Limited impact of CT-based breast tissue composition on skin toxicity, fibrosis, edema and liponecrosis prediction after moderately hypofractionated whole-breast radiotherapy.

BACKGROUND: The study assessed the role of CT-based breast tissue composition in predicting toxicities after moderately hypofractionated whole-breast postoperative Radiotherapy. MATERIALS AND METHODS: A mono-institutional cohort of 1127 patients (2009-2017) treated with 40 Gy/15 fractions was analyzed. Endpoints included acute RTOG toxicities (ACUG2 + ), 6-month edema/hyperpigmentation (EDMG2 + ), 3-year Fibrosis-Atrophy-Telangiectasia-Pain (FATP) and Liponecrosis (LIPNEC). HU-histograms (-200 to + 70 HU) were extracted from planning CTs using custom Python code, deriving mean/median HU, SD, kurtosis, skewness, percentiles, and fat/fibroglandular volumetric fractions. The population was split into training/validation (800/327). Univariate and Multivariate Logistic Regression and a bootstrap-based machine learning approach were performed, including CTV volume as a potential predictor. RESULTS: ACUG2+/EDMG2+/FATP/LIPNEC rates were 14.5%/4.5%/4.3%/11% respectively. CTV volume was significantly associated with all endpoints. No HU-histogram parameter increased the predictive power of CTV volume for ACUG2+/EDMG2+/FATP (AUC_val = 0.56/0.65/0.68). For LIPNEC, a model combining HU-Mean and the count of the maximum HU value of the histogram was the most predictive (AUC_val = 0.58). Subgroup analyses stratified by CTV volume revealed that a larger adipose fraction may exert a protective effect on acute skin reactions and edema in patients with smaller breasts. CONCLUSIONS: HU-histogram parameters show limited association with toxicities compared to CTV volume. However, subgroup analyses suggest a volume-dependent contribution of breast tissue composition, with adipose tissue playing a protective role for ACUG2 + and EDMG2 + in smaller-volume strata.