Original Research ARTICLE
A simple scoring model for prediction of rupture risk of anterior communicating artery aneurysms
- 1Department of Radiology, Xinqiao Hospital, Third Military Medical University, Xinqiao Hospital, China
- 2Department of Radiology, Xinqiao Hospital, Third Military Medical University, China
- 3Department of Radiology, Xinqiao Hospital, Third Military Medical University, China
Background: The rupture risk of anterior communicating artery aneurysms (ACoAAs) has been known to be higher than those of the other locations. Thus, the aim of this study was to investigate the clinical and morphological characteristics associated with risk factors for the rupture of ACoAAs.
Methods: A total of 361 consecutive patients with 361 ACoAAs between August 2011 and December 2017 were retrospectively reviewed. Patients and ACoAAs were divided into rupture and unrupture groups. In addition to clinical characteristics, ACoAAs characteristics were evaluated by CT angiography (CTA). Multiple logistic regression analysis was used to identify the independent risk factors associated with ACoAAs rupture. The assigning score of these variables depends on the β coefficient. Receiver operating characteristic (ROC) curve analysis was used to calculate the optimal thresholds.
Results: Multiple logistic regression model revealed that A1 dominant (odds ratio (OR) 3.034), irregular shape (OR 3.358) and aspect ratio (AR, OR 3.163) positively increased the risk of rupture, while cerebral atherosclerosis (OR 0.080) and mean diameters (OR 0.474) were negatively correlated with rupture. Incorporating these 5 factors, ROC analysis revealed that the threshold value of the multi-factors was 1, the sensitivity was 88.3%, and the specificity was 66.0%.
Conclusions: The scoring model is a sample method which based on A1 dominant, irregular shape, aspect ratio, cerebral atherosclerosis and mean diameters on CTA is of great value in the prediction of rupture risk of ACoAAs.
Keywords: Anterior communicating artery aneurysms, Risk factors, Patient characteristics, Morphological parameter, Predictive scoring model, CTA (Computed Tomographic Angiography)
Received: 15 Feb 2019;
Accepted: 01 May 2019.
Edited by:Diogo C. Haussen, Emory University, United States
Reviewed by:Karl A. Kasischke, University of South Florida, United States
Mário D. Faria, Hospital de Clínicas de Porto Alegre, Brazil
Copyright: © 2019 Wang, Wang, Liu, Gong, Zhang, Yang and Wen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: MD. Li Wen, Department of Radiology, Xinqiao Hospital, Third Military Medical University, Chongqing, China, firstname.lastname@example.org