Obesity (Silver Spring). 2025 Mar 6. doi: 10.1002/oby.24243. Online ahead of print.
ABSTRACT
OBJECTIVE: The objective of this study was to examine associations of computed tomography (CT)-derived musculoskeletal measures with demographics and traditional musculoskeletal characteristics.
METHODS: The Incorporating Nutrition, Vests, Education, and Strength Training (INVEST) in Bone Health trial (NCT04076618) acquired a battery of musculoskeletal measures in 150 older-aged adults living with overweight or obesity. At baseline, CT (i.e., volumetric bone mineral density, cortical thickness, muscle radiomics, and muscle/intermuscular adipose tissue [IMAT] area and density), dual-energy x-ray absorptiometry (DXA; i.e., areal bone mineral density, total body fat mass, appendicular lean mass, and lean body mass), and strength assessments (i.e., grip and knee extensor strength) were collected, along with demographic and clinical characteristics. Analyses employed linear regression and mixed-effects models along with factor analysis for dimensionality reduction of the radiomics data.
RESULTS: Participants were older-aged (mean [SD] age: 66 [5] years), mostly female (75%), and were living with overweight or obesity (mean [SD] BMI: 33.6 [3.3] kg/m2). Age was not significantly associated with most CT-derived bone, IMAT, or muscle measures. BMI was significantly associated with DXA and CT-derived muscle and IMAT measures, which were higher in male than female individuals (all p < 0.01). For the midthigh, muscle size was significantly related to grip and knee extensor strength (both p < 0.01).
CONCLUSIONS: Machine learning-derived CT metrics correlated strongly with DXA and muscle strength, with higher BMI linked to greater IMAT and poorer muscle quality.
PMID:40051020 | DOI:10.1002/oby.24243
