Evidence map›Paper›PMID 40132878›Full record

ArticleJournal of neurology, neurosurgery, and psychiatry2025

Muscle MRI quantifies disease progression in amyotrophic lateral sclerosis.

Uros Klickovic, Luca Zampedri, Nick Zafeiropoulos, Oliver J Ziff, Christopher Dj Sinclair, Stephen Wastling, Magdalena Dudziec, Jodie Allen, Karin Trimmel, Robin S Howard and 10 more

Abstract read
In one paragraph

Article in Journal of neurology, neurosurgery, and psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review of the Pathology of Muscle in Amyotrophic Lateral Sclerosis.International journal of molecular sciences · 2026
    Review
  4. 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

20 authors.

Uros KlickovicMND Centre, UCL Queen Square Institute of Neurology, London, UK.ORCID http://orcid.org/0009-0000-0678-4326
Luca ZampedriMND Centre, UCL Queen Square Institute of Neurology, London, UK.
Nick ZafeiropoulosMND Centre, UCL Queen Square Institute of Neurology, London, UK.
Oliver J ZiffMND Centre, UCL Queen Square Institute of Neurology, London, UK.ORCID http://orcid.org/0000-0002-1504-7245
Christopher Dj SinclairNeuroradiological Academic Unit, UCL Queen Square Institute of Neurology, London, UK.
Stephen WastlingNeuroradiological Academic Unit, UCL Queen Square Institute of Neurology, London, UK.
Magdalena DudziecMND Centre, UCL Queen Square Institute of Neurology, London, UK.
Jodie AllenMND Centre, UCL Queen Square Institute of Neurology, London, UK.
Karin TrimmelMND Centre, UCL Queen Square Institute of Neurology, London, UK.ORCID http://orcid.org/0000-0002-9203-5344
Robin S HowardMND Centre, UCL Queen Square Institute of Neurology, London, UK.
Andrea MalaspinaMND Centre, UCL Queen Square Institute of Neurology, London, UK.
Nikhil SharmaMND Centre, UCL Queen Square Institute of Neurology, London, UK.
Katie Cl SidleMND Centre, UCL Queen Square Institute of Neurology, London, UK.
Sachit ShahNeuroradiological Academic Unit, UCL Queen Square Institute of Neurology, London, UK.
Christian NaselDepartment of Radiology, University Hospital Tulln, Tulln, Austria.
Tarek A YousryNeuroradiological Academic Unit, UCL Queen Square Institute of Neurology, London, UK.
Linda GreensmithMND Centre, UCL Queen Square Institute of Neurology, London, UK.
Jasper M MorrowMND Centre, UCL Queen Square Institute of Neurology, London, UK.
John S ThorntonNeuroradiological Academic Unit, UCL Queen Square Institute of Neurology, London, UK p.fratta@ucl.ac.uk john.thornton@ucl.ac.uk.
Pietro FrattaMND Centre, UCL Queen Square Institute of Neurology, London, UK p.fratta@ucl.ac.uk john.thornton@ucl.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesQuantitative and operator-independent biomarkers of disease progression are urgently needed in amyotrophic lateral sclerosis (ALS) research. We assess the potential of skeletal muscle MRI as a sensitive and reliable outcome measure for future ALS clinical trials.

methodsIn this longitudinal cohort study, muscle MRI of head-neck, upper and lower limb regions, alongside clinical and functional assessments, were acquired at three time points over the individual maximum observation period (iMOP) of 1 year in 20 patients with ALS and 16 healthy controls. Quantitative MRI parameters cross-sectional area (CSA), volume (VOL), fat fraction, functional rest muscle area and water T2 (T

resultsAmong 20 patients with ALS, 17 completed follow-up. Progressive muscle atrophy (CSA, VOL) was observed at hand (rs=0.66), head-neck (partial η²=0.47) and lower-limb level (thighs: η²=0.56, calves: η²=0.54) over iMOP. MRI changes correlated with leg muscle strength (knee extension: r=0.77; plantar flexion: r=0.78), hand grip strength (r=0.71) and functional rating scales (r=0.68).

interpretationOur findings demonstrate the effectiveness of muscle MRI as a sensitive neuroimaging biomarker of disease progression in ALS, highlighting its potential application in clinical trials.

Indexed as

Amyotrophic Lateral SclerosisMagnetic Resonance ImagingMuscle, SkeletalAdultAgedDisease ProgressionFemaleHumansLongitudinal StudiesMaleMiddle AgedMuscle StrengthMuscular AtrophyALSMRIMUSCLE DISEASENEUROMUSCULAR

Identifiers

PMID40132878
PMCPMC12418527

What OpenQuestion holds

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Registered trials

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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.