A Monte Carlo Evaluation of Dose Distribution of Commercial Treatment Planning Systems in Heterogeneous Media Publisher Pubmed



Hasani M¹ ; Mohammadi K² ; Ghorbani M³ ; Gholami S¹ ; Knaup C⁴
Source: Journal of Cancer Research and Therapeutics Published:2019

Abstract

Introduction: Calculations from a treatment planning system (TPS) in heterogeneous regions may present significant inaccuracies due to loss of electronic equilibrium. The purpose of this study is to evaluate and quantify the differences of dose distributions computed by some of the newest dose calculation algorithms, including collapsed cone convolution (CCC), fast Fourier transform (FFT) convolution, and superposition convolution, in heterogeneity of the lung. Materials and Methods: A 6-MV Siemens Primus linear accelerator was simulated by MCNPX Monte Carlo (MC) code, and the results of percentage depth dose (PDD) and dose profile values were compared with measured data. The ISOgray TPS was used and PDDs of CCC, FFT, and superposition convolution algorithms were compared with the results obtained by MCNPX code. CT2MCNP software was used to convert the computed tomography images of the lung tissue to MC input files, and dose distributions from the three algorithms were compared to MC method. Results: For PDD curves in buildup region, the maximum underdosage of ISOgray TPS was at the surface (19%) and comes in closer agreement when depth increases (average 7.08%). Dose differences (DD) between different algorithms and MC were typically 4.81% (range: 1.95% to 7.30%), -1.55% (range: -5.14% to 5.26%) and 4.96% (range: 2.00% to 7.4%) in the lung for the CCC, FFT, and superposition algorithms, respectively. The difference between monitor units and maximum dose calculated using the three algorithms were 0.5% and 1.61%, respectively. The maximum DD of 7% was observed between MC and TPS results. Conclusion: Significant differences were found when the calculation algorithms were compared with MC method in lung tissue, and this difference is not negligible. It is recommended to use of MC-based TPS for the treatment fields including lung tissue. © 2019 Journal of Cancer Research and Therapeutics | Published by Wolters Kluwer - Medknow.