ArticleThe British journal of radiology2019
Deep learning-based muscle segmentation and quantification at abdominal CT: application to a longitudinal adult screening cohort for sarcopenia assessment.
Article in The British journal of radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.
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Who cites it
64 citing papers in PubMed.
- Musculoskeletal characteristics in older adults with overweight or obesity: INVEST in Bone Health trial baseline analysis.Obesity (Silver Spring, Md.) · 2025Trial
- A novel fully guided technique for botulinum toxin injection in lateral pterygoid muscle using muscle segmentation for TMJ disc displacement with reduction: a randomized controlled trial.BMC oral health · 2025Trial
- Automated framework for volumetric musculoskeletal segmentation and assessment of torso CT images in large-scale databases.International journal of computer assisted radiology and surgery · 2026Article
- Multi-center validation of automated CT-based L1 vertebral Hounsfield unit.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2026Article
- Longitudinal evaluation of intra-patient changes in computed tomography-based body composition measures.Abdominal radiology (New York) · 2026Article
- Whole body CT attenuation and volume charts from routine clinical scans via LLM report filtering.NPJ digital medicine · 2026Article
- Deep Learning-Based 3D and 2D Approaches for Skeletal Muscle Segmentation on Low-Dose CT Images.Journal of imaging informatics in medicine · 2026Article
- eCAPRI: a novel tool combining clinical and imaging data for post-TAVI mortality prediction.European radiology · 2026Article
- The sarcopenia artificial intelligence diagnostic decision support system (SAID DSS) - a multimodal deep learning model.BMC geriatrics · 2026Article
- Opportunistic computed tomography assessment of bone, muscle, and adipose tissue: evidence, limitations, and clinical translation.Frontiers in medicine · 2026Review
- Tumor-Derived Polyamines Initiate Fat Wasting in Cancer Cachexia.bioRxiv : the preprint server for biology · 2025Article
- Diagnostic value of computed tomography-based muscle quality and metabolic signatures in heart failure with sarcopenia.ESC heart failure · 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
- Comparing fully automated AI body composition biomarkers at differing virtual monoenergetic levels using dual-energy CT.Abdominal radiology (New York) · 2025Article
- Biological age model using explainable automated CT-based cardiometabolic biomarkers for phenotypic prediction of longevity.Nature communications · 2025Article
- Validation of musculoskeletal segmentation model with uncertainty estimation for bone and muscle assessment in hip-to-knee clinical CT images.Scientific reports · 2025Article
- An Analysis of Age-Related Body Composition Changes and Metabolic Patterns in Korean Adults Using FDG-PET/CT Health Screening Data.Diabetes & metabolism journal · 2025Article
- AI-based abdominal CT measurements of orthotopic and ectopic fat predict mortality and cardiometabolic disease risk in adults.European radiology · 2025Article
- CT imaging-derived phenotypes for abdominal muscle and their association with age and sex in a medical biobank.Scientific reports · 2024Article
- Low skeletal muscle mass predicts melanoma-specific survival in melanoma patients treated with adjuvant immune checkpoint blockade.Journal of cancer research and clinical oncology · 2024Article
4 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
Abstract
objectiveTo investigate a fully automated abdominal CT-based muscle tool in a large adult screening population.
methodsA fully automated validated muscle segmentation algorithm was applied to 9310 non-contrast CT scans, including a primary screening cohort of 8037 consecutive asymptomatic adults (mean age, 57.1±7.8 years; 3555M/4482F). Sequential follow-up scans were available in a subset of 1171 individuals (mean interval, 5.1 years). Muscle tissue cross-sectional area and attenuation (Hounsfield unit, HU) at the L3 level were assessed, including change over time.
resultsMean values were significantly higher in males for both muscle area (190.6±33.6
conclusionThis fully automated CT muscle tool allows for both individualized and population-based assessment. Such data could be automatically derived at abdominal CT regardless of study indication, allowing for opportunistic sarcopenia detection. ADVANCES IN KNOWLEDGE: This fully automated tool can be applied to routine abdominal CT scans for prospective or retrospective opportunistic sarcopenia assessment, regardless of the original clinical indication. Mean values were significantly higher in males for both muscle area and muscle density. Overall age-related muscle density (attenuation) loss was steeper than for muscle area for both sexes, and therefore may be a more valuable predictor of adverse outcomes.
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