Superb microvascular imaging for distinguishing thyroid nodules

Abstract

Abstract. Background:. Earlier studies have shown that the superb microvascular imaging (SMI) can detect tumor angiogenesis to distinguish thyroid nodules, but there is no systematic review. This meta-analysis aimed to identify the accuracy of ultrasound SMI for the diagnosis of thyroid nodules. Methods:. We searched PubMed, Cochrane Library, and CBM databases. A meta-analysis was conducted using STATA version 14.0 and Meta-Disc version 1.4 software. We calculated the summary statistics for sensitivity, specificity, positive and negative likelihood ratio (LR+/LR−), diagnostic odds ratio, and the synthetic receiver operating characteristic curve. Data will be pooled by either a fixed-effects model or a random-effects model according to the results of heterogeneity identification. Results:. 11 studies that met the inclusion criteria were included in this meta-analysis. The quality assessment of the study of diagnostic accuracy studies scores of all included studies were ≥22. A total of 1003 thyroid malignant nodules and 957 thyroid benign nodules were assessed. The main outcome included: the pooled sensitivity was 0.81 (95% confidence intervals (CI) = 0.79–0.84), and the pooled specificity was 0.86 (95% CI = 0.84–0.88); the pooled LR+ was 5.79 (95% CI = 4.44–7.54), and the pooled negative LR− was 0.23 (95% CI = 0.20–0.26); the pooled diagnostic odds ratio of SMI in the diagnosis of thyroid nodules was 26.84 (95% CI = 19.13–37.60). The area under the synthetic receiver operating characteristic curve was 0.89 (95% CI = 0.86–0.91). We found no evidence for publication bias (t = 0.72, P = .49). Conclusion:. Our meta-analysis indicates that SMI may have high diagnostic accuracy in distinguishing benign and malignant thyroid nodules. Systematic review registration:. INPLASY202080084.