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

作者：Soichiro Fujimura, Takeshi Yanagisawa, Genki Kudo, Toshiki Koshiba, Masaaki Suzuki, Hiroyuki TAKAO, Toshihiro ISHIBASHI, Hayato Ohwada, Shigeo Yamashiro, Maarten J. Kamphuis, Laura T. van der Kamp, Robert William Regenhardt, Mervyn D. I. Vergouwen, G. Rinkel, Aman B. Patel, Yuichi Murayama · 发表于：JAMA Network Open · 年份：2025 · DOI：10.1001/jamanetworkopen.2025.50772 · 被引用次数：10 · 研究领域：Intracranial Aneurysms: Treatment and Complications、Intracerebral and Subarachnoid Hemorrhage Research、Vascular Malformations Diagnosis and Treatment

Importance: Unruptured intracranial aneurysms (UIAs) affect 3.2% of the general population, and approximately 85% of subarachnoid hemorrhages result from their rupture. Despite their classification as low risk by prediction tools such as PHASES (population, hypertension, age, size of aneurysm, earlier subarachnoid hemorrhage from another aneurysm, and site of aneurysm) and the Unruptured Cerebral Aneurysm Study (UCAS), UIAs less than 10 mm are susceptible to rupture. Objective: To develop and externally validate a machine-learning model (MLM) predicting rupture risk of UIAs. Design, Setting, and Participants: This retrospective multicenter prognostic study analyzed UIAs from 4 institutions across 3 continents from January 2003 to November 2022. Each UIA was characterized by 29 clinical and 18 morphological variables. For model development, patients with UIAs were drawn from a large institutional cohort. Statistical analysis was performed from April 2024 to March 2025. Exposure: An MLM based on the Light Gradient Boosting Machine algorithm was trained, and performance was assessed for validation externally. Main Outcomes and Measures: The primary outcome was aneurysm rupture within 2 years after risk evaluation. Model performance was assessed using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and the area under the receiver operating characteristic curve (AUROC) wit...