Evidence map›Paper›PMID 41248684›Full record

ArticleNMR in biomedicine2025

Dynamic MR of Muscle Contraction During Electrical Muscle Stimulation: Potential Application to the Evaluation of Neuromuscular Diseases.

Francesco Santini, Michele Giovanni Croce, Xeni Deligianni, Marta Brigid Maggioni, Matteo Paoletti, Leonardo Barzaghi, Niels Bergsland, Arianna Faggioli, Giulia Manco, Chiara Bonizzoni and 3 more

Abstract read
In one paragraph

Article in NMR in biomedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

13 authors.

Francesco SantiniBasel Muscle MRI, Department of Biomedical Engineering, University of Basel, Basel, Switzerland.ORCID https://orcid.org/0000-0001-6984-4816
Michele Giovanni CroceDepartment of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy.
Xeni DeligianniBasel Muscle MRI, Department of Biomedical Engineering, University of Basel, Basel, Switzerland.
Marta Brigid MaggioniBasel Muscle MRI, Department of Biomedical Engineering, University of Basel, Basel, Switzerland.
Matteo PaolettiAdvanced Imaging and Artificial Intelligence Research Unit, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy.
Leonardo BarzaghiDepartment of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy.
Niels BergslandDepartment of Neurology, Jacobs School of Medicine and Biomedical Sciences, Buffalo Neuroimaging Analysis Center, University of Buffalo, the State University of New York, Buffalo, New York, USA.
Arianna FaggioliAdvanced Imaging and Artificial Intelligence Research Unit, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy.
Giulia MancoAdvanced Imaging and Artificial Intelligence Research Unit, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy.
Chiara BonizzoniAdvanced Imaging and Artificial Intelligence Research Unit, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy.
Ning JinCardiovascular MR R&D, Siemens Medical Solutions USA, Inc., Cleveland, Ohio, USA.
Sabrina RavagliaIRCCS Mondino Foundation, Pavia, Italy.
Anna PichiecchioDepartment of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy.

Funding

Ministero della Salute RC2025-27Swiss National Science Foundation 32003B_219674
6 · The paper itself

Abstract

Thanks to the rapid evolution of therapeutic strategies for muscular and neuromuscular diseases, the identification of quantitative biomarkers for disease identification and monitoring has become crucial. Magnetic resonance imaging (MRI) has been playing an important role by noninvasively assessing structural and functional muscular changes. This exploratory study investigated the potential of dynamic MRI during neuromuscular electrical stimulation (NMES) to detect differences between healthy controls (HCs) and patients with metabolic and myotonic myopathies. The study included 14 HCs and 10 patients with confirmed muscular diseases. All individuals were scanned with 3 T MRI with a protocol that included a multi-echo gradient echo sequence for fat fraction quantification, multi-echo spin-echo for water T2 relaxation time calculation, and 3D phase contrast sequences during NMES. The strain tensor, buildup, and release rates were calculated from velocity datasets. Results showed that strain and strain buildup rate were reduced in the soleus muscle of patients compared to HCs, suggesting these parameters could serve as biomarkers of muscle dysfunction. Notably, there were no significant differences in fat fraction or water T2 measurements between patients and HCs, indicating that the observed changes reflect alterations in muscle contractile properties that are not reflected by structural changes. The findings provide preliminary evidence that dynamic muscle MRI during NMES can detect abnormalities in muscle contraction in patients with myotonia and metabolic myopathies, warranting further research with larger, more homogeneous patient cohorts.

Indexed as

Electric StimulationMagnetic Resonance ImagingMuscle ContractionMuscle, SkeletalNeuromuscular DiseasesAdultAgedFemaleHumansMaleMiddle AgedYoung Adultdynamic MRImuscleneuromuscular diseasesneuromuscular electrical stimulation

Identifiers

PMID41248684
PMCPMC12623070

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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.