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Objective: Middle cerebral artery (MCA) bifurcation aneurysms are more likely to be associated with severe hemorrhage or hematoma in a clinical setting. We aimed to investigate the morphological predictors of MCA bifurcation aneurysm rupture., Patients and Methods: We conducted a retrospective analysis of 317 patients with MCA aneurysms between January 2009 and October 2016. Aneurysm status was grouped into ruptured and unruptured groups. The MCA bifurcation was defined as the bifurcation of the main trunk (the origin of the M2 trunks). Aneurysm morphologies were determined using CT angiography. We performed univariate and multivariable regression analyses to investigate the association of morphological characteristics with ruptured MCA bifurcation aneurysms., Results: A total of 268 (84.5 %) patients with 280 MCA bifurcation aneurysms were included. 207 (73.9 %) aneurysms had ruptured. In the univariate analysis, a larger aneurysm (p = 0.042), a larger size ratio (p = 0.001), a larger aspect ratio (p = 0.017), a greater bottleneck ratio (p = 0.047), an irregular aneurysm (p = 0.004) and the presence of a daughter dome (p = 0.002) were associated with aneurysm rupture. The multivariate analysis showed that a larger size ratio (OR 1.324, 95 % CI, 1.062-1.651; p = 0.013) and the presence of daughter dome (OR 2.462, 95 % CI, 1.123-5.398; p = 0.024) were independently associated with ruptured aneurysms. The threshold of the size ratio for discriminating ruptured and unruptured aneurysms was 2.53 (p < 0.001)., Conclusions: The size ratio and the presence of a daughter dome were independent predictors of the rupture of MCA bifurcation aneurysms. These parameters may contribute to the evaluation of the risk of rupture of aneurysms., Competing Interests: Declaration of Competing Interest The authors declare that they have no competing interests., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background: Mirror intracranial aneurysms with different rupture status is a useful model to investigate features associated with aneurysm rupture. Morphological and hemodynamic analyses of ruptured middle cerebral artery (MCA) mirror aneurysms are rarely reported. The purpose of this study was to determine the morphological or hemodynamic characteristics associated with ruptured MCA mirror aneurysms., Methods: We performed a retrospective analysis of consecutive 317 patients with MCA aneurysms. Ruptured MCA mirror aneurysms (1 ruptured and mirror unruptured aneurysm) were included. In the matched pairs of ruptured and unruptured mirror aneurysms, 13 morphological parameters were measured using 3-dimensional computed tomography angiography and 6 hemodynamic parameters were evaluated using high-resolution computational fluid dynamic simulations. The association of morphological and hemodynamic characteristics with the rupture of MCA mirror aneurysms was determined., Results: A total of 20 (6.31%) patients with 40 MCA mirror aneurysms were included in this study. There were significant differences in morphological and hemodynamic parameters between the ruptured and unruptured mirror aneurysms. Irregular aneurysms were 3 times more common in the ruptured aneurysms than in the unruptured aneurysms. A larger aneurysm (P = 0.025), a higher aneurysm (P = 0.020), a larger size ratio (P = 0.009), a higher bottleneck ratio (P = 0.033), an irregular aneurysm (P = 0.022), a higher maximum intra-aneurysmal wall shear stress (WSS; P = 0.020), and a lower normalized average WSS (P = 0.008) were associated with MCA mirror aneurysm rupture., Conclusions: Larger aneurysms, a larger size ratio, irregular aneurysms, a lower spatial average WSS, and a higher maximum WSS may contribute to evaluating the risk of rupture of MCA aneurysms independent of patient characteristics., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Objective: Radiomics and morphological features were associated with aneurysms rupture. However, the multicentral study of their predictive power for specific-located aneurysms rupture is rare. We aimed to determine robust radiomics features related to middle cerebral artery (MCA) aneurysms rupture and evaluate the additional value of combining morphological and radiomics features in the classification of ruptured MCA aneurysms. Methods: A total of 632 patients with 668 MCA aneurysms (423 ruptured aneurysms) from five hospitals were included. Radiomics and morphological features of aneurysms were extracted on computed tomography angiography images. The model was developed using a training dataset (407 patients) and validated with the internal (152 patients) and external validation (73 patients) datasets. The support vector machine method was applied for model construction. Optimal radiomics, morphological, and clinical features were used to develop the radiomics model (R-model), morphological model (M-model), radiomics-morphological model (RM-model), clinical-morphological model (CM-model), and clinical-radiomics-morphological model (CRM-model), respectively. A comprehensive nomogram integrating clinical, morphological, and radiomics predictors was generated. Results: We found seven radiomics features and four morphological predictors of MCA aneurysms rupture. The R-model obtained an area under the receiver operating curve (AUC) of 0.822 (95% CI, 0.776, 0.867), 0.817 (95% CI, 0.744, 0.890), and 0.691 (95% CI, 0.567, 0.816) in the training, temporal validation, and external validation datasets, respectively. The RM-model showed an AUC of 0.848 (95% CI, 0.810, 0.885), 0.865 (95% CI, 0.807, 0.924), and 0.721 (95% CI, 0.601, 0.841) in the three datasets. The CRM-model obtained an AUC of 0.856 (95% CI, 0.820, 0.892), 0.882 (95% CI, 0.828, 0.936), and 0.738 (95% CI, 0.618, 0.857) in the three datasets. The CRM-model and RM-model outperformed the CM-model and M-model in the internal datasets (p < 0.05), respectively. But these differences were not statistically significant in the external dataset. Decision curve analysis indicated that the CRM-model obtained the highest net benefit for most of the threshold probabilities. Conclusion: Robust radiomics features were determined related to MCA aneurysm rupture. The RM-model exhibited good ability in classifying ruptured MCA aneurysms. Integrating radiomics features into conventional models might provide additional value in ruptured MCA aneurysms classification. [ABSTRACT FROM AUTHOR]