Observational studyBMC pulmonary medicine2026
Thoracic myosteatosis and adipose tissue in COPD: associations of muscle quality and CT biomarkers with GOLD classification.
Observational study in BMC pulmonary medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundChronic obstructive pulmonary disease (COPD) is characterized by airflow limitation and systemic manifestations including changes in body composition. This study aimed to evaluate the association between thoracic muscle quality, adipose tissue distribution, and pulmonary function using computed tomography (CT) biomarkers in patients with COPD.
methodsA retrospective observational study was conducted on 130 patients diagnosed with COPD at a tertiary care facility. Non-contrast chest CT scans were analyzed to quantify thoracic skeletal muscle area, skeletal muscle density, subcutaneous adipose tissue, and intramuscular adipose tissue. Spirometric data including forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and FEV1/FVC ratio were collected. Statistical analyses included Pearson correlation coefficients to assess relationships between CT biomarkers and lung function, and one-way ANOVA to compare imaging parameters across different stages of disease severity based on the Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification.
resultsHigher skeletal muscle area and density were positively correlated with FEV1 and FVC values (p < 0.01). In contrast, increased subcutaneous and intramuscular adipose tissue were significantly associated with lower FEV1 and FVC (p < 0.01). There were statistically significant differences in thoracic body composition measures across GOLD severity stages (p < 0.05), with advanced stages showing reduced muscle mass and greater fat accumulation.
conclusionThoracic CT-derived body composition markers are strongly associated with pulmonary function in individuals with COPD. Muscle quality and fat distribution serve as important indicators of disease severity and may enhance clinical evaluation and risk stratification beyond conventional indices such as body mass index. Incorporating CT-based biomarkers into routine assessment may facilitate more personalized disease monitoring and management strategies.
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