Effect of Tissue Composition on Dose Distribution in Electron Beam Radiotherapy

Journal of Biomedical Physics and Engineering

Z S Tabatabaei²  A Vejdani Noghreiyan²  C Knaup¹  H Vosoughi²  M Ghorbani² 

[1] Comprehensive Cancer Centers of Nevada, Las Vegas, Nevada, USA;Medical Physics Department, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran

关键词: Electron Mode;    Linear Accelerator;    Monte Carlo Simulation;    Soft Tissue;    Tissue-equivalent Materials;   

DOI  :  

学科分类：生物科学（综合）

来源: Shiraz University of Medical Sciences

【 摘 要 】

Objective:The aim of this study is to evaluate the effect of tissue composition on dose distribution in electron beam radiotherapy.Methods : A Siemens Primus linear accelerator and a phantom were simulated using MCNPX Monte Carlo code. In a homogeneous cylindrical phantom, six types of soft tissue and three types of tissue-equivalent materials were investigated. The tissues included muscle (skeletal), adipose tissue, blood (whole), breast tissue, soft tissue (9-components) and soft tissue (4-component). The tissue-equivalent materials were water, A-150 tissue-equivalent plastic and perspex. Electron dose relative to dose in 9-component soft tissue at various depths on the beam’s central axis was determined for 8, 12, and 14 MeV electron energies.Results:The results of relative electron dose in various materials relative to dose in 9-component soft tissue were reported for 8, 12 and 14 MeV electron beams as tabulated data. While differences were observed between dose distributions in various soft tissues and tissue-equivalent materials, which vary with the composition of material, electron energy and depth in phantom, they can be ignored due to the incorporated uncertainties in Monte Carlo calculations. Conclusion : Based on the calculations performed, differences in dose distributions in various soft tissues and tissue-equivalent materials are not significant. However, due to the difference in composition of various materials, further research in this field with lower uncertainties is recommended. 

【 授权许可】

Unknown