ArticleJournal of cachexia, sarcopenia and muscle2022
Percentile-based averaging and skeletal muscle gauge improve body composition analysis: validation at multiple vertebral levels.
Article in Journal of cachexia, sarcopenia and muscle, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.
- Defining Reference Values for Skeletal Muscle Metrics on Abdominal CT Using Data From Healthy Young Adult Populations: A Systematic Review and Meta-Analysis.AJR. American journal of roentgenology · 2025Pooled it
- Future of CT body composition research: Methodological discrepancies and advances.Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition · 2026Review
- Opportunistic Screening on Chest CT, From theAJR. American journal of roentgenology · 2026Review
- Skeletal Muscle Gauge as a Prognosticator of Survival in Resected Early-Stage Non-small Cell Lung Cancer.Annals of surgical oncology · 2026Article
- Early Post-discharge Pain Trajectories After Thoracoscopic Sublobar Resection for Stage IA Non-small Cell Lung Cancer.Annals of surgical oncology · 2026Observational
- Evaluation of sarcopenia and myosteatosis to determine the impact on mortality after emergency laparotomy.BJS open · 2025Article
- Multiparameter body composition analysis on chest CT predicts clinical outcomes in resectable non-small cell lung cancer.Insights into imaging · 2025Article
- Subcutaneous and Visceral Adipose Tissue Reference Values From the Framingham Heart Study Thoracic and Abdominal CT.Investigative radiology · 2025Observational
- New Perspectives for Estimating Body Composition From Computed Tomography: Clothing Associated Artifacts.Academic radiology · 2024Article
- Unraveling the obesity paradox in small cell lung cancer immunotherapy: unveiling prognostic insights through body composition analysis.Frontiers in immunology · 2024Article
- Diagnosis of sarcopenia on thoracic computed tomography and its association with postoperative survival after anatomic lung cancer resection.Scientific reports · 2023Article
- Imaging Techniques to Determine Degree of Sarcopenia and Systemic Inflammation in Advanced Renal Cell Carcinoma.Current urology reports · 2023Review
- Role of Machine Learning-Based CT Body Composition in Risk Prediction and Prognostication: Current State and Future Directions.Diagnostics (Basel, Switzerland) · 2023Review
- The correlation of muscle quantity and quality between all vertebra levels and level L3, measured with CT: An exploratory study.Frontiers in nutrition · 2023Article
- Automated segmentation of five different body tissues on computed tomography using deep learning.Medical physics · 2023Article
- Article
- Percentile-based averaging and skeletal muscle gauge improve body composition analysis: validation at multiple vertebral levels.Journal of cachexia, sarcopenia and muscle · 2022Article
Corrections and comments
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Authors and funding
7 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSkeletal muscle metrics on computed tomography (CT) correlate with clinical and patient-reported outcomes. We hypothesize that aggregating skeletal muscle measurements from multiple vertebral levels and skeletal muscle gauge (SMG) better predict outcomes than skeletal muscle radioattenuation (SMRA) or -index (SMI) at a single vertebral level.
methodsWe performed a secondary analysis of prospectively collected clinical (overall survival, hospital readmission, time to unplanned hospital readmission or death, and readmission or death within 90 days) and patient-reported outcomes (physical and psychological symptom burden captured as Edmonton Symptom Assessment Scale and Patient Health Questionnaire) of patients with advanced cancer who experienced an unplanned admission to Massachusetts General Hospital from 2014 to 2016. First, we assessed the correlation of skeletal muscle cross-sectional area, SMRA, SMI, and SMG at one or more of the following thoracic (T) or lumbar (L) vertebral levels: T5, T8, T10, and L3 on CT scans obtained ≤50 days before index assessment. Second, we aggregated measurements across all available vertebral levels using percentile-based averaging (PBA) to create the average percentile. Third, we constructed one regression model adjusted for age, sex, sociodemographic factors, cancer type, body mass index, and intravenous contrast for each combination of (i) vertebral level and average percentile, (ii) muscle metrics (SMRA, SMI, & SMG), and (iii) clinical and patient-reported outcomes. Fourth, we compared the performance of vertebral levels and muscle metrics by ranking otherwise identical models by concordance statistic, number of included patients, coefficient of determination, and significance of muscle metric.
resultsWe included 846 patients (mean age: 63.5 ± 12.9 years, 50.5% males) with advanced cancer [predominantly gastrointestinal (32.9%) or lung (18.9%)]. The correlation of muscle measurements between vertebral levels ranged from 0.71 to 0.84 for SMRA and 0.67 to 0.81 for SMI. The correlation of individual levels with the average percentile was 0.90-0.93 for SMRA and 0.86-0.92 for SMI. The intrapatient correlation of SMRA with SMI was 0.21-0.40. PBA allowed for inclusion of 8-47% more patients than any single-level analysis. PBA outperformed single-level analyses across all comparisons with average ranks 2.6, 2.9, and 1.6 for concordance statistic, coefficient of determination, and significance (range 1-5, μ = 3), respectively. On average, SMG outperformed SMRA and SMI across outcomes and vertebral levels: the average rank of SMG was 1.4, 1.4, and 1.4 for concordance statistic, coefficient of determination, and significance (range 1-3, μ = 2), respectively.
conclusionsMultivertebral level skeletal muscle analyses using PBA and SMG independently and additively outperform analyses using individual levels and SMRA or SMI.
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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 Socratic graph.