The diagnostic accuracy of superb microvascular imaging in distinguishing thyroid nodules: A protocol for systematic review and meta analysis

Background: Ultrasonography is the first choice for clinical diagnosis and differentiation of thyroid cancer Currently. However, due to the complexity and overlapping nature of the thyroid nodule sonograms, it remains difficult to accurately identify nodules with atypical ultrasound characteristics....

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Veröffentlicht in:Medicine (Baltimore) 2020-10, Vol.99 (40), p.e22350-e22350
Hauptverfasser: Tian, Congliang, Wang, Zinan, Hou, Xiukun, Wang, Cong
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Sprache:eng
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Zusammenfassung:Background: Ultrasonography is the first choice for clinical diagnosis and differentiation of thyroid cancer Currently. However, due to the complexity and overlapping nature of the thyroid nodule sonograms, it remains difficult to accurately identify nodules with atypical ultrasound characteristics. Previous studies showed that superb microvascular imaging (SMI) can detect tumor neovascularization to differentiate benign from malignant thyroid nodules. However, the results of these studies have been contradictory with low sample sizes. This meta-analysis tested the hypothesis that SMI is accurate in distinguishing benign and malignant thyroid nodules. Methods: We will search PubMed, Web of Science, Cochrane Library, and Chinese biomedical databases from their inceptions to the August 20, 2020, without language restrictions. Two authors will independently carry out searching literature records, scanning titles and abstracts, full texts, collecting data, and assessing risk of bias. Review Manager 5.2 and Stata14.0 software ((Stata Corp, College Station, TX) will be used for data analysis. Results: This systematic review will determine the accuracy of SMI in distinguishing thyroid nodules. Conclusion: Its findings will provide helpful evidence for the accuracy of SMI in in distinguishing thyroid nodules. Systematic review registration: INPLASY202080084
ISSN:0025-7974
1536-5964
DOI:10.1097/MD.0000000000022350