谷歌浏览器插件
订阅小程序
在清言上使用

Endoscopic ultrasound elastography for differentiation of benign and malignant pancreatic masses: a systemic review and meta-analysis.

EUROPEAN JOURNAL OF GASTROENTEROLOGY & HEPATOLOGY(2013)

引用 41|浏览15
暂无评分
摘要
Background Endoscopic ultrasound (EUS) elastography is a novel method for visualization of tissue elasticity modulus during a conventional EUS examination. The reported yield of EUS elastography for the differentiation of benign and malignant pancreatic masses has shown variable results. The objective of this study was to assess the accuracy of EUS elastography by pooling data of available trials. Methods The Medline, PubMed, Embase, and Cochrane Central Trials databases were used to retrieve all the studies that assessed the diagnostic accuracy of EUS elastography for the differentiation of benign and malignant pancreatic masses. Pooling was carried out using a fixed-effect model when significant heterogeneity was not present; otherwise, the random-effect model was used. If there were less than four studies using the same diagnostic standard, forest plots were constructed without pooling. Results In six studies using the qualitative color pattern as the diagnostic standard, the sensitivity was 99% (95% confidence interval 98-100%) and the specificity was 74% (95% confidence interval 65-82%). The area under the curve under the summary receiver-operating characteristic was 0.9624. In three studies using the quantitative hue histogram value as the diagnostic standard, the sensitivity was 85-93% and the specificity was 64-76%. Conclusion EUS elastography is a promising noninvasive technique for the differentiation of pancreatic masses with a high sensitivity, and may prove to be a valuable complementary method to EUS-FNA. Eur J Gastroenterol Hepatol 25:218-224 (C) 2013 Wolters Kluwer Health vertical bar Lippincott Williams & Wilkins. European Journal of Gastroenterology & Hepatology 2013, 25:218-224
更多
查看译文
关键词
diagnosis,differentiation,endoscopic ultrasound elastography,pancreatic mass
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要