Cardiac substructure delineation in radiation therapy - A state-of-the-art review.

Delineation of cardiac substructures is crucial for a better understanding of radiation-related cardiotoxicities and to facilitate accurate and precise cardiac dose calculation for developing and applying risk models. This review examines recent advancements in cardiac substructure delineation in the radiation therapy (RT) context, aiming to provide a comprehensive overview of the current level of knowledge, challenges and future directions in this evolving field. Imaging used for RT planning presents challenges in reliably visualising cardiac anatomy. Although cardiac atlases and contouring guidelines aid in standardisation and reduction of variability, significant uncertainties remain in defining cardiac anatomy. Coupled with the inherent complexity of the heart, this necessitates auto-contouring for consistent large-scale data analysis and improved efficiency in prospective applications. Auto-contouring models, developed primarily for breast and lung cancer RT, have demonstrated performance comparable to manual contouring, marking a significant milestone in the evolution of cardiac delineation practices. Nevertheless, several key concerns require further investigation. There is an unmet need for expanding cardiac auto-contouring models to encompass a broader range of cancer sites. A shift in focus is needed from ensuring accuracy to enhancing the robustness and accessibility of auto-contouring models. Addressing these challenges is paramount for the integration of cardiac substructure delineation and associated risk models into routine clinical practice, thereby improving the safety of RT for future cancer patients.

Comprehensive nodal breast VMAT: solving the low-dose wash dilemma using an iterative knowledge-based radiotherapy planning solution.

INTRODUCTION: Aimed to develop a simple and robust volumetric modulated arc radiotherapy (VMAT) solution for comprehensive lymph node (CLN) breast cancer without increase in low-dose wash. METHODS: Forty CLN-breast patient data sets were utilised to develop a knowledge-based planning (KBP) VMAT model, which limits low-dose wash using iterative learning and base-tangential methods as benchmark. Another twenty data sets were employed to validate the model comparing KBP-generated ipsilateral VMAT (ipsi-VMAT) plans against the benchmarked hybrid (h)-VMAT (departmental standard) and bowtie-VMAT (published best practice) methods. Planning target volume (PTV), conformity/homogeneity index (CI/HI), organ-at-risk (OAR), remaining-volume-at-risk (RVR) and blinded radiation oncologist (RO) plan preference were evaluated. RESULTS: Ipsi- and bowtie-VMAT plans were dosimetrically equivalent, achieving greater nodal target coverage (P < 0.05) compared to h-VMAT with minor reduction in breast coverage. CI was enhanced for a small reduction in breast HI with improved dose sparing to ipsilateral-lung and humeral head (P < 0.05) at immaterial expense to spinal cord. Significantly, low-dose wash to OARs and RVR were comparable between all plan types demonstrating a simple VMAT class solution robust to patient-specific anatomic variation can be applied to CLN breast without need for complex beam modification (hybrid plans, avoidance sectors or other). This result was supported by blinded RO review. CONCLUSIONS: A simple and robust ipsilateral VMAT class solution for CLN breast generated using iterative KBP modelling can achieve clinically acceptable target coverage and OAR sparing without unwanted increase in low-dose wash associated with increased second malignancy risk.