Author: Hongjing Sun, Weibing Yang, Timothy C. Zhu, Yifeng Zhu 👨🔬
Affiliation: University of Pennsylvania 🌍
Purpose: This study aims to compare the commissioning results of TrueBeam and Halcyon linear accelerators with Monte Carlo (MC) simulations conducted using TOPAS. The ultimate goal is to leverage MC simulations to accurately estimate surface radiation dose for Cherenkov imaging applications, addressing the challenges associated with obtaining surface dose measurements through conventional experimental techniques.
Methods: Commissioning measurements for both the TrueBeam and Halcyon linear accelerators were conducted using a standard water phantom and a standardized experimental setup. Surface dose measurements on the phantom were obtained using a diode detector, while all other measurements were performed with a standard Farmer chamber. Key parameters, including beam profiles and percent depth dose (PDD) for various field sizes shaped by the multi-leaf collimator (MLC), were measured. Monte Carlo (MC) simulations using TOPAS were carried out for each machine, replicating the experimental conditions to ensure consistency.
Results: The MC simulation results for both TrueBeam and Halcyon showed good agreement with the commissioning data, with discrepancies within clinically acceptable limits. The MC simulations successfully modeled the PDD including buildup region for various field sizes, which is obtained by merging diode and thimble chamber measurements for buildup region and deeper depths, respectively. Profiles at depths dmax, 5, 10, 20, 30 cm were compared between MC and measurements for various field sizes and a slit field of 3x 35 cm and 4x28 cm for truebeam and halcyon, respectively, to be in good agreement. The findings suggest that MC simulations can reliably predict surface dose for Cherenkov imaging.
Conclusion: Monte Carlo simulations offer an accurate and reliable method for calculating surface radiation dose, addressing the limitations of experimental techniques. This approach is valuable for the simulation and optimization of Cherenkov imaging in clinical settings, where precise surface dose information is critical.