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Geant4 beam model for boron neutron capture therapy: investigation of neutron dose components

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Abstract

Boron neutron capture therapy (BNCT) is a biochemically-targeted type of radiotherapy, selectively delivering localized dose to tumour cells diffused in normal tissue, while minimizing normal tissue toxicity. BNCT is based on thermal neutron capture by stable \(^{10}\)B nuclei resulting in emission of short-ranged alpha particles and recoil \(^7\)Li nuclei. The purpose of the current work was to develop and validate a Monte Carlo BNCT beam model and to investigate contribution of individual dose components resulting of neutron interactions. A neutron beam model was developed in Geant4 and validated against published data. The neutron beam spectrum, obtained from literature for a cyclotron-produced beam, was irradiated to a water phantom with boron concentrations of 100 μg/g. The calculated percentage depth dose curves (PDDs) in the phantom were compared with published data to validate the beam model in terms of total and boron depth dose deposition. Subsequently, two sensitivity studies were conducted to quantify the impact of: (1) neutron beam spectrum, and (2) various boron concentrations on the boron dose component. Good agreement was achieved between the calculated and measured neutron beam PDDs (within 1%). The resulting boron depth dose deposition was also in agreement with measured data. The sensitivity study of several boron concentrations showed that the calculated boron dose gradually converged beyond 100 μg/g boron concentration. This results suggest that 100μg/g tumour boron concentration may be optimal and above this value limited increase in boron dose is expected for a given neutron flux.

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Reproduced with permission from the data of Nigg et al. [16]

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Reproduced with permission from the data of Marek et al. [20]

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Correspondence to Leyla Moghaddasi.

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Moghaddasi, L., Bezak, E. Geant4 beam model for boron neutron capture therapy: investigation of neutron dose components. Australas Phys Eng Sci Med 41, 129–141 (2018). https://doi.org/10.1007/s13246-018-0617-z

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