Prediction of radiation pneumonitis using the effective α/β of lungs and heart in NSCLC patients treated with proton beam therapy

Purpose: Radiation pneumonitis (RP) remains a major complication in non-small cell lung cancer (NSCLC) patients undergoing radiochemotherapy (RCHT). Traditionally, the mean lung dose (MLD) and the volume of the total lung receiving at least 20 Gy (V-20Gy) are used to predict RP in patients treated with normo-fractionated photon therapy. However, other models, including the actual dose-distribution in the lungs using the effective alpha/beta model or a combination of radiation doses to the lungs and heart, have been proposed for predicting RP. Moreover, the models established for photons may not hold for patients treated with passively-scattered proton therapy (PSPT). Therefore, we here tested and validated novel predictive parameters for RP in NSCLC patient treated with PSPT. Methods: Data on the occurrence of RP, structure files and dose-volume histogram parameters for lungs and heart of 96 NSCLC patients, treated with PSPT and concurrent chemotherapy, was retrospectively retrieved from prospective clinical studies of two international centers. Data was randomly split into a training set (64 patients) and a validation set (32 patients). Statistical analyses were performed using binomial logistic regression. Results: The biologically effective dose (BED) of the 'lungs - GTV' significantly predicted RP = grade 2 in the training-set using both a univariate model (p = 0.019, AUC(train) = 0.72) and a multivariate model in combination with the effective alpha/beta parameter of the heart (p(BED) = 0.006, p(alpha/beta eff) = 0.043, AUC(train) = 0.74). However, these results did not hold in the validation-set (AUC(val) = 0.52 andAUC(val) = 0.50, respectively). Moreover, these models were found to neither outperform a model built with the MLD (p = 0.015, AUC(train) = 0.73, AUC(val) = 0.51), nor a multivariate model additionally including the V-20Gy of the heart (p(MLD) = 0.039, p(V20Gy,heart) = 0.58, AUC(trai)n = 0.74, AUCval = 0.53). Conclusion: Using the effective alpha/beta parameter of the lungs and heart we achieved similar performance to commonly used models built for photon therapy, such as MLD, in predicting RP >= grade 2. Therefore, prediction models developed for photon RCHT still hold for patients treated with PSPT.

Automated summary

Traditional models for predicting radiation pneumonitis may not be applicable to non-small cell lung cancer patients treated with passively-scattered proton therapy. The use of effective alpha/beta parameter can predict the occurrence of radiation pneumonitis in these patients.