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G. Erus

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Open access Nov 2026

Topographic reference modelling of white matter hyperintensities across the adult lifespan

White matter hyperintensities (WMH) are among the most common MRI findings in older adults. They are widely regarded as markers of brain aging and cerebral small-vessel disease, and associated with risk for cognitive decline, Alzheimer’s disease and related dementias (ADRD), and stroke. White matter hyperintensities (W...

M. Alshikho, J. Pyne, Natalie C. Edwards et al. · 0 citations
Open access Nov 2026

Age-dependent structural brain aging in medication-free major depressive disorder: A multi-site analysis from COORDINATE-MDD consortium.

BACKGROUND Major depressive disorder (MDD) is associated with altered brain structure and accelerated brain aging. However, previous studies have been limited by clinical samples with mixed medication status and multiple mood states, modest sample sizes, underrepresentation of older adults with MDD, and/or reliance on...

Bhanu Sharma, P. Ballester, L. Minuzzi et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Brain2Vec: A Self-Supervised 3D Foundation Model for Structural Brain MRI

Deep learning models have become essential tools in medical imaging, yet training them end-to-end for diverse tasks remains challenging due to limited labeled data and computational constraints. To address this, we introduce Brain2Vec, a foundation model pre-trained on 74,425 T1-weighted Magnetic Resonance Imaging (MRI...

Spiros Maggioros, G. Erus, Gareth A. Harman et al. · 0 citations
Open access Sep 2026

White matter hyperintensities and the structural connectome: a network perspective on clinical heterogeneity.

It is found that WMH are more strongly associated with RcSVD-related structural connectivity changes than with those implicated in dementia, suggesting that WMH may impact structural brain network through different pathways in RcSVD and dementia.

Bianca Mazini, Caio Seguin, Jing-Lei Lv et al. · 0 citations
Preprint Aug 2026

GenFAR: A generalized representation of brain structure, derived from 49,246 multi-cohort MRIs via deep learning

GenFAR, a modular deep learning framework that learns general, clinically informed features from brain MRIs, is introduced, showing that using the learned feature representation can substantially increase the sample efficiency of secondary deep learning training tasks and models, as well as improve their accuracy.

V. Bashyam, G. Erus, Jun-Hao Wen et al. · 0 citations
Open access Dec 2025

Developing Topics.

BACKGROUND Demonstrating the specificity of plasma biomarkers to AD-related neurodegeneration would add support to their prognostic and diagnostic clinical use. METHOD Participants from the Baltimore Longitudinal Study of Aging were cognitively unimpaired at the time of their plasma Aβ42/Aβ40, GFAP, NfL (Quanterix Ne...

Murat Bilgel, Ishaan Shah, Jasmine M. Cooper et al. · 0 citations
Open access Sep 2026

Association of plasma biomarkers with longitudinal change in age- and Alzheimer’s disease-related brain atrophy patterns

Among CU individuals, plasma p-tau217 was associated with subsequent MCI/dementia due to AD and showed the most extensive associations with longitudinal AD-related brain atrophy, compared with SPARE-BA or R-indices capturing subcortical, diffuse cortical, or perisylvian atrophy.

Murat Bilgel, Ishaan Shah, Jasmine M. Cooper et al. · 0 citations

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