Independent replication of advanced brain age in mild cognitive impairment and dementia: detection of future cognitive dysfunction.

ABSTRACT: We previously developed a novel machine-learning-based brain age model that was sensitive to amyloid. We aimed to independently validate it and to demonstrate its utility using independent clinical data. We recruited 650 participants from South Korean memory clinics to undergo magnetic resonance imaging and clinical assessments. We employed a pretrained brain age model that used data from an independent set of largely Caucasian individuals (n = 757) who had no or relatively low levels of amyloid as confirmed by positron emission tomography (PET). We investigated the association between brain age residual and cognitive decline. We found that our pretrained brain age model was able to reliably estimate brain age (mean absolute error = 5.68 years, r(650) = 0.47, age range = 49-89 year) in the

SUBMITTER: Karim HT 

PROVIDER: S-EPMC9763106 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature