Dosimetry Study of a VARIAN 600 C/D Linear Accelerator Head Model using MCNP5 Monte Carlo Code

Authors

  • Claubia Pereira Universidade Federal de Minas Gerais
  • Jorge L. Batista Cancino Universidade Federal de Minas Gerais
  • Carlos E. Cabrera Universidade Federal de Minas Gerais
  • Lorena C. Fernandes Universidade Federal de Minas Gerais
  • Clarysson A. M. da Silva Universidade Federal de Minas Gerais
  • Rômulo V. Sousa Universidade Federal de Minas Gerais

DOI:

https://doi.org/10.15392/bjrs.v7i3.832

Keywords:

MCNP, PDD, radiotherapy

Abstract

In radiotherapy treatment planning, tools that improve the accuracy and quality of the radiation treatment for cancer are important for the decreased death of healthy tissue and the probability to produce cancer cells. The purpose is to establish the simulation principles in MCNP reproducing the x-ray generation from the electron beam to the resultant photon beam used for radiotherapy in a LINAC VARIAN 600 C/D, being the main goal to approximate the x-ray spectrum, the profile dose and the relative dose to experimental ones. This analysis shows the difficulties to simulate the linear accelerator and how they are represented in the profile dose and relative dose and the probable margin of error obtained compared to the real case. These difficulties are due to the lack of information from the suppliers to the academic public. Therefore, some parts of the model should be inferred, such as the electron beam source and its angle.

The results show the experimentally measured data comparison to the Monte Carlo results, where the measurements of PDD are inside the margin of error for buildup region and the flat region for the beam profile dose according to reference criteria. The developed model would help to optimize the simulation of patient dosimetry in radiotherapy treatment planning.

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References

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Published

2019-07-04

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Articles

How to Cite

Dosimetry Study of a VARIAN 600 C/D Linear Accelerator Head Model using MCNP5 Monte Carlo Code. Brazilian Journal of Radiation Sciences, Rio de Janeiro, Brazil, v. 7, n. 3, 2019. DOI: 10.15392/bjrs.v7i3.832. Disponível em: https://bjrs.org.br/revista/index.php/REVISTA/article/view/832.. Acesso em: 22 nov. 2024.

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