Analysis of independent risk factors for aneurysm rupture based on carotid tortuosity index and morphological parameters of single intracranial aneurysms in anterior circulation

医学 颈内动脉 动脉瘤 单变量分析 曲折 大脑前动脉 逐步回归 心脏病学 计算机断层血管造影 放射科 多元分析 血管造影 内科学 核医学 大脑中动脉 工程类 岩土工程 缺血 多孔性
作者
Yusong Pei,Zhiguo Wang,Shanhu Hao,Ruixian Wu,Xinxin Qiao,Guoxu Zhang
出处
期刊:Clinical Neurology and Neurosurgery [Elsevier BV]
卷期号:234: 107993-107993 被引量:2
标识
DOI:10.1016/j.clineuro.2023.107993
摘要

Our study focused on the risk factors associated with anterior circulation intracranial aneurysm (IA) rupture by examining the carotid artery (CA) tortuosity index (TI) and anterior circulation IA morphological parameters.This study conducted a retrospective analysis of clinical and imaging data from 163 patients with anterior circulation IA diagnosed by head and neck computed tomography angiography (CTA). The patients were categorized into two groups: the ruptured group (57 cases) and the unruptured group (106 cases). CA was categorized based on its location into three segments: the extracranial segment of the internal carotid artery (EICA) TI, the angle of the internal carotid artery (ICA) and the common carotid artery (CCA) TI. Measure the morphological parameters of all IA: IA length neck (L), IA height (H), aneurysm diameter width (D), the ratio of L to the mean diameter of the IA-bearing artery (SR), the ratio of H to D (AR), the angle of flow inflow (FA) and IA angle (AA). The study conducted five types of analysis to determine the risk factors for anterior circulation IA rupture. The first was an univariate analysis of the risk factors. The second was an analysis of the correlation between CA TI and IA morphological parameters. The third used multivariate logistic stepwise regression analysis to analyse independent risk factors for IA rupture. The fourth was to plot ROC curves to build a predictive model for IA rupture and calculate diagnostic thresholds. Finally, a data set from another hospital (78 cases) was used as a validation set to validate the multivariate model.Univariate analysis revealed that there were statistically significant differences (P < 0.05) in gender, EICA TI, location of IA and IA morphological parameters (FA, H, AR, L, SR), which acted as risk factors for anterior circulation IA rupture. The results of Spearman correlation analysis indicate that CCA TI is significantly correlated with SR, H and L (P < 0.05), while EICA TI is significantly correlated with FA and L (P < 0.05). The results of multivariate logistic analysis showed that FA (OR = 1.072, 95%CI = 1.04-1.10, P < 0.001), SR (OR = 4.949, 95%CI = 1.96-12.53, P = 0.001), EICA TI (OR = 1.037, 95%CI = 1.01-1.07, P = 0.003) were independent risk factors for IA rupture. The ROC curve plotting results suggest that the area under the curve (AUC) of FA is 0.860 with a diagnostic threshold of 110.1°; the AUC of SR is 0.786 with a diagnostic threshold of 1.67; the AUC of EICA TI is 0.723 with a diagnostic threshold of 28.845; the AUC of the three combined is 0.903 with a threshold of 0.480. The combined factor diagnostic model is validated according to the validation set, and the results show that the AUC (0.866) of the validation set is not much different from the AUC (0.903) of the multivariate model, and the multivariate model has a better diagnostic effect.In clinical practice, it is important to consider the evaluation of aneurysm rupture in combination with imaging, as FA, SR and ECIA TI are independent risk factors for IA rupture in the anterior circulation. Unlike the IA morphological parameters, EICA TI is an often overlooked extracranial parameter, but is equally important in its power to predict IA rupture. When the EICA TI exceeds 28.845, the IA has the possibility of rupture. Finally, multivariate diagnostic model are of interest when considering rupture of the anterior circulation IA.
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