Nomogram-Based Risk Model of Small (≤5 mm) Intracranial Aneurysm Rupture in an Eastern Asian Study

BACKGROUND AND PURPOSE: Risk stratification of small unruptured intracranial aneurysms (IAs) (< =5 mm) is important for clinical decision-making and management. The aim of this study was to develop an individualized rupture risk model for small IAs in an eastern Asian population. METHODS: This study retrospectively enrolled 343 patients with ruptured (n = 96) and unruptured (n = 285) small IAs. Clinical data and aneurysmal morphology were taken into consideration, regression analysis was performed to identify significant variables, and these variables were then incorporated into a predictive nomogram. The diagnostic performance of the nomogram was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC) and calibration plot. Clinical effectiveness was validated by decision curve analysis (DCA). The PHASES score calculated for each case was used for comparison. RESULTS: The nomogram achieved an AUC of 0.849 (95% CI: 0.805–0.893), with a sensitivity of 86.5%, a specificity of 70.9%, and accuracy of 74.7%, which was superior to PHASES score system (AUC = 0.693, sensitivity = 83.6%, specificity = 48.8%, and accuracy = 57.5%). A good agreement between predicted rupture risk and actual rupture status in the small aneurysms was observed, and DCA illustrated the benefit of using the nomogram when decisions needed to be made clinically. CONCLUSIONS: The nomogram based on clinical and morphological risk factors can be useful in assisting clinicians with individualized assessments and benefit-risk balancing in patients with small IAs (< =5 mm).