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Background: Different modern radiation therapy treatment solutions for breast cancer (BC) and regional nodal irradiation (RNI) have been proposed. In this study, we evaluate the potential reduction in radiation-induced skin morbidity obtained by intensity modulated proton therapy (IMPT) compared with intensity modulated photon therapy (IMXT) for left-side BC and RNI. Material and Methods: Using CT scans from 10 left-side BC patients, treatment plans were generated using IMXT and IMPT techniques. A dose of 50 Gy (or Gy [RBE] for IMPT) was prescribed to the target volume (involved breast, the internal mammary, supraclavicular, and infraclavicular nodes). Two single filed optimization IMPT (IMPT 1 and IMPT 2 ) plans were calculated without and with skin optimization. For each technique, skin dose-metrics were extracted and normal tissue complication probability (NTCP) models from the literature were employed to estimate the risk of radiation-induced skin morbidity. NTCPs for relevant organs-at-risk (OARs) were also considered for reference. The non-parametric Anova (Friedman matched-pairs signed-rank test) was used for comparative analyses. Results: IMPT improved target coverage and dose homogeneity even if the skin was included into optimization strategy (HI IMPT2 = 0.11 vs. HI IMXT = 0.22 and CI IMPT2 = 0.96 vs. CI IMXT = 0.82, p  < .05). A significant relative skin risk reduction (RR = NTCP IMPT /NTCP IMXT ) was obtained with IMPT 2 including the skin in the optimization with a RR reduction ranging from 0.3 to 0.9 depending on the analyzed skin toxicity endpoint/model. Both IMPT plans attained significant OARs dose sparing compared with IMXT. As expected, the heart and lung doses were significantly reduced using IMPT. Accordingly, IMPT always provided lower NTCP values. Conclusions: IMPT guarantees optimal target coverage, OARs sparing, and simultaneously minimizes the risk of skin morbidity. The applied model-based approach supports the potential clinical relevance of IMPT for left-side BC and RNI and might be relevant for the setup of cost-effectiveness evaluation strategies based on NTCP predictions, as well as for establishing patient selection criteria.

Background: Proton beam therapy represents a promising modality for left-side breast cancer (BC) treatment, but concerns have been raised about skin toxicity and poor cosmesis. The aim of this study is to apply skin normal tissue complication probability (NTCP) model for intensity modulated proton therapy (IMPT) optimization in left-side BC., Material and Methods: Ten left-side BC patients undergoing photon irradiation after breast-conserving surgery were randomly selected from our clinical database. Intensity modulated photon (IMRT) and IMPT plans were calculated with iso-tumor-coverage criteria and according to RTOG 1005 guidelines. Proton plans were computed with and without skin optimization. Published NTCP models were employed to estimate the risk of different toxicity endpoints for skin, lung, heart and its substructures., Results: Acute skin NTCP evaluation suggests a lower toxicity level with IMPT compared to IMRT when the skin is included in proton optimization strategy (0.1% versus 1.7%, p < 0.001). Dosimetric results show that, with the same level of tumor coverage, IMPT attains significant heart and lung dose sparing compared with IMRT. By NTCP model-based analysis, an overall reduction in the cardiopulmonary toxicity risk prediction can be observed for all IMPT compared to IMRT plans: the relative risk reduction from protons varies between 0.1 and 0.7 depending on the considered toxicity endpoint., Conclusions: Our analysis suggests that IMPT might be safely applied without increasing the risk of severe acute radiation induced skin toxicity. The quantitative risk estimates also support the potential clinical benefits of IMPT for left-side BC irradiation due to lower risk of cardiac and pulmonary morbidity. The applied approach might be relevant on the long term for the setup of cost-effectiveness evaluation strategies based on NTCP predictions.

Background: Severe acute radiation-induced skin toxicity (RIST) after breast irradiation is a side effect impacting the quality of life in breast cancer (BC) patients. The aim of the present study was to develop normal tissue complication probability (NTCP) models of severe acute RIST in BC patients., Patients and Methods: We evaluated 140 consecutive BC patients undergoing conventional three-dimensional conformal radiotherapy (3D-CRT) after breast conserving surgery in a prospective study assessing acute RIST. The acute RIST was classified according to the RTOG scoring system. Dose-surface histograms (DSHs) of the body structure in the breast region were extracted as representative of skin irradiation. Patient, disease, and treatment-related characteristics were analyzed along with DSHs. NTCP modeling by Lyman-Kutcher-Burman (LKB) and by multivariate logistic regression using bootstrap resampling techniques was performed. Models were evaluated by Spearman's Rs coefficient and ROC area., Results: By the end of radiotherapy, 139 (99%) patients developed any degree of acute RIST. G3 RIST was found in 11 of 140 (8%) patients. Mild-moderate (G1-G2) RIST was still present at 40 days after treatment in six (4%) patients. Using DSHs for LKB modeling of acute RIST severity (RTOG G3 vs. G0-2), parameter estimates were TD50=39 Gy, n=0.38 and m=0.14 [Rs = 0.25, area under the curve (AUC) = 0.77, p = 0.003]. On multivariate analysis, the most predictive model of acute RIST severity was a two-variable model including the skin receiving ≥30 Gy (S30) and psoriasis [Rs = 0.32, AUC = 0.84, p < 0.001]., Conclusions: Using body DSH as representative of skin dose, the LKB n parameter was consistent with a surface effect for the skin. A good prediction performance was obtained using a data-driven multivariate model including S30 and a pre-existing skin disease (psoriasis) as a clinical factor.

Purpose: To develop a predictive multivariate normal tissue complication probability (NTCP) model for radiation-induced heart valvular damage (RVD). The influence of combined heart-lung irradiation on RVD development was included., Material and Methods: Multivariate logistic regression modeling with the least absolute shrinkage and selection operator (LASSO) was used to build an NTCP model to predict RVD based on a cohort of 90 Hodgkin lymphoma patients treated with sequential chemo-radiation therapy. In addition to heart irradiation factors, clinical variables, along with left and right lung dose-volume histogram statistics, were included in the analysis. To avoid overfitting, 10-fold cross-validation (CV) was used for LASSO logistic regression modeling, with 50 reshuffled cycles. Model performance was assessed using the area under the receiver operating characteristic (ROC) curve (AUC) and Spearman's correlation coefficient (Rs)., Results: At a median follow-up time of 55 months (range 12-92 months) after the end of radiation treatment, 27 of 90 patients (30%) manifested at least one kind of RVD (mild or moderate), with a higher incidence of left-sided valve defects (64%). Fourteen prognostic factors were frequently selected (more than 100/500 model fits) by LASSO, which included mainly heart and left lung dosimetric variables along with their volume variables. The averaged cross-validated performance was AUC-CV = 0.685 and Rs = 0.293. The overall performance of a final NTCP model for RVD obtained applying LASSO logistic regression to the full dataset was satisfactory (AUC = 0.84, Rs = 0.55, p < 0.001)., Conclusion: LASSO proved to be an improved and flexible modeling method for variable selection. Applying LASSO, we showed, for the first time, the importance of jointly considering left lung irradiation and left lung volume size in the prediction of subclinical radiation-related heart disease resulting in RVD.

Background: Our aim was to define predictors of late radiation-induced lung injury (RILI) in Hodgkin's lymphoma (HL) survivors treated with bleomycin-containing chemotherapy and radiotherapy., Material and Methods: Eighty consecutive patients treated with chemotherapy and subsequent supradiaphragmatic radiation therapy for HL were retrospectively reviewed for symptoms and/or radiological signs of RILI. Median patient age was 26 years (range 14-55). Left, right, and total lung dosimetric parameters along with clinical, disease, and treatment-related characteristics were analyzed. Multivariate logistic regression analyses were performed. A receiver operator characteristic (ROC) curve analysis was performed to find possible cutoff values dividing patients into high- and low-risk groups., Results: Seven of 80 (9%) patients had lung disease at baseline. Four of 80 (5%) had toxicity after chemotherapy and before the beginning of radiotherapy. These patients were excluded from further evaluation. At a median time of 10 months (range 9-18), 9/69 patients (13%) developed lung radiological changes on computed tomography (CT) after treatment. Four of nine patients were diagnosed RTOG grade ≥ 2. On multivariate analyses, left-lung V30 (p = 0.004, OR = 1.108 95% CI 1.033-1.189) and total-lung V30 (p = 0.009, OR = 1.146 95% CI 1.035-1.270) resulted to be predictors of lung CT changes with a cutoff value of 16% and 15%, respectively. When only symptomatic RILI was considered a left-lung V30 cutoff value of 32% was estimated., Conclusion: Bleomycin and RT may cause lung injury in a small, but significant fraction of HL patients. Left-lung V30 predicts the risk of developing asymptomatic or symptomatic RILI after sequential chemo-radiotherapy.