Predicting Future Brain Atrophy Based on Longitudinal MRI.

ABSTRACT: Neuron loss is a key feature of neurodegenerative diseases often leading to brain atrophy detectable through magnetic resonance imaging (MRI). Various brain atrophy measures are essential in research of Alzheimer' disease (AD) and related dementias. This study aims to forecast future annual percentage changes in hippocampal, ventricular, and total gray matter (TGM) volumes in individuals with varying cognitive statuses, from healthy to dementia. We developed a machine learning model using elastic net linear regression and tested two approaches: (1) a baseline model using predictors from a single-time-point and (2) a longitudinal model using predictors derived from longitudinal MRI. Both approaches were evaluated with MRI-only models and models that combined MRI with additional risk factors

SUBMITTER: Hadji M 

PROVIDER: S-EPMC12632670 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature