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Monte Carlo simulation of whole body dose distribution in patients with total body X (γ) ray irradiation / 中华放射肿瘤学杂志
Article em Zh | WPRIM | ID: wpr-734343
Biblioteca responsável: WPRO
ABSTRACT
Objective To explore the feasibility of application of the Monte Carlo method to simulate the whole body dose distribution in patients with total body X (γ) ray irradiation by comparing the actual measurement results.Methods A Monte Carlo model of a 6 MV Elekta Synergy Clinical linear accelerator was established by MCNPX.According to the relationship between the CT value and the density of the material,the CT of the ATOM physical phantom was converted into a voxel phantom for MCNPX calculation.The dose distribution of the whole body was simulated in the total body X (γ) ray irradiation.The simulated results were compared with the measurement values of the thermoluminescence dosimetry at different positions in the ATOM physical phantom to analyze the differences.Results The difference between the depth dose curve and the off-axis dose curve and the actual measurement values calculated by the 6 MV accelerator treatment head model in the water tank was less than 2%,with the maximum dose depth of approximately 1.5 cm and field size of 10 cm× 10 cm,which were consistent with the actual measurement values.The maximum difference between the simulated results at different locations in the body and the thermoluminescence dosimeter was approximately 4%,and the simulated results of MCNPX were almost in good agreement with the results of thermoluminescence.Conclusions The whole body dose distribution in patient with total body X (γ) ray irradiation can be accurately simulated by MCNPX.Monte Carlo simulation makes it possible to optimize the uniformity of the total body dose during the total body irradiation process.
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Texto completo: 1 Índice: WPRIM Idioma: Zh Revista: Chinese Journal of Radiation Oncology Ano de publicação: 2019 Tipo de documento: Article
Texto completo: 1 Índice: WPRIM Idioma: Zh Revista: Chinese Journal of Radiation Oncology Ano de publicação: 2019 Tipo de documento: Article