Evidence map›Paper›PMID 33219846›Full record

ArticleEuropean radiology2021

Global versus individual muscle segmentation to assess quantitative MRI-based fat fraction changes in neuromuscular diseases.

Harmen Reyngoudt, Benjamin Marty, Jean-Marc Boisserie, Julien Le Louër, Cedi Koumako, Pierre-Yves Baudin, Brenda Wong, Tanya Stojkovic, Anthony Béhin, Teresa Gidaro and 4 more

2 registry-linked trialsAbstract read
PubMed Publisher
In one paragraph

Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
3.1field-weighted citation impact, top 7% of its field
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.

NCT05618080 active not recruitingnot on this mapstarted 2024, after this paper: background citation

GRASP-01-003: Trial Readiness and Endpoint Assessment in LGMD R1

TypeobservationalSponsorVirginia Commonwealth UniversityRan2024 to 2028Enrolled100ConditionsCalpain-3 Deficiency Limb Girdle Muscular Dystrophy Type 2A, Limb Girdle Muscular Dystrophy, Limb Girdle Muscular Dystrophy Type R1, LGMD2A
NCT05989620 recruitingnot on this mapstarted 2023, after this paper: background citation

Long-Term Development of Muscular Dystrophy Outcome Assessments (GRASP-01-005)

TypeobservationalSponsorVirginia Commonwealth UniversityRan2023 to 2029Enrolled1,000ConditionsLGMD1B, LGMD1C, LGMD1D, LGMD1E
3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 35 citations in OpenAlex.

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  14. Journal of orthopaedic translation · 2023
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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

14 authors at 4 institutions in 4 countries.

Harmen ReyngoudtNMR Laboratory, Neuromuscular Investigation Center, Institute of Myology, Paris, France. h.reyngoudt@institut-myologie.org.ORCID http://orcid.org/0000-0002-0777-2711
Benjamin MartyNMR Laboratory, Neuromuscular Investigation Center, Institute of Myology, Paris, France.
Jean-Marc BoisserieNMR Laboratory, Neuromuscular Investigation Center, Institute of Myology, Paris, France.
Julien Le LouërNMR Laboratory, Neuromuscular Investigation Center, Institute of Myology, Paris, France.
Cedi KoumakoNMR Laboratory, Neuromuscular Investigation Center, Institute of Myology, Paris, France.
Pierre-Yves BaudinConsultants for Research in Imaging and Spectroscopy, Tournai, Belgium.
Brenda WongDepartment of Neurology, Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, USA.
Tanya StojkovicNeuromuscular Reference Center, Institute of Myology, Pitié-Salpêtrière Hospital (AP-HP), Paris, France.
Anthony BéhinNeuromuscular Reference Center, Institute of Myology, Pitié-Salpêtrière Hospital (AP-HP), Paris, France.
Teresa GidaroI-Motion - Pediatric Clinical Trials Department, Trousseau Hospital (AP-HP), Paris, France.
Yves AllenbachDepartment of Internal Medicine and Clinical Immunology, University Pierre et Marie Curie, AP-HP, GH Pitié-Salpêtrière, Paris, France.
Olivier BenvenisteDepartment of Internal Medicine and Clinical Immunology, University Pierre et Marie Curie, AP-HP, GH Pitié-Salpêtrière, Paris, France.
Laurent ServaisI-Motion - Pediatric Clinical Trials Department, Trousseau Hospital (AP-HP), Paris, France.
Pierre G CarlierNMR Laboratory, Neuromuscular Investigation Center, Institute of Myology, Paris, France.
Commissariat à l'Énergie Atomique et aux Énergies Alternatives · FRSorbonne Université · FRCincinnati Children's Hospital Medical Center · USUniversity of Liège · BE

Funding

BioMarin Pharmaceutical NCT01753804FP7 Bioimage-NMDJain Foundation NCT01676077Roche NCT0239183
6 · The paper itself

Abstract

objectivesMagnetic resonance imaging (MRI) constitutes a powerful outcome measure in neuromuscular disorders, yet there is a broad diversity of approaches in data acquisition and analysis. Since each neuromuscular disease presents a specific pattern of muscle involvement, the recommended analysis is assumed to be the muscle-by-muscle approach. We, therefore, performed a comparative analysis of different segmentation approaches, including global muscle segmentation, to determine the best strategy for evaluating disease progression.

methodsIn 102 patients (21 immune-mediated necrotizing myopathy/IMNM, 21 inclusion body myositis/IBM, 10 GNE myopathy/GNEM, 19 Duchenne muscular dystrophy/DMD, 12 dysferlinopathy/DYSF, 7 limb-girdle muscular dystrophy/LGMD2I, 7 Pompe disease, 5 spinal muscular atrophy/SMA), two MRI scans were obtained at a 1-year interval in thighs and lower legs. Regions of interest (ROIs) were drawn in individual muscles, muscle groups, and the global muscle segment. Standardized response means (SRMs) were determined to assess sensitivity to change in fat fraction (ΔFat%) in individual muscles, muscle groups, weighted combinations of muscles and muscle groups, and in the global muscle segment.

resultsGlobal muscle segmentation gave high SRMs for ΔFat% in thigh and lower leg for IMNM, DYSF, LGMD2I, DMD, SMA, and Pompe disease, and only in lower leg for GNEM and thigh for IBM.

conclusionsGlobal muscle segment Fat% showed to be sensitive to change in most investigated neuromuscular disorders. As compared to individual muscle drawing, it is a faster and an easier approach to assess disease progression. The use of individual muscle ROIs, however, is still of interest for exploring selective muscle involvement. KEY POINTS: • MRI-based evaluation of fatty replacement in muscles is used as an outcome measure in the assessment of 1-year disease progression in 8 different neuromuscular diseases. • Different segmentation approaches, including global muscle segmentation, were evaluated for determining 1-year fat fraction changes in lower limb skeletal muscles. • Global muscle segment fat fraction has shown to be sensitive to change in lower leg and thigh in most of the investigated neuromuscular diseases.

Indexed as

Muscular Dystrophies, Limb-GirdleNeuromuscular DiseasesAdipose TissueHumansMagnetic Resonance ImagingMusclesMuscle, SkeletalThighAdipose tissueMagnetic resonance imagingNeuromuscular diseasesOutcome measuresSkeletal muscle

Identifiers

PMID33219846
OpenAlexW3100736633

What OpenQuestion holds

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Registered trials

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 OpenQuestion graph.