Evidence map›Paper›PMID 40293996›Full record

ArticlePloS one2025

Multi-parametric quantitative MRI of the lower limb muscles in a longitudinal study of limb-girdle muscular dystrophy R9.

Susanne S Rauh, Pierre-Yves Baudin, Tanya Stojkovic, Simone Birnbaum, Valérie Decostre, Rachida-Lydie Zanfongnon, Yves Fromes, Melissa T Hooijmans, Gustav J Strijkers, Jean-Yves Hogrel and 3 more

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

13 authors.

Susanne S RauhInstitute of Myology, Neuromuscular Investigation Center, NMR Laboratory, Paris, France.ORCID 0000-0001-6526-7847
Pierre-Yves BaudinInstitute of Myology, Neuromuscular Investigation Center, NMR Laboratory, Paris, France.
Tanya StojkovicNeuromuscular Reference Center, Institute of Myology, Pitié-Salpêtrière Hospital (AP-HP), Paris, France.
Simone BirnbaumInstitute of Myology, Neuromuscular Investigation Center, Neuromuscular Physiology and Evaluation Laboratory, Paris, France.
Valérie DecostreInstitute of Myology, Neuromuscular Investigation Center, Neuromuscular Physiology and Evaluation Laboratory, Paris, France.
Rachida-Lydie ZanfongnonGénéthon, Evry, France.
Yves FromesInstitute of Myology, Neuromuscular Investigation Center, NMR Laboratory, Paris, France.ORCID 0000-0002-6792-9549
Melissa T HooijmansAmsterdam Movement Sciences, Musculoskeletal Health, Amsterdam, The Netherlands.
Gustav J StrijkersAmsterdam Movement Sciences, Musculoskeletal Health, Amsterdam, The Netherlands.
Jean-Yves HogrelInstitute of Myology, Neuromuscular Investigation Center, Neuromuscular Physiology and Evaluation Laboratory, Paris, France.
Sophie OlivierAtamyo Therapeutics, Evry, France.
Benjamin MartyInstitute of Myology, Neuromuscular Investigation Center, NMR Laboratory, Paris, France.
Harmen ReyngoudtInstitute of Myology, Neuromuscular Investigation Center, NMR Laboratory, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesLimb-girdle muscular dystrophy R9 (LGMD-R9) is a rare neuromuscular disease with no curative treatment. Sensitive non-invasive biomarkers are necessary to monitor disease progression and evaluate the efficacy of novel therapies. Here, we investigated several quantitative MRI parameters as suitable biomarkers for evaluating disease progression in LGMD-R9.

methodsBilateral quantitative MRI of the lower limbs was performed in individuals with LGMD-R9 and healthy controls. Quantitative thigh and leg muscle MRI, functional tests (including time-up-and-go (TUG) and time-to-climb-4-stairs (4S climb)), and muscle strength tests were performed in individuals with LGMD-R9 at baseline, 1-year, and 2-years. qMRI included assessment of muscle fat fraction (FF), water T2, water T1, intramuscular pH from 1H MR spectroscopy, and diffusion tensor imaging (DTI) parameters. Differences between LGMD-R9 and controls, over time, and the relationship between baseline water T1 and water T2 parameters and disease progression (FF, functional and strength parameters) were assessed by linear mixed models and correlation analyses.

results18 individuals with LGMD-R9 and 13 controls were enrolled. At baseline, elevated FF, water T2, water T1, and pH were observed in LGMD-R9 (p < 0.05). No differences between controls and LGMD-R9 were found in the DTI parameters. An overall tendency to an increase in FF and a decrease in functional measures were observed over 2 years. However, the changes did not reach significance (p = 0.057-0.752). Baseline water T1 and baseline water T2 correlated with the increase in FF (ΔFF) and change in TUG (ΔTUG) and 4S climb (Δ4S climb) over 2 years (correlation coefficient ≥  0.6, p < 0.05). No correlation with the strength measures was found.

conclusionOur findings suggest that FF, water T2, water T1, and pH are effective biomarkers for LGMD-R9. The correlation of water T2 and water T1 with ΔFF, ΔTUG, and Δ4S climb suggests their potential in predicting disease progression.

Indexed as

Lower ExtremityMagnetic Resonance ImagingMuscle, SkeletalMuscular Dystrophies, Limb-GirdleAdolescentAdultCase-Control StudiesDiffusion Tensor ImagingDisease ProgressionFemaleHumansLongitudinal StudiesMaleMiddle AgedMuscle StrengthYoung Adult

Identifiers

PMID40293996
PMCPMC12036925

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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.