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Background: Determining the rupture risk of unruptured intracranial aneurysm is crucial for treatment strategy. The purpose of this study was to predict the rupture risk of middle cerebral artery (MCA) aneurysms using a machine learning technique. Methods: We retrospectively reviewed 403 MCA aneurysms and randomly partitioned them into the training and testing datasets with a ratio of 8:2. A generalized linear model with logit link was developed using training dataset to predict the aneurysm rupture risk based on the clinical variables and morphological features manually measured from computed tomography angiography. To facilitate the clinical application, we further constructed an easy-to-use nomogram based on the developed model. Results: Ruptured MCA aneurysm had larger aneurysm size, aneurysm height, perpendicular height, aspect ratio, size ratio, bottleneck factor, and height-width ratio. Presence of a daughter-sac was more common in ruptured than in unruptured MCA aneurysms. Six features, including aneurysm multiplicity, lobulations, size ratio, bottleneck factor, height-width ratio, and aneurysm angle, were adopted in the model after feature selection. The model achieved a relatively good performance with areas under the receiver operating characteristic curves of 0.77 in the training dataset and 0.76 in the testing dataset. The nomogram provided a visual interpretation of our model, and the rupture risk probability of MCA aneurysms can be directly read from it. Conclusion: Our model can be used to predict the rupture risk of MCA aneurysm. [ABSTRACT FROM AUTHOR]

Objectives: Anterior communicating artery (ACOM) aneurysms are the most common intracranial aneurysms, and predicting their rupture risk is challenging. We aimed to predict this risk using a two-layer feed-forward artificial neural network (ANN).Materials and Method: 594 ACOM aneurysms, 54 unruptured and 540 ruptured, were reviewed. A two-layer feed-forward ANN was designed for ACOM aneurysm rupture-risk analysis. To improve ANN efficiency, an adaptive synthetic (ADASYN) sampling approach was applied to generate more synthetic data for unruptured aneurysms. Seventeen parameters (13 morphological parameters of ACOM aneurysm measured from these patients' CT angiography (CTA) images, two demographic factors, and hypertension and smoking histories) were adopted as ANN input.Results: Age, vessel size, aneurysm height, perpendicular height, aneurysm neck size, aspect ratio, size ratio, aneurysm angle, vessel angle, aneurysm projection, A1 segment configuration, aneurysm lobulations and hypertension were significantly different between the ruptured and unruptured groups. Areas under the ROC curve for training, validating, testing and overall data sets were 0.953, 0.937, 0.928 and 0.950, respectively. Overall prediction accuracy for raw 594 samples was 94.8 %.Conclusion: This ANN presents good performance and offers a valuable tool for prediction of rupture risk in ACOM aneurysms, which may facilitate management of unruptured ACOM aneurysms.Key Points: • A feed-forward ANN was designed for the prediction of rupture risk in ACOM aneurysms. • Two demographic parameters, 13 morphological aneurysm parameters, and hypertension/smoking history were acquired. • An ADASYN sampling approach was used to improve ANN quality. • Overall prediction accuracy of 94.8 % for the raw samples was achieved. [ABSTRACT FROM AUTHOR]

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. 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. 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. 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. [ABSTRACT FROM AUTHOR]