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Figure 1. A schematic illustration of the proton beam nozzle and a water phantom modeled by TOPAS. The initial proton beam is directed from left to right. The central line in the water phantom (gray line) indicates the scoring volume used to calculate the percent depth dose.

Figure 2. Flowchart for patient dose calculation using TOPAS. The upper section is for recording phase-space file and the lower section is for patient dose calculation.​

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Figure 3. The results of the dose calculation in the IMN case. The upper rows show the dose distribution calculated with Eclipse RTP (a) and TOPAS MC (b). The lower rows show the corresponding dose difference (c) and gamma plot (d). DVHs calculated​

Abstract

For the independent validation of treatment plans, we developed a fully automated Monte Carlo (MC)-based patient dose calculation system with the tool for particle simulation (TOPAS) and proton therapy machine installed at the National Cancer Center in Korea to enable routine and automatic dose recalculation for each patient. The proton beam nozzle was modeled with TOPAS to simulate the therapeutic beam, and MC commissioning was performed by comparing percent depth dose with the measurement. The beam set-up based on the prescribed beam range and modulation width was automated by modifying the vendor-specific method. The CT phantom was modeled based on the DICOM CT files with TOPAS-built-in function, and an in-house-developed C++ code directly imports the CT files for positioning the CT phantom, RT-plan file for simulating the treatment plan, and RT-structure file for applying the Hounsfield unit (HU) assignment, respectively. The developed system was validated by comparing the dose distributions with those calculated by the treatment planning system (TPS) for a lung phantom and two patient cases of abdomen and internal mammary node. The results of the beam commissioning were in good agreement of up to 0.8 mm2 [Formula: see text] for B8 option in both of the beam range and the modulation width of the spread-out Bragg peaks. The beam set-up technique can predict the range and modulation width with an accuracy of 0.06% and 0.51%, respectively, with respect to the prescribed range and modulation in arbitrary points of B5 option (128.3, 132.0, and 141.2 mm2 [Formula: see text] of range). The dose distributions showed higher than 99% passing rate for the 3D gamma index (3 mm distance to agreement and 3% dose difference) between the MC simulations and the clinical TPS in the target volume. However, in the normal tissues, less favorable agreements were obtained for the radiation treatment planning with the lung phantom and internal mammary node cases. The discrepancies might come from the limitations of the clinical TPS, which is the inaccurate dose calculation algorithm for the scattering effect, in the range compensator and inhomogeneous material. Moreover, the steep slope of the compensator, conversion of the HU values to the human phantom, and the dose calculation algorithm for the HU assignment also could be reasons of the discrepancies. The current study could be used for the independent dose validation of treatment plans including high inhomogeneities, the steep compensator, and riskiness such as lung, head & neck cases. According to the treatment policy, the dose discrepancies predicted with MC could be used for the acceptance decision of the original treatment plan.

Author information

Shin WG1, Testa M, Kim HS, Jeong JH, Lee SB, Kim YJ, Min CH.

1Department of Radiation Convergence Engineering, Yonsei University, Wonju, Korea.