Evidence map›Paper›PMID 27854210›Full record

ReviewJournal of neuromuscular diseases2016

Skeletal Muscle Quantitative Nuclear Magnetic Resonance Imaging and Spectroscopy as an Outcome Measure for Clinical Trials.

Pierre G Carlier, Benjamin Marty, Olivier Scheidegger, Paulo Loureiro de Sousa, Pierre-Yves Baudin, Eduard Snezhko, Dmitry Vlodavets

Open access · bronzeAbstract readReview
In one paragraph

Review in Journal of neuromuscular diseases, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 99 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
99citing papers in PubMed, 1 pooled it
6.6field-weighted citation impact, top 3% 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

99 citing papers in PubMed, 1 synthesis or guideline pooled it, 180 citations in OpenAlex.

  1. Guideline
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  14. Observational
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39 more citing papers are in PubMed but not listed here.

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

7 authors at 5 institutions in 4 countries.

Pierre G CarlierInstitute of Myology, Pitie-Salpetriere University Hospital, Paris, France.
Benjamin MartyInstitute of Myology, Pitie-Salpetriere University Hospital, Paris, France.
Olivier ScheideggerInstitute of Myology, Pitie-Salpetriere University Hospital, Paris, France.
Paulo Loureiro de SousaStrasbourg University, CNRS, ICube, Strasbourg, France.
Pierre-Yves BaudinConsultants for Research in Imaging and Spectroscopy, Tournai, Belgium.
Eduard SnezhkoNational Academy of Sciences, United Institute for Informatics Problems, Minsk, Belarus.
Dmitry VlodavetsN.I. Prirogov Russian National Medical Research University, Clinical Research Institute of Pediatrics, Moscow, Russian Federation.
National Academy of Sciences of Belarus · BYCentre National de la Recherche Scientifique · FRCommissariat à l'Énergie Atomique et aux Énergies Alternatives · FRPirogov Russian National Research Medical University · RUUniversity of Bern · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent years have seen tremendous progress towards therapy of many previously incurable neuromuscular diseases. This new context has acted as a driving force for the development of novel non-invasive outcome measures. These can be organized in three main categories: functional tools, fluid biomarkers and imagery. In the latest category, nuclear magnetic resonance imaging (NMRI) offers a considerable range of possibilities for the characterization of skeletal muscle composition, function and metabolism. Nowadays, three NMR outcome measures are frequently integrated in clinical research protocols. They are: 1/ the muscle cross sectional area or volume, 2/ the percentage of intramuscular fat and 3/ the muscle water T2, which quantity muscle trophicity, chronic fatty degenerative changes and oedema (or more broadly, "disease activity"), respectively. A fourth biomarker, the contractile tissue volume is easily derived from the first two ones. The fat fraction maps most often acquired with Dixon sequences have proven their capability to detect small changes in muscle composition and have repeatedly shown superior sensitivity over standard functional evaluation. This outcome measure will more than likely be the first of the series to be validated as an endpoint by regulatory agencies. The versatility of contrast generated by NMR has opened many additional possibilities for characterization of the skeletal muscle and will result in the proposal of more NMR biomarkers. Ultra-short TE (UTE) sequences, late gadolinium enhancement and NMR elastography are being investigated as candidates to evaluate skeletal muscle interstitial fibrosis. Many options exist to measure muscle perfusion and oxygenation by NMR. Diffusion NMR as well as texture analysis algorithms could generate complementary information on muscle organization at microscopic and mesoscopic scales, respectively. 31P NMR spectroscopy is the reference technique to assess muscle energetics non-invasively during and after exercise. In dystrophic muscle, 31P NMR spectrum at rest is profoundly perturbed, and several resonances inform on cell membrane integrity. Considerable efforts are being directed towards acceleration of image acquisitions using a variety of approaches, from the extraction of fat content and water T2 maps from one single acquisition to partial matrices acquisition schemes. Spectacular decreases in examination time are expected in the near future. They will reinforce the attractiveness of NMR outcome measures and will further facilitate their integration in clinical research trials.

Indexed as

Clinical Trials as TopicHumansMagnetic Resonance ImagingMuscle, SkeletalNeuromuscular DiseasesOutcome Assessment, Health Care

Identifiers

PMID27854210
PMCPMC5271435
OpenAlexW2328069846

What OpenQuestion holds

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LicenceCC BY-NC
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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 OpenQuestion graph.