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WE-C-108-04: A Monte Carlo Investigation of Low-Z Targets in a TrueBeam Linear Accelerator Using Varian Virtualinac.

PURPOSE
The focus of this work was to investigate the implementation of low-Z targets in a TrueBeam linear accelerator (linac) using Monte Carlo simulations.


METHODS
Simulation of a TrueBeam linac was accomplished by using Varian Virtualinac. Virtualinac is a cloud based web application utilizing GEANT4 Monte Carlo code to model TrueBeam components. Phase spaces were recorded above the jaws and used as input to BEAMnrc simulations of the lower portion of TrueBeam. Dose distributions and spectral distributions were calculated using DOSXYZnrc and BEAMdp, respectively. For validation, 6 MV flattened and FFF photon beams were generated and compared to measurement. Two low-Z targets were investigated: a carbon target operated at 2.35 MeV and the proposed 2.50 MeV commercial imaging target. The carbon target was also simulated in a 2100EX Clinac using BEAMnrc. Contrast simulations were made by scoring the dose in the phosphor layer of an IUD20 detector after propagating through 4 and 20 cm thick water and ICRP bone phantoms.


RESULTS
Measured and modeled depth dose curves for 6 MV flattened and FFF beams agree within 2% for 99.7% of points at depths greater than 0.85 cm. The two low-Z target photon spectra produced in TrueBeam are harder than that from a Clinac. Percent dose at depth 10 cm is greater by 8.6% and 14.2%; the fraction of photons in the diagnostic energy range is lower by 7% and 25%; and contrasts are lower by factors of 1.2 and 1.5 (thin phantom) and 1.06 and 1.4 (thick), for the TrueBeam 2.35 MV/carbon and commercial imaging beams, respectively.


CONCLUSION
Virtualinac is effective for Monte Carlo modeling of novel target designs. A significant spectral difference is observed between the low-Z target beam on the Clinac platform, and the proposed imaging beam line on TrueBeam, with the former providing greater diagnostic energy content. This research was supported by Varian Medical Systems and was accomplished using Varian's Virtualinac Monte Carlo application.