Progression of Cerebral Atrophy in Alzheimer's Disease and Its Consequences on Traumatic Brain Injury: Insights From Longitudinal Mri Studies Publisher Pubmed



Abdi H ; Sanchezmolina D ; Garciavilana S ; Azizi S ; Rahimimovaghar V
Source: International Journal for Numerical Methods in Biomedical Engineering Published:2026

Abstract

Alzheimer's disease (AD) is characterized by progressive cerebral atrophy that alters the brain's biomechanical response to external loading and may increase susceptibility to traumatic brain injury (TBI). This study aimed to quantify how varying degrees of AD-related atrophy affect intracranial dynamics under impact conditions and to compare these effects with those observed in normal aging. Three-dimensional finite-element head models were constructed in COMSOL Multiphysics, incorporating skull, cerebrospinal fluid (CSF), and brain tissue. Longitudinal MRI data informed annual volume-reduction rates of 0.5% (healthy aging), 1% (moderate AD), and 4% (severe AD) over a four-year period. Fluid–structure interaction (FSI) was employed to simulate dynamic interactions between the CSF and deformable brain tissue under a standardized blunt impact scenario. Key biomechanical metrics—relative brain–skull displacement and peak intracranial pressure—were recorded in frontal and occipital regions. At approximately 15.07% total volume reduction (severe AD), relative brain–skull displacement increased by 12.6% in the frontal region and 28.0% in the occipital region compared with healthy aging. Peak intracranial pressure decreased by 5.51% in the frontal region and 4.95% in the occipital region under severe atrophy, indicating enhanced energy absorption by the expanded CSF layer but greater overall brain motion. The amplified displacement patterns suggest elevated strain on bridging veins and a higher risk of subdural hematoma formation. Progressive brain atrophy in AD significantly modifies intracranial biomechanics under impact, underscoring the importance of accounting for neurodegenerative changes in TBI risk assessments. Incorporation of patient-specific viscoelastic properties—obtainable via Magnetic Resonance Elastography—into future models may further enhance predictive accuracy for vulnerable populations. © 2026 The Author(s). International Journal for Numerical Methods in Biomedical Engineering published by John Wiley & Sons Ltd.