Intrapatient Changes in CT-Based Body Composition After Initiation of Semaglutide (Glucagon-Like Peptide-1 Receptor Agonist) Therapy

Abstract

BACKGROUND. The long-acting glucagon-like peptide-1 receptor agonist semaglutide is used to treat type 2 diabetes or obesity in adults. Clinical trials have observed associations of semaglutide with weight loss, improved control of diabetes, and cardiovascular risk reduction. OBJECTIVE. The purpose of this study was to evaluate intrapatient changes in body composition after initiation of semaglutide therapy by applying an automated suite of CT-based artificial intelligence (AI) body composition tools. METHODS. This retrospective study included adult patients who were receiving semaglutide treatment and who, between January 2016 and November 2023, underwent abdominopelvic CT within both 5 years before and 5 years after initiation of semaglutide. An automated suite of previously validated CT-based AI body composition tools was applied to scans obtained before semaglutide initiation (hereafter, presemaglutide scans) and scans obtained after semaglutide initiation (hereafter, postsemaglutide scans) to quantify visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) area, skeletal muscle area and attenuation, intermuscular adipose tissue (IMAT) area, liver volume and attenuation, and trabecular bone mineral density (BMD). Patients with weight loss of 5 kg or more and those with weight gain of 5 kg or more between the scans were compared. RESULTS. The study included 241 patients (151 women and 90 men; mean age, 60.4 ± 12.4 [SD] years). In the weight-loss group (n = 67), the postsemaglutide scan, compared with the presemaglutide scan, showed a decrease in VAT area (309.4 vs 341.1 cm², p < .001), SAT area (371.4 vs 410.7 cm², p < .001), muscle area (179.2 vs 193.0, p < .001), and liver volume (2379.0 vs 2578 HU, p = .009) and an increase in liver attenuation (74.5 vs 67.6 HU, p = .03). In the weight-gain group (n = 48), the postsemaglutide scan, compared with the presemaglutide scan, showed an increase in VAT area (334.0 vs 312.8, p = .002), SAT area (485.8 vs 448.8 cm², p = .01), and IMAT area (48.4 vs 37.6, p = .009) and a decrease in muscle attenuation (5.9 vs 13.1, p < .001). Other comparisons were not statistically significant (p > .05). CONCLUSION. Patients using semaglutide who lost versus gained weight showed distinct patterns of changes in CT-based body composition measures. Those with weight loss had overall favorable shifts in measures related to cardiometabolic risk. A decrease in muscle attenuation in those with weight gain is consistent with decreased muscle quality. CLINICAL IMPACT. Among patients using semaglutide, automated CT-based AI tools provide biomarkers of changes in body composition beyond those that are evident by standard clinical measures.

Keywords: CT; artificial intelligence; diabetes; glucagon-like peptide-1 receptor agonist; semaglutide.