Qualitative and quantitative wall enhancement associated with unstable intracranial aneurysms: a meta-analysis

医学 科克伦图书馆 荟萃分析 接收机工作特性 磁共振成像 科学网 动脉瘤 放射科 内科学
作者
Guizhi Xu,Ning Luo,Yuhui Deng
出处
期刊:Acta Radiologica [SAGE]
卷期号:64 (5): 1974-1984 被引量:2
标识
DOI:10.1177/02841851221141238
摘要

Background Unstable intracranial aneurysms (UIAs) are more likely to rupture and cause serious consequences. Evaluating the stability of unruptured aneurysms facilitates clinical management stratification. Purpose To compare and evaluate the predictive performance of qualitative and quantitative wall enhancement (aneurysmal wall enhancement [AWE], circumferential aneurysmal wall enhancement [CAWE], wall enhancement ratio [WER]) on high-resolution magnetic resonance imaging (MRI) of the vessel wall to predict the presence of UIA. Material and Methods Original articles describing the depiction of aneurysmal wall enhancement on 3.0-T or 1.5-T high-resolution vessel wall imaging were retrieved from the Web of Science, Medline/PubMed, the Cochrane Library, and EMBASE databases up to 15 February 2022. The combined sensitivity, specificity, and summary area under the receiver operating characteristic curve (AUC) were calculated, and meta-regression analysis was performed. Results In total, 12 original articles involving 1619 intracranial aneurysms (IAs) were included. The combined sensitivity and specificity of AWE, CAWE, and WER were 91% and 67%, 59% and 83%, and 86% and 75%, respectively, in the diagnosis of UIA. The summary AUC values of these items were, in order from high to low, 0.88 (WER), 0.84 (AWE), and 0.77 (CAWE), and the differences among them were significant ( z = 2.976, P = 0.003 and z = 2.950, P = 0.003). The meta-regression analysis identified average size and 2D/3D magnetic imaging technology as possible sources of heterogeneity. Conclusion Qualitative and quantitative wall enhancement showed moderate accuracy in predicting UIA, and WER had the highest accuracy among them in this meta-analysis. Two covariates were found to explain the heterogeneity.
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