Increased MRI-based Brain Age in chronic migraine patients.

ABSTRACT:

Introduction

Neuroimaging has revealed that migraine is linked to alterations in both the structure and function of the brain. However, the relationship of these changes with aging has not been studied in detail. Here we employ the Brain Age framework to analyze migraine, by building a machine-learning model that predicts age from neuroimaging data. We hypothesize that migraine patients will exhibit an increased Brain Age Gap (the difference between the predicted age and the chronological age) compared to healthy participants.

Methods

We trained a machine learning model to predict Brain Age from 2,771 T1-weighted magnetic resonance imaging scans of healthy subjects. The processing pipeline included the automatic segmentation of the images, the extraction of 1,479 imaging fea

SUBMITTER: Navarro-Gonzalez R 

PROVIDER: S-EPMC10557155 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature