Cerebral morphometric alterations predict the outcome of migraine diagnosis and subtyping: a radiomics analysis.

ABSTRACT:

Background

This study aimed to identify cerebral radiomic features related to migraine diagnosis and subtyping into migraine with aura (MwA) and migraine without aura (MwoA) and to develop predictive models based on these markers.

Method

We retrospectively analyzed MR imaging from 88 migraine patients (32 MwA and 56 MwoA) and 49 healthy control subjects (HCs). Features representing the gray matter morphometry and diffusion properties were extracted from participants via histogram analysis. These features were put through an all-relevant feature selection procedure within cross-validation loops to identify features with significant discriminative power for migraine diagnosis and subtyping. Based on the selected features, the predictive ability of the random forest models cons

SUBMITTER: Wang TX 

PROVIDER: S-EPMC11978170 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature