A computational framework to predict the spreading of Alzheimer's disease.

Overview

1. Department of Construction and Manufacturing Engineering, University of Oviedo,Gijón, 33203 Spain
2. Department of Engineering Science, University of Oxford,Oxford, OX1 3PJ UK

Abstract

Alzheimer’s disease is characterised by the spreading of misfolded proteins and progressive structural changes in the brain. Despite significant clinical research, understanding how microscopic protein dynamics translate into macroscopic tissue degeneration remains a major challenge. In this work, we present a three-dimensional, finite element-based computational framework to model disease progression by combining multi-protein transport and brain tissue deformation within anatomically realistic geometries. The propagation of toxic tau and amyloid- proteins is described using reaction–diffusion equations of the Fisher-Kolmogorov type, incorporating prion-like growth mechanisms and anisotropic transport along white matter fibre tracts. Brain atrophy is represented through a hyperelastic constitutive model driven by protein-dependent volume loss. Subject-specific simulations are achieved through an automated preprocessing pipeline that generates finite element meshes and reconstructs axonal orientation fields from medical imaging data. The model reproduces key morphological patterns observed in Alzheimer’s disease and shows good quantitative agreement with longitudinal imaging measurements. Overall, the proposed framework offers an extensible computational platform for studying Alzheimer’s disease progression across subject-specific brain geometries. The models developed, including the image processing framework (BrainImage2Mesh) and the coupled bio-chemo-mechanical COMSOL finite element implementation, are made freely available to download at https://mechmat.web.ox.ac.uk/codes.

Supplementary Information: The online version contains supplementary material available at 10.1007/s00366-026-02313-5.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Version 2, 28 September 2026

• Publisher: n/a → Springer Science+Business Media

Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 4 authors, 5 keywords, 2 funders, 24 references.

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This paper

Vazquez-Palomo, A., Betegón, C., Weickenmeier, J., & Martínez-Pañeda, E. (2026). A computational framework to predict the spreading of Alzheimer's disease. Engineering with computers, 42(2), 78. https://doi.org/10.1007/s00366-026-02313-5

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