ArticleJMIR medical informatics2020
Assessment of Myosteatosis on Computed Tomography by Automatic Generation of a Muscle Quality Map Using a Web-Based Toolkit: Feasibility Study.
Article in JMIR medical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.
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32 citing papers in PubMed, 1 synthesis or guideline pooled it, 56 citations in OpenAlex.
- Pooled it
- Contralateral-controlled thigh muscle biomarkers on CT angiography for prediction of 1-year restenosis after endovascular therapy for unilateral peripheral artery disease.Insights into imaging · 2026Article
- Association of biological age acceleration with muscle aging phenotype in young and middle-aged adults: a prospective cohort study.GeroScience · 2026Article
- Association of CT-derived muscle quality with multiple geriatric syndromes in older adults: a cross-sectional study.GeroScience · 2026Article
- Characterization of body composition dynamics throughout treatment in patients with early-stage breast cancer.NPJ breast cancer · 2026Article
- Temporal Degradation of Skeletal Muscle Quality on CT as a Prognostic Marker in Septic Shock.Diagnostics (Basel, Switzerland) · 2026Article
- Potential Role of Imaging in the Evaluation of Adiposity and Approval of Anti-Obesity Drugs.Korean journal of radiology · 2026Review
- Developing an explainable machine learning model using body composition to predict cardiovascular mortality in initial dialysis patients: a multicenter study.Frontiers in physiology · 2026Article
- Body composition and immunotherapy outcomes in patients with advanced urothelial carcinoma.BMC cancer · 2025Article
- Implementation of Fully Automated AI-Integrated System for Body Composition Assessment on Computed Tomography for Opportunistic Sarcopenia Screening: Multicenter Prospective Study.JMIR formative research · 2025Article
- The Role of Muscle Density in Predicting the Amputation Risk in Peripheral Arterial Disease: A Tissue Composition Study Using Lower Extremity CT Angiography.Diagnostics (Basel, Switzerland) · 2025Article
- Comparison of Sarcopenia Assessment in Liver Transplant Recipients by Computed Tomography Freehand Region-of-Interest versus an Automated Deep Learning System.Clinical transplantation · 2025Article
- Longitudinal changes in body composition during palliative systemic chemotherapy and survival outcomes in metastatic colorectal cancer.World journal of gastrointestinal oncology · 2025Article
- Muscle quality correlates with hearing thresholds: a cross-sectional analysis.Frontiers in aging · 2025Article
- Myosteatosis as an independent predictor for all-cause and cardiac mortality in initial-dialysis patients: a multicenter, retrospective cohort study.Frontiers in physiology · 2025Article
- The development of an attention mechanism enhanced deep learning model and its application for body composition assessment with L3 CT images.Scientific reports · 2024Article
- Muscle Quality as a Potential Diagnostic Marker of Advanced Liver Fibrosis in Patients with Non-alcoholic Fatty Liver Disease.Journal of obesity & metabolic syndrome · 2024Article
- Skeletal muscle alterations indicate poor prognosis in cirrhotic patients: a multicenter cohort study in China.Hepatology international · 2024Article
- Computed tomography reveals hypertrophic remodelling of the diaphragm in cystic fibrosis but not in COPD.ERJ open research · 2023Article
- Artificial Intelligence in Gastric Cancer Imaging With Emphasis on Diagnostic Imaging and Body Morphometry.Journal of gastric cancer · 2023Review
Corrections and comments
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMuscle quality is associated with fatty degeneration or infiltration of the muscle, which may be associated with decreased muscle function and increased disability.
objectiveThe aim of this study is to evaluate the feasibility of automated quantitative measurements of the skeletal muscle on computed tomography (CT) images to assess normal-attenuation muscle and myosteatosis.
methodsWe developed a web-based toolkit to generate a muscle quality map by categorizing muscle components. First, automatic segmentation of the total abdominal muscle area (TAMA), visceral fat area, and subcutaneous fat area was performed using a predeveloped deep learning model on a single axial CT image at the L3 vertebral level. Second, the Hounsfield unit of each pixel in the TAMA was measured and categorized into 3 components: normal-attenuation muscle area (NAMA), low-attenuation muscle area (LAMA), and inter/intramuscular adipose tissue (IMAT) area. The myosteatosis area was derived by adding the LAMA and IMAT area. We tested the feasibility of the toolkit using randomly selected healthy participants, comprising 6 different age groups (20 to 79 years). With stratification by sex, these indices were compared between age groups using 1-way analysis of variance (ANOVA). Correlations between the myosteatosis area or muscle densities and fat areas were analyzed using Pearson correlation coefficient r.
resultsA total of 240 healthy participants (135 men and 105 women) with 40 participants per age group were included in the study. In the 1-way ANOVA, the NAMA, LAMA, and IMAT were significantly different between the age groups in both male and female participants (P≤.004), whereas the TAMA showed a significant difference only in male participants (male, P<.001; female, P=.88). The myosteatosis area had a strong negative correlation with muscle densities (r=-0.833 to -0.894), a moderate positive correlation with visceral fat areas (r=0.607 to 0.669), and a weak positive correlation with the subcutaneous fat areas (r=0.305 to 0.441).
conclusionsThe automated web-based toolkit is feasible and enables quantitative CT assessment of myosteatosis, which can be a potential quantitative biomarker for evaluating structural and functional changes brought on by aging in the skeletal muscle.
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