The Risk of Cardiac Disease in Asian Breast Cancer Patients: Impact of Patient-Specific Factors and Heart Dose Based on Individual Heart Dose Calculation from Three-Dimensional RT Planning

Normal tissue exposure and second malignancy risk in vertebral-body-sparing craniospinal irradiation

The purpose of this study was to compare dose to anterior organs at risk (OARs) and quantify the risk of developing secondary malignancy (SMN) in pediatric patients treated with vertebral-body-sparing (VBS) vs vertebral body (VB) pencil beam scanning proton craniospinal irradiation (CSI). Comparative plans of VBS and VB CSI were created for 10 previously treated patients. Dose-volume histograms were used to evaluate dose to OARs. Absolute excess risk of SMN was calculated according to the organ-specific, radiation-induced cancer incidence based on the organ equivalent dose. OAR dosimetric parameters and absolute excess risk of SMN were compared for VBS and VB plans using the Kruskal-Wallis H test (α = 0.05). VBS CSI leads to significantly lower radiation dose to the heart, esophagus, kidney, liver and bowel. Excluding the vertebral body also significantly decreases the absolute excess risk of SMN for liver, esophagus and bowel. For these reasons, implementation of VBS pencil beam scanning proton CSI should be considered.

Hypofractionated volumetric-modulated arc therapy for breast cancer: A propensity-score-weighted comparison of radiation-related toxicity

We assessed the clinical benefit of combining volumetric-modulated arc therapy (VMAT) and hypofractionated radiotherapy (HF-RT) considering the incidence of radiation-related toxicities. After a retrospective review for breast cancer patients treated with adjuvant RT between 2005 and 2017, a total of 4209 patients treated with three-dimensional conventional fractionation (CF-3D, 50.4 Gy/28 fractions) and 1540 patients treated with HF-RT (768 received HF-3D; 772, HF-VMAT; 40 Gy/15 fractions) were included. A total of 2229 patients (38.8%) received regional node irradiation (RNI): 1642 (39.0%), 167 (21.7%) and 420 (54.4%) received RNI via CF-3D, HF-3D and HF-VMAT, respectively. Acute/subacute and late toxicities were evaluated. Propensity scores were calculated via logistic regression. Grade 2+ acute/subacute toxicities was the highest in CF-3D group (15.0%, 2.6% and 1.6% in CF-3D, HF-3D and HF-VMAT, respectively; P < .001). HF-VMAT reduced Grade 2+ acute/subacute toxicities significantly compared to CF-3D (odds ratio [OR] 0.11, P < .001) and HF-3D (OR 0.45, P = .010). The 3-year cumulative rate of late toxicities was 18.0% (20.1%, 10.9% and 13.4% in CF-3D, HF-3D and HF-VMAT, respectively; P < .001). On sensitivity analysis, the benefit of HF-VMAT was high in the RNI group. Acute and late toxicities were fewer after HF-VMAT than after HF-3D or CF-3D, especially in women who underwent RNI.

Clinical evaluation of atlas- and deep learning-based automatic segmentation of multiple organs and clinical target volumes for breast cancer

Manual segmentation is the gold standard method for radiation therapy planning; however, it is time-consuming and prone to inter- and intra-observer variation, giving rise to interests in auto-segmentation methods. We evaluated the feasibility of deep learning-based auto-segmentation (DLBAS) in comparison to commercially available atlas-based segmentation solutions (ABAS) for breast cancer radiation therapy. This study used contrast-enhanced planning computed tomography scans from 62 patients with breast cancer who underwent breast-conservation surgery. Contours of target volumes (CTVs), organs, and heart substructures were generated using two commercial ABAS solutions and DLBAS using fully convolutional DenseNet. The accuracy of the segmentation was assessed using 14 test patients using the Dice Similarity Coefficient and Hausdorff Distance referencing the expert contours. A sensitivity analysis was performed using non-contrast planning CT from 14 additional patients. Compared to ABAS, the proposed DLBAS model yielded more consistent results and the highest average Dice Similarity Coefficient values and lowest Hausdorff Distances, especially for CTVs and the substructures of the heart. ABAS showed limited performance in soft-tissue-based regions, such as the esophagus, cardiac arteries, and smaller CTVs. The results of sensitivity analysis between contrast and non-contrast CT test sets showed little difference in the performance of DLBAS and conversely, a large discrepancy for ABAS. The proposed DLBAS algorithm was more consistent and robust in its performance than ABAS across the majority of structures when examining both CTVs and normal organs. DLBAS has great potential to aid a key process in the radiation therapy workflow, helping optimise and reduce the clinical workload.