paul Yushkevich, and S. Aylward

The Insight Journal, Aug 2016

Cited by 22

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This document describes a new class, itk::MorphologicalContourInterpolator, which implements a method proposed by Albu et al. in 2008. Interpolation is done by first determining correspondence between shapes on adjacent segmented slices by detecting overlaps, then aligning the corresponding shapes, generating transition sequence of one-pixel dilations and taking the median as result. Recursion is employed if the original segmented slices are separated by more than one empty slice.This class is n-dimensional, and supports inputs of 3 or more dimensions. ‘Slices’ are n-1-dimensional, and can be both automatically detected and manually set. The class is efficient in both memory used and execution time. It requires little memory in addition to allocation of input and output images. The implementation is multi-threaded, and processing one of the test inputs takes around 1-2 seconds on a quad-core processor.The class is tested to operate on both itk::Image and itk::RLEImage. Since all the processing is done on extracted slices, usage of itk::RLEImage for input and/or output affects performance to a limited degree.This class is implemented to ease manual segmentation in ITK-SNAP (www.itksnap.org). The class, along with test data and automated regression tests is packaged as an ITK remote module https://github.com/KitwareMedical/ITKMorphologicalContourInterpolation.
P1‐265: TAU Binding Measured Using PET in Medial Temporal Lobe Correlates with Subregional Atrophy and Episodic Memory Performance In Alzheimer’s Disease

Sandhitsu R. Das, Jeffrey S. Phillips, L. Wisse, Grace E Stockbower, Kylie Ternes, C. McMillan, Paul Yushkevich, M. Grossman, I. Nasrallah, and D. Wolk

Alzheimer’s & Dementia, Jul 2016

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F4‐04‐01: Biomarkers for Personalized Treatment of Neurodegenerative Spectrum Disease

C. Mcmillan, and D. Wolk

Alzheimer’s & Dementia, Jul 2016

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Systematic comparison of different techniques to measure hippocampal subfield volumes in ADNI2

S. Mueller, Paul Yushkevich, Sandhitsu R. Das, Lei Wang, K. Van Leemput, J. Iglesias, Kathryn I. Alpert, Adam Mezher, Peter Ng, Katrina Paz, and M. Weiner

NeuroImage : Clinical, Jul 2016

Cited by 63

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Objective Subfield-specific measurements provide superior information in the early stages of neurodegenerative diseases compared to global hippocampal measurements. The overall goal was to systematically compare the performance of five representative manual and automated T1 and T2 based subfield labeling techniques in a sub-set of the ADNI2 population. Methods The high resolution T2 weighted hippocampal images (T2-HighRes) and the corresponding T1 images from 106 ADNI2 subjects (41 controls, 57 MCI, 8 AD) were processed as follows. A. T1-based: 1. Freesurfer + Large-Diffeomorphic-Metric-Mapping in combination with shape analysis. 2. FreeSurfer 5.1 subfields using in-vivo atlas. B. T2-HighRes: 1. Model-based subfield segmentation using ex-vivo atlas (FreeSurfer 6.0). 2. T2-based automated multi-atlas segmentation combined with similarity-weighted voting (ASHS). 3. Manual subfield parcellation. Multiple regression analyses were used to calculate effect sizes (ES) for group, amyloid positivity in controls, and associations with cognitive/memory performance for each approach. Results Subfield volumetry was better than whole hippocampal volumetry for the detection of the mild atrophy differences between controls and MCI (ES: 0.27 vs 0.11). T2-HighRes approaches outperformed T1 approaches for the detection of early stage atrophy (ES: 0.27 vs.0.10), amyloid positivity (ES: 0.11 vs 0.04), and cognitive associations (ES: 0.22 vs 0.19). Conclusions T2-HighRes subfield approaches outperformed whole hippocampus and T1 subfield approaches. None of the different T2-HghRes methods tested had a clear advantage over the other methods. Each has strengths and weaknesses that need to be taken into account when deciding which one to use to get the best results from subfield volumetry.
P2‐232: TAU Burden and Cognition in Early‐Onset Versus Late‐Onset Alzheimer’s Disease Spectrum

S. Mueller, Paul Yushkevich, Lei Wang, K. V. Leemput, K. Alpert, Katrina Paz, Sandhitsu R. Das, Eugenio Iglesias, and M. Weiner

Alzheimer’s & Dementia, Jul 2016

Cited by 16

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IC‐P‐085: Suspected Non‐Ad Pathology in Mild Cognitive Impairment: Defined by Cross‐Sectional or Longitudinal Neurodegeneration

L. Wisse, Sandhitsu R. Das, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2016

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P1‐022: Suspected NON‐AD Pathology in Mild Cognitive Impairment: Defined by Cross‐Sectional or Longitudinal Neurodegeneration

L. Wisse, Sandhitsu R. Das, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2016

DOI
P2‐060: A Harmonized Protocol for Medial Temporal Lobe Subfield Segmentation: Initial Results of The 3‐Tesla Protocol For The Hippocampal Body

L. Wisse, Ana M. Daugherty, R. Amaral, D. Berron, Valerie A. Carr, Arne D. Ekstrom, P. Kanel, G. Kerchner, S. Mueller, J. Pluta, Craig E. L. Stark, T. Steve, Lei Wang, M. Yassa, Paul Yushkevich, and R. La Joie

Alzheimer’s & Dementia, Jul 2016

Cited by 2

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IC‐P‐174: Fast Automatic Segmentation of Hippocampal Subfields and Medial Temporal Lobe Subregions In 3 Tesla and 7 Tesla T2‐Weighted MRI

Paul Yushkevich, J. Pluta, Hong-Zhi Wang, L. Wisse, Sandhitsu R. Das, and D. Wolk

Alzheimer’s & Dementia, Jul 2016

Cited by 108

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The value of preoperative 3-dimensional over 2-dimensional valve analysis in predicting recurrent ischemic mitral regurgitation after mitral annuloplasty

Inez J. Wijdh-Den Hamer, W. Bouma, Eric K. Lai, M. Levack, Eric K. Shang, A. Pouch, T. Eperjesi, Theodore J. Plappert, Paul Yushkevich, J. Hung, M. Mariani, K. Khabbaz, Thomas G. Gleason, F. Mahmood, M. Acker, Y. Woo, A. Cheung, Matthew J. Gillespie, B. Jackson, J. Gorman, and R. Gorman

The Journal of thoracic and cardiovascular surgery, Jun 2016

Cited by 29

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Objectives Repair for ischemic mitral regurgitation with undersized annuloplasty is characterized by high recurrence rates. We sought to determine the value of pre-repair 3-dimensional echocardiography over 2-dimensional echocardiography in predicting recurrence at 6 months. Methods Intraoperative transesophageal 2-dimensional echocardiography and 3-dimensional echocardiography were performed in 50 patients undergoing undersized annuloplasty for ischemic mitral regurgitation. Two-dimensional echocardiography annular diameter and tethering parameters were measured in the apical 2- and 4-chamber views. A customized protocol was used to assess 3-dimensional annular geometry and regional leaflet tethering. Recurrence (grade ≥2) was assessed with 2-dimensional transthoracic echocardiography at 6 months. Results Preoperative 2- and 3-dimensional annular geometry were similar in all patients with ischemic mitral regurgitation. Preoperative 2- and 3-dimensional leaflet tethering were significantly higher in patients with recurrence (n = 13) when compared with patients without recurrence (n = 37). Multivariate logistic regression revealed preoperative 2-dimensional echocardiography posterior tethering angle as an independent predictor of recurrence with an optimal cutoff value of 32.0° (area under the curve, 0.81; 95% confidence interval, 0.68–0.95; P = .002) and preoperative 3-dimensional echocardiography P3 tethering angle as an independent predictor of recurrence with an optimal cutoff value of 29.9° (area under the curve, 0.92; 95% confidence interval, 0.84–1.00; P < .001). The predictive value of the 3-dimensional geometric multivariate model can be augmented by adding basal aneurysm/dyskinesis (area under the curve, 0.94; 95% confidence interval, 0.87–1.00; P < .001). Conclusions Preoperative 3-dimensional echocardiography P3 tethering angle is a stronger predictor of ischemic mitral regurgitation recurrence after annuloplasty than preoperative 2-dimensional echocardiography posterior tethering angle, which is highly influenced by viewing plane. In patients with a preoperative P3 tethering angle of 29.9° or larger (especially when combined with basal aneurysm/dyskinesis), chordal-sparing valve replacement should be strongly considered.
Automated Hippocampal Subfield Segmentation at 7T MRI

L. Wisse, H.J. Kuijf, A. Honingh, H. Wang, J. Pluta, S.R. Das, D. Wolk, J. Zwanenburg, Paul Yushkevich, and M. Geerlings

American Journal of Neuroradiology, Jun 2016

Cited by 91

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BACKGROUND AND PURPOSE: High resolution 7T MRI is increasingly used to investigate hippocampal subfields in vivo, but most studies rely on manual segmentation which is labor intensive. We aimed to evaluate an automated technique to segment hippocampal subfields and the entorhinal cortex at 7T MRI. MATERIALS AND METHODS: The cornu ammonis (CA)1, CA2, CA3, dentate gyrus, subiculum, and entorhinal cortex were manually segmented, covering most of the long axis of the hippocampus on 0.70-mm3 T2-weighted 7T images of 26 participants (59 ± 9 years, 46% men). The automated segmentation of hippocampal subfields approach was applied and evaluated by using leave-one-out cross-validation. RESULTS: Comparison of automated segmentations with corresponding manual segmentations yielded a Dice similarity coefficient of >0.75 for CA1, the dentate gyrus, subiculum, and entorhinal cortex and >0.54 for CA2 and CA3. Intraclass correlation coefficients were >0.74 for CA1, the dentate gyrus, and subiculum; and >0.43 for CA2, CA3, and the entorhinal cortex. Restricting the comparison of the entorhinal cortex segmentation to a smaller range along the anteroposterior axis improved both intraclass correlation coefficients (left: 0.71; right: 0.82) and Dice similarity coefficients (left: 0.78; right: 0.77). The accuracy of the automated segmentation versus a manual rater was lower, though only slightly for most subfields, than the intrarater reliability of an expert manual rater, but it was similar to or slightly higher than the accuracy of an expert-versus-manual rater with ∼170 hours of training for almost all subfields. CONCLUSIONS: This work demonstrates the feasibility of using a computational technique to automatically label hippocampal subfields and the entorhinal cortex at 7T MRI, with a high accuracy for most subfields that is competitive with the labor-intensive manual segmentation. The software and atlas are publicly available: http://www.nitrc.org/projects/ashs/.
In-vivo heterogeneous functional and residual strains in human aortic valve leaflets

Ankush Aggarwal, A. Pouch, Eric K. Lai, John Lesicko, Paul Yushkevich, J. Gorman, R. Gorman, and M. Sacks

Journal of biomechanics, May 2016

Cited by 44

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Residual and physiological functional strains in soft tissues are known to play an important role in modulating organ stress distributions. Yet, no known comprehensive information on residual strains exist, or non-invasive techniques to quantify in-vivo deformations for the aortic valve (AV) leaflets. Herein we present a completely non-invasive approach for determining heterogeneous strains – both functional and residual – in semilunar valves and apply it to normal human AV leaflets. Transesophageal 3D echocardiographic (3DE) images of the AV were acquired from open-heart transplant patients, with each AV leaflet excised after heart explant and then imaged in a flattened configuration ex-vivo. Using an established spline parameterization of both 3DE segmentations and digitized ex-vivo images (Aggarwal et al., 2014), surface strains were calculated for deformation between the ex-vivo and three in-vivo configurations: fully open, just-coapted, and fully-loaded. Results indicated that leaflet area increased by an average of 20% from the ex-vivo to in-vivo open states, with a highly heterogeneous strain field. The increase in area from open to just-coapted state was the highest at an average of 25%, while that from just-coapted to fully-loaded remained almost unaltered. Going from the ex-vivo to in-vivo mid-systole configurations, the leaflet area near the basal attachment shrank slightly, whereas the free edge expanded by 10%. This was accompanied by a 10° −20° shear along the circumferential-radial direction. Moreover, the principal stretches aligned approximately with the circumferential and radial directions for all cases, with the highest stretch being along the radial direction. Collectively, these results indicated that even though the AV did not support any measurable pressure gradient in the just-coapted state, the leaflets were significantly pre-strained with respect to the excised state. Furthermore, the collagen fibers of the leaflet were almost fully recruited in the just-coapted state, making the leaflet very stiff with marginal deformation under full pressure. Lastly, the deformation was always higher in the radial direction and lower along the circumferential one, the latter direction made stiffer by the preferential alignment of collagen fibers. These results provide significant insight into the distribution of residual strains and the in-vivo strains encountered during valve opening and closing in AV leaflets, and will form an important component of the tool that can evaluate valve’s functional properties in a non-invasive manner.
Short-Term Memory Depends on Dissociable Medial Temporal Lobe Regions in Amnestic Mild Cognitive Impairment.

Sandhitsu R. Das, L. Mancuso, Ingrid R. Olson, S. Arnold, and D. Wolk

Cerebral cortex, May 2016

Cited by 23

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Quantification of Left Ventricular Function with Premature Ventricular Complexes Reveals Variable Hemodynamics

F. Contijoch, Kelly Rogers, Hannah Rears, M. Shahid, P. Kellman, J. Gorman, R. Gorman, Paul Yushkevich, Erica S. Zado, G. Supple, F. Marchlinski, W. Witschey, and Yu-Chi Han

Circulation. Arrhythmia and electrophysiology, Apr 2016

Cited by 21

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Background—Premature ventricular complexes (PVCs) are prevalent in the general population and are sometimes associated with reduced ventricular function. Current echocardiographic and cardiovascular magnetic resonance imaging techniques do not adequately address the effect of PVCs on left ventricular function. Methods and Results—Fifteen subjects with a history of frequent PVCs undergoing cardiovascular magnetic resonance imaging had real-time slice volume quantification performed using a 2-dimensional (2D) real-time cardiovascular magnetic resonance imaging technique. Synchronization of 2D real-time imaging with patient ECG allowed for different beats to be categorized by the loading beat RR duration and beat RR duration. For each beat type, global volumes were quantified via summation over all slices covering the entire ventricle. Different patterns of ectopy, including isolated PVCs, bigeminy, trigeminy, and interpolated PVCs, were observed. Global functional measurement of the different beat types based on timing demonstrated differences in preload, stroke volume, and ejection fraction. An average of hemodynamic function was quantified for each subject depending on the frequency of each observed beat type. Conclusions—Application of real-time cardiovascular magnetic resonance imaging in patients with PVCs revealed differential contribution of PVCs to hemodynamics.
Defining and validating a short form Montreal Cognitive Assessment (s-MoCA) for use in neurodegenerative disease

D. Roalf, Tyler M. Moore, D. Wolk, S. Arnold, D. Mechanic-Hamilton, Jacqueline Rick, S. Kabadi, K. Ruparel, A. Chen-Plotkin, L. Chahine, N. Dahodwala, J. Duda, D. Weintraub, and P. Moberg

Journal of neurology, neurosurgery, and psychiatry, Apr 2016

Cited by 67

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Introduction Screening for cognitive deficits is essential in neurodegenerative disease. Screening tests, such as the Montreal Cognitive Assessment (MoCA), are easily administered, correlate with neuropsychological performance and demonstrate diagnostic utility. Yet, administration time is too long for many clinical settings. Methods Item response theory and computerised adaptive testing simulation were employed to establish an abbreviated MoCA in 1850 well-characterised community-dwelling individuals with and without neurodegenerative disease. Results 8 MoCA items with high item discrimination and appropriate difficulty were identified for use in a short form (s-MoCA). The s-MoCA was highly correlated with the original MoCA, showed robust diagnostic classification and cross-validation procedures substantiated these items. Discussion Early detection of cognitive impairment is an important clinical and public health concern, but administration of screening measures is limited by time constraints in demanding clinical settings. Here, we provide as-MoCA that is valid across neurological disorders and can be administered in approximately 5 min.
A brain stress test: Cerebral perfusion during memory encoding in mild cognitive impairment

Long Xie, S. Dolui, Sandhitsu R. Das, Grace E Stockbower, Molly Daffner, H. Rao, Paul Yushkevich, J. Detre, and D. Wolk

NeuroImage : Clinical, Mar 2016

Cited by 31

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Arterial spin labeled perfusion magnetic resonance imaging (ASL MRI) provides non-invasive quantification of cerebral blood flow, which can be used as a biomarker of brain function due to the tight coupling between cerebral blood flow (CBF) and brain metabolism. A growing body of literature suggests that regional CBF is altered in neurodegenerative diseases. Here we examined ASL MRI CBF in subjects with amnestic mild cognitive impairment (n = 65) and cognitively normal healthy controls (n = 62), both at rest and during performance of a memory-encoding task. As compared to rest, task-enhanced ASL MRI improved group discrimination, which supports the notion that physiologic measures during a cognitive challenge, or “stress test”, may increase the ability to detect subtle functional changes in early disease stages. Further, logistic regression analysis demonstrated that ASL MRI and concomitantly acquired structural MRI provide complementary information of disease status. The current findings support the potential utility of task-enhanced ASL MRI as a biomarker in early Alzheimer’s disease.
Preoperative Three-Dimensional Valve Analysis Predicts Recurrent Ischemic Mitral Regurgitation After Mitral Annuloplasty.

W. Bouma, E. Lai, M. Levack, E. Shang, A. Pouch, T. Eperjesi, T. Plappert, Paul Yushkevich, M. Mariani, K. Khabbaz, T. Gleason, Feroze Mahmood, M. Acker, Y. Woo, A. Cheung, B. Jackson, J. Gorman, and R. Gorman

The Annals of thoracic surgery, Feb 2016

Cited by 53

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Maturation Along White Matter Tracts in Human Brain Using a Diffusion Tensor Surface Model Tract-Specific Analysis

Zhang Chen, Hui Zhang, Paul Yushkevich, Min Liu, and C. Beaulieu

Frontiers in Neuroanatomy, Feb 2016

Cited by 47

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Previous diffusion tensor imaging tractography studies have demonstrated exponential patterns of developmental changes for diffusion parameters such as fractional anisotropy (FA) and mean diffusivity (MD) averaged over all voxels in major white matter (WM) tracts of the human brain. However, this assumes that the entire tract is changing in unison, which may not be the case. In this study, a surface model based tract-specific analysis was applied to a cross-sectional cohort of 178 healthy subjects (83 males/95 females) aged from 6 to 30 years to spatially characterize the age-related changes of FA and MD along the trajectory of seven major WM tracts – corpus callosum (CC) and six bilateral tracts. There were unique patterns of regions that showed different exponential and linear rates of increasing FA or decreasing MD and age at which FA or MD levels off along each tract. Faster change rate of FA was observed in genu of CC and frontal-parietal part of superior longitudinal fasciculus (SLF). Inferior corticospinal tract (CST), posterior regions of association tracts such as inferior longitudinal fasciculus, inferior frontal occipital fasciculus and uncinate fasciculus also displayed earlier changing patterns for FA. MD decreases with age also exhibited this posterior-to-anterior WM maturation pattern for most tracts in females. Both males and females displayed similar FA/MD patterns of change with age along most large tracts; however, males had overall reached the FA maxima or MD minima later compared with females in most tracts with the greater differences occurring in the CST and frontal-parietal part of SLF for MD. Therefore, brain WM development has spatially varying trajectories along tracts that depend on sex and the tract.
Automated hippocampal subfield segmentation at 7 tesla MRI

L. Wisse, H. Kuijf, A. Honingh, Hong-Zhi Wang, J. Pluta, Sandhitsu R. Das, D. Wolk, J. Zwanenburg, Paul Yushkevich, and M. Geerlings

AJNR. American journal of neuroradiology, Feb 2016

Cited by 88

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BACKGROUND AND PURPOSE: High resolution 7T MRI is increasingly used to investigate hippocampal subfields in vivo, but most studies rely on manual segmentation which is labor intensive. We aimed to evaluate an automated technique to segment hippocampal subfields and the entorhinal cortex at 7T MRI. MATERIALS AND METHODS: The cornu ammonis (CA)1, CA2, CA3, dentate gyrus, subiculum, and entorhinal cortex were manually segmented, covering most of the long axis of the hippocampus on 0.70-mm3 T2-weighted 7T images of 26 participants (59 ± 9 years, 46% men). The automated segmentation of hippocampal subfields approach was applied and evaluated by using leave-one-out cross-validation. RESULTS: Comparison of automated segmentations with corresponding manual segmentations yielded a Dice similarity coefficient of >0.75 for CA1, the dentate gyrus, subiculum, and entorhinal cortex and >0.54 for CA2 and CA3. Intraclass correlation coefficients were >0.74 for CA1, the dentate gyrus, and subiculum; and >0.43 for CA2, CA3, and the entorhinal cortex. Restricting the comparison of the entorhinal cortex segmentation to a smaller range along the anteroposterior axis improved both intraclass correlation coefficients (left: 0.71; right: 0.82) and Dice similarity coefficients (left: 0.78; right: 0.77). The accuracy of the automated segmentation versus a manual rater was lower, though only slightly for most subfields, than the intrarater reliability of an expert manual rater, but it was similar to or slightly higher than the accuracy of an expert-versus-manual rater with ∼170 hours of training for almost all subfields. CONCLUSIONS: This work demonstrates the feasibility of using a computational technique to automatically label hippocampal subfields and the entorhinal cortex at 7T MRI, with a high accuracy for most subfields that is competitive with the labor-intensive manual segmentation. The software and atlas are publicly available: http://www.nitrc.org/projects/ashs/.
Alterations in ectopic myocardial contraction assessed using real-time MRI

M. Shahid, Joseph Solomon, F. Contijoch, B. Avants, Paul Yushkevich, J. Pilla, Yu-Chi Han, and W. Witschey

Journal of Cardiovascular Magnetic Resonance, Jan 2016

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Author(s): Shahid, Mohammed; Solomon, Joseph; Contijoch, Francisco; Avants, Brian; Yushkevich, Paul; Pilla, James J; Han, Yuchi; Witschey, Walter R
Core episodic encoding and retrieval processes revealed by dynamics of neural activity

J. Kragel, Youssef Ezzyat, M. Sperling, R. Gorniak, G. Worrell, Brent M. Berry, Cory S. Inman, Jui-Jui Lin, K. Davis, Sandhitsu R. Das, J. Stein, B. Jobst, K. Zaghloul, S. Sheth, D. Rizzuto, and M. Kahana

Jan 2016
Neuron Direct electrical stimulation of the human entorhinal region and hippocampus impairs memory

Jonathan F. Miller, Sang-Ah Lee, Tom Coffey, Andrew J. Watrous, M. Sperling, A. Sharan, Gregory A. Worrell, Brent M. Berry, B. Lega, B. Jobst, K. Davis, Robert E. Gross, S. Sheth, Youssef Ezzyat, Sandhitsu R. Das, J. Stein, R. Gorniak, M. Kahana, and D. Rizzuto

Jan 2016
Automated placenta segmentation from 3 D ultrasound images

I. Oguz, A. Pouch, N. Yushkevich, Hong-Zhi Wang, James, C. Gee, N. Schwartz, and Paul Yushkevich

Jan 2016

Cited by 7

2015

Preoperative Three-Dimensional Valve Analysis Predicts Recurrent Ischemic Mitral Regurgitation after Mitral Annuloplasty

W. Bouma, Eric K. Lai, M. Levack, Eric K. Shang, A. Pouch, T. Eperjesi, Theodore J. Plappert, Paul Yushkevich, M. Mariani, K. Khabbaz, Thomas G. Gleason, F. Mahmood, M. Acker, Y. Woo, A. Cheung, B. Jackson, J. Gorman, and R. Gorman

The Annals of thoracic surgery, Dec 2015

Cited by 53

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Background Valve repair for ischemic mitral regurgitation (IMR) with undersized annuloplasty rings is characterized by high IMR recurrence rates. Patient-specific preoperative imaging-based risk stratification for recurrent IMR would optimize results. We sought to determine if pre-repair three-dimensional (3D) echocardiography combined with a novel valve modeling algorithm would be predictive of IMR recurrence 6 months after repair. Methods Intraoperative transesophageal real-time 3D echocardiography was performed in 50 patients undergoing undersized ring annuloplasty for IMR (and in 21 patients with normal mitral valves). A customized image analysis protocol was used to assess 3D annular geometry and regional leaflet tethering. IMR recurrence (≥grade 2) was assessed with two-dimensional transthoracic echocardiography 6 months after repair. Results Preoperative annular geometry was similar in all IMR patients; and preoperative leaflet tethering was significantly higher in patients with recurrent IMR (n=13) as compared with patients in whom IMR did not recur IMR (n=37) (tethering index 3.91±1.01 vs. 2.90±1.17, P=0.008; tethering angles of A3 (23.5±8.9° vs. 14.4± 11.4°, P=0.012), P2 (44.4±8.8° vs. 28.2±17.0°, P=0.002), and P3 (35.2±6.0° vs. 18.6±12.7°, P<0.001)). Multivariate logistic regression analysis revealed preoperative P3 tethering angle as an independent predictor of IMR recurrence with an optimal cut-off value of 29.9° (AUC 0.92, 95%CI 0.84–1.00, P<0.001). Conclusions 3D echocardiography combined with valve modeling is predictive of recurrent IMR. Preoperative regional leaflet tethering of segment P3 is a strong independent predictor of IMR recurrence after undersized ring annuloplasty. In patients with a preoperative P3 tethering angle ≥29.9° chordal-sparing valve replacement rather than valve repair should be strongly considered.
The feasibility of quantitative MRI of perivascular spaces at 7T.

K. Cai, Rong-Wen Tain, Sandhitsu R. Das, Frederick C. Damen, Y. Sui, T. Valyi-Nagy, M. Elliott, and Xiaohong Joe Zhou

Journal of neuroscience methods, Dec 2015

Cited by 64

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Assessing atrophy measurement techniques in dementia: Results from the MIRIAD atrophy challenge

D. Cash, C. Frost, Leonardo O. Iheme, Devrim Ünay, M. Kandemir, J. Fripp, Olivier Salvado, P. Bourgeat, M. Reuter, B. Fischl, Marco Lorenzi, G. Frisoni, X. Pennec, R. Pierson, J. Gunter, M. Senjem, C. Jack, N. Guizard, Vladimir S Fonov, D. Collins, M. Modat, M. Jorge Cardoso, K. Leung, Hong-Zhi Wang, Sandhitsu R. Das, Paul Yushkevich, I. Malone, Nick C Fox, J. Schott, and S. Ourselin

Neuroimage, Dec 2015

Cited by 79

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Structural MRI is widely used for investigating brain atrophy in many neurodegenerative disorders, with several research groups developing and publishing techniques to provide quantitative assessments of this longitudinal change. Often techniques are compared through computation of required sample size estimates for future clinical trials. However interpretation of such comparisons is rendered complex because, despite using the same publicly available cohorts, the various techniques have been assessed with different data exclusions and different statistical analysis models. We created the MIRIAD atrophy challenge in order to test various capabilities of atrophy measurement techniques. The data consisted of 69 subjects (46 Alzheimer’s disease, 23 control) who were scanned multiple (up to twelve) times at nine visits over a follow-up period of one to two years, resulting in 708 total image sets. Nine participating groups from 6 countries completed the challenge by providing volumetric measurements of key structures (whole brain, lateral ventricle, left and right hippocampi) for each dataset and atrophy measurements of these structures for each time point pair (both forward and backward) of a given subject. From these results, we formally compared techniques using exactly the same dataset. First, we assessed the repeatability of each technique using rates obtained from short intervals where no measurable atrophy is expected. For those measures that provided direct measures of atrophy between pairs of images, we also assessed symmetry and transitivity. Then, we performed a statistical analysis in a consistent manner using linear mixed effect models. The models, one for repeated measures of volume made at multiple time-points and a second for repeated “direct” measures of change in brain volume, appropriately allowed for the correlation between measures made on the same subject and were shown to fit the data well. From these models, we obtained estimates of the distribution of atrophy rates in the Alzheimer’s disease (AD) and control groups and of required sample sizes to detect a 25% treatment effect, in relation to healthy ageing, with 95% significance and 80% power over follow-up periods of 6, 12, and 24 months. Uncertainty in these estimates, and head-to-head comparisons between techniques, were carried out using the bootstrap. The lateral ventricles provided the most stable measurements, followed by the brain. The hippocampi had much more variability across participants, likely because of differences in segmentation protocol and less distinct boundaries. Most methods showed no indication of bias based on the short-term interval results, and direct measures provided good consistency in terms of symmetry and transitivity. The resulting annualized rates of change derived from the model ranged from, for whole brain: − 1.4% to − 2.2% (AD) and − 0.35% to − 0.67% (control), for ventricles: 4.6% to 10.2% (AD) and 1.2% to 3.4% (control), and for hippocampi: − 1.5% to − 7.0% (AD) and − 0.4% to − 1.4% (control). There were large and statistically significant differences in the sample size requirements between many of the techniques. The lowest sample sizes for each of these structures, for a trial with a 12 month follow-up period, were 242 (95% CI: 154 to 422) for whole brain, 168 (95% CI: 112 to 282) for ventricles, 190 (95% CI: 146 to 268) for left hippocampi, and 158 (95% CI: 116 to 228) for right hippocampi. This analysis represents one of the most extensive statistical comparisons of a large number of different atrophy measurement techniques from around the globe. The challenge data will remain online and publicly available so that other groups can assess their methods.
Suspected non-AD pathology in mild cognitive impairment.

L. Wisse, N. Butala, Sandhitsu R. Das, C. Davatzikos, B. Dickerson, S. Vaishnavi, Paul Yushkevich, and D. Wolk

Neurobiology of aging, Dec 2015

Cited by 77

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Glutamate Imaging (GluCEST) Lateralizes Epileptic Foci in Non-Lesional Temporal Lobe Epilepsy

K. Davis, R. Nanga, Sandhitsu R. Das, Stephanie H. Chen, P. Hadar, J. Pollard, Timothy H. Lucas, R. Shinohara, B. Litt, H. Hariharan, M. Elliott, J. Detre, and R. Reddy

Science translational medicine, Oct 2015

Cited by 189

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Noninvasive glutamate brain imaging (GluCEST) can localize seizure foci to one hemisphere in patients with temporal lobe epilepsy. Toward visualizing the focus Many seizures, especially those that originate in the brain’s temporal lobe, start at a single spot in the brain. If drugs fail, excision of this region can often provide relief from seizures. A new imaging method that harnesses the power of a 7-T magnet shows promise in locating hard-to-find epileptic foci by visualizing the neurotransmitter glutamate. In a pilot study, the authors used glutamate chemical exchange saturation transfer (GluCEST), a very high resolution magnetic resonance imaging contrast method, to measure how much glutamate was in the hippocampi of four patients with epilepsy. Glutamate is elevated in epileptic foci. The amount of glutamate was clearly higher in one of the hippocampi in all four patients, and confirmatory methods (electroencephalography or magnetic resonance spectra) verified independently that the hippocampus with the elevated glutamate was located in the same hemisphere as the epileptic focus. Although the authors have only taken a first step toward noninvasively finding epileptic foci, their demonstration that GluCEST can localize small brain hot spots of high glutamate is promising. This approach can potentially allow a higher rate of successful surgeries in this difficult disease. When neuroimaging reveals a brain lesion, drug-resistant epilepsy patients show better outcomes after resective surgery than do the one-third of drug-resistant epilepsy patients who have normal brain magnetic resonance imaging (MRI). We applied a glutamate imaging method, GluCEST (glutamate chemical exchange saturation transfer), to patients with nonlesional temporal lobe epilepsy based on conventional MRI. GluCEST correctly lateralized the temporal lobe seizure focus on visual and quantitative analyses in all patients. MR spectra, available for a subset of patients and controls, corroborated the GluCEST findings. Hippocampal volumes were not significantly different between hemispheres. GluCEST allowed high-resolution functional imaging of brain glutamate and has potential to identify the epileptic focus in patients previously deemed nonlesional. This method may lead to improved clinical outcomes for temporal lobe epilepsy as well as other localization-related epilepsies.
Glutamate imaging (GluCEST) lateralizes epileptic foci in nonlesional temporal lobe epilepsy

K. Davis, R. Nanga, Sandhitsu R. Das, Stephanie H. Chen, P. Hadar, J. Pollard, T. Lucas, R. Shinohara, B. Litt, H. Hariharan, M. Elliott, J. Detre, and R. Reddy

Science Translational Medicine, Oct 2015

Cited by 185

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The Feasibility of Quantitative MRI of Perivascular Spaces at 7T

K. Cai, Rong-Wen Tain, Sandhitsu R. Das, Frederick C. Damen, Y. Sui, T. Valyi-Nagy, M. Elliott, and X. J. Zhou

Journal of neuroscience methods, Sep 2015

Cited by 66

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Background Dilated brain perivascular spaces (PVSs) are found to be associated with many conditions, including aging, dementia, and Alzheimer’s disease (AD). Conventionally, PVS assessment is mainly based on subjective observations of the number, size and shape of PVSs in MR images collected at clinical field strengths (≤ 3T). This study tests the feasibility of imaging and quantifying brain PVS with an ultrahigh 7T whole-body MRI scanner. New Method 3D high resolution T2-weighted brain images from healthy subjects (n=3) and AD patients (n=5) were acquired on a 7T whole-body MRI scanner. To automatically segment the small hyperintensive fluid-filling PVS structures, we also developed a quantitative program based on algorithms for spatial gradient, component connectivity, edge-detection, k-means clustering, etc, producing quantitative results of white matter PVS volume densities. Results The 3D maps of automatically segmented PVS show an apparent increase in PVS density in AD patients compared to age-matched healthy controls due to the PVS dilation (8.0 ± 2.1 v/v% in AD vs. 4.9 ± 1.3% in controls, p<0.05). Comparison with Existing Method We demonstrated that 7T provides sufficient SNR and resolution for quantitatively measuring PVSs in deep white matter that is challenging with clinical MRI systems (≤ 3T). Compared to the conventional visual counting and rating for the PVS assessment, the quantitation method we developed is automatic and objective. Conclusions Quantitative PVS MRI at 7T may serve as a non-invasive and endogenous imaging biomarker for diseases with PVS dilation.
Medially constrained deformable modeling for segmentation of branching medial structures: Application to aortic valve segmentation and morphometry

A. Pouch, Sijie Tian, Manabu Takebe, Jiefu Yuan, R. Gorman, A. Cheung, Hong-Zhi Wang, B. Jackson, J. Gorman, R. Gorman, and Paul Yushkevich

Medical image analysis, Sep 2015

Cited by 35

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Deformable modeling with medial axis representation is a useful means of segmenting and parametrically describing the shape of anatomical structures in medical images. Continuous medial representation (cm-rep) is a “skeleton-first” approach to deformable medial modeling that explicitly parameterizes an object’s medial axis and derives the object’s boundary algorithmically. Although cm-rep has effectively been used to segment and model a number of anatomical structures with non-branching medial topologies, the framework is challenging to apply to objects with branching medial geometries since branch curves in the medial axis are difficult to parameterize. In this work, we demonstrate the first clinical application of a new “boundary-first” deformable medial modeling paradigm, wherein an object’s boundary is explicitly described and constraints are imposed on boundary geometry to preserve the branching configuration of the medial axis during model deformation. This “boundary-first” framework is leveraged to segment and morphologically analyze the aortic valve apparatus in 3D echocardiographic images. Relative to manual tracing, segmentation with deformable medial modeling achieves a mean boundary error of 0.41 ± 0.10 mm (approximately one voxel) in 22 3DE images of normal aortic valves at systole. Deformable medial modeling is additionally demonstrated on pathological cases, including aortic stenosis, Marfan syndrome, and bicuspid aortic valve disease. This study demonstrates a promising approach for quantitative 3DE analysis of aortic valve morphology.
Suspected non-AD pathology in Mild Cognitive Impairment

L. Wisse, N. Butala, Sandhitsu R. Das, C. Davatzikos, B. Dickerson, S. Vaishnavi, Paul Yushkevich, and D. Wolk

Neurobiology of aging, Sep 2015

Cited by 84

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We aim to better characterize Mild Cognitive Impairment (MCI) patients with suspected non-Alzheimer’s Disease (AD) pathology (SNAP) based on their longitudinal outcome, cognition, biofluid and neuroimaging profile. MCI participants (n=361) from ADNI-GO/2 were designated ‘amyloid positive’ with abnormal Aβ42 levels (AMY+) and ‘neurodegeneration positive’ (NEU+) with abnormal hippocampal volume or hypometabolism using FDG-PET. SNAP was compared with the other MCI groups and with AMY− controls. AMY−NEU+/SNAP, 16.6%, were older than the NEU− groups, but not AMY− controls. They had a lower conversion rate to AD after 24 months than AMY+NEU+ MCI participants. SNAP MCI participants had similar Aβ42 levels, florbetapir and tau levels, but larger white matter hyperintensity volumes than AMY− controls and AMY−NEU− MCI participants. SNAP participants performed worse on all memory domains and on other cognitive domains, than AMY−NEU− participants, but less so than AMY+NEU+ participants. Subthreshold levels of cerebral amyloidosis are unlikely to play a role in SNAP MCI, but pathologies involving the hippocampus and cerebrovascular disease may underlie the neurodegeneration and cognitive impairment in this group.
O1‐07‐05: Mild cognitive impairment patients with suspected non‐alzheimer’s disease pathology

L. Wisse, N. Butala, Sandy Das, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2015

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P4‐258: Towards a harmonized protocol for hippocampal subfield segmentation: An update

L. Wisse, Ana M. Daugherty, R. La Joie, R. Insausti, M. Yassa, Valerie A. Carr, Arne D. Ekstrom, G. Kerchner, S. Mueller, Craig E. L. Stark, Lei Wang, and Paul Yushkevich

Alzheimer’s & Dementia, Jul 2015

DOI
User-initialized active contour segmentation and golden-angle real-time cardiovascular magnetic resonance enable accurate assessment of LV function in patients with sinus rhythm and arrhythmias

F. Contijoch, W. Witschey, Kelly Rogers, Hannah Rears, M. Hansen, Paul Yushkevich, J. Gorman, R. Gorman, and Yu-Chi Han

Journal of Cardiovascular Magnetic Resonance, May 2015

Cited by 36

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BackgroundData obtained during arrhythmia is retained in real-time cardiovascular magnetic resonance (rt-CMR), but there is limited and inconsistent evidence to show that rt-CMR can accurately assess beat-to-beat variation in left ventricular (LV) function or during an arrhythmia.MethodsMulti-slice, short axis cine and real-time golden-angle radial CMR data was collected in 22 clinical patients (18 in sinus rhythm and 4 patients with arrhythmia). A user-initialized active contour segmentation (ACS) software was validated via comparison to manual segmentation on clinically accepted software. For each image in the 2D acquisitions, slice volume was calculated and global LV volumes were estimated via summation across the LV using multiple slices. Real-time imaging data was reconstructed using different image exposure times and frame rates to evaluate the effect of temporal resolution on measured function in each slice via ACS. Finally, global volumetric function of ectopic and non-ectopic beats was measured using ACS in patients with arrhythmias.ResultsACS provides global LV volume measurements that are not significantly different from manual quantification of retrospectively gated cine images in sinus rhythm patients. With an exposure time of 95.2 ms and a frame rate of > 89 frames per second, golden-angle real-time imaging accurately captures hemodynamic function over a range of patient heart rates. In four patients with frequent ectopic contractions, initial quantification of the impact of ectopic beats on hemodynamic function was demonstrated.ConclusionUser-initialized active contours and golden-angle real-time radial CMR can be used to determine time-varying LV function in patients. These methods will be very useful for the assessment of LV function in patients with frequent arrhythmias.
Prevalence of Cerebral Amyloid Pathology in Persons Without Dementia

W. Jansen, R. Ossenkoppele, D. Knol, B. Tijms, P. Scheltens, F. Verhey, P. Visser, P. Aalten, D. Aarsland, D. Alcolea, Myriam Alexander, I. Almdahl, Steven E. Arnold, I. Baldeiras, H. Barthel, B. N. Berckel, K. Bibeau, K. Blennow, David J. Brooks, M. Buchem, V. Camus, E. Cavedo, Ke-Wei Chen, G. Chételat, A. Cohen, A. Drzezga, S. Engelborghs, A. Fagan, T. Fladby, A. Fleisher, W. M. Flier, Lisa Ford, Stefan Förster, J. Fortea, N. Foskett, K. Frederiksen, Y. Freund-Levi, G. Frisoni, L. Froelich, T. Gabryelewicz, K. Gill, O. Gkatzima, E. Gómez-Tortosa, M. F. Gordon, T. Grimmer, Harald Hampel, L. Hausner, Sabine Hellwig, S. Herukka, Helmut Hildebrandt, and 79 more authors

JAMA, May 2015

Cited by 1518

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IMPORTANCE Cerebral amyloid-β aggregation is an early pathological event in Alzheimer disease (AD), starting decades before dementia onset. Estimates of the prevalence of amyloid pathology in persons without dementia are needed to understand the development of AD and to design prevention studies. OBJECTIVE To use individual participant data meta-analysis to estimate the prevalence of amyloid pathology as measured with biomarkers in participants with normal cognition, subjective cognitive impairment (SCI), or mild cognitive impairment (MCI). DATA SOURCES Relevant biomarker studies identified by searching studies published before April 2015 using the MEDLINE and Web of Science databases and through personal communication with investigators. STUDY SELECTION Studies were included if they provided individual participant data for participants without dementia and used an a priori defined cutoff for amyloid positivity. DATA EXTRACTION AND SYNTHESIS Individual records were provided for 2914 participants with normal cognition, 697 with SCI, and 3972 with MCI aged 18 to 100 years from 55 studies. MAIN OUTCOMES AND MEASURES Prevalence of amyloid pathology on positron emission tomography or in cerebrospinal fluid according to AD risk factors (age, apolipoprotein E [APOE] genotype, sex, and education) estimated by generalized estimating equations. RESULTS The prevalence of amyloid pathology increased from age 50 to 90 years from 10% (95% CI, 8%-13%) to 44% (95% CI, 37%-51%) among participants with normal cognition; from 12% (95% CI, 8%-18%) to 43% (95% CI, 32%-55%) among patients with SCI; and from 27% (95% CI, 23%-32%) to 71% (95% CI, 66%-76%) among patients with MCI. APOE-ε4 carriers had 2 to 3 times higher prevalence estimates than noncarriers. The age at which 15% of the participants with normal cognition were amyloid positive was approximately 40 years for APOEε4ε4 carriers, 50 years for ε2ε4 carriers, 55 years for ε3ε4 carriers, 65 years for ε3ε3 carriers, and 95 years for ε2ε3 carriers. Amyloid positivity was more common in highly educated participants but not associated with sex or biomarker modality. CONCLUSIONS AND RELEVANCE Among persons without dementia, the prevalence of cerebral amyloid pathology as determined by positron emission tomography or cerebrospinal fluid findings was associated with age, APOEgenotype, and presence of cognitive impairment. These findings suggest a 20- to 30-year interval between first development of amyloid positivity and onset of dementia.
The relationship of contextual cueing and hippocampal volume in amnestic MCI patients and cognitively normal older adults

S. Negash, Daria Kliot, D. V. Howard, J. H. Howard, Sandihitsu R. Das, Paul Yushkevich, J. Pluta, S. Arnold, and D. Wolk

Journal of the International Neuropsychological Society : JINS, Apr 2015

Cited by 16

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Abstract There is currently some debate as to whether hippocampus mediates contextual cueing. In the present study, we examined contextual cueing in patients diagnosed with mild cognitive impairment (MCI) and healthy older adults, with the main goal of investigating the role of hippocampus in this form of learning. Amnestic MCI (aMCI) patients and healthy controls completed the contextual cueing task, in which they were asked to search for a target (a horizontal T) in an array of distractors (rotated L’s). Unbeknownst to them, the spatial arrangement of elements on some displays was repeated thus making the configuration a contextual cue to the location of the target. In contrast, the configuration for novel displays was generated randomly on each trial. The difference in response times between repeated and novel configurations served as a measure of contextual learning. aMCI patients, as a group, were able to learn spatial contextual cues as well as healthy older adults. However, better learning on this task was associated with higher hippocampal volume, particularly in right hemisphere. Furthermore, contextual cueing performance was significantly associated with hippocampal volume, even after controlling for age and MCI status. These findings support the role of the hippocampus in learning of spatial contexts, and also suggest that the contextual cueing paradigm can be useful in detecting neuropathological changes associated with the hippocampus. (JINS, 2015, 21, 285–296)
Relationship of Contextual Cueing and Hippocampal Volume in Amnestic Mild Cognitive Impairment Patients and Cognitively Normal Older Adults

S. Negash, Daria Kliot, D. V. Howard, J. Howard, Sandihitsu R. Das, Paul Yushkevich, J. Pluta, S. Arnold, and D. Wolk

Journal of the International Neuropsychological Society, Apr 2015

Cited by 16

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4D-transesophageal echocardiography and emerging imaging modalities for guiding mitral valve repair.

A. Pouch, B. Jackson, Paul Yushkevich, J. Gorman, and R. Gorman

Annals of cardiothoracic surgery, Apr 2015

Cited by 5

DOI
Multi-atlas label fusion with augmented atlases for fast and accurate segmentation of cardiac MR images

Long Xie, S. Sedai, Xi Liang, Colin B. Compas, Hong-Zhi Wang, Paul Yushkevich, and T. Syeda-Mahmood

In IEEE International Symposium on Biomedical Imaging, Apr 2015

Cited by 6

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Quantitative Comparison of 21 Protocols for Labeling Hippocampal Subfields and Parahippocampal Subregions in In Vivo MRI: Towards a Harmonized Segmentation Protocol

Paul Yushkevich, R. Amaral, Jean C. Augustinack, Andrew R. Bender, Jeffrey D. Bernstein, M. Boccardi, M. Bocchetta, A. Burggren, Valerie A. Carr, M. Chakravarty, G. Chételat, Ana M. Daugherty, L. Davachi, Song-Lin Ding, Arne D. Ekstrom, M. Geerlings, Abdul S. Hassan, Yu-Shan Huang, Eugenio Iglesias, R. La Joie, G. Kerchner, Karen F. Larocque, L. Libby, N. Malykhin, S. Mueller, R. Olsen, D. Palombo, M. Parekh, J. Pluta, Alison R. Preston, Jens C. Pruessner, Charan Ranganath, N. Raz, Margaret L. Schlichting, D. Schoemaker, Sachi Singh, Craig E. L. Stark, N. Suthana, A. Tompary, Marta M. Turowski, Koenraad Van Leemput, A. Wagner, Lei Wang, Julie L. Winterburn, L. Wisse, M. Yassa, and Michael M. Zeineh

NeuroImage, Jan 2015

Cited by 350

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OBJECTIVE An increasing number of human in vivo magnetic resonance imaging (MRI) studies have focused on examining the structure and function of the subfields of the hippocampal formation (the dentate gyrus, CA fields 1–3, and the subiculum) and subregions of the parahippocampal gyrus (entorhinal, perirhinal, and parahippocampal cortices). The ability to interpret the results of such studies and to relate them to each other would be improved if a common standard existed for labeling hippocampal subfields and parahippocampal subregions. Currently, research groups label different subsets of structures and use different rules, landmarks, and cues to define their anatomical extents. This paper characterizes, both qualitatively and quantitatively, the variability in the existing manual segmentation protocols for labeling hippocampal and parahippocampal substructures in MRI, with the goal of guiding subsequent work on developing a harmonized substructure segmentation protocol. METHOD MRI scans of a single healthy adult human subject were acquired both at 3 Tesla and 7 Tesla. Representatives from 21 research groups applied their respective manual segmentation protocols to the MRI modalities of their choice. The resulting set of 21 segmentations was analyzed in a common anatomical space to quantify similarity and identify areas of agreement. RESULTS The differences between the 21 protocols include the region within which segmentation is performed, the set of anatomical labels used, and the extents of specific anatomical labels. The greatest overall disagreement among the protocols is at the CA1/subiculum boundary, and disagreement across all structures is greatest in the anterior portion of the hippocampal formation relative to the body and tail. CONCLUSIONS The combined examination of the 21 protocols in the same dataset suggests possible strategies towards developing a harmonized subfield segmentation protocol and facilitates comparison between published studies.
Anterior and posterior MTL networks in aging and MCI.

Sandhitsu R. Das, J. Pluta, L. Mancuso, Daria Kliot, Paul Yushkevich, and D. Wolk

Neurobiology of aging, Jan 2015

Cited by 55

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Novel Imaging Biomarkers for Alzheimer’s Disease and Related Disorders (NIBAD)

Lei Wang, Paul Yushkevich, and S. Ourselin

Jan 2015

Cited by 1

2014

White Matter Disease Contributes to Apathy and Disinhibition in Behavioral Variant Frontotemporal Dementia

John P. Powers, Lauren Massimo, C. McMillan, Paul Yushkevich, Hui Zhang, J. Gee, and M. Grossman

Cognitive and behavioral neurology : official journal of the Society for Behavioral and Cognitive Neurology, Dec 2014

Cited by 40

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Objective:To relate changes in fractional anisotropy associated with behavioral variant frontotemporal dementia to measures of apathy and disinhibition. Background:Apathy and disinhibition are the 2 most common behavioral features of behavioral variant frontotemporal dementia, and these symptoms are associated with accelerated patient decline and caregiver stress. However, little is known about how white matter disease contributes to these symptoms. Methods:We collected neuropsychiatric data, volumetric magnetic resonance imaging, and diffusion-weighted imaging in 11 patients who met published criteria for behavioral variant frontotemporal dementia and had an autopsy-validated cerebrospinal fluid profile consistent with frontotemporal lobar degeneration. We also collected imaging data on 34 healthy seniors for analyses defining regions of disease in the patients. We calculated and analyzed fractional anisotropy with a white matter tract-specific method. This approach uses anatomically guided data reduction to increase sensitivity, and localizes results within canonically defined tracts. We used nonparametric, cluster-based statistical analysis to relate fractional anisotropy to neuropsychiatric measures of apathy and disinhibition. Results:The patients with behavioral variant frontotemporal dementia had widespread reductions in fractional anisotropy in anterior portions of frontal and temporal white matter, compared to the controls. Fractional anisotropy correlated with apathy in the left uncinate fasciculus and with disinhibition in the right corona radiata. Conclusions:In patients with behavioral variant frontotemporal dementia, apathy and disinhibition are associated with distinct regions of white matter disease. The implicated fiber tracts likely support frontotemporal networks that are involved in goal-directed behavior.
Large-scale evaluation of ANTs and FreeSurfer cortical thickness measurements

N. Tustison, Philip A Cook, Arno Klein, G. Song, Sandhitsu R. Das, J. Duda, Benjamin M. Kandel, Niels Strien, J. Stone, J. Gee, and B. Avants

NeuroImage, Oct 2014

Cited by 692

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Anterior and Posterior MTL Networks in Aging and MCI

Sandhitsu R. Das, J. Pluta, L. Mancuso, Daria Kliot, Paul Yushkevich, and D. Wolk

Neurobiology of aging, Sep 2014

Cited by 58

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Two neuroanatomically dissociable, large-scale cortical memory networks, referred to as the anterior and posterior MTL (medial temporal lobe) networks have recently been described (Kahn et al 2008; Libby et al 2012) in young adults using resting-state BOLD-fMRI-based functional connectivity (fc-BOLD). They have been hypothesized to subserve distinct mnemonic, as well as non-memory cognitive functions, and are thought to be associated with differential vulnerability in neurological disorders (Ranganath & Ritchey 2012). In this paper, we demonstrate the existence of these functional networks in an older adult population, and in a cohort of patients diagnosed with amnestic mild cognitive impairment (MCI). Anatomical subregions of interest (ROI) in the MTL were defined using high-resolution T2-weighted MRI and used as seeds for defining the putative networks using fc-BOLD. While the literature has suggested that the posterior MTL network is particularly vulnerable to early Alzheimer’s Disease, we show that both networks are affected in MCI, to varying degrees, compared to the control group. Further, cortical thickness in the brain regions defined by these networks was reduced in MCI.
Segmentation of the Aortic Valve Apparatus in 3D Echocardiographic Images: Deformable Modeling of a Branching Medial Structure

A. Pouch, Sijie Tian, Manabu Takabe, Hong-Zhi Wang, Jiefu Yuan, A. Cheung, B. Jackson, J. Gorman, R. Gorman, and Paul Yushkevich

In International Workshop on Statistical Atlases and Computational Models of the Heart, Sep 2014

Cited by 14

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3D echocardiographic (3DE) imaging is a useful tool for assessing the complex geometry of the aortic valve apparatus. Segmentation of this structure in 3DE images is a challenging task that benefits from shape-guided deformable modeling methods, which enable inter-subject statistical shape comparison. Prior work demonstrates the efficacy of using continuous medial representation (cm-rep) as a shape descriptor for valve leaflets. However, its application to the entire aortic valve apparatus is limited since the structure has a branching medial geometry that cannot be explicitly parameterized in the original cm-rep framework. In this work, we show that the aortic valve apparatus can be accurately segmented using a new branching medial modeling paradigm. The segmentation method achieves a mean boundary displacement of 0.6 ± 0.1 mm (approximately one voxel) relative to manual segmentation on 11 3DE images of normal open aortic valves. This study demonstrates a promising approach for quantitative 3DE analysis of aortic valve morphology.
Automatic Clustering and Thickness Measurement of Anatomical Variants of the Human Perirhinal Cortex

Long Xie, J. Pluta, Hong-Zhi Wang, Sandhitsu R. Das, L. Mancuso, Dasha Kliot, B. Avants, Song-Lin Ding, D. Wolk, and Paul Yushkevich

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Sep 2014

Cited by 10

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The entorhinal cortex (ERC) and the perirhinal cortex (PRC) are subregions of the medial temporal lobe (MTL) that play important roles in episodic memory representations, as well as serving as a conduit between other neocortical areas and the hippocampus. They are also the sites where neuronal damage first occurs in Alzheimer’s disease (AD). The ability to automatically quantify the volume and thickness of the ERC and PRC is desirable because these localized measures can potentially serve as better imaging biomarkers for AD and other neurodegenerative diseases. However, large anatomical variation in the PRC makes it a challenging area for analysis. In order to address this problem, we propose an automatic segmentation, clustering, and thickness measurement approach that explicitly accounts for anatomical variation. The approach is targeted to highly anisotropic (0.4×0.4×2.0mm3) T2-weighted MRI scans that are preferred by many authors for detailed imaging of the MTL, but which pose challenges for segmentation and shape analysis. After automatically labeling MTL substructures using multi-atlas segmentation, our method clusters subjects into groups based on the shape of the PRC, constructs unbiased population templates for each group, and uses the smooth surface representations obtained during template construction to extract regional thickness measurements in the space of each subject. The proposed thickness measures are evaluated in the context of discrimination between patients with Mild Cognitive Impairment (MCI) and normal controls (NC).
Automated Volumetry and Regional Thickness Analysis of Hippocampal Subfields and Medial Temporal Cortical Structures in Mild Cognitive Impairment

Paul Yushkevich, J. Pluta, Hong-Zhi Wang, Long Xie, Song-Lin Ding, E. Gertje, L. Mancuso, Daria Kliot, Sandhitsu R. Das, and D. Wolk

Human brain mapping, Sep 2014

Cited by 612

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We evaluate a fully automatic technique for labeling hippocampal subfields and cortical subregions in the medial temporal lobe in in vivo 3 Tesla MRI. The method performs segmentation on a T2‐weighted MRI scan with 0.4 × 0.4 × 2.0 mm3 resolution, partial brain coverage, and oblique orientation. Hippocampal subfields, entorhinal cortex, and perirhinal cortex are labeled using a pipeline that combines multi‐atlas label fusion and learning‐based error correction. In contrast to earlier work on automatic subfield segmentation in T2‐weighted MRI [Yushkevich et al., 2010], our approach requires no manual initialization, labels hippocampal subfields over a greater anterior‐posterior extent, and labels the perirhinal cortex, which is further subdivided into Brodmann areas 35 and 36. The accuracy of the automatic segmentation relative to manual segmentation is measured using cross‐validation in 29 subjects from a study of amnestic mild cognitive impairment (aMCI) and is highest for the dentate gyrus (Dice coefficient is 0.823), CA1 (0.803), perirhinal cortex (0.797), and entorhinal cortex (0.786) labels. A larger cohort of 83 subjects is used to examine the effects of aMCI in the hippocampal region using both subfield volume and regional subfield thickness maps. Most significant differences between aMCI and healthy aging are observed bilaterally in the CA1 subfield and in the left Brodmann area 35. Thickness analysis results are consistent with volumetry, but provide additional regional specificity and suggest nonuniformity in the effects of aMCI on hippocampal subfields and MTL cortical subregions. Hum Brain Mapp, 36:258–287, 2015. © 2014 Wiley Periodicals, Inc.
IC‐P‐168: INVOLVEMENT OF ANTERIOR AND POSTERIOR MTL NETWORKS IN EARLY ALZHEIMER’S DISEASE

Sandhitsu R. Das, J. Pluta, L. Mancuso, Dasha Kliot, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2014

Cited by 1

DOI
IC‐P‐169: MTL SUBREGIONAL MORPHOMETRY USING HIGH RESOLUTION MRI IN ADNI2

Sandhitsu R. Das, J. Pluta, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2014

DOI
P3‐184: MTL SUBREGIONAL MORPHOMETRY USING HIGH RESOLUTION MRI IN ADNI2

Sandhitsu R. Das, J. Pluta, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2014

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P4‐104: INVOLVEMENT OF ANTERIOR AND POSTERIOR MEDIAL TEMPORAL LOBE NETWORKS IN EARLY ALZHEIMER’S DISEASE

Sandhitsu R. Das, J. Pluta, L. Mancuso, Dasha Kliot, Paul Yushkevich, and D. Wolk

Alzheimer’s & Dementia, Jul 2014

Cited by 1

DOI
Subject-specific functional parcellation via Prior Based Eigenanatomy

Paramveer S. Dhillon, D. Wolk, Sandhitsu R. Das, L. Ungar, J. Gee, and B. Avants

NeuroImage, May 2014

Cited by 18

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We present a new framework for prior-constrained sparse decomposition of matrices derived from the neuroimaging data and apply this method to functional network analysis of a clinically relevant population. Matrix decomposition methods are powerful dimensionality reduction tools that have found widespread use in neuroimaging. However, the unconstrained nature of these totally data-driven techniques makes it difficult to interpret the results in a domain where network-specific hypotheses may exist. We propose a novel approach, Prior Based Eigenanatomy (p-Eigen), which seeks to identify a data-driven matrix decomposition but at the same time constrains the individual components by spatial anatomical priors (probabilistic ROIs). We formulate our novel solution in terms of prior-constrained ℓ1 penalized (sparse) principal component analysis. p-Eigen starts with a common functional parcellation for all the subjects and refines it with subject-specific information. This enables modeling of the inter-subject variability in the functional parcel boundaries and allows us to construct subject specific networks with reduced sensitivity to ROI placement. We show that while still maintaining correspondence across subjects, p-Eigen extracts biologically-relevant and patient-specific functional parcels that facilitate hypothesis-driven network analysis. We construct Default Mode Network (DMN) connectivity graphs using p-Eigen refined ROIs and use them in a classification paradigm. Our results show that the functional connectivity graphs derived from p-Eigen significantly aid classification of Mild Cognitive Impairment (MCI) as well as the prediction of scores in a Delayed Recall memory task when compared to graph metrics derived from 1) standard registration-based seed ROI definitions, 2) totally data driven ROIs 3) a model based on standard demographics plus hippocampal volume as covariates and 4) Ward Clustering based data driven ROIs. In summary, p-Eigen incarnates a new class of prior-constrained dimensionality reduction tools that may improve our understanding of the relationship between MCI and functional connectivity.
Real-time magnetic resonance imaging technique for determining left ventricle pressure-volume loops.

W. Witschey, F. Contijoch, Jeremy R. McGarvey, V. Ferrari, M. Hansen, Madonna E. Lee, S. Takebayashi, C. Aoki, J. Chirinos, Paul Yushkevich, J. Gorman, J. Pilla, and R. Gorman

The Annals of thoracic surgery, May 2014

Cited by 20

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A Real-Time Magnetic Resonance Imaging Technique for Determining Left Ventricle Pressure-Volume Loops

W. Witschey, F. Contijoch, Jeremy R. McGarvey, V. Ferrari, M. Hansen, Madonna E. Lee, Satoshi Takebayashi, Chikashi Aoki, J. Chirinos, Paul Yushkevich, J. Gorman, J. Pilla, and R. Gorman

The Annals of thoracic surgery, Mar 2014

Cited by 20

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Background Rapid determination of the left ventricular (LV) pressure-volume (PV) relationship as loading conditions are varied is the gold standard for assessment of LV function. Cine magnetic resonance imaging (MRI) does not have sufficient spatiotemporal resolution to assess beat-to-beat changes of the LV PV relationship required to measure the LV end-systolic elastance (EES) or preload-recruitable stroke work (PRSW). Our aim was to investigate real-time MRI and semi-automated LV measurement of LV volume to measure PV relations in large animals under normal and inotropically stressed physiologic conditions. Methods and Results We determined that PV relationships could be accurately measured using an image exposure time Tex < 100 ms and frame rate Tfr < 50 ms at elevated heart rates ( 140 bpm) using a golden angle radial MRI k-space trajectory and active contour segmentation. With an optimized exposure time (Tex = 95 ms and frame rate Tfr = 2.8 ms), we found that there was no significant difference between cine and real-time MRI at rest in end-diastolic volume (EDV), end-systolic volume (ESV), ejection fraction (EF), stroke volume (SV) or cardiac output (CO) (n=5, P<0.05) at either normal or elevated heart rates. We found EES increased from 1.9 ± 0.7 to 3.1 ± 0.3 mmHg/mL and PRSW increased from 6.2 ± 1.2 to 9.1 ± 0.9 mmHg during continuous IV dobutamine infusion (n=5, P<0.05). Conclusions Real-time MRI can assess LV volumes, EES and PRSW at baseline and elevated inotropic states.
Quantification of left ventricular deformation fields from undersampled radial, real-time cardiac MRI

F. Contijoch, Kelly Rogers, B. Avants, Paul Yushkevich, Vahid Hoshmand, R. Gorman, Yu-Chi Han, and W. Witschey

Journal of Cardiovascular Magnetic Resonance, Jan 2014

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Background Regional ventricular elasticity is altered in ischemic heart disease and LV hypertrophy, potentially contributing to and sustaining a ventricular remodeling process. Conventional methods to measure regional ventricular elasticity in preclinical animal models require high fidelity ventricular pressure measurement, sonomicrometry transducers and dynamic modulation of preload. These procedures are highly invasive and provide only limited regional information; patient studies are prohibitive. We dynamically measure global LV elastance using undersampled radial real-time MRI and seek to find regional LV elastance in these studies. This requires tracking LV motion derived from wall thickness measurements in a large number of real-time image frames at high accuracy. We assessed several motion tracking algorithms and characterize their fidelity with respect to true motion labeled by experts and sensitivity to residual radial streak artifact. Methods A series of short axis MR slices were acquired in 9 patients using a golden-angle radial bSSFP trajectory (total views = 4000, radial views per image = 34, shared profiles = 31, reconstructed frame rate = 98 fps) and reconstructed via conjugate gradient-SENSE based iterative reconstruction. Two independent researchers manually segmented the datasets and the movies were restricted to three full heartbeats to limit the number of images. Image registrations were performed between the initial end-diastolic frame and all subsequent frames. The image registrations were performed using b-spline and symmetric diffeomorphic (SyN) image registration across a range of spatial scales (shown in Table 1). Four separate image registration metrics were investigated (mutual information, meansquared overlap, cross-correlation, and demons). Although we expected mean squares and cross-correlation to perform better in this intramodality registration, radial streaking could potentially corrupt data integrity. The resulting deformation fields were evaluated using an array of metrics (dice coefficient, area overlap, false positive, and false negative rate) for all registrations, image frames and patients.
The Frank-Starling relationship of the heart revealed in a large animal study utilizing real-time undersampled radial MRI at variable inotropic state and heart rate

W. Witschey, F. Contijoch, Jeremy R. McGarvey, V. Ferrari, M. Hansen, J. Chirinos, Paul Yushkevich, J. Gorman, R. Gorman, and J. Pilla

Journal of Cardiovascular Magnetic Resonance, Jan 2014

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Background LV performance is coupled to loading conditions (i.e. preload and afterload) and myocardial contractility (1,2). Therefore load-independence is an important means to isolate and study LV contractility in preclinical studies of cardiovascular pharmaceuticals and devices (3). Precise and rapid assessment of LV pressure is achieved with high fidelity catheter-based pressure transducers but measurements of LV volume are more difficult and less reliable. Thus far, MRI has not demonstrated sufficient spatiotemporal resolution to measure beat-to-beat changes of the pressure-volume (PV) loop to measure left ventricular (LV) elasticity or preload-recruitable stroke work (PRSW). Our aim was to develop a realtime (rtMRI) approach to measure PV and FrankStarling relationships in a preclinical model of heart disease under normal and stressed physiologic conditions.
Statistical assessment of normal mitral annular geometry using automated three-dimensional echocardiographic analysis.

A. Pouch, M. Vergnat, Jeremy R. McGarvey, G. Ferrari, B. Jackson, C. Sehgal, Paul Yushkevich, R. Gorman, and J. Gorman

The Annals of thoracic surgery, Jan 2014

Cited by 20

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2013

White Matter Disease Correlates with Lexical Retrieval Deficits in Primary Progressive Aphasia

John P. Powers, C. McMillan, C. Brun, Paul Yushkevich, Hui Zhang, J. Gee, and M. Grossman

Frontiers in Neurology, Dec 2013

Cited by 30

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Objective: To relate fractional anisotropy (FA) changes associated with the semantic and logopenic variants of primary progressive aphasia (PPA) to measures of lexical retrieval. Methods: We collected neuropsychological testing, volumetric magnetic resonance imaging, and diffusion-weighted imaging on semantic variant PPA (svPPA) (n = 11) and logopenic variant PPA (lvPPA) (n = 13) patients diagnosed using published criteria. We also acquired neuroimaging data on a group of demographically comparable healthy seniors (n = 34). FA was calculated and analyzed using a white matter (WM) tract-specific analysis approach. This approach utilizes anatomically guided data reduction to increase sensitivity and localizes results within canonically defined tracts. We used non-parametric, cluster-based statistical analysis to relate language performance to FA and determine regions of reduced FA in patients. Results: We found widespread FA reductions in WM for both variants of PPA. FA was related to both confrontation naming and category naming fluency performance in left uncinate fasciculus and corpus callosum in svPPA and left superior and inferior longitudinal fasciculi in lvPPA. Conclusion: SvPPA and lvPPA are associated with distinct disruptions of a large-scale network implicated in lexical retrieval, and the WM disease in each phenotype may contribute to language impairments including lexical retrieval.
Subjective Memory Complaints, Cognitive Performance, and Psychological Factors in Healthy Older Adults

S. Steinberg, S. Negash, M. Sammel, H. Bogner, B. Harel, Melissa Livney, Hannah McCoubrey, D. Wolk, M. Kling, and S. Arnold

American journal of Alzheimer’s disease and other dementias, Dec 2013

Cited by 171

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Objective: To determine whether subjective memory complaints (SMCs) are associated with performance on objective cognitive measures and psychological factors in healthy, community-dwelling older adults. Method: The cohort was composed of adults, 65 years and older with no clinical evidence of cognitive impairment (n = 125). Participants were administered: CogState computerized neurocognitive battery, Prospective Retrospective Memory Questionnaire, personality and meaning-in-life measures. Results: SMCs were associated with poorer performance on measures of executive function (p = 0.001). SMCs were also associated with impaired delayed recall (p = 0.006) but this did not remain significant after statistical adjustment for multiple comparisons. SMCs were inversely associated with conscientiousness (p = 0.004) and directly associated with neuroticism (p < 0.001). Higher scores on SMCs were associated with higher perceived stress (p = 0.001), and ineffective coping styles (p = 0.001). Factors contributing to meaning-in-life were associated with fewer SMCs (p < 0.05). Conclusions: SMCs may reflect early, subtle cognitive changes and are associated with personality traits and meaning-in-life in healthy, older adults.
Multi-atlas segmentation with joint label fusion and corrective learning—an open source implementation

Hong-Zhi Wang, and Paul Yushkevich

Frontiers in Neuroinformatics, Nov 2013

Cited by 227

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Label fusion based multi-atlas segmentation has proven to be one of the most competitive techniques for medical image segmentation. This technique transfers segmentations from expert-labeled images, called atlases, to a novel image using deformable image registration. Errors produced by label transfer are further reduced by label fusion that combines the results produced by all atlases into a consensus solution. Among the proposed label fusion strategies, weighted voting with spatially varying weight distributions derived from atlas-target intensity similarity is a simple and highly effective label fusion technique. However, one limitation of most weighted voting methods is that the weights are computed independently for each atlas, without taking into account the fact that different atlases may produce similar label errors. To address this problem, we recently developed the joint label fusion technique and the corrective learning technique, which won the first place of the 2012 MICCAI Multi-Atlas Labeling Challenge and was one of the top performers in 2013 MICCAI Segmentation: Algorithms, Theory and Applications (SATA) challenge. To make our techniques more accessible to the scientific research community, we describe an Insight-Toolkit based open source implementation of our label fusion methods. Our implementation extends our methods to work with multi-modality imaging data and is more suitable for segmentation problems with multiple labels. We demonstrate the usage of our tools through applying them to the 2012 MICCAI Multi-Atlas Labeling Challenge brain image dataset and the 2013 SATA challenge canine leg image dataset. We report the best results on these two datasets so far.
Fully automatic segmentation of the mitral leaflets in 3D transesophageal echocardiographic images using multi-atlas joint label fusion and deformable medial modeling

A. Pouch, Hong-Zhi Wang, Manabu Takabe, B. Jackson, J. Gorman, R. Gorman, Paul Yushkevich, and C. Sehgal

Medical image analysis, Oct 2013

Cited by 86

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Comprehensive visual and quantitative analysis of in vivo human mitral valve morphology is central to the diagnosis and surgical treatment of mitral valve disease. Real-time 3D transesophageal echocardiography (3D TEE) is a practical, highly informative imaging modality for examining the mitral valve in a clinical setting. To facilitate visual and quantitative 3D TEE image analysis, we describe a fully automated method for segmenting the mitral leaflets in 3D TEE image data. The algorithm integrates complementary probabilistic segmentation and shape modeling techniques (multi-atlas joint label fusion and deformable modeling with continuous medial representation) to automatically generate 3D geometric models of the mitral leaflets from 3D TEE image data. These models are unique in that they establish a shape-based coordinate system on the valves of different subjects and represent the leaflets volumetrically, as structures with locally varying thickness. In this work, expert image analysis is the gold standard for evaluating automatic segmentation. Without any user interaction, we demonstrate that the automatic segmentation method accurately captures patient-specific leaflet geometry at both systole and diastole in 3D TEE data acquired from a mixed population of subjects with normal valve morphology and mitral valve disease.
Statistical Assessment of Normal Mitral Annular Geometry Using Automated 3D Echocardiographic Analysis

A. Pouch, M. Vergnat, Jeremy R. McGarvey, G. Ferrari, B. Jackson, C. Sehgal, Paul Yushkevich, R. Gorman, and J. Gorman

The Annals of thoracic surgery, Oct 2013

Cited by 23

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Background The basis of mitral annuloplasty ring design has progressed from qualitative surgical intuition to experimental and theoretical analysis of annular geometry with quantitative imaging techniques. In this work, we present an automated 3D echocardiographic (3DE) image analysis method that can be used to statistically assess variability in normal mitral annular geometry to support advancement in annuloplasty ring design. Methods 3D patient-specific models of the mitral annulus were automatically generated from 3DE images acquired from subjects with normal mitral valve structure and function. Geometric annular measurements including annular circumference (AC), annular height (AH), septolateral diameter (SLD), intercommissural width (ICW), and the AH to ICW ratio (AHCWR) were automatically calculated. A mean 3D annular contour was computed, and principal component analysis (PCA) was used evaluate variability in normal annular shape. Results The following mean ± standard deviations were obtained from 3DE image analysis: 107.0 ± 14.6 mm (AC), 7.6 ± 2.8 mm (AH), 28.5 ± 3.7 mm (SLD), 33.0 ± 5.3 mm (ICW), and 22.7 ± 6.9 % (AHCWR). PCA indicated that shape variability was primarily related to overall annular size, with more subtle variation in the skewness and height of the anterior annular peak, independent of annular diameter. Conclusions Patient-specific 3DE-based modeling of the human mitral valve enables statistical analysis of physiologically normal mitral annular geometry. The tool can potentially lead to the development of a new generation of annuloplasty rings that restore the diseased mitral valve annulus back to a truly normal geometry.
Histology-derived volumetric annotation of the human hippocampal subfields in postmortem MRI

D. Adler, J. Pluta, Salmon Kadivar, C. Craige, J. Gee, B. Avants, and Paul Yushkevich

NeuroImage, Sep 2013

Cited by 163

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Recently, there has been a growing effort to analyze the morphometry of hippocampal subfields using both in vivo and postmortem magnetic resonance imaging (MRI). However, given that boundaries between subregions of the hippocampal formation (HF) are conventionally defined on the basis of microscopic features that often lack discernible signature in MRI, subfield delineation in MRI literature has largely relied on heuristic geometric rules, the validity of which with respect to the underlying anatomy is largely unknown. The development and evaluation of such rules is challenged by the limited availability of data linking MRI appearance to microscopic hippocampal anatomy, particularly in three dimensions (3D). The present paper, for the first time, demonstrates the feasibility of labeling hippocampal subfields in a high resolution volumetric MRI dataset based directly on microscopic features extracted from histology. It uses a combination of computational techniques and manual post-processing to map subfield boundaries from a stack of histology images (obtained with 200 μm spacing and 5 μm slice thickness; stained using the Kluver-Barrera method) onto a postmortem 9.4 Tesla MRI scan of the intact, whole hippocampal formation acquired with 160 μm isotropic resolution. The histology reconstruction procedure consists of sequential application of a graph-theoretic slice stacking algorithm that mitigates the effects of distorted slices, followed by iterative affine and diffeomorphic co-registration to postmortem MRI scans of approximately 1 cm-thick tissue sub-blocks acquired with 200 μm isotropic resolution. These 1 cm blocks are subsequently co-registered to the MRI of the whole HF. Reconstruction accuracy is evaluated as the average displacement error between boundaries manually delineated in both the histology and MRI following the sequential stages of reconstruction. The methods presented and evaluated in this single-subject study can potentially be applied to multiple hippocampal tissue samples in order to construct a histologically informed MRI atlas of the hippocampal formation.
Automated segmentation and geometrical modeling of the tricuspid aortic valve in 3D echocardiographic images

A. Pouch, Hong-Zhi Wang, Manabu Takabe, B. Jackson, C. Sehgal, J. Gorman, R. Gorman, and Paul Yushkevich

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Sep 2013

Cited by 25

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The aortic valve has been described with variable anatomical definitions, and the consistency of 2D manual measurement of valve dimensions in medical image data has been questionable. Given the importance of image-based morphological assessment in the diagnosis and surgical treatment of aortic valve disease, there is considerable need to develop a standardized framework for 3D valve segmentation and shape representation. Towards this goal, this work integrates template-based medial modeling and multi-atlas label fusion techniques to automatically delineate and quantitatively describe aortic leaflet geometry in 3D echocardiographic (3DE) images, a challenging task that has been explored only to a limited extent. The method makes use of expert knowledge of aortic leaflet image appearance, generates segmentations with consistent topology, and establishes a shape-based coordinate system on the aortic leaflets that enables standardized automated measurements. In this study, the algorithm is evaluated on 11 3DE images of normal human aortic leaflets acquired at mid systole. The clinical relevance of the method is its ability to capture leaflet geometry in 3DE image data with minimal user interaction while producing consistent measurements of 3D aortic leaflet geometry.
Groupwise Segmentation with Multi-Atlas Joint Label Fusion

Hong-Zhi Wang, and Paul Yushkevich

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Sep 2013

Cited by 25

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Groupwise segmentation that simultaneously segments a set of images and ensures that the segmentations for the same structure of interest from different images are consistent usually can achieve better performance than segmenting each image independently. Our main contribution is that we adopt the groupwise segmentation framework to improve the performance of multi-atlas label fusion. We develop a novel statistical model to allow this extension. Comparing to previous atlas propagation and groupwise segmentation work, one key novelty of our method is that the error produced during label propagation is explicitly addressed in the joint label fusion framework. Experiments on hippocampus segmentation in magnetic resonance images show the effectiveness of the new groupwise segmentation technique.
Multi-Atlas Segmentation without Registration: A Supervoxel-based Approach

Hong-Zhi Wang, and Paul Yushkevich

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Sep 2013

Cited by 45

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Multi-atlas segmentation is a powerful segmentation technique. It has two components: label transfer that transfers segmentation labels from prelabeled atlases to a novel image and label fusion that combines the label transfer results. For reliable label transfer, most methods assume that the structure of interest to be segmented have localized spatial support across different subjects. Although the technique has been successful for many applications, the strong assumption also limits its applicability. For example, multi-atlas segmentation has not been applied for tumor segmentation because it is difficult to derive reliable label transfer for such applications due to the substantial variation in tumor locations. To address this limitation, we propose a label transfer technique for multi-atlas segmentation. Inspired by the Superparsing work [13], we approach this problem in two steps. Our method first oversegments images into homogeneous regions, called supervoxels. For a voxel in a novel image, to find its correspondence in atlases for label transfer, we first locate supervoxels in atlases that are most similar to the supervoxel the target voxel belongs to. Then, voxel-wise correspondence is found through searching for voxels that have most similar patches to the target voxel within the selected atlas supervoxels. We apply this technique for brain tumor segmentation and show promising results.
Multi-Atlas Segmentation with Robust Label Transfer and Label Fusion

Hong-Zhi Wang, A. Pouch, Manabu Takabe, B. Jackson, J. Gorman, R. Gorman, and Paul Yushkevich

Information processing in medical imaging : proceedings of the ... conference, Jun 2013

Cited by 39

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Multi-atlas segmentation has been widely applied in medical image analysis. This technique relies on image registration to transfer segmentation labels from pre-labeled atlases to a novel target image and applies label fusion to reduce errors produced by registration-based label transfer. To improve the performance of registration-based label transfer against registration errors, our first contribution is to propose a label transfer scheme that generates multiple warped versions of each atlas to one target image through registration paths obtained by composing inter-atlas registrations and atlas-target registrations. The problem of decreasing quality of warped atlases caused by accumulative errors in composing multiple registrations is properly addressed by an atlas selection method that is guided by atlas segmentations. To improve the performance of label fusion against registration errors, our second contribution is to integrate the probabilistic correspondence model employed by the non-local mean approach with the joint label fusion technique, both of which have shown excellent performance for label fusion. Experiments on mitral-valve segmentation in 3D transesophageal echocardiography (TEE) show the effectiveness of the proposed techniques.
Deformable Modeling Using a 3D Boundary Representation with Quadratic Constraints on the Branching Structure of the Blum Skeleton

Paul Yushkevich, and Hui Zhang

Information processing in medical imaging : proceedings of the ... conference, Jun 2013

Cited by 17

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We propose a new approach for statistical shape analysis of 3D anatomical objects based on features extracted from skeletons. Like prior work on medial representations [7,15,9], the approach involves deforming a template to target shapes in a way that preserves the branching structure of the skeleton and provides intersubject correspondence. However, unlike medial representations, which parameterize the skeleton surfaces explicitly, our representation is boundary-centric, and the skeleton is implicit. Similar to prior constrained modeling methods developed 2D objects [8] or tube-like 3D objects [13], we impose symmetry constraints on tuples of boundary points in a way that guarantees the preservation of the skeleton’s topology under deformation. Once discretized, the problem of deforming a template to a target shape is formulated as a quadratically constrained quadratic programming problem. The new technique is evaluated in terms of its ability to capture the shape of the corpus callosum tract extracted from diffusion-weighted MRI.
Arterial spin labeled MRI in prodromal Alzheimer’s disease: A multi-site study

Ze Wang, Sandhitsu R. Das, Sharon X. Xie, S. Arnold, J. Detre, and D. Wolk

NeuroImage : Clinical, Apr 2013

Cited by 112

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We examined differences in cerebral blood flow (CBF) measured by Arterial Spin Labeled perfusion MRI (ASL MRI) across the continuum from cognitively normal (CN) older adults to mild Alzheimer’s Disease (AD) using data from the multi-site Alzheimer’s Disease Neuroimaging Initiative (ADNI). Measures of CBF, in a predetermined set of regions (meta-ROI), and hippocampal volume were compared between CN (n = 47), patients with early and late Mild Cognitive Impairment [EMCI (n = 32), LMCI (n = 35)], and AD (n = 15). Associations between these measures and disease severity, assessed by Clinical Dementia Rating scale sum of boxes (CDR SB), were also assessed. Mean meta-ROI CBF was associated with group status and significant hypoperfusion was observed in LMCI and AD relative to CN. Hippocampal volume was associated with group status, but only AD patients had significantly smaller volumes than the CN. When examining the relationship between these measures and disease severity, both were significantly associated with CDR SB and appeared to provide independent prediction of status. In light of the tight link between CBF and metabolism, ASL MRI represents a promising functional biomarker for early diagnosis and disease tracking in AD and this study is the first to demonstrate the feasibility in a multi-site context in this population. Combining functional and structural measures, which can be acquired in the same scanning session, appears to provide additional information about disease severity relative to either measure alone.
The ANTs cortical thickness processing pipeline

N. Tustison, B. Avants, Philip A Cook, G. Song, Sandhitsu R. Das, N. V. Van Strien, J. Stone, and J. Gee

Medical Imaging, Mar 2013

Cited by 35

DOI
White Matter Disease Correlates with Naming Impairment in Semantic Variant Primary Progressive Aphasia (P06.041)

John P. Powers, C. McMillan, C. Brun, Paul Yushkevich, Jim Gee, and M. Grossman

Neurology, Feb 2013

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OBJECTIVE: To evaluate the role of white matter (WM) disease in naming impairment in semantic variant primary progressive aphasia (svPPA) using a novel, tract-specific analysis (TSA) technique. BACKGROUND: svPPA is a clinical syndrome most commonly associated with frontotemporal lobar degeneration. svPPA is characterized by deficits in naming as well as single-word and object comprehension resulting in fluent but empty speech. However, little is known about the role of WM disease in naming impairment in svPPA. The Boston Naming Test (BNT) is widely used in clinical assessment of aphasia to evaluate lexical/semantic retrieval. Here we use TSA to relate BNT performance to WM integrity as measured by fractional anisotropy (FA) in svPPA. DESIGN/METHODS: BNT was collected for 11 patients with svPPA. 30-directional diffusion-weighted images were acquired for these patients and 34 demographically-matched healthy seniors. 11 WM tracts were segmented from a local, aging, DTI template, converted to binary volumes, and modeled as medial surface meshes. For each individual, local maximum FA was computed and projected onto the medial model. This dimensionality reduction increases sensitivity in exchange for a small decrease in local specificity. Permutation-based, cluster-based statistics were used to identify regions of reduced FA in patients with svPPA relative to healthy seniors and areas of correlation between FA and total score on BNT. RESULTS: Areas of reduced FA were present in bilateral inferior fronto-occipital, inferior longitudinal, superior longitudinal, and uncinate fasciculi as well as corpus callosum. Regions of reduced FA were associated with decreased naming performance in bilateral inferior fronto-occipital, bilateral uncinate, corpus callosum, and right inferior longitudinal fasciculi. CONCLUSIONS: TSA revealed significant, widespread WM disease in patients with svPPA, and naming deficits correlated with disease in WM structures related to frontal and temporal neural networks. These findings underline the disruption of a large-scale neural network for naming in svPPA. Supported by: NIH Grants AG17586, NS44266, AG15116, AG32953, NS53488, HD060406 and the Wyncote Foundation. Disclosure: Dr. Powers has nothing to disclose. Dr. McMillan has nothing to disclose. Dr. Brun has nothing to disclose. Dr. Yushkevich has received research support from Pfizer Inc. Dr. Gee has received research support from Pfizer Inc. Dr. Grossman has nothing to disclose.
Subfields of Medial Temporal Lobe Involvement in Prodromal Alzheimer’s Disease and Semantic Dementia (P06.027)

Khaing T. Win, J. Pluta, Paul Yushkevich, D. Wolk, and M. Grossman

Neurology, Feb 2013

DOI
Frequency and Clinicopathological Characteristics of Presenilin 1 Gly206Ala Mutation in Puerto Rican Hispanics with Dementia

S. Arnold, Irving E. Vega, J. Karlawish, David A. Wolk, J. Nuñez, Mirna Negrón, S. Xie, Li-San Wang, J. Dubroff, Elisabeth McCarty-Wood, J. Trojanowski, and V. V. Van Deerlin

Journal of Alzheimer’s Disease, Jan 2013

Cited by 20

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1868 Structure Specific Analysis of white and gray matter in the rat brain after exposure to chronic stress

Philip A Cook, Paul Yushkevich, Sijie Tian, S. Luz, S. Bhatnagar, and J. Gee

Jan 2013
Alzheimer’s Imaging Consortium Poster Presentations: IC-P P51 IC-P-086 EVALUATION OF THE INVERSE U-SHAPED ACTIVATION HYPOTHESIS IN ALZHEIMER’S DISEASEANDMILDCOGNITIVE IMPAIRMENT: A QUANTITATIVE META-ANALYSIS OF FUNCTIONAL IMAGING RESEARCH

A. Puente, N. Lazar, B. Soher, G. Matson, Rudolph Walter, Seghel Yohannes, M. Weiner, Paul Yushkevich, Lei Wang, Koenraad Van Leemput, Adam Mezher, J. Iglesias, and Sandhitsu R. Das

Jan 2013

Cited by 8
Oral Sessions: O4-08: Diagnosis and Prognosis: Non-Amyloid P699 beta-amyloid- NL and beta-amyloid- early mild cognitive impairment

David A. Wolk, Dong Young Lee, B. Sohn, E. Seo, I. Choo, Y. Kim, Jong Min Lee, Ji Young Han, H. Choi, Jinsick Park, J. Woo, J. Schneider, and David A. Bennett

Jan 2013

2012

Comparative accuracies of two common screening instruments for the classification of Alzheimer’s disease, mild cognitive impairment and healthy aging

D. Roalf, Paul J. Moberg, S. Xie, D. Wolk, S. Moelter, and Steven E. Arnold

Alzheimer’s & dementia : the journal of the Alzheimer’s Association, Dec 2012

Cited by 397

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The aim of this study was to compare the utility and diagnostic accuracy of the Montreal Cognitive Assessment (MoCA) and Mini‐Mental State Examination (MMSE) in the diagnosis of Alzheimer’s disease (AD) and mild cognitive impairment (MCI) in a clinical cohort.
Abstract 10662: Variability in Normal Mitral Annular Geometry and its Impact on Annuloplasty Ring Selection and Design

A. Pouch, M. Levack, B. Jackson, Paul Yushkevich, J. Gorman, R. Gorman, and C. Sehgal

Circulation, Nov 2012

Cited by 1
Robust Automated Amygdala Segmentation via Multi-Atlas Diffeomorphic Registration

J. Hanson, J. Suh, Brendon M. Nacewicz, Matthew J. Sutterer, Amelia A. Cayo, Diane E. Stodola, Cory A. Burghy, Hong-Zhi Wang, B. Avants, Paul Yushkevich, M. Essex, S. Pollak, and R. Davidson

Frontiers in Neuroscience, Oct 2012

Cited by 39

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Here, we describe a novel method for volumetric segmentation of the amygdala from MRI images collected from 35 human subjects. This approach is adapted from open-source techniques employed previously with the hippocampus (Suh et al., 2011; Wang et al., 2011a,b). Using multi-atlas segmentation and machine learning-based correction, we were able to produce automated amygdala segments with high Dice (Mean = 0.918 for the left amygdala; 0.916 for the right amygdala) and Jaccard coefficients (Mean = 0.850 for the left; 0.846 for the right) compared to rigorously hand-traced volumes. This automated routine also produced amygdala segments with high intra-class correlations (consistency = 0.830, absolute agreement = 0.819 for the left; consistency = 0.786, absolute agreement = 0.783 for the right) and bivariate (r = 0.831 for the left; r = 0.797 for the right) compared to hand-drawn amygdala. Our results are discussed in relation to other cutting-edge segmentation techniques, as well as commonly available approaches to amygdala segmentation (e.g., Freesurfer). We believe this new technique has broad application to research with large sample sizes for which amygdala quantification might be needed.
Fully automatic segmentation of the open mitral leaflets in 3D transesophageal echocardiographic images using multi-atlas label fusion and deformable medial modeling

A. Pouch, Hong-Zhi Wang, Paul Yushkevich, Manabu Takabe, B. Jackson, J. Gorman, R. Gorman, and C. Sehgal

In 2012 IEEE International Ultrasonics Symposium, Oct 2012

Cited by 6

DOI
Guiding Automatic Segmentation with Multiple Manual Segmentations

Hong-Zhi Wang, and Paul Yushkevich

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Oct 2012

Cited by 8

DOI
Advancing Alzheimer’s Diagnosis, Treatment and Care: Recommendations from the Ware Invitational Summit

Mary D. Naylor, Jason H. Karlawish, Steven E. Arnold, A. Khachaturian, Z. Khachaturian, V. M. Lee, M. Baumgart, Sube Banerjee, C. Beck, K. Blennow, R. Brookmeyer, K. Brunden, K. Buckwalter, M. Comer, K. Covinsky, L. Feinberg, G. Frisoni, C. Green, R. M. Guimarães, Lisa P. Gwyther, Franz Hefti, Michael L. Hutton, C. Kawas, D. Kent, Lewis H. Kuller, K. Langa, R. Mahley, K. Maslow, C. Masters, Diane Meier, P. Neumann, S. Paul, Ronald C. Petersen, M. Sager, M. Sano, D. Schenk, H. Soares, R. Sperling, S. Stahl, V. Van Deerlin, Y. Stern, D. Weir, D. Wolk, and J. Trojanowski

Alzheimer’s & dementia : the journal of the Alzheimer’s Association, Sep 2012

Cited by 54

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To address the pending public health crisis due to Alzheimer’s disease (AD) and related neurodegenerative disorders, the Marian S. Ware Alzheimer Program at the University of Pennsylvania held a meeting entitled “State of the Science Conference on the Advancement of Alzheimer’s Diagnosis, Treatment and Care,” on June 21‐22, 2012. The meeting comprised four workgroups focusing on Biomarkers; Clinical Care and Health Services Research; Drug Development; and Health Economics, Policy, and Ethics. The workgroups shared, discussed, and compiled an integrated set of priorities, recommendations, and action plans, which are presented in this article.
Increased Functional Connectivity within Medial Temporal Lobe in Mild Cognitive Impairment

Sandhitsu R. Das, J. Pluta, L. Mancuso, Dasha Kliot, Sylvia Orozco, B. Dickerson, Paul Yushkevich, and D. Wolk

Hippocampus, Jul 2012

Cited by 102

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Pathology at preclinical and prodromal stages of Alzheimer’s disease (AD) may manifest itself as measurable functional change in neuronal networks earlier than detectable structural change. Functional connectivity as measured using resting‐state functional magnetic resonance imaging has emerged as a useful tool for studying disease effects on baseline states of neuronal networks. In this study, we use high resolution MRI to label subregions within the medial temporal lobe (MTL), a site of early pathology in AD, and report an increase in functional connectivity in amnestic mild cognitive impairment between entorhinal cortex and subregions of the MTL, with the strongest effect in the anterior hippocampus. However, our data also replicated the effects of decreased connectivity of the MTL to other nodes of the default mode network reported by other researchers. This dissociation of changes in functional connectivity within the MTL versus the MTL’s connection with other neocortical structures can help enrich the characterization of early stages of disease progression in AD. © 2012 Wiley Periodicals, Inc.
Multi-Atlas Segmentation with Joint Label Fusion

Hong-Zhi Wang, J. Suh, Sandhitsu R. Das, J. Pluta, C. Craige, and Paul Yushkevich

IEEE transactions on pattern analysis and machine intelligence, Jun 2012

Cited by 859

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Multi-atlas segmentation is an effective approach for automatically labeling objects of interest in biomedical images. In this approach, multiple expert-segmented example images, called atlases, are registered to a target image, and deformed atlas segmentations are combined using label fusion. Among the proposed label fusion strategies, weighted voting with spatially varying weight distributions derived from atlas-target intensity similarity have been particularly successful. However, one limitation of these strategies is that the weights are computed independently for each atlas, without taking into account the fact that different atlases may produce similar label errors. To address this limitation, we propose a new solution for the label fusion problem in which weighted voting is formulated in terms of minimizing the total expectation of labeling error and in which pairwise dependency between atlases is explicitly modeled as the joint probability of two atlases making a segmentation error at a voxel. This probability is approximated using intensity similarity between a pair of atlases and the target image in the neighborhood of each voxel. We validate our method in two medical image segmentation problems: hippocampus segmentation and hippocampus subfield segmentation in magnetic resonance (MR) images. For both problems, we show consistent and significant improvement over label fusion strategies that assign atlas weights independently.
Spatial Bias in Multi-Atlas Based Segmentation

Hong-Zhi Wang, and Paul Yushkevich

In 2012 IEEE Conference on Computer Vision and Pattern Recognition, Jun 2012

Cited by 15

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Multi-atlas segmentation has been widely applied in medical image analysis. With deformable registration, this technique realizes label transfer from pre-labeled atlases to unknown images. When deformable registration produces error, label fusion that combines results produced by multiple atlases is an effective way for reducing segmentation errors. Among the existing label fusion strategies, similarity-weighted voting strategies with spatially varying weight distributions have been particularly successful. We show that, weighted voting based label fusion produces a spatial bias that under-segments structures with convex shapes. The bias can be approximated as applying spatial convolution to the ground truth spatial label probability maps, where the convolution kernel combines the distribution of residual registration errors and the function producing similarity-based voting weights. To reduce this bias, we apply a standard spatial deconvolution to the spatial probability maps obtained from weighted voting. In a brain image segmentation experiment, we demonstrate the spatial bias and show that our technique substantially reduces this spatial bias.
From label fusion to correspondence fusion: a new approach to unbiased groupwise registration

Paul Yushkevich, Hong-Zhi Wang, J. Pluta, and B. Avants

In 2012 IEEE Conference on Computer Vision and Pattern Recognition, Jun 2012

Cited by 16

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Label fusion strategies are used in multi-atlas image segmentation approaches to compute a consensus segmentation of an image, given a set of candidate segmentations produced by registering the image to a set of atlases [19, 11, 8]. Effective label fusion strategies, such as local similarity-weighted voting [1, 13] substantially reduce segmentation errors compared to single-atlas segmentation. This paper extends the label fusion idea to the problem of finding correspondences across a set of images. Instead of computing a consensus segmentation, weighted voting is used to estimate a consensus coordinate map between a target image and a reference space. Two variants of the problem are considered: (1) where correspondences between a set of atlases are known and are propagated to the target image; (2) where correspondences are estimated across a set of images without prior knowledge. Evaluation in synthetic data shows that correspondences recovered by fusion methods are more accurate than those based on registration to a population template. In a 2D example in real MRI data, fusion methods result in more consistent mappings between manual segmentations of the hippocampus.
RECONSTRUCTION OF THE HUMAN HIPPOCAMPUS IN 3D FROM HISTOLOGY AND HIGH-RESOLUTION EX-VIVO MRI

D. Adler, A. Liu, J. Pluta, Salmon Kadivar, Sylvia Orozco, Hong-Zhi Wang, J. Gee, B. Avants, and Paul Yushkevich

In IEEE International Symposium on Biomedical Imaging, May 2012

Cited by 14

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In this paper, we present methods for the reconstruction of 3D histological volumes of the human hippocampal formation from histology slices. Inter-slice alignment is guided by a graph-theoretic approach that minimizes the impact of badly distorted slices. The reconstruction is refined by iterative affine and deformable co-registration with a high-resolution MRI of the postmortem tissue sample. We present an evaluation of reconstruction accuracy that is based on measures of similarity between boundaries drawn on both histology and MRI. Our methodology is currently being applied to an MRI atlas of the human hippocampal formation, in which atlas anatomical labels are derived from segmentation of reconstructed histology.
White matter imaging contributes to the multimodal diagnosis of frontotemporal lobar degeneration

C. McMillan, C. Brun, S. Siddiqui, M. Churgin, D. Libon, Paul Yushkevich, Hui Zhang, A. Boller, J. Gee, and M. Grossman

Neurology, May 2012

Cited by 53

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DEPENDENCY PRIOR FOR MULTI-ATLAS LABEL FUSION

Hong-Zhi Wang, and Paul Yushkevich

In IEEE International Symposium on Biomedical Imaging, May 2012

Cited by 10

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Multi-atlas label fusion has been widely applied in medical image analysis. To reduce the bias in label fusion, we proposed a joint label fusion technique to reduce correlated errors produced by different atlases via considering the pair-wise dependencies between them. Using image similarities from image patches to estimate the pairwise dependencies, we showed promising performance. To address the unreliability in purely using local image similarity for dependency estimation, we propose to improve the accuracy of the estimated dependencies by including empirical knowledge, which is learned from the atlases in a leave-one-out strategy. We apply the new technique to segment the hippocampus from MRI and show significant improvement over our initial results.
User-Independent Analyses of White Matter Tractography in Primary Progressive Aphasia (P03.091)

C. Brun, C. McMillan, Paul Yushkevich, J. Gee, and M. Grossman

Neurology, Apr 2012

Cited by 1

DOI
White Matter Tract Specific Analysis of Behaviorial Variant Frontotemporal Degeneration (P03.095)

C. Brun, C. McMillan, K. Rascovsky, A. Boller, Paul Yushkevich, J. Gee, and M. Grossman

Apr 2012

DOI
A Diffusion Tensor Imaging Analysis of White Matter Disease in Corticobasal Syndrome (P05.041)

K. Chandrasekaren, C. McMillan, C. Brun, Philip A Cook, Paul Yushkevich, J. Gee, and M. Grossman

Neurology, Apr 2012

Cited by 1

DOI
The Contribution of White Matter Neuroimaging to Multimodal Diagnosis of Frontotemporal Lobar Degeneration (P03.096)

C. McMillan, C. Brun, S. Siddiqui, M. Churgin, D. Libon, Paul Yushkevich, Hui Zhang, A. Boller, J. Gee, and M. Grossman

Apr 2012

DOI
Comparative Methods for Analyzing Diffusion Tensor Imaging in Semantic Variant Primary Progressive Aphasia (P03.098)

John P. Powers, C. McMillan, Philip A Cook, C. Brun, Paul Yushkevich, J. Gee, and M. Grossman

Neurology, Apr 2012

Cited by 1

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Semi-automated mitral valve morphometry and computational stress analysis using 3D ultrasound.

A. Pouch, Chun Xu, Paul Yushkevich, A. Jassar, M. Vergnat, J. Gorman, R. Gorman, C. Sehgal, and B. Jackson

Journal of biomechanics, Mar 2012

Cited by 58

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Development of a semi-automated method for mitral valve modeling with medial axis representation using 3D ultrasound.

A. Pouch, Paul Yushkevich, B. Jackson, A. Jassar, M. Vergnat, J. Gorman, R. Gorman, and C. Sehgal

Medical physics, Feb 2012

Cited by 35

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Dynamic shape modeling of the mitral valve from real-time 3D ultrasound images using continuous medial representation

A. Pouch, Paul Yushkevich, B. Jackson, J. Gorman, R. Gorman, and C. Sehgal

Medical Imaging, Feb 2012

Cited by 3

DOI
Measuring longitudinal change in the hippocampal formation from in vivo high-resolution T2-weighted MRI

Sandhitsu R. Das, B. Avants, J. Pluta, Hong-Zhi Wang, J. Suh, M. Weiner, S. Mueller, and Paul Yushkevich

NeuroImage, Jan 2012

Cited by 49

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The hippocampal formation (HF) is a brain structure of great interest because of its central role in learning and memory, and its associated vulnerability to several neurological disorders. In vivo oblique coronal T2-weighted MRI with high in-plane resolution ( 0.5 mm×0.5 mm), thick slices ( 2.0 mm), and a field of view tailored to imaging the hippocampal formation (denoted HF-MRI in this paper) has been advanced as a useful imaging modality for detailed hippocampal morphometry. Cross-sectional analysis of volume measurements derived from HF-MRI has shown the modality’s promise to yield sensitive imaging-based biomarker for neurological disorders such as Alzheimer’s disease. However, the utility of this modality for making measurements of longitudinal change has not yet been demonstrated. In this paper, using an unbiased deformation-based morphometry (DBM) pipeline, we examine the suitability of HF-MRI for estimating longitudinal change by comparing atrophy rates measured in the whole hippocampus from this modality with those measured from more common isotropic ( 1 mm3) T1-weighted MRI in the same set of individuals, in a cohort of healthy controls and patients with cognitive impairment. While measurements obtained from HF-MRI were largely consistent with those obtained from T1-MRI, HF-MRI yielded slightly larger group effect of greater atrophy rates in patients than in controls. The estimated minimum sample size required for detecting a 25% change in patients’ atrophy rate in the hippocampus compared to the control group with a statistical power β=0.8 was N=269. For T1-MRI, the equivalent sample size was N=325. Using a dataset of test–retest scans, we show that the measurements were free of additive bias. We also demonstrate that these results were not a confound of certain methodological choices made in the DBM pipeline to address the challenges of making longitudinal measurements from HF-MRI, using a region of interest (ROI) around the HF to globally align serial images, followed by slice-by-slice deformable registration to measure local volume change. Additionally, we present a preliminary study of atrophy rate measurements within hippocampal subfields using HF-MRI. Cross-sectional differences in atrophy rates were detected in several subfields.
In vivo analysis of hippocampal subfield atrophy in mild cognitive impairment via semi-automatic segmentation of T2-weighted MRI

J. Pluta, Paul Yushkevich, Sandhitsu R. Das, and D. Wolk

Journal of Alzheimer’s Disease, Jan 2012

Cited by 121

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The measurement of hippocampal volumes using MRI is a useful in-vivo biomarker for detection and monitoring of early Alzheimer’s disease (AD), including during the amnestic mild cognitive impairment (a-MCI) stage. The pathology underlying AD has regionally selective effects within the hippocampus. As such, we predict that hippocampal subfields are more sensitive in discriminating prodromal AD (i.e., a-MCI) from cognitively normal controls than whole hippocampal volumes, and attempt to demonstrate this using a semi-automatic method that can accurately segment hippocampal subfields. High-resolution coronal-oblique T2-weighted images of the hippocampal formation were acquired in 45 subjects (28 controls and 17 a-MCI (mean age: 69.5 ± 9.2; 70.2 ± 7.6)). CA1, CA2, CA3, and CA4/DG subfields, along with head and tail regions, were segmented using an automatic algorithm. CA1 and CA4/DG segmentations were manually edited. Whole hippocampal volumes were obtained from the subjects’ T1-weighted anatomical images. Automatic segmentation produced significant group differences in the following subfields: CA1 (left: p = 0.001, right: p = 0.038), CA4/DG (left: p = 0.002, right: p = 0.043), head (left: p = 0.018, right: p = 0.002), and tail (left: p = 0.019). After manual correction, differences were increased in CA1 (left: p < 0.001, right: p = 0.002), and reduced in CA4/DG (left: p = 0.029, right: p = 0.221). Whole hippocampal volumes significantly differed bilaterally (left: p = 0.028, right: p = 0.009). This pattern of atrophy in a-MCI is consistent with the topography of AD pathology observed in postmortem studies, and corrected left CA1 provided stronger discrimination than whole hippocampal volume (p = 0.03). These results suggest that semi-automatic segmentation of hippocampal subfields is efficient and may provide additional sensitivity beyond whole hippocampal volumes.
Semi-Automated Mitral Valve Morphometry and Computational Stress Analysis Using 3D Ultrasound

A. Pouch, Chun Xu, Paul Yushkevich, A. Jassar, M. Vergnat, J. Gorman, R. Gorman, C. Sehgal, and B. Jackson

Journal of Biomechanics, Jan 2012

Cited by 57

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In vivo human mitral valves (MV) were imaged using real-time 3D transesophageal echocardiography (rt-3DTEE), and volumetric images of the MV at mid-systole were analyzed by user-initialized segmentation and 3D deformable modeling with continuous medial representation, a compact representation of shape. The resulting MV models were loaded with physiologic pressures using finite element analysis (FEA). We present the regional leaflet stress distributions predicted in normal and diseased (regurgitant) MVs. Rt-3DTEE, semi-automated leaflet segmentation, 3D deformable modeling, and FEA modeling of the in vivo human MV is tenable and useful for evaluation of MV pathology.
Amyloid Imaging in Dementias With Atypical Presentation

D. Wolk, J. Price, Charles Madeira, Judith A. Saxton, B. Snitz, Oscar L. Lopez, Chester A. Mathis, W. Klunk, and S. DeKosky

Alzheimer’s & dementia : the journal of the Alzheimer’s Association, Jan 2012

Cited by 49

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With the potential emergence of disease specific therapies, an accurate biomarker of Alzheimer’s Disease pathology is needed in cases in which the underlying etiology is uncertain. We explored the potential value of amyloid imaging in patients with atypical presentations of dementia.
Assessing Arterial Spin Labeled Perfusion MRI as an Early-Alzheimer ’ s Disease Marker using the ADNI 2 data

Ze Wang, Sandhitsu R. Das, D. Wolk, and J. Detre

Jan 2012

Cited by 1

2011

Heterogeneity of Functional Activation During Memory Encoding Across Hippocampal Subfields in Temporal Lobe Epilepsy

Sandhitsu R. Das, D. Mechanic-Hamilton, J. Pluta, M. Korczykowski, J. Detre, and Paul Yushkevich

Neuroimage, Jul 2011

Cited by 22

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Pathology studies have shown that the anatomical subregions of the hippocampal formation are differentially affected in various neurological disorders, including temporal lobe epilepsy (TLE). Analysis of structure and function within these subregions using magnetic resonance imaging (MRI) has the potential to generate insights on disease associations as well as normative brain function. In this study, an atlas-based normalization method (Yushkevich et al., 2009) was used to label hippocampal subregions, making it possible to examine subfield-level functional activation during an episodic memory task in two different cohorts of healthy controls and subjects diagnosed with intractable unilateral TLE. We report, for the first time, functional activation patterns within hippocampal subfields in TLE. We detected group differences in subfield activation between patients and controls as well as inter-hemispheric activation asymmetry within subfields in patients, with dentate gyrus (DG) and the anterior hippocampus region showing the greatest effects. DG was also found to be more active than CA1 in controls, but not in patients’ epileptogenic side. These preliminary results will encourage further research on the utility of subfield-based biomarkers in TLE.
IC‐02‐05: MRI‐based biomarkers from hippocampal subfields: Advances in automatic labeling, longitudinal atrophy estimation and postmortem anatomical atlas

Sandhitsu R. Das, B. Avants, Salmon Kadivar, S. Mueller, J. Pluta, Sylvia Orozco, Hong-Zhi Wang, M. Weiner, D. Wolk, and Paul Yushkevich

Alzheimer’s & Dementia, Jul 2011

DOI
Optimal Weights for Multi-Atlas Label Fusion

Hong-Zhi Wang, J. Suh, J. Pluta, M. Altinay, and Paul Yushkevich

Information processing in medical imaging : proceedings of the ... conference, Jul 2011

Cited by 41

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Multi-atlas based segmentation has been applied widely in medical image analysis. For label fusion, previous studies show that image similarity-based local weighting techniques produce the most accurate results. However, these methods ignore the correlations between results produced by different atlases. Furthermore, they rely on preselected weighting models and ad hoc methods to choose model parameters. We propose a novel label fusion method to address these limitations. Our formulation directly aims at reducing the expectation of the combined error and can be efficiently solved in a closed form. In our hippocampus segmentation experiment, our method significantly outperforms similarity-based local weighting. Using 20 atlases, we produce results with 0.898 ± 0.019 Dice overlap to manual labelings for controls.
Hippocampus segmentation using a stable maximum likelihood classifier ensemble algorithm

Hong-Zhi Wang, J. Suh, Sandhitsu R. Das, M. Altinay, J. Pluta, and Paul Yushkevich

In IEEE International Symposium on Biomedical Imaging, Jun 2011

Cited by 8

DOI
Regression-Based Label Fusion for Multi-Atlas Segmentation

Hong-Zhi Wang, J. Suh, Sandhitsu R. Das, J. Pluta, M. Altinay, and Paul Yushkevich

Conference on Computer Vision and Pattern Recognition Workshops IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops, Jun 2011

Cited by 68

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Automatic segmentation using multi-atlas label fusion has been widely applied in medical image analysis. To simplify the label fusion problem, most methods implicitly make a strong assumption that the segmentation errors produced by different atlases are uncorrelated. We show that violating this assumption significantly reduces the efficiency of multi-atlas segmentation. To address this problem, we propose a regression-based approach for label fusion. Our experiments on segmenting the hippocampus in magnetic resonance images (MRI) show significant improvement over previous label fusion techniques.
A Learning-Based Wrapper Method to Correct Systematic Errors in Automatic Image Segmentation: Consistently Improved Performance in Hippocampus, Cortex and Brain Segmentation

Hong-Zhi Wang, Sandhitsu R. Das, J. Suh, M. Altinay, J. Pluta, C. Craige, B. Avants, and Paul Yushkevich

NeuroImage, Jan 2011

Cited by 181

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We propose a simple but generally applicable approach to improving the accuracy of automatic image segmentation algorithms relative to manual segmentations. The approach is based on the hypothesis that a large fraction of the errors produced by automatic segmentation are systematic, i.e., occur consistently from subject to subject, and serves as a wrapper method around a given host segmentation method. The wrapper method attempts to learn the intensity, spatial and contextual patterns associated with systematic segmentation errors produced by the host method on training data for which manual segmentations are available. The method then attempts to correct such errors in segmentations produced by the host method on new images. One practical use of the proposed wrapper method is to adapt existing segmentation tools, without explicit modification, to imaging data and segmentation protocols that are different from those on which the tools were trained and tuned. An open-source implementation of the proposed wrapper method is provided, and can be applied to a wide range of image segmentation problems. The wrapper method is evaluated with four host brain MRI segmentation methods: hippocampus segmentation using FreeSurfer (Fischl et al., 2002); hippocampus segmentation using multi-atlas label fusion (Artaechevarria et al., 2009); brain extraction using BET (Smith, 2002); and brain tissue segmentation using FAST (Zhang et al., 2001). The wrapper method generates 72%, 14%, 29% and 21% fewer erroneously segmented voxels than the respective host segmentation methods. In the hippocampus segmentation experiment with multi-atlas label fusion as the host method, the average Dice overlap between reference segmentations and segmentations produced by the wrapper method is 0.908 for normal controls and 0.893 for patients with mild cognitive impairment. Average Dice overlaps of 0.964, 0.905 and 0.951 are obtained for brain extraction, white matter segmentation and gray matter segmentation, respectively.
DTI Tractography for Neurosurgical Planning : A Grand Challenge Sunday September 18 , 2011 MICCAI 2011 , Toronto , Canada

C. Brun, Hong-Zhi Wang, Ramón Aranda, Alonso Ramírez-Manzanares, M. Rivera, Paul Yushkevich, and J. Gee

Jan 2011

Cited by 2
EARLY DIFFUSION CHANGES IN A MOUSE MODEL OF NEUROFIBRILLARY TANGLES

R. Crescenzi, D. Adler, Paul Yushkevich, Virginia M. Y. Lee, and J. Detre

Jan 2011
Automatic Segmentation of the Hippocampus in T1-Weighted MRI with Multi-Atlas Label Fusion Using Open Source Software: Evaluation in 1.5 and 3.0T ADNI MRI

J. Suh, Hong-Zhi Wang, B. Avants, and Paul Yushkevich

Jan 2011

Cited by 7

2010

3D mesh based wall thickness measurement: Identification of left ventricular hypertrophy phenotypes

C. Tobon-Gomez, C. Butakoff, Paul Yushkevich, M. Huguet, and Alejandro F Frangi

In 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, Nov 2010

Cited by 10

DOI
A semi-automated solution for increasing the reliability of manually defined visual area boundaries

Sandhitsu R. Das, Robyn T. Oliver, B. Avants, Petya D. Radoeva, D. Brainard, G. Aguirre, and J. Gee

Journal of Vision, Sep 2010

Cited by 2

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Automatic Cardiac MRI Segmentation Using a Biventricular Deformable Medial Model

Hui Sun, Alejandro F Frangi, Hong-Zhi Wang, F. Sukno, C. Tobon-Gomez, and Paul Yushkevich

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Sep 2010

Cited by 38

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Standing on the Shoulders of Giants: Improving Medical Image Segmentation via Bias Correction

Hong-Zhi Wang, Sandhitsu R. Das, J. Pluta, C. Craige, M. Altinay, B. Avants, Michael Weiner, Susanne G. Mueller, and Paul Yushkevich

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Sep 2010

Cited by 11

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We propose a simple strategy to improve automatic medical image segmentation. The key idea is that without deep understanding of a segmentation method, we can still improve its performance by directly calibrating its results with respect to manual segmentation. We formulate the calibration process as a bias correction problem, which is addressed by machine learning using training data. We apply this methodology on three segmentation problems/methods and show significant improvements for all of them.
Cerebral Cortical Folding Analysis with Multivariate Modeling and Testing: Studies on Gender Differences and Neonatal Development

Suyash P. Awate, Paul Yushkevich, Song Zhuang, D. Licht, and J. Gee

NeuroImage, Jul 2010

Cited by 61

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This paper presents a novel statistical framework for human cortical folding pattern analysis that relies on a rich multivariate descriptor of folding patterns in a region of interest (ROI). The ROI-based approach avoids problems faced by spatial-normalization-based approaches stemming from the deficiency of homologous features between typical human cerebral cortices. Unlike typical ROI-based methods that summarize folding by a single number, the proposed descriptor unifies multiple characteristics of surface geometry in a high-dimensional space (hundreds/thousands of dimensions). In this way, the proposed framework couples the reliability of ROI-based analysis with the richness of the novel cortical folding pattern descriptor. This paper presents new mathematical insights into the relationship of cortical complexity with intra-cranial volume (ICV). It shows that conventional complexity descriptors implicitly handle ICV Differences in Different ways, thereby lending Different meanings to “complexity”. The paper proposes a new application of a non-parametric permutation-based approach for rigorous statistical hypothesis testing with multivariate cortical descriptors. The paper presents two cross-sectional studies applying the proposed framework to study folding Differences between genders and in neonates with complex congenital heart disease. Both studies lead to novel interesting results.
A Computational White Matter Atlas for Aging with Surface-Based Representation of Fasciculi

Hui Zhang, Paul Yushkevich, D. Rueckert, and J. Gee

In Workshop on Biomedical Image Registration, Jul 2010

Cited by 34

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Nearly Automatic Segmentation of Hippocampal Subfields in In Vivo Focal T2-Weighted MRI

Paul Yushkevich, Hong-Zhi Wang, J. Pluta, Sandhitsu R. Das, C. Craige, B. Avants, M. Weiner, and S. Mueller

NeuroImage, Jun 2010

Cited by 258

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We present and evaluate a new method for automatically labeling the subfields of the hippocampal formation in focal 0.4×0.5×2.0mm3 resolution T2-weighted magnetic resonance images that can be acquired in the routine clinical setting with under 5 min scan time. The method combines multi-atlas segmentation, similarity-weighted voting, and a novel learning-based bias correction technique to achieve excellent agreement with manual segmentation. Initial partitioning of MRI slices into hippocampal ‘head’, ‘body’ and ‘tail’ slices is the only input required from the user, necessitated by the nature of the underlying segmentation protocol. Dice overlap between manual and automatic segmentation is above 0.87 for the larger subfields, CA1 and dentate gyrus, and is competitive with the best results for whole-hippocampus segmentation in the literature. Intraclass correlation of volume measurements in CA1 and dentate gyrus is above 0.89. Overlap in smaller hippocampal subfields is lower in magnitude (0.54 for CA2, 0.62 for CA3, 0.77 for subiculum and 0.79 for entorhinal cortex) but comparable to overlap between manual segmentations by trained human raters. These results support the feasibility of subfield-specific hippocampal morphometry in clinical studies of memory and neurodegenerative disease.
A tract-specific framework for white matter morphometry combining macroscopic and microscopic tract features

Hui Zhang, Suyash P. Awatea, Sandhitsu R. Das, J. Woo, E. Melhem, J. Gee, and Paul Yushkevich

Medical image analysis, May 2010

Cited by 69

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Diffusion tensor imaging plays a key role in our understanding of white matter both in normal populations and in populations with brain disorders. Existing techniques focus primarily on using diffusivity-based quantities derived from diffusion tensor as surrogate measures of microstructural tissue properties of white matter. In this paper, we describe a novel tract-specific framework that enables the examination of white matter morphometry at both the macroscopic and microscopic scales. The framework leverages the skeleton-based modeling of sheet-like white matter fasciculi using the continuous medial representation, which gives a natural definition of thickness and supports its comparison across subjects. The thickness measure provides a macroscopic characterization of white matter fasciculi that complements existing analysis of microstructural features. The utility of the framework is demonstrated in quantifying white matter atrophy in Amyotrophic Lateral Sclerosis, a severe neurodegenerative disease of motor neurons. We show that, compared to using microscopic features alone, combining the macroscopic and microscopic features gives a more complete characterization of the disease.
N4ITK: Improved N3 Bias Correction

N. Tustison, B. Avants, Philip A Cook, Yuan-Jie Zheng, A. Egan, Paul Yushkevich, and J. Gee

IEEE transactions on medical imaging, Apr 2010

Cited by 5936

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A variant of the popular nonparametric nonuniform intensity normalization (N3) algorithm is proposed for bias field correction. Given the superb performance of N3 and its public availability, it has been the subject of several evaluation studies. These studies have demonstrated the importance of certain parameters associated with the B-spline least-squares fitting. We propose the substitution of a recently developed fast and robust B-spline approximation routine and a modified hierarchical optimization scheme for improved bias field correction over the original N3 algorithm. Similar to the N3 algorithm, we also make the source code, testing, and technical documentation of our contribution, which we denote as ¿N4ITK,¿ available to the public through the Insight Toolkit of the National Institutes of Health. Performance assessment is demonstrated using simulated data from the publicly available Brainweb database, hyperpolarized 3He lung image data, and 9.4T postmortem hippocampus data.
Shape-based semi-automatic hippocampal subfield segmentation with learning-based bias removal

Hong-Zhi Wang, Sandhitsu R. Das, J. Pluta, C. Craige, M. Altinay, M. Weiner, S. Mueller, and Paul Yushkevich

In IEEE International Symposium on Biomedical Imaging, Apr 2010

Cited by 2

DOI
Bias in estimation of hippocampal atrophy using deformation-based morphometry arises from asymmetric global normalization: An illustration in ADNI 3 T MRI data

Paul Yushkevich, B. Avants, Sandhitsu R. Das, J. Pluta, M. Altinay, and C. Craige

NeuroImage, Apr 2010

Cited by 144

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Sensitivity to motion features in upright and inverted point-light displays

Sandhitsu R. Das, M. Lazarewicz, Robert C. Wilson, and L. Finkel

Journal of Vision, Mar 2010

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Automatic Measurement of Atrophy Rates in Hippocampal Subfields from Longitudinal High-Resolution T 2-weighted MRI

S. Das, B. Avants, J. Pluta, C. Craige, M. Weiner, S. Mueller, and Paul Yushkevich

Mar 2010
Functional Asymmetry of Hippocampal Subfields in Tempoal Lobe Epilepsy: An Application of Postmortem Atlas

Sandhitsu R. Das, M. Korczykowski, J. Pluta, and J. Detre

Mar 2010
Functional Activation Within Hippocampal Subfields During Scene Memory Encoding In Temporal Lobe Epilepsy

S. Das, D. Mechanic-Hamilton, M. Korczykowski, J. Pluta, J. Detre, and Paul Yushkevich

Mar 2010
A General-Purpuse Learning-Based Wrapper Method to Correct Systematic Errors in Automatic Image Segmentation : Consistently Improved Performance in Hippocampus , Cortex and Brain Segmentation

H. Wang, S. Das, M. Altinay, J. Pluta, J. Suh, C. Craige, B. Avants, and Paul Yushkevich

Mar 2010

Cited by 1
Measuring the volumes and thickness of hippocampal subfields in vivo using automatic segmentation of T 2-weighted MRI : A pilot evaluation study

Paul Yushkevich, H. Wang, J. Pluta, S. Das, B. Avants, M. Weiner, S. Mueller, and D. Wolk

Mar 2010

Cited by 1

2009

Bias in Estimation of Hippocampal Atrophy using Deformation-Based Morphometry Arises from Asymmetric Global Normalization: An Illustration in ADNI 3 Tesla MRI Data

Paul Yushkevich, B. Avants, Sandhitsu R. Das, J. Pluta, M. Altinay, and C. Craige

NeuroImage, Dec 2009

Cited by 147

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Measurement of brain change due to neurodegenerative disease and treatment is one of the fundamental tasks of neuroimaging. Deformation-based morphometry (DBM) has been long recognized as an effective and sensitive tool for estimating the change in the volume of brain regions over time. This paper demonstrates that a straightforward application of DBM to estimate the change in the volume of the hippocampus can result in substantial bias, i.e., an overestimation of the rate of change in hippocampal volume. In ADNI data, this bias is manifested as a non-zero intercept of the regression line fitted to the 6 and 12 month rates of hippocampal atrophy. The bias is further confirmed by applying DBM to repeat scans of subjects acquired on the same day. This bias appears to be the result of asymmetry in the interpolation of baseline and followup images during longitudinal image registration. Correcting this asymmetry leads to bias-free atrophy estimation.
The Optimal Template Effect in Hippocampus Studies of Diseased Populations

B. Avants, Paul Yushkevich, J. Pluta, D. Minkoff, M. Korczykowski, J. Detre, and J. Gee

NeuroImage, Oct 2009

Cited by 654

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We evaluate the impact of template choice on template-based segmentation of the hippocampus in epilepsy. Four dataset-specific strategies are quantitatively contrasted: the “closest to average” individual template, the average shape version of the closest to average template, a best appearance template and the best appearance and shape template proposed here and implemented in the open source toolkit Advanced Normalization Tools (ANTS). The cross-correlation similarity metric drives the correspondence model and is used consistently to determine the optimal appearance. Minimum shape distance in the diffeomorphic space determines optimal shape. Our evaluation results show that, with respect to gold-standard manual labeling of hippocampi in epilepsy, optimal shape and appearance template construction outperforms the other strategies for gaining data-derived templates. Our results also show the improvement is most significant on the diseased side and insignificant on the healthy side. Thus, the importance of the template increases when used to study pathology and may be less critical for normal control studies. Furthermore, explicit geometric optimization of the shape component of the unbiased template positively impacts the study of diseased hippocampi.
Gender Differences in Cerebral Cortical Folding: Multivariate Complexity-Shape Analysis with Insights into Handling Brain-Volume Differences

Suyash P. Awate, Paul Yushkevich, D. Licht, and J. Gee

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Oct 2009

Cited by 15

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Tensor-Based Morphometry of Fibrous Structures with Application to Human Brain White Matter

Hui Zhang, Paul Yushkevich, D. Rueckert, and J. Gee

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Oct 2009

Cited by 6

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Tensor-based morphometry (TBM) is a powerful approach for examining shape changes in anatomy both across populations and in time. Our work extends the standard TBM for quantifying local volumetric changes to establish both rich and intuitive descriptors of shape changes in fibrous structures. It leverages the data from diffusion tensor imaging to determine local spatial configuration of fibrous structures and combines this information with spatial transformations derived from image registration to quantify fibrous structure-specific changes, such as local changes in fiber length and in thickness of fiber bundles. In this paper, we describe the theoretical framework of our approach in detail and illustrate its application to study brain white matter. Our results show that additional insights can be gained with the proposed analysis.
Hippocampal volumetry and functional MRI of memory in temporal lobe epilepsy.

D. Mechanic-Hamilton, M. Korczykowski, Paul Yushkevich, Kathy Lawler, J. Pluta, Simon Glynn, J. Tracy, R. Wolf, M. Sperling, Jacqueline A. French, and J. Detre

Epilepsy & behavior : E&B, Sep 2009

Cited by 36

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Hippocampal Volumetry and Memory fMRI in Temporal Lobe Epilepsy

D. Mechanic-Hamilton, M. Korczykowski, Paul Yushkevich, K. Lawler, J. Pluta, Simon Glynn, J. Tracy, R. Wolf, M. Sperling, Jacqueline A. French, and J. Detre

Epilepsy & behavior : E&B, Aug 2009

Cited by 38

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This study examined the utility of structural and functional MRI at 1.5 and 3 Tesla (T) in the pre-surgical evaluation and prediction of post-surgical cognitive outcome in temporal lobe epilepsy (TLE). Forty-nine patients undergoing presurgical evaluation for temporal lobe (TL) resection and twenty-five control subjects were studied. Patients completed standard pre-surgical evaluations including, intracarotid amobarbital test (IAT) and neuropsychological testing. During functional imaging, subjects performed a complex visual scene-encoding task. High-resolution structural MRI scans were used to quantify hippocampal volumes. Both structural and functional imaging successfully lateralized the seizure focus and correlated with IAT memory lateralization, with improvement for functional imaging at 3T as compared to 1.5T. Ipsilateral structural and functional MRI data was related to cognitive outcome and greater functional asymmetry was related to earlier age of onset. These findings support continued investigation of the utility of MRI and fMRI in the presurgical evaluation of TLE.
Multivariate Cortical Folding Pattern Analysis in Neonatal Complex Congenital Heart Disease

Suyash P. Awate, Paul Yushkevich, Song Zhuang, D. Licht, and J. Gee

NeuroImage, Jul 2009

DOI
Multivariate High-Dimensional Cortical Folding Analysis, Combining Complexity and Shape, in Neonates with Congenital Heart Disease

Suyash P. Awate, Paul Yushkevich, Song Zhuang, D. Licht, and J. Gee

Information processing in medical imaging : proceedings of the ... conference, Jul 2009

Cited by 21

DOI
Hippocampal subfield atrophy using shape based normalization: a preliminary study using the ADNI dataset

Sandhitsu R. Das, J. Pluta, B. Avants, Hd Soares, and Paul Yushkevich

NeuroImage, Jul 2009

DOI
O2‐01‐04: A preliminary study of hippocampal subfield atrophy using the ADNI dataset

Sandhitsu R. Das, J. Pluta, B. Avants, H. Soares, and Paul Yushkevich

Alzheimer’s & Dementia, Jul 2009

DOI
Reliability of semi-automated visual area definitions in retinotopy

Sandhitsu R. Das, Robyn T. Oliver, B. Avants, Petya D. Radoeva, D. Brainard, G. Aguirre, and J. Gee

NeuroImage, Jul 2009

DOI
Structure Specific Analysis of the Hippocampus in Temporal Lobe Epilepsy

Sandhitsu R. Das, D. Mechanic-Hamilton, M. Korczykowski, J. Pluta, Simon Glynn, B. Avants, J. Detre, and Paul Yushkevich

Hippocampus, Jun 2009

Cited by 23

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The hippocampus is a major structure of interest affected by temporal lobe epilepsy (TLE). Region of interest (ROI)‐based analysis has traditionally been used to study hippocampal involvement in TLE, although spatial variation of structural and functional pathology have been known to exist within the ROI. In this article, structure‐specific analysis (Yushkevich et al. (2007) Neuroimage 35:1516–1530) is applied to the study of both structure and function in TLE patients. This methodology takes into account information about the spatial correspondence of voxels within ROIs on left and right sides of the same subject as well as between subjects. Hippocampal thickness is studied as a measure of structural integrity, and functional activation in a functional magnetic resonance imaging (fMRI) experiment in which subjects performed a memory encoding task is studied as a measure of functional integrity. Pronounced disease‐related decrease in thickness is found in posterior and anterior hippocampus. A region in the body also shows increased thickness in patients’ healthy hippocampi compared with controls. Functional activation in diseased hippocampi is reduced in the body region compared to controls, whereas a region in the tail showing greater right‐lateralized activation in controls also shows greater activation in healthy hippocampi compared with the diseased side in patients. Summary measurements generated by integrating quantities of interest over the entire hippocampus can also be used, as is done in conventional ROI analysis. © 2009 Wiley‐Liss, Inc.
Ventricularwall thickness analysis in acute myocardial infarction and hypertrophic cardiomyopathy

Hui Sun, C. Tobon-Gomez, Sandhitsu R. Das, M. Huguet, Paul Yushkevich, and Alejandro F Frangi

In IEEE International Symposium on Biomedical Imaging, Jun 2009

Cited by 1

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Ventricular wall thickness and thickening are important biomarkers that are informative about myocardial function, especially for patients suffering from acute myocardial infarction (AMI) and hypertrophic cardiomyopathy (HCM). In this paper, the medial modeling is applied to produce thickness and thickening maps on skeleton meshes, on which surface-based statistical analysis can be directly performed. As an example, the statistics derived from healthy group is used to identify regions with abnormal thickness or thickening in a new patient. Cluster-based analysis is also performed to study the prevalent patterns of thickness and thickening change for AMI and HCM patients in the dataset.
Seeing People Move: Perception of Biological Motion by Intermediate-Level Motion Features and its Use in Computer Vision

Sandhitsu R. Das

Jan 2009
Live-Wire-ing the Insight Toolkit with Intelligent Scissors

N. Tustison, Paul Yushkevich, and J. Gee

The Insight Journal, Jan 2009

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Semi-automatic image segmentation algorithms depend on interaction with the user to accurately define a region of interest within an image. Once such method is a dynamic programming approach called em Intelligent Scissors developed by Mortenson and Barret citeMortensen1992,Mortensen1995,Barrett1996,Barrett1997. Standard interaction involves the user-placement of a seed point on or near the boundary of the object to be extracted. Using a gradient-based cost function, a em live-wire image path from the seed point to a subsequently placed boundary point is determined. As this free point is manipulated with the mouse cursor, the live-wire boundary, which extends from the seed point to the varying free point, locks onto nearby edges within the image. Although some applications do not require such user-interaction (e.g. citeHu2001) warranting inclusion within the toolkit, incorporating live-wire capabilities into ITK-SNAP citeYushkevich2006 has been discussed and, therefore, we would like to, as a preliminary step, vet the code within the ITK community.
A high-resolution computational atlas of the human hippocampus from postmortem magnetic resonance imaging at 9.4 T

Paul Yushkevich, B. Avants, J. Pluta, Sandhitsu R. Das, D. Minkoff, D. Mechanic-Hamilton, Simon Glynn, S. Pickup, Weixia Liu, J. Gee, M. Grossman, and J. Detre

NeuroImage, Jan 2009

Cited by 180

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Sensitivity to motion features in point light displays of biological motion.

Sandhitsu R. Das, M. Lazarewicz, Robert C. Wilson, and L. Finkel

Spatial vision, Jan 2009

Cited by 3

DOI
Automatic Segmentation of Hippocampal Subfields in T 2-Weighted In Vivo MRI

H. Wang, J. Pluta, B. Avants, S. Das, C. Craige, M. Altinay, M. Weiner, S. Mueller, and Paul Yushkevich

Jan 2009
Introduction to the Science of Medical Imaging: Linear systems

Paul Yushkevich

Jan 2009

DOI

2008

Registration Based Cortical Thickness Measurement

Sandhitsu R. Das, B. Avants, M. Grossman, and J. Gee

NeuroImage, Dec 2008

Cited by 268

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Cortical thickness is an important biomarker for image-based studies of the brain. A Diffeomorphic registration based cortical thickness (DiReCT) measure is introduced where a continuous one-to-one correspondence between the gray matter-white matter interface and the estimated gray matter-cerebrospinal fluid interface is given by a Diffeomorphic mapping in the image space. Thickness is then defined in terms of a distance measure between the interfaces of this sheet like structure. This technique also provides a natural way to compute continuous estimates of thickness within buried sulci by preventing opposing gray matter banks from intersecting. In addition, the proposed method incorporates neuroanatomical constraints on thickness values as part of the mapping process. Evaluation of this method is presented on synthetic images. As an application to brain images, a longitudinal study of thickness change in frontotemporal dementia (FTD) spectrum disorder is reported.
Continuous Medial Representation of Brain Structures Using the Biharmonic PDE

Paul Yushkevich

NeuroImage, Nov 2008

Cited by 48

Abs DOI PDF

A new approach for constructing deformable continuous medial models for anatomical structures is presented. Medial models describe geometrical objects by first specifying the skeleton of the object and then deriving the boundary surface corresponding to the skeleton. However, an arbitrary specification of a skeleton will not be “Valid” unless a certain set of sufficient conditions is satisfied. The most challenging of these is the non-linear equality constraint that must hold along the boundaries of the manifolds forming the skeleton. The main contribution of this paper is to leverage the biharmonic partial differential equation as a mapping from a codimension-0 subset of Euclidean space to the space of skeletons that satisfy the equality constraint. The PDE supports robust numerical solution on freeform triangular meshes, providing additional flexibility for shape modeling. The approach is evaluated by generating continuous medial models for a large dataset of hippocampus shapes. Generalizations to modeling more complex shapes and to representing branching skeletons are demonstrated.
3D Cerebral Cortical Morphometry in Autism: Increased Folding in Children and Adolescents in Frontal, Parietal, and Temporal Lobes

Suyash P. Awate, Lawrence Win, Paul Yushkevich, R. Schultz, and J. Gee

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Sep 2008

Cited by 33

DOI PDF
Cardiac Medial Modeling and Time-Course Heart Wall Thickness Analysis

Hui Sun, B. Avants, Alejandro F Frangi, F. Sukno, J. Gee, and Paul Yushkevich

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Sep 2008

Cited by 21

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A High-Resolution Computational Atlas of the Human Hippocampus from Postmortem Magnetic Resonance Imaging at 9.4 Tesla

Paul Yushkevich, B. Avants, J. Pluta, Sandhitsu R. Das, D. Minkoff, D. Mechanic-Hamilton, Simon Glynn, S. Pickup, Wei-Xia Liu, J. Gee, M. Grossman, and J. Detre

NeuroImage, Sep 2008

Cited by 184

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This paper describes the construction of a computational anatomical atlas of the human hippocampus. The atlas is derived from high-resolution 9.4 Tesla MRI of postmortem samples. The main subfields of the hippocampus (cornu Ammonis fields CA1, CA2/3; the dentate gyrus; and the vestigial hippocampal sulcus) are labeled in the images manually using a combination of distinguishable image features and geometrical features. A synthetic average image is derived from the MRI of the samples using shape and intensity averaging in the diffeomorphic non-linear registration framework, and a consensus labeling of the template is generated. The agreement of the consensus labeling with manual labeling of each sample is measured, and the effect of aiding registration with landmarks and manually generated mask images is evaluated. The atlas is provided as an online resource with the aim of supporting subfield segmentation in emerging hippocampus imaging and image analysis techniques. An example application examining subfield-level hippocampal atrophy in temporal lobe epilepsy demonstrates the application of the atlas to in vivo studies.
Shape-Based Alignment of Hippocampal Subfields: Evaluation in Postmortem MRI

Paul Yushkevich, B. Avants, J. Pluta, D. Minkoff, J. Detre, M. Grossman, and J. Gee

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Sep 2008

Cited by 11

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IC‐P2‐124: Gray matter changes in cognitively normal control subjects with PiB retention

J. Price, J. James, H. Aizenstein, D. Wolk, Oscar L. Lopez, Kathryn L. Dunfee, R. Nebes, Judith A. Saxton, B. Snitz, Edythe E. Halligan, A. Cohen, Chester A. Mathis, W. Klunk, and S. DeKosky

Alzheimer’s & Dementia, Jul 2008

DOI
Spatial correspondence based asymmetry analysis in FMRI

Sandhitsu R. Das, D. Mechanic-Hamilton, M. Korczykowski, B. Avants, J. Detre, J. Gee, and Paul Yushkevich

In IEEE International Symposium on Biomedical Imaging, May 2008

Cited by 1

DOI
Branching medial models for cardiac shape representation

Hui Sun, B. Avants, Alejandro F Frangi, S. Ordas, J. Gee, and Paul Yushkevich

In IEEE International Symposium on Biomedical Imaging, May 2008

Cited by 9

DOI
Building an atlas of hippocampal subfields using postmortem MRI

Paul Yushkevich, B. Avants, J. Pluta, D. Minkoff, S. Pickup, Wei-Xia Liu, J. Detre, M. Grossman, and J. Gee

In IEEE International Symposium on Biomedical Imaging, May 2008

Cited by 2

DOI
Surface-based modeling of white matter fasciculi with orientation encoding

Hui Zhang, Paul Yushkevich, T. Simon, and J. Gee

In IEEE International Symposium on Biomedical Imaging, May 2008

Cited by 1

DOI
Spatial Correspondence Based Asymmetry Analysis in Hippocampus: Application to Temporal Lobe Epilepsy

Sandhitsu R. Das, D. Mechanic-Hamilton, M. Korczykowski, Simon Glynn, B. Avants, J. Detre, J. Gee, and Paul Yushkevich

May 2008
Synthesis, Deformation, and Statistics of 3D Objects via M-Reps

S. Pizer, Qiong Han, S. Joshi, P. Fletcher, Paul Yushkevich, and Andrew Thall

Medial Representations, May 2008

Cited by 7

DOI
A computational DTI template for aging studies

H. Zhang, Paul Yushkevich, D. Rueckert, and J. Gee

May 2008

Cited by 2

2007

Measuring Cortical Thickness Using An Image Domain Local Surface Model And Topology Preserving Segmentation

Sandhitsu R. Das, B. Avants, M. Grossman, and J. Gee

In IEEE International Conference on Computer Vision, Dec 2007

Cited by 4

DOI
Structure-Specific Statistical Mapping of White Matter Tracts using the Continuous Medial Representation

Paul Yushkevich, Hui Zhang, T. Simon, and J. Gee

In IEEE International Conference on Computer Vision, Dec 2007

Cited by 197

DOI PDF
Electrical and optical properties of Al doped cadmium oxide thin films deposited by radio frequency magnetron sputtering

B. Saha, Sandhitsu R. Das, and K. Chattopadhyay

Solar Energy Materials and Solar Cells, Nov 2007

Cited by 184

DOI
Evaluation of Shape-Based Normalization in the Corpus Callosum for White Matter Connectivity Analysis

Hui Sun, Paul Yushkevich, Hui Zhang, Philip A Cook, J. Duda, T. Simon, and J. Gee

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Oct 2007

Cited by 1

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High-Dimensional Spatial Normalization of Diffusion Tensor Images Improves the Detection of White Matter Differences: An Example Study Using Amyotrophic Lateral Sclerosis

Hui Zhang, B. Avants, Paul Yushkevich, J. Woo, Sumei Wang, L. Mccluskey, L. Elman, E. Melhem, and J. Gee

IEEE Transactions on Medical Imaging, Oct 2007

Cited by 263

DOI
Unbiased White Matter Atlas Construction Using Diffusion Tensor Images

Hui Zhang, Paul Yushkevich, D. Rueckert, and J. Gee

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Oct 2007

Cited by 89

DOI PDF
Shape-Based Normalization of the Corpus Callosum for DTI Connectivity Analysis

Hui Sun, Paul Yushkevich, Hui Zhang, Philip A Cook, J. Duda, T. Simon, and J. Gee

IEEE Transactions on Medical Imaging, Sep 2007

Cited by 26

DOI
Neuroinformatics for Genome-Wide 3-D Gene Expression Mapping in the Mouse Brain

L. Ng, Sayan D. Pathak, C. Kuan, C. Lau, Hong-wei Dong, Andrew Sodt, Chinh Dang, B. Avants, Paul Yushkevich, J. Gee, D. Haynor, E. Lein, Allan R. Jones, and M. Hawrylycz

IEEE/ACM Transactions on Computational Biology and Bioinformatics, Jul 2007

Cited by 138

DOI
Hippocampus-specific fMRI group activation analysis using the continuous medial representation

Paul Yushkevich, J. Detre, D. Mechanic-Hamilton, M. Fernández-Seara, K. Tang, Angela Hoang, M. Korczykowski, Hui Zhang, and J. Gee

NeuroImage, May 2007

Cited by 32

DOI PDF
NON-UNIFORM SMOOTHING IN HIPPOCAMPUS-SPECIFIC GROUP FMRI ANALYSIS

Paul Yushkevich, J. Detre, and J. Gee

In IEEE International Symposium on Biomedical Imaging, Apr 2007

DOI

2006

Continuous Medial Representation for Anatomical Structures

Paul Yushkevich, Hui Zhang, and J. Gee

IEEE Transactions on Medical Imaging, Nov 2006

Cited by 132

DOI
Hippocampus-Specific fMRI Group Activation Analysis with Continuous M-Reps

Paul Yushkevich, J. Detre, K. Tang, A. Hoang, D. Mechanic-Hamilton, M. Fernández-Seara, M. Korczykowski, Hui Zhang, and J. Gee

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Oct 2006

Cited by 3

DOI
Deformable registration of diffusion tensor MR images with explicit orientation optimization

Hui Zhang, Paul Yushkevich, D. Alexander, and J. Gee

Medical image analysis, Oct 2006

Cited by 512

DOI
Support for "cub" image format

Pablo D. Burstein, Paul Yushkevich, and J. Gee

The Insight Journal, Aug 2006

Abs DOI PDF

VoxBo (www.voxbo.org) is a distributed processing framework, developed at the Center of Functional Neuroimaging at the University of Penssylvania, with the purpose of processing and analyzing brain functional MRI data. VoxBo is written in C++, and it is escentially a fair translation of some SPM functionality, originally written in Matlab. Along with the software, VoxBo defines two new image formats: 1) .cub, a 3D image format, used for anatomical data and single EPI frames. It is important to notice that this format defines a proper origin field, lacking, for instance, in Analyze. 2) .tes, a 4D image format, designed to contain the temporal EPI information. It is worth noticing that this format organizes the voxels in such a way to optimize longitudinal (temporal) voxel access. Furthermore, the tes format is compressed through encoding of the functional voxels alone, i.e., background voxels are not stored for each frame, but only for the first one.In this work we present the necessary IO classes that allow ImageFileReader and ImageFileWriter to properly identify, read and write .cub files only. We will provide .tes support in a subsequent work. This effort is carried out with the purpose of letting VoxBo implementors to take advantage of ITK’s power and overcome the limitations currently afflicting VoxBo.
3D Mouse Brain Reconstruction from Histology Using a Coarse-to-Fine Approach

Paul Yushkevich, B. Avants, L. Ng, M. Hawrylycz, Pablo D. Burstein, Hui Zhang, and J. Gee

In Workshop on Biomedical Image Registration, Jul 2006

Cited by 79

DOI
User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability

Paul Yushkevich, J. Piven, H. Hazlett, R. Smith, Sean Ho, J. Gee, and G. Gerig

NeuroImage, Jul 2006

Cited by 9022

DOI PDF
Efficient Generation of Shape-Based Reference Frames for the Corpus Callosum for DTI-based Connectivity Analysis

Hui Sun, Paul Yushkevich, Hui Zhang, J. Gee, and T. Simon

In 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW’06), Jun 2006

Cited by 2

DOI PDF
Gait recognition by two-stage principal component analysis

Sandhitsu R. Das, Robert C. Wilson, M. Lazarewicz, and L. Finkel

In International Conference on Automatic Face and Gesture Recognition, Apr 2006

Cited by 15

DOI
Two-Stage PCA Extracts Spatiotemporal Features for Gait Recognition

Sandhitsu R. Das, Robert C. Wilson, M. Lazarewicz, and L. Finkel

J. Multim., Jan 2006

Cited by 22

DOI
Perception of biological motion by intermediate-level motion features

Sandhitsu R. Das

Jan 2006
Anatomy-Based Visualizations of Diffusion Tensor Images of Brain White Matter

J. Gee, Hui Zhang, A. Dubb, B. Avants, Paul Yushkevich, and J. Duda

Visualization and Processing of Tensor Fields, Jan 2006

Cited by 7

DOI
Quantitation of Pulmonary Structure via Registration and Normalization of Serial 3 He MR Images

J. Gee, T. Sundaram, B. Avants, Pablo D. Burstein, Paul Yushkevich, H. Zhang, Ingrid Casselbrant, P. Åkeson, G. Pettersson, B. Wyman, and B. Peterson

Jan 2006
Motion as Shape: A Novel Method for the Recognition and Prediction of Biological Motion

Robert C. Wilson, Sandhitsu R. Das, and L. Finkel

In British Machine Vision Conference, Jan 2006

Cited by 1

DOI

2005

An Automated Approach to Connectivity-Based Partitioning of Brain Structures

Philip A Cook, Hui Zhang, B. Avants, Paul Yushkevich, D. Alexander, J. Gee, O. Ciccarelli, and A. Thompson

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Oct 2005

Cited by 38

DOI PDF
Regional structural characterization of the brain of schizophrenia patients.

Paul Yushkevich, A. Dubb, Zhi-Yong Xie, R. Gur, R. Gur, and J. Gee

Academic Radiology, Oct 2005

Cited by 14

DOI
Statistical Modeling of Shape and Appearance Using the Continuous Medial Representation

Paul Yushkevich, Hui Zhang, and J. Gee

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Oct 2005

Cited by 11

DOI PDF
Parametric Medial Shape Representation in 3-D via the Poisson Partial Differential Equation with Non-linear Boundary Conditions

Paul Yushkevich, Hui Zhang, and J. Gee

Information processing in medical imaging : proceedings of the ... conference, Jul 2005

Cited by 14

DOI
User-Guided Level Set Segmentation of Anatomical Structures with ITK-SNAP

Paul Yushkevich, J. Piven, H. Cody, Sean Ho, J. Gee, and G. Gerig

The Insight Journal, Jul 2005

Cited by 91

Abs DOI PDF

Active contour segmentation and its robust implementation using level sets have been studied thoroughly in the medical image analysis literature. Despite the availability of these powerful methods, clinical research still largely relies on manual slice-by-slice outlining for anatomical structure segmentation. To bridge the gap between methodological advances and clinical routine, we developed ITK-SNAP: an open source application intended to make level set segmentation easily accessible to a wide range of users with various levels of mathematical expertise. We briefly describe this new tool and report the results of a validation study in which ITK-SNAP was compared to manual segmentation of the caudate in the context of an ongoing child neuroimaging autism study.
Recognition of temporal event sequences by a network of cortical neurons

M. Lazarewicz, Sandhitsu R. Das, and L. Finkel

Neurocomputing, Jun 2005

Cited by 2

DOI

2004

Towards diffusion profile image registration

Hui Zhang, Paul Yushkevich, and J. Gee

In IEEE International Symposium on Biomedical Imaging, Dec 2004

Cited by 6

DOI
Regional Structural Characterization of the Brain of Schizophrenia Patients

A. Dubb, Paul Yushkevich, Zhi-Yong Xie, R. Gur, R. Gur, and J. Gee

In International Conference on Medical Image Computing and Computer-Assisted Intervention, Sep 2004

Cited by 22

DOI
Registration of diffusion tensor images

Hui Zhang, Paul Yushkevich, and J. Gee

In Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., Jul 2004

Cited by 41

DOI
Statistical variability in nonlinear spaces: application to shape analysis and dt-mri

P. Fletcher, S. Pizer, S. Joshi, G. Gerig, J. S. Marron, M. Kerckhove, Michael, Paul Yushkevich, Andrew Thall, Y. Fridman, Sean Ho, Qiong Han, E. Broadhurst, E. Chaney, James R. Damon, Daniel A Fristch, Keith Graham Gash, G. Muller, Mỹ, My Friends Tom, Josh Dave, K. Shelby, and Eli

Jul 2004

Cited by 61

2003

Deformable M-Reps for 3D Medical Image Segmentation

S. Pizer, P. Fletcher, S. Joshi, Andrew Thall, James Z. Chen, Y. Fridman, D. Fritsch, A. G. Gash, J. Glotzer, M. Jiroutek, Conglin Lu, K. Muller, G. Tracton, Paul Yushkevich, and E. Chaney

International Journal of Computer Vision, Nov 2003

Cited by 381

DOI PDF
Feature Selection for Shape-Based Classification of Biological Objects

Paul Yushkevich, S. Joshi, S. Pizer, J. Csernansky, and Lei E. Wang

Information processing in medical imaging : proceedings of the ... conference, Jul 2003

Cited by 36

DOI PDF
Continuous medial representations for geometric object modeling in 2D and 3D

Paul Yushkevich, P. Fletcher, S. Joshi, Andrew Thall, and S. Pizer

Image Vis. Comput., Jan 2003

Cited by 82

DOI PDF
Statistical shape characterization using the medial representation

S. Pizer, and Paul Yushkevich

Jan 2003

Cited by 13

2002

Multiscale deformable model segmentation and statistical shape analysis using medial descriptions

S. Joshi, S. Pizer, P. Fletcher, Paul Yushkevich, Andrew Thall, and J. Marron

IEEE Transactions on Medical Imaging, May 2002

Cited by 161

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2001

Intuitive, Localized Analysis of Shape Variability

Paul Yushkevich, S. Pizer, S. Joshi, and J. Marron

Information Processing in Medical Imaging, Jun 2001

Cited by 53

DOI

1999

Segmentation, registration, and measurement of shape variation via image object shape

S. Pizer, D. Fritsch, Paul Yushkevich, V. Johnson, and E. Chaney

IEEE Transactions on Medical Imaging, Feb 1999

Cited by 378

DOI
Towards Automatic, Model-Driven Determination of 3D Patient Setup Errorsormal Radiotherapy

Paul Yushkevich, D. Fritsch, S. Pizer, and E. Chaney

Feb 1999

Cited by 1

IN AGING AND ALZHEIMER’S DISEASE

Ana.M. Daugherty, LauraWisse, R. Amaral, K. Amunts, Jean C. Augustinack, Arnold Bakker, A. Bender, D. Berron, A. Burggren, M. Chakravarty, Robin de, Flores, Song‐Lin Ding, Arne D. Ekstrom, P. Kanel, O. Kedo, R. Insausti, N. Malykhin, Susanne G. Mueller, N. Ofen, D. Palombo, J. Pluta, D. Schoemaker, C. Stark, T. Steve, Lei Wang, M. Yassa, Qi-Jing Yu, Paul Yushkevich, Valerie A. Carr, Ayesha Nadiadwala, Carmen Azevedo, Wan-Jia Guo, Jessa Castillo, Jacob N. Hall, A. Trelle, S. Sha, Manasi Jayakumar, Natalie J. Tanner, Marc B. Harrison, G. Deutsch, C. Fredericks, M. Greicius, Shyam M. Srinivas, Michelle L. James, G. Zaharchuk, A. D. Wagner, and Frederick T. Chin

Feb 1999

Cited by 1
Repeatability of B1 Inhomogeneity Correction of Volumetric (3D) Glutamate CEST via High-Permittivity Dielectric Padding at 7T

Paul S. Jacobs, R. Nanga, Abigail T. J. Cember, D. Tisdall, Sandhitsu R. Das, J. Detre, D. Roalf, and Ravinder Reddy

ISMRM Annual Meeting, Feb 1999

Abs DOI

Dielectric pads were used to improve the contrast of volumetric (3D) gluCEST via enhanced homogenization of B1 fields. Effective placement of the pads required additional coverage of the face due to their physical size to achieve the saturated B1 strength necessary to recover the gluCEST signal from the anterior portions of the brain. The origin of gluCEST’s need for high B1 is discussed, and examples of 3D gluCEST images acquired with and without the use of the dielectric pads are provided and repeatability of the 3D gluCEST in the presence of pad placement was determined.
Lateralization of Memory Function in Temporal Lobe Epilepsy using Scene Memory fMRI

William Tackett, D. Mechanic-Hamilton, Sandhitsu R. Das, K. Davis, and J. Detre

ISMRM Annual Meeting, Feb 1999

Cited by 1

Abs DOI

Surgery to treat mesial temporal lobe epilepsy (TLE) offers freedom from seizures but risks postsurgical memory decline. Lateralizing memory function is essential for mitigating the risk of resecting “eloquent” cortex. Memory laterality has traditionally been assessed using the Wada test, but it is invasive and poses its own risks. The noninvasive method of functional magnetic resonance imaging (fMRI) has become a possible alternative. However, questions remain about fMRI’s reliability in lateralizing memory. Our group has shown that a scene memory task is capable of activating hippocampus and lateralizing memory function. Here, we present an improved version of that experimental paradigm.
Developing a Craniofacial Soft Tissue Anthropomorphic Database: Applying Diffeomorphic Template Building Methods to MRI

D. Villavisanis, Pulkit Khandelwal, Zachary D. Zapatero, Connor S. Wagner, D. Cho, Liana Cheung, J. Blum, J. Swanson, Jesse A. Taylor, Paul Yushkevich, and S. Bartlett

ISMRM Annual Meeting, Feb 1999

Abs DOI

Craniofacial surgery requires reconciliation of several factors for deformity reconstruction and aesthetic enhancement. Here, we present data in developing a racially and ethnically sensitive anthropomorphic database to provide plastic and craniofacial surgeons with a set of “normal” anatomic measurements to optimize aesthetic and reconstructive outcomes. Images were used to construct composite (template) images with Advanced Normalization Tools (ANTs) and Greedy Tools. Composite templates demonstrated age-appropriate anatomic measurements as proof of concept. Application of diffeomorphic algorithms via ANTs to MRI is effective in developing composite templates representing “normal” soft tissue anatomy, which may aid in objectively quantifying anatomic abnormality.
Neurobiology of Aging

L. Wisse, Long Xie, Sandhitsu R. Das, R. Flores, O. Hansson, M. Habes, J. Doshi, C. Davatzikos, Paul Yushkevich, and D. Wolk

Feb 1999
NeuroImage: Clinical

L.E.M. Wisse, S. Das, C. Davatzikos, B. Dickerson, S. X. Xie, Paul Yushkevich, and D. Wolk

Feb 1999
Author Manuscript, Published in "1st Miccai Workshop on Mathematical Foundations of Computational Anatomy: Geometrical, Statistical and Registration Methods for Modeling Biological Shape Variability Hippocampus-specific Fmri Group Activation Analysis with Continuous M-reps

Paul Yushkevich, J. Detre, K. Tang, Angela Hoang, D. Mechanic-Hamilton, M. Fernández-Seara, M. Korczykowski, Hui Zhang, and J. Gee

Feb 1999

Cited by 3