The rupture of intracranial aneurysms (IAs) is a complicated phenomenon of which the mechanism is not fully understood. The purpose of this study is to associate local solid mechanical, hemodynamic, and morphological characteristics with rupture regions through statistical means, in an attempt to identify the parameters that are indicative of rupture propensity for IAs. Twenty patient-specific ruptured IA models were reconstructed from digital subtraction angiography (DSA), and applied in the analysis of wall tension, wall shear stress (WSS) and curvature. The precise rupture locations were marked out through intraoperative videos. Pearson correlation analysis was employed to investigate the correlations of these three parameters with patient characteristics and global geometric features. Univariate and multivariate logistic regression analysis were further performed on wall tension, WSS and curvature with regards to rupture and nonrupture regions. Receiver operating characteristic (ROC) analysis defining area under the curve (AUC) was performed on these three parameters. The univariate model of wall tension (AUC, 0.9750), WSS (AUC, 0.9300), curvature (0.8150) and their combined multivariate model (AUC, 0.9875) all present high AUC values. The wall tension, WSS and curvature are acceptable parameters relating to rupture regions. The rupture odd is more sensitive to the wall tension and WSS than curvature. Each logistic model is capable in discriminating ruptures from nonrupture regions, while the multivariate model is the most efficient.
Keywords: curvature; intracranial aneurysm; rupture region; statistical means; wall shear stress; wall tension.
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