Predicting future cognitive decline from non-brain and multimodal brain imaging data in healthy and pathological aging.

ABSTRACT: Previous literature has focused on predicting a diagnostic label from structural brain imaging. Since subtle changes in the brain precede a cognitive decline in healthy and pathological aging, our study predicts future decline as a continuous trajectory instead. Here, we tested whether baseline multimodal neuroimaging data improve the prediction of future cognitive decline in healthy and pathological aging. Nonbrain data (demographics, clinical, and neuropsychological scores), structural MRI, and functional connectivity data from OASIS-3 (N = 662; age = 46-96 years) were entered into cross-validated multitarget random forest models to predict future cognitive decline (measured by CDR and MMSE), on average 5.8 years into the future. The analysis was preregistered, and all analysis code is p

SUBMITTER: Hebling Vieira B 

PROVIDER: S-EPMC9853405 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature