Clinical physiology and functional imaging · 2026
Estimation of whole-body skeletal muscle volume using pectoralis muscle area and anthropometric measurements from chest CT in a Korean population.
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Baek Kiook, Yoon Soon Ho, Hong Jung Hee
Аннотация
INTRODUCTION: Skeletal muscle is a critical organ influencing prognosis and overall health; however, the direct measurements of muscle mass are not easily attainable. This study aimed to estimate whole-body skeletal muscle volume (WBM) using pectoralis muscle area (PMA) derived from a single chest-CT slice and basic anthropometric data in a Korean population.
METHODS: We analyzed PET-CT data from 201 adults (101 women, 100 men). WBM was segmented using deep learning-based software. The PMA was delineated and was divided into pectoralis major and minor. Sex-specific LASSO regression models were developed: Model 1 included total PMA, Model 2A pectoralis major, Model 2B pectoralis minor, and Model 2C both muscles as separate predictors while Model 3 was based on L3 muscle area for comparison. All models additionally included age, height, weight, and waist circumference.
RESULTS: In females and in males, R² values were 0.76 and 0.75 (Model 1), 0.77 and 0.76 (Model 2C), and 0.84 and 0.81 (Model 3), respectively. Bland-Altman bias were 0.5% (95% CI: -13.6%, 14.7%), 1.1% (95% CI: -20.4%, 22.6%) (Model 1), 0.5% (95% CI: -13.7%, 14.7%) 1.0% (95% CI: -20.1%, 22.2%) (Model 2C), 0.4% (95% CI: -12.2%, 13.0%) and 1.0% (95% CI: -18.2, 20.3) (Model 3), respectively.
CONCLUSION: WBM can be reliably estimated using PMA measured in a single chest-CT slice and basic body measurements (age, height, weight, and waist circumference). This method offers a practical and efficient surrogate for muscle assessment based on routinely acquired chest CT images.
METHODS: We analyzed PET-CT data from 201 adults (101 women, 100 men). WBM was segmented using deep learning-based software. The PMA was delineated and was divided into pectoralis major and minor. Sex-specific LASSO regression models were developed: Model 1 included total PMA, Model 2A pectoralis major, Model 2B pectoralis minor, and Model 2C both muscles as separate predictors while Model 3 was based on L3 muscle area for comparison. All models additionally included age, height, weight, and waist circumference.
RESULTS: In females and in males, R² values were 0.76 and 0.75 (Model 1), 0.77 and 0.76 (Model 2C), and 0.84 and 0.81 (Model 3), respectively. Bland-Altman bias were 0.5% (95% CI: -13.6%, 14.7%), 1.1% (95% CI: -20.4%, 22.6%) (Model 1), 0.5% (95% CI: -13.7%, 14.7%) 1.0% (95% CI: -20.1%, 22.2%) (Model 2C), 0.4% (95% CI: -12.2%, 13.0%) and 1.0% (95% CI: -18.2, 20.3) (Model 3), respectively.
CONCLUSION: WBM can be reliably estimated using PMA measured in a single chest-CT slice and basic body measurements (age, height, weight, and waist circumference). This method offers a practical and efficient surrogate for muscle assessment based on routinely acquired chest CT images.