Tian Congliang, Wang Zinan, Hou Xiukun, Wang Cong
Pediatrics Department of the First Affiliated Hospital of Dalian Medical University.
Nutrition Department of the First Affiliated Hospital of Dalian Medical University.
Medicine (Baltimore). 2020 Oct 2;99(40):e22350. doi: 10.1097/MD.0000000000022350.
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.
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.
This systematic review will determine the accuracy of SMI in distinguishing thyroid nodules.
Its findings will provide helpful evidence for the accuracy of SMI in in distinguishing thyroid nodules.Systematic review registration: INPLASY202080084.
超声检查是目前甲状腺癌临床诊断与鉴别诊断的首选方法。然而，由于甲状腺结节超声图像的复杂性和重叠性，准确识别具有非典型超声特征的结节仍然困难。既往研究表明，超微血管成像（SMI）能够检测肿瘤新生血管，以鉴别甲状腺良恶性结节。然而，这些研究结果相互矛盾，且样本量较小。本荟萃分析检验了SMI在鉴别甲状腺良恶性结节方面准确这一假设。
我们将检索PubMed、科学网、Cochrane图书馆以及中国生物医学数据库，检索时间从建库至2020年8月20日，无语言限制。两名作者将独立进行文献记录检索、标题和摘要筛选、全文筛选、数据收集以及偏倚风险评估。将使用Review Manager 5.2和Stata14.0软件（Stata公司，德克萨斯州大学城）进行数据分析。
本系统评价将确定SMI在鉴别甲状腺结节方面的准确性。
其研究结果将为SMI在鉴别甲状腺结节方面的准确性提供有益证据。系统评价注册：INPLASY202080084。
