Development and Validation of a Brain Aging Biomarker in Middle-Aged and Older Adults: Deep Learning Approach.

ABSTRACT:

Background

Precise assessment of brain aging is crucial for early detection of neurodegenerative disorders and aiding clinical practice. Existing magnetic resonance imaging (MRI)-based methods excel in this task, but they still have room for improvement in capturing local morphological variations across brain regions and preserving the inherent neurobiological topological structures.

Objective

To develop and validate a deep learning framework incorporating both connectivity and complexity for accurate brain aging estimation, facilitating early identification of neurodegenerative diseases.

Methods

We used 5889 T1-weighted MRI scans from the Alzheimer's Disease Neuroimaging Initiative dataset. We proposed a novel brain vision graph neural network (BVGN), incorporating n

SUBMITTER: Li Z 

PROVIDER: S-EPMC12357125 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature