The Accuracy in Rupture Risk Prediction of Intracranial Aneurysms by Artificial Intelligence Algorithms Using Imaging Data From CTA and DSA: A Systematic Review and Meta-Analysis.

ABSTRACT: Ruptured intracranial aneurysms (IAs) are the leading cause of aSAH. There are limitations in combining traditional imaging methods (CTA and DSA) and clinical scores (PHASES) to predict IAs rupture risk, whereas artificial intelligence (AI) algorithms show potential. This meta-analysis evaluated AI algorithm performance for predicting IAs rupture risk based on CTA and DSA. As of February 2025, we searched Web of Science, PubMed, Scopus, and Embase, extracting TP, FP, FN, and TN from included studies. The combined sensitivity, specificity, and AUC were synthesised with a bivariate random-effects model. Subgroup analyses were performed. PROSPERO: CRD420251008866. Twenty studies (13,232 patients, 14,344 IAs) reported pooled sensitivity 0.84 (95% CI: 0.80-0.87), specificity 0.82 (95% CI: 0.78-

SUBMITTER: Zhang R 

PROVIDER: S-EPMC12729478 | biostudies-literature | 2026 Jan-Dec

REPOSITORIES: biostudies-literature