Brain age as a surrogate marker for cognitive performance in multiple sclerosis.

ABSTRACT:

Background and purpose

Data from neuro-imaging techniques allow us to estimate a brain's age. Brain age is easily interpretable as 'how old the brain looks' and could therefore be an attractive communication tool for brain health in clinical practice. This study aimed to investigate its clinical utility by investigating the relationship between brain age and cognitive performance in multiple sclerosis (MS).

Methods

A linear regression model was trained to predict age from brain magnetic resonance imaging volumetric features and sex in a healthy control dataset (HC_train, n = 1673). This model was used to predict brain age in two test sets: HC_test (n = 50) and MS_test (n = 201). Brain-predicted age difference (BPAD) was calculated as BPAD = brain age minus chronological age.

SUBMITTER: Denissen S 

PROVIDER: S-EPMC9541923 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature