Monte Carlo simulations for brachytherapy

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Brachytherapy is an internal radiation treatment where a small, encapsulated radioactive source is placed at different dwell positions close to or within the tumor. The standard method for treatment planning in brachytherapy is to follow the TG43-formalism where the full patient geometry is treated as water. This approximation has limitations in the modelling of skin–air interfaces and tissue variations and does not take into consideration shielding effects. To overcome the limitations of this analytical framework, Monte Carlo (MC) simulations can be used. To reduce the computational time, which is often a limiting factor in MC computations, pre-generated information about the radiation can be utilized. In this work, independent Monte Carlo simulations performed with the software egs_brachy are setup to characterize the radiation from a high-dose-rate brachytherapy source. The output is a phase space with information about the radiation properties. The phase space is analyzed and resulted in a 4D-histogram which can be used as an input to the brachy Monte Carlo dose engine prototype in the treatment planning system RayStation®. In addition to constructing the input data, dose distributions for two different treatment plans are scored with egs_brachy in both water and tissue. The same treatment plans are used to compute dose with TG43 and the brachy Monte Carlo prototype and the dose distributions are compared with the ones obtained with egs_brachy. Local gamma tests were performed with gamma criteria (1%/1 mm) and (3%/2 mm), yielding low fail rates in comparison to both RayStation dose engines. The favorable gamma results show that both TG43 and the brachy Monte Carlo dose engine can reproduce the simulated dose distributions from egs_brachy well. In conclusion, the produced phase space is suitable as input for the brachy MC dose engine and the simulated dose distributions can be utilized in a validation framework.

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brachytherapy, treatment planning, dose calculation, Monte Carlo simulations, phase space

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