This study evaluated the utility of CT-based psoas muscle volume (PV) as a novel diagnostic indicator for sarcopenia. Sarcopenia, characterized by progressive skeletal muscle mass loss, significantly impacts quality of life and increases the risk of various health complications. The research team quantified psoas muscle volume from CT imaging using automated segmentation and analyzed its correlation with conventional skeletal muscle index (SMI)-based diagnostic criteria. AVIEW Body-Composition software (Coreline Soft, Seoul, Korea) was used to automatically segment the psoas muscle area and quantify PV values, employing the nnU-Net segmentation algorithm. Results demonstrated that PV showed high concordance with existing sarcopenia diagnostic criteria, and that 3D volumetric measurement is a more robust diagnostic indicator compared to single-slice area measurements. This study proposes PV as an effective new diagnostic criterion for sarcopenia, suggesting its potential for improving early detection and clinical management of sarcopenia in elderly patients.