Li YW, Jiao Y, Chen N, Gao Q, Chen YK, Zhang YF, Wen QP, Zhang ZM. How to select the quantitative magnetic resonance technique for subjects with fatty liver: A systematic review. World J Clin Cases 2022; 10(25): 8906-8921 [PMID: 36157636 DOI: 10.12998/wjcc.v10.i25.8906]
Corresponding Author of This Article
Zong-Ming Zhang, MD, PhD, Chief Doctor, Director, Professor, Department of General Surgery, Beijing Electric Power Hospital, State Grid Corporation of China, Capital Medical University, No. 1 Taipingqiaoxili, Fengtai District, Beijing 100073, China. zhangzongming@mail.tsinghua.edu.cn
Research Domain of This Article
Methodology
Article-Type of This Article
Systematic Reviews
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Clin Cases. Sep 6, 2022; 10(25): 8906-8921 Published online Sep 6, 2022. doi: 10.12998/wjcc.v10.i25.8906
How to select the quantitative magnetic resonance technique for subjects with fatty liver: A systematic review
You-Wei Li, Yang Jiao, Na Chen, Qiang Gao, Yu-Kun Chen, Yuan-Fang Zhang, Qi-Ping Wen, Zong-Ming Zhang
You-Wei Li, Yu-Kun Chen, Yuan-Fang Zhang, Qi-Ping Wen, Department of Radiology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China
Yang Jiao, Department of Rehabilitation Psychology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China
Na Chen, Department of Otorhinolaryngology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China
Qiang Gao, Department of Gastroenterology and Hepatology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China
Zong-Ming Zhang, Department of General Surgery, Beijing Electric Power Hospital, State Grid Corporation of China, Capital Medical University, Beijing 100073, China
Author contributions: Li YW and Jiao Y contributed equally to this study; Zhang ZM conceived and designed this study; Li YW, Jiao Y, Chen N, Gao Q and Chen YK drafted the manuscript; Zhang YF developed the search strategy; Wen QP provided statistical expertise; All authors contributed to developing the selection criteria, risk-of-bias assessment strategy, and data extraction criteria, they read, provided feedback, and approved the final manuscript.
Supported byBeijing Municipal Science and Technology Commission, No. Z171100000417056; and Key Support Project of Guo Zhong Health Care of China General Technology Group, No. SGGK202201001.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Zong-Ming Zhang, MD, PhD, Chief Doctor, Director, Professor, Department of General Surgery, Beijing Electric Power Hospital, State Grid Corporation of China, Capital Medical University, No. 1 Taipingqiaoxili, Fengtai District, Beijing 100073, China. zhangzongming@mail.tsinghua.edu.cn
Received: January 25, 2022 Peer-review started: January 25, 2022 First decision: May 9, 2022 Revised: May 25, 2022 Accepted: July 22, 2022 Article in press: July 22, 2022 Published online: September 6, 2022 Processing time: 213 Days and 0.2 Hours
Abstract
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.
Core Tip: This study focused on properly selecting commonly used quantitative magnetic resonance (MR) techniques to quantify fatty liver disease. 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. Three techniques including spectroscopy, two-point Dixon imaging, and multiple-point Dixon imaging, were compared. We found that proton density fat fraction derived from multiple-point Dixon imaging is a noninvasive method for accurate quantitative measurement of hepatic fat content. It can be used to diagnose fatty liver disease and monitor disease progression as well as treatment effects.