CT-Derived Muscle and Adipose Tissue Characteristics and Survival in Advanced NSCLC Treated with First-Line Immunotherapy-Based Regimens

Abstract

Simple Summary Patients with advanced non-small cell lung cancer who receive immunotherapy-based treatment often experience markedly different outcomes, highlighting the need for additional prognostic biomarkers. Routine computed tomography (CT) scans contain valuable information beyond tumor assessment, including measurements of skeletal muscle and body fat. In this retrospective study, we used an artificial intelligence-based tool to automatically quantify body composition from routinely acquired CT images. We investigated both individual body composition parameters and integrated phenotypes combining skeletal muscle volume and visceral adiposity. Higher skeletal muscle density, a marker of better muscle quality, was associated with improved overall survival. Higher visceral adiposity was associated with poorer overall survival. In the exploratory integrated phenotype analysis using cohort-specific, sex-stratified median values, patients with a high-muscle/low-visceral-adiposity phenotype showed numerically favorable survival, although a consistent survival gradient across phenotype groups was not observed. These findings suggest that automated analysis of routine CT scans may provide complementary prognostic information without requiring additional examinations or increasing patient burden. Because this was a single-center retrospective study with a relatively small cohort, our results should be considered exploratory and require confirmation in larger, prospective studies before routine clinical implementation.