ReviewNeural regeneration research2017
MRI analysis and clinical significance of lower extremity muscle cross-sectional area after spinal cord injury.
Review in Neural regeneration research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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.
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Who cites it
10 citing papers in PubMed.
- Comparison of Longitudinal Skeletal Thigh Muscle Findings With Magnetic Resonance Imaging in Patients With Peripheral Artery Disease With-Versus-Without Diabetes Mellitus.The American journal of cardiology · 2022Trial
- Neuromuscular electrical stimulation resistance training enhances oxygen uptake and ventilatory efficiency independent of mitochondrial complexes after spinal cord injury: a randomized clinical trial.Journal of applied physiology (Bethesda, Md. : 1985) · 2021Trial
- Prediction of thigh skeletal muscle mass using dual energy x-ray absorptiometry compared to magnetic resonance imaging after spinal cord injury.The journal of spinal cord medicine · 2019Trial
- Intra- and inter-rater reliability of skeletal muscle mass MRI assessment among adults: a systematic review.Quantitative imaging in medicine and surgery · 2026Review
- Fully-automated segmentation of muscle and inter-/intra-muscular fat from magnetic resonance images of calves and thighs: an open-source workflow in Python.Skeletal muscle · 2024Article
- Predictors of muscle hypertrophy responsiveness to electrically evoked resistance training after spinal cord injury.European journal of applied physiology · 2023Article
- Employment of Neuromuscular Electrical Stimulation to Examine Muscle and Bone Qualities after Spinal Cord Injury.Journal of clinical medicine · 2022Article
- The effects of spasticity on glucose metabolism and soft tissue body composition in patients with spinal cord injury.Turkish journal of physical medicine and rehabilitation · 2022Article
- Semi-automated segmentation of magnetic resonance images for thigh skeletal muscle and fat using threshold technique after spinal cord injury.Neural regeneration research · 2018Article
- Quantification of intermuscular and intramuscular adipose tissue using magnetic resonance imaging after neurodegenerative disorders.Neural regeneration research · 2017Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Shortly after spinal cord injury (SCI), the musculoskeletal system undergoes detrimental changes in size and composition, predominantly below the level of injury. The loss of muscle size and strength, along with increased immobility, predisposes persons with SCI to rapid and severe loss in bone mineral density and other health related consequences. Previous studies have highlighted the significance of measuring thigh muscle cross-sectional area, however, measuring the size and composition of muscles of the lower leg may provide insights on how to decrease the risk of various comorbidities. The purpose of the current review was to summarize the methodological approach to manually trace and measure the muscles of the lower leg in individuals with SCI, using magnetic resonance imaging. We also intend to highlight the significance of analyzing lower leg muscle cross-sectional area and its relationship to musculoskeletal and vascular systems in persons with SCI.
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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.