Simulation-informed Modelling and Personalized Evaluation (SIMPLE): A Computational Study of MRI-based Brain Age Matrices

Multimodal magnetic resonance imaging (MRI), detecting brain structural and functional changes, has emerged as a powerful and promising technique to study individual's brain, as T1-weighted scans can detect morphometric features, diffusion tensor imaging (DTI) scans can quantify structural connectivity, and functional MRI can capture the features of functional connectivity. Notably, with the advances in quantitative methods, computational models of brain age and brain-predicted age difference (brain-PAD) detecting the ageing effects on individual's brain features are becoming increasingly popular in clinical studies, which might revolutionize the diagnostic and prognostic phonotypes of age-related brain diseases globally.