Abstract
OBJECTIVES: To compare quantitative MRI markers of brain health in their ability to predict functional outcome after acute ischemic stroke (AIS). METHODS: We included AIS survivors from the international MRI-GENIE study (multicenter; 2003-2011) with acute T2-FLAIR imaging. Automated pipelines estimated white matter hyperintensity volume (WMHv), brain volume, and intracranial volume (ICV). Assessed brain health markers included: brain parenchymal fraction (brain volume relative to ICV); radiomics derived brain age; brain reserve (normal appearing brain volume relative to ICV), and effective Reserve (eR, latent variable based on age, WMH load and brain volume). We added the markers to a clinical reference model, comparing model performances between separate multivariable regression models in their prediction of unfavorable outcome (90-day modified Rankin Scale score 3-5), using Bayesian Information Criterion (BIC). RESULTS: We analyzed 2,223 patients (median age 67 years, 45% female, 24% unfavorable outcome). All models using brain health markers outperformed the clinical reference model (ΔBIC > 10). The eR model showed the lowest BIC value (BIC=2171.8), providing strong statistical evidence to outperform the brain age model (BIC=2179.5, ΔBIC > 6), and very strong (ΔBIC > 10) statistical evidence to outperform all other models. DISCUSSION: Quantitative MRI markers of brain health, especially eR, enhance personalized outcome prognostication after AIS.