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Monte Carlo simulation and analysis of eye lens dose of the first operator in interventional therapy / 中国辐射卫生
Article in Chinese | WPRIM (Western Pacific) | ID: wpr-1006227
Responsible library: WPRO
ABSTRACT
Objective To establish a model for estimating the eye lens dose of the first operator in interventional therapy based on the Monte Carlo simulation, and to provide a scientific basis for the rapid and accurate evaluation of the eye lens dose for radiation workers in interventional therapy. Methods Based on the MIRD phantom and eye model for adult Chinese males, the MCNPX program was used to establish the physical model to calculate the spatial distribution of radiation field and eye lens dose for the first operator. A GR200 Type A LiF (Mg, Cu, P) thermoluminescence dosimeter was used for experimental measurement to verify the simulation results. Results Monte Carlo simulation and experimental measurements showed that the spatial distribution of radiation field was symmetrical. Compared with the measured doses, the errors of the simulated eye lens dose of the first operator were between −8.3% and 7.3%. The dose of the left eye lens was higher than that of the right eye. Conclusion The Monte Carlo model constructed in this study initially realizes the simulation of eye lens dose of the first operator in interventional therapy. In the future, the model will be further optimized based on irradiation parameters such as exposure time, tube voltage, tube current, and projection direction used in clinic practice, so as to more accurately evaluate the eye lens dose of interventional therapy staff.

Full text: Available Health context: Sustainable Health Agenda for the Americas Health problem: Goal 4: Health financing Database: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Radiological Health Year: 2023 Document type: Article
Full text: Available Health context: Sustainable Health Agenda for the Americas Health problem: Goal 4: Health financing Database: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Radiological Health Year: 2023 Document type: Article
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