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| The predictive value of morphological and radiomics-derived features in the rupture of middle cerebral artery mirror aneurysms |
| WANG Hao, ZHOU Jiafeng, LIN Boli, CHEN Yongchun |
| Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325015, China |
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WANG Hao,ZHOU Jiafeng,LIN Boli, et al. The predictive value of morphological and radiomics-derived features in the rupture of middle cerebral artery mirror aneurysms[J]. JOURNAL OF WEZHOU MEDICAL UNIVERSITY, 2022, 52(2): 121-125.
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Abstract bjective: To investigate the predicting value of morphological and radiomics-derived feature logistic model in the rupture of middle cerebral artery mirror aneurysm. Methods: Totally 38 patients with middle cerebral artery mirror aneurysms (one side ruptured and one side unruptured) in the First Affiliated Hospital of Wenzhou Medical University from May 2010 to October 2020 were retrospectively analyzed. In the pairing of ruptured and unruptured mirror aneurysms, 7 morphological parameters were measured using CTA, and 12 radiomics-derived morphological parameters were extracted using Pyradiomics. Univariate analysis was used to select the related factors of aneurysm rupture. Logistic regression model for predicting the rupture of the middle cerebral artery mirror aneurysms was established based on morphological features, radiomics-derived features and morphological features combined with radiomics-derived features. Receiver operating characteristic curve and area under curve were used to evaluate the predictive performance of the model. Results: After univariate analysis, 7 morphological parameters (including aneurysm size, perpendicular height, aneurysm height, aneurysm neck size, aspect radio, size radio and aneurysm shape) and 6 radiomics-derived parameters (including Maximum3DDiameter, Maxium2DDiameterSlice, Maximum2DDiameterColumn, Maximun2DDiameterRow, SurfaceArea and SurfaceVolumeRatio) were selected. The results of the ROC curve were as follows: The AUC of combined model was 0.85, which was higher than that of morphological model (AUC=0.83) and radiomics model (AUC=0.71).Conclusion: Logistic regression model based on morphological and radiomics-derived features may be helpful in assessing the risks of middle cerebral artery aneurysm rupture independent of individual patient’s characteristics.
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. [J]. JOURNAL OF WEZHOU MEDICAL UNIVERSITY, 2022, 52(9): 762-763. |
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