Prediction of amyloid pathology in cognitively unimpaired individuals using structural MRI

Background: Structural MRI measurements can contribute to the prediction of amyloid pathology in cognitively unimpaired (CU) individuals. In this work, we aimed at studying the predictive capacity, robustness, and generalizability of ML techniques to predict amyloid-ß pathology in CU individuals, as well as identifying key brain regions contributing to this prediction. Method: We included 653 and 250 CU individuals from the EPAD and ADNI studies, respectively, with available T1w MRI and CSF Aß42 measurements. Subjects were categorized as amyloid-ß positive (Aß+) or negative (Aß-) according to established cut-offs (CSF Aß42<1000pg/mL for EPAD and