Author: David Ayala Alvarez, Facundo Ballester, Luc Beaulieu, Francisco Berumen-Murillo, Jean-Simon Cote, Ernesto Mainegra-Hing, Iymad Mansour, Gaël Ndoutoume-Paquet, Rowan M. Thomson, Christian Valdes, Javier Vijande, Peter G. Watson 👨🔬
Affiliation: Département de physique, de génie physique et d'optique, Université Laval, Laval University, Princess Margaret Cancer Centre, McGill University, Department of Physics and Medical Physics Unit, McGill University, IFIC-UV, University of Valencia, National Research Council Canada, Carleton University, 5Service de Physique Médicale et de Radioprotection, Centre Intégré de Cancérologie, CHU de Québec- Université Laval et Centre de recherche du CHU de Québec, Nuclear Medicine Department, Hospital Regional de Antofagasta 🌍
Purpose: Modelling electronic brachytherapy (eBT) sources is difficult because of the high-dose gradients and challenges associated with low-energy modelling. This study examines the accuracy of available treatment planning software and provides clinical users with the first two clinical test cases for commissioning eBT model-based dose calculation algorithms (MBDCA).
Methods: MC simulations of the INTRABEAM® eBT system with a surface applicator were conducted using EGSnrc and Penelope MC codes as reference to validate the accuracy of the MC-based treatment planning software Radiance. Two test cases for level 1 (TG43 scenario; homogeneous water phantom) and 2 (clinical scenario; heterogeneous phantom simulating skin treatment consisting of 4 slabs of skin, adipose, bone and soft-tissue) were modelled. Dosimetric data from both test cases calculated using Penleope, EGSnrc, and Radiance are hosted online for public access.
Results: For both scenario 1 and 2, voxel-by-voxel differences between the TPS and reference MC codes were below 5% in the first 0.5 cm along the central axis, and average global differences within the phantom were below 1%. Areas of large difference (>5%) in the Radiance TPS are typically localized in areas off-axis (penumbra and umbra regions), deep within the scoring volume (where the magnitude of dose is generally small), and downstream from areas of large differences in material composition (i.e., bone to soft-tissue).
Conclusion: This dataset represents a valuable resource for the commissioning of electronic brachytherapy MBDCAs, providing a foundation for the development of clinical test cases for other eBT systems. Additionally, it serves as an educational tool for examining the unique characteristics, advantages, and limitations of various eBT devices. Moreover, brachytherapy researchers requiring a benchmark for dosimetric calculations in the low-energy domain will find this dataset indispensable.