Development and Validation of a Prediction Model for Intracranial Aneurysm Rupture Risk

Can a machine-learning model (MLM) predict the rupture risk of unruptured intracranial aneurysms (UIAs) using prerupture data?In this prognostic study of 11 579 UIAs from a cohort of 8846 patients, an MLM trained on prerupture clinical and morphological data demonstrated robust performance in both internal and external validation, including on aneurysms smaller than 10 mm.The findings of this study suggest that an MLM may improve risk stratification and inform treatment decision-making for patients with UIAs, providing additional guidance even for smaller aneurysms traditionally considered low risk.

Corresponding Author: Yuichi Murayama, MD, Department of Neurosurgery, The Jikei University School of Medicine, 3-25-8 Nishi-shinbashi, Minato-ku, Tokyo 105-8461, Japan (ymurayama@jikei.ac.jp).

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