M. R. Ashraf1, S. Melemenidis1, J. B. Schulz1, and B. W. Loo Jr2; 1Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, 2Department of Radiation Oncology, Stanford University, Stanford, CA
Purpose/Objective(s): Monte Carlo (MC) based treatment planning solutions for FLASH have typically been confined within proprietary treatment planning systems (TPS), lacking a true open-source implementation. This study aims to establish an open-source treatment planning workflow by integrating the Tool for Particle Simulation (TOPAS) MC code with a Python graphical user interface (GUI) to accurately calculate 3D dose across various electron cut-out apertures and geometries. Materials/
Methods: The treatment head of the FLASH-enabled linac was modeled using CAD files. Depth dose and beam profiles were acquired using radiographic film with different circular collimators. A beam model was created through inverse Bayesian optimization, minimizing the difference between measured and simulated profiles. The total particle count for each radiation pulse passing through the beam current transformer (BCT) on the mobile electron linear accelerator was estimated from measurements and then the BCT was integrated into the MC simulation, establishing a calibration relationship between MC output, absolute dose and number of histories. The whole workflow was then used for end-to-end testing incorporating an anatomically correct 3D printed mouse phantom. Results: Inverse optimization yielded a beam energy of 8.4 MeV with a spread of 1 MeV and a source spot size of 2 mm with an angular spread of 4 degrees. The simulated and measured depth dose for the 10 cm collimator agreed to within <1% of each other. Simulated beam profiles for various insert sizes exhibited good agreement (<3%) with the measured profiles, although variations were noted in the low dose region for all profiles. A Python GUI was developed enabling the importation of CT scans and beam apertures to calculate 3D dose distributions by invoking the TOPAS MC code for simulation. Conclusion: A recent multi-institutional dosimetric audit uncovered discrepancies of up to 10%, particularly in areas with tissue inhomogeneities. Given the tissue-protective benefits of FLASH radiation are on the order of 10-20%, it is imperative to employ precise planning and delivery tools. Our open-source MC beam model and Python GUI will be invaluable resources for ensuring accuracy in FLASH research, with the potential for seamless adaptation into clinical trials.
