Identifying individuals with Alzheimer's disease-like brains based on structural imaging in the Human Connectome Project Aging cohort.

ABSTRACT: Given the difficulty in factoring out typical age effects from subtle Alzheimer's disease (AD) effects on brain structure, identification of very early, as well as younger preclinical "at-risk" individuals has unique challenges. We examined whether age-correction procedures could be used to better identify individuals at very early potential risk from adults who did not have any existing cognitive diagnosis. First, we obtained cross-sectional age effects for each structural feature using data from a selected portion of the Human Connectome Project Aging (HCP-A) cohort. After age detrending, we weighted AD structural deterioration with patterns quantified from data of the Alzheimer's Disease Neuroimaging Initiative. Support vector machine was then used to classify individuals with brains th

SUBMITTER: Li B 

PROVIDER: S-EPMC8559490 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature