Detection of mild cognitive impairment in a community-dwelling population using quantitative, multiparametric MRI-based classification.

ABSTRACT: Early and accurate mild cognitive impairment (MCI) detection within a heterogeneous, nonclinical population is needed to improve care for persons at risk of developing dementia. Magnetic resonance imaging (MRI)-based classification may aid early diagnosis of MCI, but has only been applied within clinical cohorts. We aimed to determine the generalizability of MRI-based classification probability scores to detect MCI on an individual basis within a general population. To determine classification probability scores, an AD, mild-AD, and moderate-AD detection model were created with anatomical and diffusion MRI measures calculated from a clinical Alzheimer's Disease (AD) cohort and subsequently applied to a population-based cohort with 48 MCI and 617 normal aging subjects. Each model's ability

SUBMITTER: Bouts MJRJ 

PROVIDER: S-EPMC6563478 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature