ArticleNeurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology2023
Comparison of quantitative muscle ultrasound and whole-body muscle MRI in facioscapulohumeral muscular dystrophy type 1 patients.
Article in Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed, 10 citations in OpenAlex.
- Multi-scale machine learning model predicts muscle and functional disease progression.Scientific reports · 2025Article
- Skeletal muscle as a pro- and anti-inflammatory tissue: insights from children to adults and ultrasound findings.Journal of ultrasound · 2024Review
- Immune-Mediated Necrotizing Myopathy (IMNM): A Story of Antibodies.Antibodies (Basel, Switzerland) · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionMuscle ultrasound is a fast, non-invasive and cost-effective examination that can identify structural muscular changes by assessing muscle thickness and echointensity (EI) with a quantitative analysis (QMUS). To assess applicability and repeatability of QMUS, we evaluated patients with genetically confirmed facioscapulohumeral muscular dystrophy type 1 (FSHD1), comparing their muscle ultrasound characteristics with healthy controls and with those detected by MRI. We also evaluated relationships between QMUS and demographic and clinical characteristics. MATERIALS AND
methodsThirteen patients were included in the study. Clinical assessment included MRC sum score, FSHD score and The Comprehensive Clinical Evaluation Form (CCEF). QMUS was performed with a linear transducer scanning bilaterally pectoralis major, deltoid, rectus femoris, tibialis anterior and semimembranosus muscles in patients and healthy subjects. For each muscle, we acquired three images, which were analysed calculating muscle EI by computer-assisted grey-scale analysis. QMUS analysis was compared with semiquantitative 1.5 T muscle MRI scale.
resultsAll muscles in FSHD patients showed a significant increased echogenicity compared to the homologous muscles in healthy subjects. Older subjects and patients with higher FSHD score presented increased muscle EI. Tibialis anterior MRC showed a significant inverse correlation with EI. Higher median EI was found in muscles with more severe MRI fat replacement.
conclusionsQMUS allows quantitative evaluation of muscle echogenicity, displaying a tight correlation with muscular alterations, clinical and MRI data. Although a confirmation on larger sample is needed, our research suggests a possible future application of QMUS in diagnosis and management of muscular disorders.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.