Association between low skeletal muscle mass assessed by deep learning-based CT and MASLD: a prospective cohort study.
Authors
Affiliations (10)
Affiliations (10)
- Health Management Center, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China.
- Department of Health Management, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
- Department of Radiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China.
- Lab for Artificial Intelligence in Medical Imaging (LAIMI), School of Medical Imaging, Nanjing Medical University, Nanjing, Jiangsu, China.
- Department of Information, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China.
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
- Health Management Center, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China. [email protected].
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China. [email protected].
- Health Management Center, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China. [email protected].
- Department of Health Management, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China. [email protected].
Abstract
To explore the role of abdominal skeletal muscle mass in metabolic dysfunction-associated steatotic liver disease (MASLD) incidence and resolution, we established two independent cohorts in a Chinese population. This study included 3139 participants without MASLD (incidence cohort) and 1130 MASLD patients (resolution cohort) at baseline, all of whom underwent abdominal computed tomography (CT) during routine health examinations from 2019 to 2024. Skeletal muscle mass was quantified from the third lumbar vertebra (L3) CT images using automated deep learning and analyzed in tertiles. MASLD was diagnosed by ultrasonographic hepatic steatosis and cardiometabolic risk factors. Cox models assessed the association of muscle mass with MASLD; logistic regression was used to assess the joint effects of skeletal muscle change rate and MASLD-related genetic risk on resolution. Among the incidence cohort (median follow-up: 1.8 years), 516 developed MASLD. Lower body weight-adjusted total abdominal muscle area (TAMA/weight) was associated with higher MASLD incidence, regardless of sex. Compared with the highest tertile of TAMA/weight, the lowest tertile had hazard ratio (HR) of 2.39 (95% confidence interval [CI], 1.75 to 3.26) in men, and 2.11 (95% CI, 1.45 to 3.07) in women, respectively. Higher annual TAMA/weight promoted MASLD resolution, with the odds ratio (OR) of 1.81 (95% CI, 1.28-2.56) in men and 1.75 (95% CI, 1.04-2.96) in women. Increased muscle mass tended to be more associated with MASLD resolution in low genetic risk individuals. Lower muscle mass correlates with higher MASLD risk. Increasing skeletal muscle mass may help prevent and manage the disease.