ESTRO 2025 - Abstract Book

S2714

Physics - Dose calculation algorithms

ESTRO 2025

Conclusion: The new fMC demonstrates performance, both calculation speed and dose accuracy, required to enable the next generation of adaptive treatment strategies.

Keywords: fast monte carlo for adaptiveRT

References: 1. Wee, L., Aerts, H. J.L., Kalendralis, P., & Dekker, A. (2019). Data from NSCLC-Radiomics-Interobserver1 [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/tcia.2019.cwvlpd26.  2. Keall, P. et al. Real-Time Image Guided Ablative Prostate Cancer Radiation Therapy: Results From the TROG 15.01 SPARK Trial. Int J Radiat Oncol Biol Phys 107, 530–538 (2020). 3. Keall, P. et al. Stereotactic prostate adaptive radiotherapy utilising kilovoltage intrafraction monitoring: the TROG 15.01 SPARK trial. BMC Cancer 17, 180 (2017). 4. Heinzerling, et al. Full Dose SBRT in Combination With Mediastinal Chemoradiation for Locally Advanced, Non Small Cell Lung Cancer: LU-008 Trial. Pract Radiat Oncol 13, 531–539 (2023).

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Digital Poster U2Dose - An open source treatment planning for research and education David Tilly, Nina Tilly Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden

Purpose/Objective: To develop an open-source treatment planning code that can be used by anyone with only basic Python skills for the purpose of research and education in radiotherapy in general and proton therapy in particular. Material/Methods: U2Dose was developed as a proton Monte Carlo dose calculation algorithm together with an optimisation engine in an object-oriented Python package that can easily be extended. The dose calculation algorithm implements multiple scattering and nuclear (elastic and non-elastic) interactions with established physics models. Different interaction channels can easily be turned on/off or changed. U2Dose achieves comparable speed to compiled languages using Numba acceleration. The dose calculation was benchmarked vs the TOPAS [1] Monte Carlo code for single mono energetic (100, 150, 200 MeV) spots. Results: The U2Dose code is of high-quality, easily readable, follows published coding guidelines for Python, and with a unit test coverage of > 90%. U2Dose is available as open-source at github.com/davidtilly/U2Dose and collaborations are handled using pull requests. A series of Python Notebooks documents the physical models and exemplifies the functionality of U2Dose that includes the proton Monte Carlo as well as treatment plan optimisation. The U2Dose proton dose calculation passed with gamma 2%/2mm for > 99% of all dose points with dose > 10% of max dose. Conclusion: An open-source easy-to-use Python package was implemented for the purpose of research, collaboration and education in proton radiotherapy.

Keywords: Proton Monte Carlo OpenSource

References: 1. J Perl, J Shin, J Schümann, B Faddegon, H Paganetti. "TOPAS: an innovative proton Monte Carlo platform for research and clinical applications." Med Phys. 2012 Nov; 39(11):6818-37