Validation of the analytical irradiator model and Monte Carlo dose engine in the small animal irradiation treatment planning system µ-RayStation 8B

Abstract

Dose calculation in preclinical context with a clinical level of accuracy is a challenge due to the small animal scale and the medium photon energy range. In this work, we evaluate the effectiveness and accuracy of an analytical irradiator model combined with Monte Carlo (MC) calculations in the irradiated volume to calculate the dose delivered by a modern small animal irradiator.A model of the XRAD225Cx was created in µ-RayStation 8B, a preclinical treatment planning system, allowing arc and static beams for seven cylindrical collimators. Calculations with the µ-RayStation MC dose engine were compared with EBT3 measurements in water for all static beams and with a validated GATE model in water, heterogeneous media and a mouse CT. The GATE model is a complete MC representation of the XRAD225Cx.In water, µ-RayStation calculations, compared to GATE calculations and EBT3 measurements, agreed within a maximal error of 3.2% (mean absolute error of 0.6% and 0.8% respectively) and maximal distance-to-agreement (DTA) was 0.2 mm at 50% of the central dose. For a 5 mm static beam in heterogeneous media, the maximal absolute error between µ-RayStation and GATE calculations was below 1.3% in each medium and DTA was 0.1 mm at interfaces. For calculations on a mouse CT, µ-RayStation and GATE calculations agreed well for both static and arc beams. The 2D local gamma passing rate was >98.9% for 1%/0.3 mm criteria and >92.9% for 1%/0.2 mm criteria. Moreover, µ-RayStation reduces calculation time significantly comparing with GATE (speed-up factor between 120 and 680).These findings show that the analytical irradiator model presented in this work combined with the µ-RayStation MC dose engine accurately computes dose for the XRAD225Cx irradiator. The improvements in calculation time and availability of functionality and tools for managing, planning and evaluating the irradiation makes this platform very useful for pre-clinical irradiation research.