Evidence map›Paper›PMID 36157636›Full record

ArticleWorld journal of clinical cases2022

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

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Article in World journal of clinical cases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

You-Wei LiDepartment of Radiology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China.
Yang JiaoDepartment of Rehabilitation Psychology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China.
Na ChenDepartment of Otorhinolaryngology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China.
Qiang GaoDepartment of Gastroenterology and Hepatology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China.
Yu-Kun ChenDepartment of Radiology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China.
Yuan-Fang ZhangDepartment of Radiology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China.
Qi-Ping WenDepartment of Radiology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China.
Zong-Ming ZhangDepartment of General Surgery, Beijing Electric Power Hospital, State Grid Corporation of China, Capital Medical University, Beijing 100073, China. zhangzongming@mail.tsinghua.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEarly 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.

aimTo provide information for the proper selection of commonly used quantitative MR techniques to quantify fatty liver.

methodsWe 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

resultsForty 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.

conclusionThe 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.

Indexed as

1H-magnetic resonance spectroscopyFatty liverHepatic fat contentMultiple-point Dixon imagingTwo-point Dixon imaging

Identifiers

PMID36157636
PMCPMC9477046

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