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The Use of Variance Reduction Techniques for Photon Dose Estimation in the Design of Radiotherapy Facilities at 10 and 15 MeV via Monte Carlo Simulations

C. Fedon, R. P. Kollaard, A. Metz

Nuclear Science and Engineering / Volume 199 / Number 1S / April 2025 / Pages S500-S506

Research Article / dx.doi.org/10.1080/00295639.2024.2357435

Received:November 17, 2023
Accepted:May 14, 2024
Published:April 30, 2025

In the context of designing radiotherapy facilities, typical dose estimation methods involve analytical approaches, as outlined in International Atomic Energy Agency (IAEA) Safety Reports Series No. 47 (IAEA 47). These methods are known for their ease of use and rapid calculations, but they could lead to either overestimation or underestimation of radiation doses. Hence, the integration of Monte Carlo (MC) methods is considered valuable. In this particular study, a radiotherapy facility was modeled using MCNP version 6.2, and dose calculations were conducted using analytical techniques following both IAEA 47 guidelines and MC simulations. The study focused on monoenergetic photon cone beams with energies of 10 and 15 MeV. Notably, the beam’s orientation prevented primary radiation from reaching the dose location at the entrance of the maze, allowing only scatter radiation to contribute to the tally. Given the challenges associated with obtaining reliable and accurate results through standard MCNP calculations, the investigation focused on the use of weight windows as a variance reduction technique. The findings revealed that the IAEA method tends to provide conservative results only when the same conditions were replicated in the MC simulations. In fact, approximately 50% of the final dose estimated through MC methods accounted for factors that were not considered in the analytical calculations. The primary contributor to scattering (averaging around 30%) was identified as the floor and ceiling. This study underscores the need for caution when relying solely on the analytical approach, as it may not consistently yield conservative outcomes.