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Purpose: Recent radiotherapy technologies including carbon-ion radiotherapy can improve the dose concentration in the target volume, thereby not only reducing side effects in organs at risk but also the secondary cancer risk within or near the irradiation field. However, secondary cancer risk in the low-dose region is considered to be non-negligible, especially for younger patients. To achieve a dose estimation of the whole body of each patient receiving carbon-ion radiotherapy, which is essential for risk assessment and epidemiological studies, Monte Carlo simulation plays an important role because the treatment planning system can provide dose distribution only in/near the irradiation field and the measured data are limited. However, validation of Monte Carlo simulations is necessary. The primary purpose of this study was to establish a calculation method using the Monte Carlo code to estimate the dose and quality factor in the body and to validate the proposed method by comparison with experimental data. Furthermore, we show the distributions of dose equivalent in a phantom and identify the partial contribution of each radiation type. Methods: We proposed a calculation method based on a Monte Carlo simulation using the PHITS code to estimate absorbed dose, dose equivalent, and dose-averaged quality factor by using the Q(L)-L relationship based on the ICRP 60 recommendation. The values obtained by this method in modeling the passive beam line at the Heavy-Ion Medical Accelerator in Chiba were compared with our previously measured data. Results: It was shown that our calculation model can estimate the measured value within a factor of 2, which included not only the uncertainty of this calculation method but also those regarding the assumptions of the geometrical modeling and the PHITS code. Also, we showed the differences in the doses and the partial contributions of each radiation type between passive and active carbon-ion beams using this calculation method. These results indicated that it is essentially important to include the dose by secondary neutrons in the assessment of the secondary cancer risk of patients receiving carbon-ion radiotherapy with active as well as passive beams. Conclusions: We established a calculation method with a Monte Carlo simulation to estimate the distribution of dose equivalent in the body as a first step toward routine risk assessment and an epidemiological study of carbon-ion radiotherapy at NIRS. This method has the advantage of being verifiable by the measurement. |
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