Body Composition and Setup Errors in Radiotherapy (BODY-SET)

Radiotherapy is a cornerstone of cancer treatment, with approximately 50-70% of patients requiring radiotherapy during their disease course. Accurate patient positioning is essential for ensuring adequate target volume coverage while sparing organs at risk. Thermoplastic masks are among the most commonly used immobilization devices; however, setup reproducibility varies considerably among patients. Previous studies have demonstrated that patients with BMI ≥24 kg/m² exhibit significantly greater setup errors across multiple directions in breast, cervical, and thoracic cancers compared with normal-weight patients. However, BMI is a crude anthropometric measure that cannot distinguish between fat and muscle mass-two tissue types with fundamentally different mechanical properties that may affect mask fit and positional reproducibility. Bioelectrical impedance analysis (BIA) provides a non-invasive, convenient method for measuring body composition parameters, including skeletal muscle mass (SMM), body fat percentage (BFP), phase angle (PhA), and fat-free mass (FFM). Phase angle, in particular, reflects cell membrane integrity and cellular mass, and has been validated as a sensitive marker of muscle quality and nutritional status in cancer patients. However, the value of BIA-derived body composition parameters in predicting radiotherapy setup errors has not been systematically explored. This study is a single-center, prospective observational cohort study conducted at the Department of Radiation Oncology, Shijiazhuang People's Hospital, China. A total of 120-150 patients with pathologically confirmed malignancies receiving radical or adjuvant intensity-modulated radiotherapy (≥25 fractions) with thermoplastic mask immobilization will be enrolled. Body composition parameters will be measured using BIA at baseline (T0) and at fraction 20 (T1). Setup errors (six degrees of freedom: Tx, Ty, Tz, Rx, Ry, Rz) will be recorded via cone-beam computed tomography (week 1: 3 times; thereafter: weekly). The primary outcome is the association between baseline body composition parameters and setup errors. Secondary outcomes include the relationship between body composition changes and setup error evolution, and identification of threshold values for clinically significant setup error increases. Data will be analyzed using multiple linear regression and generalized estimating equations. Results will be disseminated through peer-reviewed publications and conference presentations.