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arXiv · 2107.12184

Development and validation of an optimal GATE model for proton pencil-beam scanning delivery

A. Asadi·A. Akhavanallaf·S. A. Hosseini·N. vosoughi·H. Zaidi
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Abstract

Objective: To develop and validate an independent Monet Carlo dose calculation engine to support for software verification of treatment planning systems and quality assurance workflow. Method: GATE Monte Carlo toolkit was employed to simulate a fixed horizontal active scan-based proton beam delivery. Within the nozzle, two primary and secondary dose monitors have been designed allowing to compare the accuracy of dose estimation from MC simulation with respect to physical quality assurance measurements. The developed beam model was validated against a series of commissioning measurements using pinpoint chambers and 2D array ionization chambers in terms of lateral profiles and depth dose distributions. Furthermore, beam delivery module and treatment planning has been validated against the literature deploying various clinical test cases of AAPM TG-119 and a prostate patient. Result: MC simulation showed an excellent agreement with measurements in the lateral depth-dose parameters and SOBP characteristics within maximum relative error of 0.95% in range, 3.4% in entrance to peak ratio, 2.3% in mean point to point, and 0.852% in peak location. Mean relative absolute difference between MC simulation and the measurement in terms of absorbed dose in SOBP region was $0.93\% \pm 0.88\%$. Clinical phantom study showed a good agreement compared to a commercial treatment planning system (relative error for TG-119 PTV-D${}{95}$ $\mathrm{\sim}$ 1.8%; and for prostate PTV-D$_{95}$ $\mathrm{\sim}$ -0.6%). Conclusion: The results confirm the capability of GATE simulation as a reliable surrogate for verifying TPS dose maps prior to patient treatment.

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A. Asadi, A. Akhavanallaf, S. A. Hosseini, N. vosoughi, H. Zaidi. 2021-07-23. Development and validation of an optimal GATE model for proton pencil-beam scanning delivery. https://arxiv.org/abs/2107.12184

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