Ultrasound Department of the First Affiliated Hospital of Dalian Medical University, Liaoning Province, China.
Medicine (Baltimore). 2021 Jan 22;100(3):e24411. doi: 10.1097/MD.0000000000024411.
Superb microvascular imaging (SMI) is a new ultrasound vascular imaging technology, which uses a new Doppler algorithm, it has the characteristics of high sensitivity and high resolution to detect low velocity blood flow; it is easier to detect microvessels with low-velocity flow compared with color Doppler flow imaging in theory; and it can image the microvessels of the lesion without angiography.[1] Previous studies showed that SMI can detect tumor neovascularization to differentiate benign from malignant focal liver lessions (FLLs). 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 FLLs.
We will search PubMed, Web of Science, Cochrane Library, and Chinese biomedical databases from their inceptions to the November 30, 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 will be used for data analysis.
This systematic review will determine the accuracy of SMI in the differential diagnosis between benign and malignant FLLs.
Its findings will provide helpful evidence for the accuracy of SMI in the differential diagnosis between benign and malignant FLLs.
INPLASY2020120081.
Superb 微血管成像(SMI)是一种新的超声血管成像技术,它使用新的多普勒算法,具有高灵敏度和高分辨率来检测低速血流的特点;与彩色多普勒血流成像相比,它在理论上更容易检测到低速血流的微血管;并且可以对无造影的病变微血管进行成像。[1]先前的研究表明,SMI 可以检测肿瘤新生血管,从而区分良性和恶性局灶性肝脏病变(FLL)。然而,这些研究的结果因样本量小而相互矛盾。本荟萃分析检验了 SMI 准确区分良性和恶性 FLL 的假设。
我们将从成立之初到 2020 年 11 月 30 日,在 PubMed、Web of Science、Cochrane 图书馆和中国生物医学数据库中搜索文献,不限制语言。两位作者将独立进行搜索文献记录、扫描标题和摘要、全文、收集数据和评估偏倚风险。使用 Review Manager 5.2 和 Stata14.0 软件进行数据分析。
本系统评价将确定 SMI 在鉴别良性和恶性 FLL 中的准确性。
其研究结果将为 SMI 在鉴别良性和恶性 FLL 中的准确性提供有价值的证据。
INPLASY2020120081。