How to select the quantitative magnetic resonance technique for subjects with fatty liver: A systematic review

WORLD JOURNAL OF CLINICAL CASES(2022)

引用 0|浏览6
暂无评分
摘要
BACKGROUND Early quantitative assessment of liver fat content is essential for patients with fatty liver disease. Mounting evidence has shown that magnetic resonance (MR) technique has high accuracy in the quantitative analysis of fatty liver, and is suitable for monitoring the therapeutic effect on fatty liver. However, many packaging methods and postprocessing functions have puzzled radiologists in clinical applications. Therefore, selecting a quantitative MR imaging technique for patients with fatty liver disease remains challenging. AIM To provide information for the proper selection of commonly used quantitative MR techniques to quantify fatty liver. METHODS We completed a systematic literature review of quantitative MR techniques for detecting fatty liver, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol. Studies were retrieved from PubMed, Embase, and Cochrane Library databases, and their quality was assessed using the Quality Assessment of Diagnostic Studies criteria. The Reference Citation Analysis database (https:// www.referencecitationanalysis.com) was used to analyze citation of articles which were included in this review. RESULTS Forty studies were included for spectroscopy, two-point Dixon imaging, and multiple-point Dixon imaging comparing liver biopsy to other imaging methods. The advantages and disadvantages of each of the three techniques and their clinical diagnostic performances were analyzed. CONCLUSION The proton density fat fraction derived from multiple-point Dixon imaging is a noninvasive method for accurate quantitative measurement of hepatic fat content in the diagnosis and monitoring of fatty liver progression.
更多
查看译文
关键词
Fatty liver, Hepatic fat content, H-1-magnetic resonance spectroscopy, Multiple-point Dixon imaging, Two-point Dixon imaging
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