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Abstract #5327

Increased T1w MRI-based brain age in chronic migraine patients

Rafael Navarro-González1, David García-Azorín2, Ángel L. Guerrero2, Álvaro Planchuelo-Gómez1,3, Santiago Aja-Fernández1, and Rodrigo de Luis-García1
1Image Processing Laboratory, Universidad de Valladolid, Valladolid, Spain, 2Hospital ClĂ­nico Universitario de Valladolid, Valladolid, Spain, 3CUBRIC, Cardiff University, Cardiff, United Kingdom

Synopsis

Keywords: Machine Learning/Artificial Intelligence, Aging, MigraineBrain-age is an emerging neuroimaging biomarker that represents the aging status of the brain using machine learning techniques from MRI data. It has been successfully applied to the study of different neurological and psychiatric conditions. We hypothesize that patients with migraine may show an increased brain age gap (difference between the age estimated from the MRI data and the chronological age). After building a brain age model from 2,781 healthy subjects, we tested this hypothesis on a dataset with 210 healthy controls and migraine patients. Results showed an increased brain age in chronic migraine patients with respect to healthy controls.

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Keywords