Considerations on brain age predictions from repeatedly sampled data across time.

ABSTRACT:

Introduction

Brain age, the estimation of a person's age from magnetic resonance imaging (MRI) parameters, has been used as a general indicator of health. The marker requires however further validation for application in clinical contexts. Here, we show how brain age predictions perform for the same individual at various time points and validate our findings with age-matched healthy controls.

Methods

We used densely sampled T1-weighted MRI data from four individuals (from two densely sampled datasets) to observe how brain age corresponds to age and is influenced by acquisition and quality parameters. For validation, we used two cross-sectional datasets. Brain age was predicted by a pretrained deep learning model.

Results

We found small within-subject correlations betw

SUBMITTER: Korbmacher M 

PROVIDER: S-EPMC10570486 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature