Cumulative rib fracture risk after stereotactic body radiotherapy in patients with localized non-small cell lung cancer.

INTRODUCTION: Rib fracture is a known complication after stereotactic body radiotherapy (SBRT). Patient-related parameters are essential to provide patient-tailored risk estimation, however, their impact on rib fracture is less documented compared to dosimetric parameters. This study aimed to predict the risk of rib fractures in patients with localized non-small cell lung cancer (NSCLC) post-SBRT based on both patient-related and dosimetric parameters with death as a competing risk. MATERIALS AND METHODS: In total, 602 patients with localized NSCLC treated with SBRT between 2010-2020 at Odense University Hospital, Denmark were included. All patients received SBRT with 45-66 Gray (Gy)/3 fractions. Rib fractures were identified in CT-scans using a word embedding model. The cumulative incidence function was based on cause-specific Cox hazard models with variable selection based on cross-validation model likelihood performed using 50 bootstraps. RESULTS: In total, 19 % of patients experienced a rib fracture. The cumulative risk of rib fracture increased rapidly from 6-54 months post-SBRT. Female gender, bone density, near max dose to the rib, V30 and V40 to the rib, gross tumor volume, and mean lung dose were significantly associated with rib fracture risk in univariable analysis. The final multi-variable model consisted of V20 and V30 to the rib and mean lung dose. CONCLUSION: Female gender and low bone density in male patients are significant predictors of rib fracture risk. The final model predicting cumulative rib fracture risk of 19 % in patients with localized NSCLC treated with SBRT contained no patient-related parameters, suggesting that dosimetric parameters are the primary drivers.

Heart and Lung Dose as Predictors of Overall Survival in Patients With Locally Advanced Lung Cancer. A National Multicenter Study.

Introduction: It is an ongoing debate how much lung and heart irradiation impact overall survival (OS) after definitive radiotherapy for lung cancer. This study uses a large national cohort of patients with locally advanced NSCLC to investigate the association between OS and irradiation of lung and heart. Methods: Treatment plans were acquired from six Danish radiotherapy centers, and patient characteristics were obtained from national registries. A hybrid segmentation tool automatically delineated the heart and substructures. Dose-volume histograms for all structures were extracted and analyzed using principal component analyses (PCAs). Parameter selection for a multivariable Cox model for OS prediction was performed using cross-validation based on bootstrapping. Results: The population consisted of 644 patients with a median survival of 26 months (95% confidence interval [CI]: 24-29). The cross-validation selected two PCA variables to be included in the multivariable model. PCA1 represented irradiation of the heart and affected OS negatively (hazard ratio, 1.14; 95% CI: 1.04-1.26). PCA2 characterized the left-right balance (right atrium and left ventricle) irradiation, showing better survival for tumors near the right side (hazard ratio, 0.92; 95% CI: 0.84-1.00). Besides the two PCA variables, the multivariable model included age, sex, body-mass index, performance status, tumor dose, and tumor volume. Conclusions: Besides the classic noncardiac risk factors, lung and heart doses had a negative impact on survival, while it is suggested that the left side of the heart is a more radiation dose-sensitive region. The data indicate that overall heart irradiation should be reduced to improve the OS if possible.

Radiation therapy in older patients with cancer.

The general population is aging, which expectedly will lead to a future increase in older patients with cancer. This review summarises the recent advances in radiotherapy. Technological advances have led radiotherapy to be an efficient and well-tolerated treatment option in older patient with cancer. Studies show no difference in toxicity and disease control rates compared with the ones in younger patients with cancer. MR-guided radiotherapy, proton therapy, and integration of artificial intelligence in treatment planning represent the latest advances in the field of radiotherapy and hold potential to further improve the treatment of older patients with cancer.

An open source auto-segmentation algorithm for delineating heart and substructures - Development and validation within a multicenter lung cancer cohort.

BACKGROUND AND PURPOSE: Irradiation of the heart in thoracic cancers raises toxicity concerns. For accurate dose estimation, automated heart and substructure segmentation is potentially useful. In this study, a hybrid automatic segmentation is developed. The accuracy of delineation and dose predictions were evaluated, testing the method's potential within heart toxicity studies. MATERIALS AND METHODS: The hybrid segmentation method delineated the heart, four chambers, three large vessels, and the coronary arteries. The method consisted of a nnU-net heart segmentation and partly atlas- and model-based segmentation of the substructures. The nnU-net training and atlas segmentation was based on lung cancer patients and was validated against a national consensus dataset of 12 patients with breast cancer. The accuracy of dose predictions between manual and auto-segmented heart and substructures was evaluated by transferring the dose distribution of 240 previously treated lung cancer patients to the consensus data set. RESULTS: The hybrid auto-segmentation method performed well with a heart dice similarity coefficient (DSC) of 0.95, with no statistically significant difference between the automatic and manual delineations. The DSC for the chambers varied from 0.78-0.86 for the automatic segmentation and was comparable with the inter-observer variability. Most importantly, the automatic segmentation was as precise as the clinical experts in predicting the dose distribution to the heart and all substructures. CONCLUSION: The hybrid segmentation method performed well in delineating the heart and substructures. The prediction of dose by the automatic segmentation was aligned with the manual delineations, enabling measurement of heart and substructure dose in large cohorts. The delineation algorithm will be available for download.