Evidence map›Paper›PMID 29030457›Full record

ArticleNeurology2017

Adding quantitative muscle MRI to the FSHD clinical trial toolbox.

Karlien Mul, Sanne C C Vincenten, Nicol C Voermans, Richard J L F Lemmers, Patrick J van der Vliet, Silvère M van der Maarel, George W Padberg, Corinne G C Horlings, Baziel G M van Engelen

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PubMed Full text at PMC Publisher
In one paragraph

Article in Neurology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 1 pooled it
4.0field-weighted citation impact, top 5% 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.

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

52 citing papers in PubMed, 1 synthesis or guideline pooled it, 90 citations in OpenAlex.

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  18. Comparison of quantitative muscle ultrasound and whole-body muscle MRI in facioscapulohumeral muscular dystrophy type 1 patients.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 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

9 authors at 1 institution in 1 country.

Karlien MulFrom the Department of Neurology (K.M., S.C.C.V., N.C.V., G.W.P., C.G.C.H., B.G.M.v.E.), Radboud University Medical Center, Nijmegen; and Department of Human Genetics (R.J.L.F.L., P.J.v.d.V., S.M.v.d.M.), Leiden University Medical Center, the Netherlands. karlien.mul@radboudumc.nl.
Sanne C C VincentenFrom the Department of Neurology (K.M., S.C.C.V., N.C.V., G.W.P., C.G.C.H., B.G.M.v.E.), Radboud University Medical Center, Nijmegen; and Department of Human Genetics (R.J.L.F.L., P.J.v.d.V., S.M.v.d.M.), Leiden University Medical Center, the Netherlands.
Nicol C VoermansFrom the Department of Neurology (K.M., S.C.C.V., N.C.V., G.W.P., C.G.C.H., B.G.M.v.E.), Radboud University Medical Center, Nijmegen; and Department of Human Genetics (R.J.L.F.L., P.J.v.d.V., S.M.v.d.M.), Leiden University Medical Center, the Netherlands.
Richard J L F LemmersFrom the Department of Neurology (K.M., S.C.C.V., N.C.V., G.W.P., C.G.C.H., B.G.M.v.E.), Radboud University Medical Center, Nijmegen; and Department of Human Genetics (R.J.L.F.L., P.J.v.d.V., S.M.v.d.M.), Leiden University Medical Center, the Netherlands.
Patrick J van der VlietFrom the Department of Neurology (K.M., S.C.C.V., N.C.V., G.W.P., C.G.C.H., B.G.M.v.E.), Radboud University Medical Center, Nijmegen; and Department of Human Genetics (R.J.L.F.L., P.J.v.d.V., S.M.v.d.M.), Leiden University Medical Center, the Netherlands.
Silvère M van der MaarelFrom the Department of Neurology (K.M., S.C.C.V., N.C.V., G.W.P., C.G.C.H., B.G.M.v.E.), Radboud University Medical Center, Nijmegen; and Department of Human Genetics (R.J.L.F.L., P.J.v.d.V., S.M.v.d.M.), Leiden University Medical Center, the Netherlands.
George W PadbergFrom the Department of Neurology (K.M., S.C.C.V., N.C.V., G.W.P., C.G.C.H., B.G.M.v.E.), Radboud University Medical Center, Nijmegen; and Department of Human Genetics (R.J.L.F.L., P.J.v.d.V., S.M.v.d.M.), Leiden University Medical Center, the Netherlands.
Corinne G C HorlingsFrom the Department of Neurology (K.M., S.C.C.V., N.C.V., G.W.P., C.G.C.H., B.G.M.v.E.), Radboud University Medical Center, Nijmegen; and Department of Human Genetics (R.J.L.F.L., P.J.v.d.V., S.M.v.d.M.), Leiden University Medical Center, the Netherlands.
Baziel G M van EngelenFrom the Department of Neurology (K.M., S.C.C.V., N.C.V., G.W.P., C.G.C.H., B.G.M.v.E.), Radboud University Medical Center, Nijmegen; and Department of Human Genetics (R.J.L.F.L., P.J.v.d.V., S.M.v.d.M.), Leiden University Medical Center, the Netherlands.
Radboud University Nijmegen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo add quantitative muscle MRI to the clinical trial toolbox for facioscapulohumeral muscular dystrophy (FSHD) by correlating it to clinical outcome measures in a large cohort of genetically and clinically well-characterized patients with FSHD comprising the entire clinical spectrum.

methodsQuantitative MRI scans of leg muscles of 140 patients with FSHD1 and FSHD2 were assessed for fatty infiltration and TIRM hyperintensities and were correlated to multiple clinical outcome measures.

resultsThe mean fat fraction of the total leg musculature correlated highly with the motor function measure, FSHD clinical score, Ricci score, and 6-minute walking test (correlation coefficients -0.845, 0.835, 0.791, -0.701, respectively). Fat fraction per muscle group correlated well with corresponding muscle strength (correlation coefficients up to -0.82). The hamstring muscles, adductor muscles, rectus femoris, and gastrocnemius medialis were affected most frequently, also in early stage disease and in patients without leg muscle weakness. Muscle involvement was asymmetric in 20% of all muscle pairs and fatty infiltration within muscles showed a decrease from distal to proximal of 3.9%. TIRM hyperintense areas, suggesting inflammation, were found in 3.5% of all muscles, with and without fatty infiltration.

conclusionsWe show a strong correlation between quantitative muscle MRI and clinical outcome measures. Muscle MRI is able to detect muscle pathology before clinical involvement of the leg muscles. This indicates that quantitative leg muscle MRI is a promising biomarker that captures disease severity and motor functioning and can thus be included in the FSHD trial toolbox.

Indexed as

LegMuscle, SkeletalMuscular Dystrophy, FacioscapulohumeralSeverity of Illness IndexAdolescentAdultAgedAged, 80 and overClinical Trials as TopicFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedYoung Adult

Identifiers

PMID29030457
PMCPMC5711504
OpenAlexW2762195302

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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.