Evidence map›Paper›PMID 39621041›Full record

ArticlePediatric radiology2025

Multi-parameter quantitative magnetic resonance imaging for early detecting skeletal muscle involvement and predicting functional decline in children with Becker muscular dystrophy.

Fei Peng, Huayan Xu, Ting Xu, Ke Xu, Xiaotang Cai, Deqiu Tang, Shuhao Li, Jiaoyang Li, Weipeng Qing, Shuai Liu and 3 more

Abstract read
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In one paragraph

Article in Pediatric radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Fei PengDepartment of Radiology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Chuanshan Road No. 69, 421001, Hengyang, China.
Huayan XuDepartment of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, 20# Section 3 South Renmin Road, 610041, Chengdu, China.
Ting XuDepartment of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, 20# Section 3 South Renmin Road, 610041, Chengdu, China.
Ke XuDepartment of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, 20# Section 3 South Renmin Road, 610041, Chengdu, China.
Xiaotang CaiDepartment of Pediatrics Neurology, West China Second University Hospital, Sichuan University, Chengdu, China.
Deqiu TangDepartment of Radiology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Chuanshan Road No. 69, 421001, Hengyang, China.
Shuhao LiDepartment of Medical Imaging Center, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Jiaoyang LiDepartment of Occupational and Environmental Health, School of Public Health, Wuhan University, Wuhan, China.
Weipeng QingDepartment of Radiology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Chuanshan Road No. 69, 421001, Hengyang, China.
Shuai LiuDepartment of Radiology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Chuanshan Road No. 69, 421001, Hengyang, China.
Limin LiuDepartment of Ultrasound, The Second Affiliated Hospital, Hengyang Medical School, University of South China, Jiefang Road No. 35, 421001, Hengyang, China. 897418569@qq.com.
Yingkun GuoDepartment of Radiology, Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, 20# Section 3 South Renmin Road, 610041, Chengdu, China. gykpanda@163.com.
Heng ZhaoDepartment of Radiology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Chuanshan Road No. 69, 421001, Hengyang, China. angerh9@126.com.

Funding

Health Research Project of Hunan Provincial Health Commission 202109010099Health Research Project of Hunan Provincial Health Commission D202309017771Hunan Provincial Natural Science Foundation of China 2023JJ30552The College Student Innovation and Entrepreneurship Training Project of the University of South China 20200021001the Scientific Research Project of Department of Education of Hunan Province 20A437
6 · The paper itself

Abstract

backgroundThe extreme clinical heterogeneity of children with Becker muscular dystrophy significantly poses a great challenge to accurately assess their disease status.

objectiveTo detect skeletal muscle involvement in children with Becker muscular dystrophy using multiple-parameter quantitative magnetic resonance imaging (qMRI), and to determine the preferred muscle site and qMRI biomarker. MATERIALS AND

methodsFat fraction, T1, and T2 measurements were conducted in Becker muscular dystrophy (n=29) and healthy controls (n=23). North Star Ambulatory Assessment (NSAA) was performed in Becker muscular dystrophy. Group differences were compared by using the Mann-Whitney or Kruskal-Wallis test or a linear mixed-effect model. Receiver operating characteristic analysis with area under curve (AUC) was used to compare the diagnostic performance. Logistic regression was used to identify the predictor of functional decline.

resultsBoth fat fraction and T2 were effective in detecting muscle involvement across different functional stages that were categorized by NSAA, with fat fraction in gluteus maximus demonstrating the most superior diagnostic performance (AUC range, 0.85-0.98). The combination of T2 and T1 enables a good diagnosis of no abnormal fat-infiltrated muscles (AUC=0.82). Overall, fat fraction in gluteus maximus exhibited the strongest negative correlation with the NSAA score (r=-0.69, P<0.01) and emerged as an independent risk factor for functional decline (odds ratio=1.12, P=0.02).

conclusionMulti-parametric qMRI demonstrate effective capabilities for early detection of muscle involvement, with gluteus maximus being the preferred muscle site. Fat fraction in gluteus maximus may serve as a potential biomarker for predicting functional decline.

Indexed as

Magnetic Resonance ImagingMuscle, SkeletalMuscular Dystrophy, DuchenneAdolescentChildChild, PreschoolEarly DiagnosisFemaleHumansMaleBecker muscular dystrophyChildrenFunctional declineQuantitative magnetic resonance imagingSkeletal muscle

Identifiers

PMID39621041

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.