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

机译:甲状腺结节区分优化微血管成像的诊断准确性:系统审查和元分析的方案

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摘要

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.
机译:背景:超声检查是目前甲状腺癌临床诊断和分化的首选。然而,由于甲状腺结节图的复杂性和重叠性,它仍然难以准确地识别具有非典型超声特性的结节。以前的研究表明,极好的微血管成像(SMI)可以检测肿瘤新生血管,以区分恶性甲状腺结节。然而,这些研究的结果具有低样本尺寸的矛盾。该荟萃分析测试了SMI在区分良性和恶性甲状腺结节中的准确性的假设。方法:我们将在没有语言限制的情况下将PubMed,Cochrane图书馆和中国生物医学数据库中搜索PubMed,Cochrane图书馆和中国生物医学数据库。两位作者将独立地开展搜索文献记录,扫描标题和摘要,全文,收集数据和评估偏差风险。查看Manager 5.2和Stata14.0软件((Stata Corp,College Station,TX)将用于数据分析。结果:该系统审查将确定SMI在区分甲状腺结节时的准确性。结论:其调查结果将提供有用的证据SMI在区分甲状腺结节中的准确性。

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