ArticleNMR in biomedicine2020
Quantitative MRI of skeletal muscle in a cross-sectional cohort of patients with spinal muscular atrophy types 2 and 3.
Article in NMR in biomedicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled 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.
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
39 citing papers in PubMed, 1 synthesis or guideline pooled it, 60 citations in OpenAlex.
- Muscle MRI and Muscle Ultrasound Applications in MND/ALS: Academic Insights and Clinical Opportunities.European journal of neurology · 2026Pooled it
- Ten years of disease-modifying therapy in spinal muscular atrophy: lessons learned and future directions.Nature reviews. Neurology · 2026Review
- Standardizing quantitative muscle MRI: an inter-vendor evaluation in healthy adults.Magma (New York, N.Y.) · 2026Article
- Temperature-induced symptoms in adolescents and adults with spinal muscular atrophy.Journal of neuromuscular diseases · 2026Article
- Automated deep-learning quantification of intramuscular fat in lumbar spine muscles on Dixon MRI: validation and normative reference values from 173 healthy adults.BMC medical imaging · 2026Article
- Quantitative Whole-Body Muscle MRI in Adults With Spinal Muscular Atrophy-A Sensitive Tool for Long-Time Evaluation of Disease Progression.European journal of neurology · 2026Article
- Magnetic resonance imaging applications to amyotrophic lateral sclerosis beyond the central nervous system.Frontiers in neurology · 2026Review
- Quantitative Magnetic Resonance Imaging of the Forearm in Myotonic Dystrophy Type 1.Tomography (Ann Arbor, Mich.) · 2025Article
- Dynamic MR of Muscle Contraction During Electrical Muscle Stimulation: Potential Application to the Evaluation of Neuromuscular Diseases.NMR in biomedicine · 2025Article
- Course of joint range of motion in children with spinal muscular atrophy receiving disease-modifying treatment.Orphanet journal of rare diseases · 2025Article
- Advancing personalized spinal muscular atrophy care: matching the right biomarker to the right patient at the right time.Journal of neurology · 2025Review
- Quantitative cervical cord MRI in spinal muscular atrophy: a sensitive imaging biomarker of disease evolution and treatment.Journal of neurology · 2025Article
- Assessment of muscle fiber types transformation in rats with discogenic low back pain using diffusion tensor image of paraspinal muscles.BMC medical imaging · 2025Article
- Whole-body muscle MRI in patients with spinal muscular atrophy.Journal of neurology · 2025Article
- Calculation of the Minimal Clinically Important Difference in Upper and Lower Limb Motor Assessment in Spinal Muscular Atrophy.Progress in rehabilitation medicine · 2025Article
- Pre- and post-skeletal muscle biopsy quantitative magnetic resonance imaging reveals correlations with histopathological findings.European journal of neurology · 2024Article
- The Relevance of Spinal Muscular Atrophy Biomarkers in the Treatment Era.Biomedicines · 2024Review
- Compositional and Functional MRI of Skeletal Muscle: A Review.Journal of magnetic resonance imaging : JMRI · 2024Review
- Evaluation of Neuromuscular Diseases and Complaints by Quantitative Muscle MRI.Journal of clinical medicine · 2024Article
- Applications of Diffusion-Weighted MRI to the Musculoskeletal System.Journal of magnetic resonance imaging : JMRI · 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
13 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this study was to document upper leg involvement in spinal muscular atrophy (SMA) with quantitative MRI (qMRI) in a cross-sectional cohort of patients of varying type, disease severity and age. Thirty-one patients with SMA types 2 and 3 (aged 29.6 [7.6-73.9] years) and 20 healthy controls (aged 37.9 [17.7-71.6] years) were evaluated in a 3 T MRI with a protocol consisting of DIXON, T2 mapping and diffusion tensor imaging (DTI). qMRI measures were compared with clinical scores of motor function (Hammersmith Functional Motor Scale Expanded [HFMSE]) and muscle strength. Patients exhibited an increased fat fraction and fractional anisotropy (FA), and decreased mean diffusivity (MD) and T2 compared with controls (all P < .001). DTI parameters FA and MD manifest stronger effects than can be accounted for the effect of fatty replacement. Fat fraction, FA and MD show moderate correlation with muscle strength and motor function: FA is negatively associated with HFMSE and Medical Research Council sum score (τ = -0.56 and -0.59; both P < .001) whereas for fat fraction values are τ = -0.50 and -0.58, respectively (both P < .001). This study shows that DTI parameters correlate with muscle strength and motor function. DTI findings indirectly indicate cell atrophy and act as a measure independently of fat fraction. Combined these data suggest the potential of muscle DTI in monitoring disease progression and to study SMA pathogenesis in muscle.
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.