超声造影对颈动脉粥样硬化斑块内新生血管诊断试验Meta分析

摘要

目的 研究超声造影用于颈动脉粥样硬化斑块诊断的精确性.方法 计算机检索The Cochrane Library(2016年第3期)、EMbase及PubMed,收集采用超声造影与金标准(病理活检)比较诊断颈动脉粥样硬化斑块的诊断性试验,检索时限均为从1982年至2016年11月.由2位研究者根据纳入与排除标准独立筛选文献、提取资料,纳入研究包括斑块内新生血管的诊断与组织学标本的定量分析和/或发生斑块相关症状的目测比较,参数评价包括斑块和斑块超声造影定量超声强度及视觉分级;对敏感性(SEN)、特异性(SPE)、阳性似然比(+LR)、阴性似然比(-LR)、诊断比值比(DOR)进行异质性检验和合并分析.采用随机效应进行似然比、诊断比值比的Meta分析,并根据受试者工作曲线特征计算曲线下面积.结果 最终纳入7个研究,507例患者,Meta分析结果显示:SEN合并=0.68,95%CI:0.63~0.73;SPE合并=0.78,95%CI:0.72~0.84;+LR=2.92,95%CI:1.60~5.33;-LR=0.34,95%CI:0.19~0.61;DOR合并=9.47,95%CI:3.33~26.95;AUC=0.8346.结论 超声造影对颈动脉粥样硬化斑块有较高的敏感性、较高的特异性,可作为诊断颈动脉粥样硬化斑块有效可行的方法.%Objective To study the clinical value of contrast enhanced ultrasound (CEUS) for diagnosing carotid atherosclerotic plaque. Methods We searched the databases including The Cochrane Library (Issue 3, 2016), EMbase, PubMed for diagnostic tests on carotid atherosclerotic plaque diagnosed with CEUS vs. with pathological biopsy or systemic (golden standard) from 1982 to the November, 2016. Two reviewers independently screened literature according to the inclusion and exclusion criteria, extracted data, and assessed the methodological quality of the included studies according to (Quality Assessment of Diagnostic Accuracy Studies, QUADAS) items. The Meta-DiSc software (version 1.4) was used to conduct pooling on sensitivity, specificity, positive likelihood radio, and negative likelihood radio. Heterogeneity test was performed and the summary receiver operating characteristic curve (SROC) was drawn for area under the curve (AUC). Results A total of 7 studies involving 507 patients were included. The results of meta-analysis showed that, SEN, SPE, +LR, -LR and DOR were (0.68, 95%CI: 0.63~0.73), (0.78, 95%CI: 0.72~0.84), (3.16, 95%CI: 0.93~10.72), (0.34, 95%CI: 0.19~0.61) and (9.47, 95%CI: 3.33~26.95), respectively. The AUC of SROC curve was 0.8346. Conclusion Current evidence shows that CEUS is a promising noninvasive diagnostic modality for detecting intra-plaque neovascularization. Standardization of quantitative analysis and visual grading classification is needed to increase reliability and reduce technical heterogeneity.