An evaluation of calculation parameters in the EGSnrc/BEAMnrc Monte Carlo codes and their effect on surface dose calculation

被引:15
|
作者
Kim, Jung-Ha [1 ]
Hill, Robin [1 ,2 ]
Kuncic, Zdenka [1 ]
机构
[1] Univ Sydney, Sch Phys, Inst Med Phys, Sydney, NSW 2006, Australia
[2] Royal Prince Alfred Hosp, Dept Radiat Oncol, Camperdown, NSW 2050, Australia
关键词
ION-CHAMBER RESPONSE; ENERGY-DEPENDENCE; BREAST-CANCER; CALCULATION ALGORITHMS; ELECTRON-TRANSPORT; PHOTON; RADIOTHERAPY; SIMULATION; DOSIMETRY; FILM;
D O I
10.1088/0031-9155/57/14/N267
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
The Monte Carlo (MC) method has proven invaluable for radiation transport simulations to accurately determine radiation doses and is widely considered a reliable computational measure that can substitute a physical experiment where direct measurements are not possible or feasible. In the EGSnrc/BEAMnrc MC codes, there are several user-specified parameters and customized transport algorithms, which may affect the calculation results. In order to fully utilize the MC methods available in these codes, it is essential to understand all these options and to use them appropriately. In this study, the effects of the electron transport algorithms in EGSnrc/BEAMnrc, which are often a trade-off between calculation accuracy and efficiency, were investigated in the buildup region of a homogeneous water phantom and also in a heterogeneous phantom using the DOSRZnrc user code. The algorithms and parameters investigated include: boundary crossing algorithm (BCA), skin depth, electron step algorithm (ESA), global electron cutoff energy (ECUT) and electron production cutoff energy (AE). The variations in calculated buildup doses were found to be larger than 10% for different user-specified transport parameters. We found that using BCA = EXACT gave the best results in terms of accuracy and efficiency in calculating buildup doses using DOSRZnrc. In addition, using the ESA = PRESTA-I option was found to be the best way of reducing the total calculation time without losing accuracy in the results at high energies (few keV similar to MeV). We also found that although choosing a higher ECUT/AE value in the beam modelling can dramatically improve computation efficiency, there is a significant trade-off in surface dose uncertainty. Our study demonstrates that a careful choice of user-specified transport parameters is required when conducting similar MC calculations.
引用
收藏
页码:N267 / N278
页数:12
相关论文
共 50 条
  • [21] IVBTMc, A Monte Carlo dose calculation tool for intravascular brachytherapy
    Chibani, O
    Li, XA
    MEDICAL PHYSICS, 2003, 30 (01) : 44 - 51
  • [22] Monte Carlo-based dose calculation engine for minibeam radiation therapy
    Martinez-Rovira, I.
    Sempau, J.
    Prezado, Y.
    PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS, 2014, 30 (01): : 57 - 62
  • [23] A clinical study of lung cancer dose calculation accuracy with Monte Carlo simulation
    Zhao, Yanqun
    Qi, Guohai
    Yin, Gang
    Wang, Xianliang
    Wang, Pei
    Li, Jian
    Xiao, Mingyong
    Li, Jie
    Kang, Shengwei
    Liao, Xiongfei
    RADIATION ONCOLOGY, 2014, 9
  • [24] GPU-based fast Monte Carlo dose calculation for proton therapy
    Jia, Xun
    Schuemann, Jan
    Paganetti, Harald
    Jiang, Steve B.
    PHYSICS IN MEDICINE AND BIOLOGY, 2012, 57 (23) : 7783 - 7797
  • [25] Recommended dose voxel size and statistical uncertainty parameters for precision of Monte Carlo dose calculation in stereotactic radiotherapy
    Goodall, Simon K.
    Ebert, Martin A.
    JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS, 2020, 21 (12): : 120 - 130
  • [26] DOSE CALCULATION ACCURACY OF THE MONTE CARLO ALGORITHM FOR CYBERKNIFE COMPARED WITH OTHER COMMERCIALLY AVAILABLE DOSE CALCULATION ALGORITHMS
    Sharma, Subhash
    Ott, Joseph
    Williams, Jamone
    Dickow, Danny
    MEDICAL DOSIMETRY, 2011, 36 (04) : 347 - 350
  • [27] Monte Carlo calculation of In0.53Ga0.47As and InAs noise parameters
    Karishy, Slyman
    Palermo, Christophe
    Sabatini, Giulio
    Marinchio, Hugues
    Varani, Luca
    Mateos, Javier
    Gonzalez, Tomas
    2017 INTERNATIONAL CONFERENCE ON NOISE AND FLUCTUATIONS (ICNF), 2017,
  • [28] Calculation of kinetic parameters for mixed TRIGA cores with Monte Carlo
    Snoj, Luka
    Kavcic, Andrej
    Zerovnik, Gasper
    Ravnik, Matjaz
    ANNALS OF NUCLEAR ENERGY, 2010, 37 (02) : 223 - 229
  • [29] Calculation of dose point kernel values for monoenergetic electrons and beta emitting radionuclides: Intercomparison of Monte Carlo codes
    Mendes, Bruno Melo
    Guimaraes Antunes, Paula Cristina
    Lopes Branco, Isabela Soares
    do Nascimento, Eduardo
    Seniwal, Baljeet
    Ferreira Fonseca, Telma Cristina
    Yoriyaz, Helio
    RADIATION PHYSICS AND CHEMISTRY, 2021, 181
  • [30] Clinical verification of treatment planning dose calculation in lung SBRT with GATE Monte Carlo simulation code
    Boiset, Gisell Ruiz
    Batista, Delano V. S.
    Cardoso, Simone Coutinho
    PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS, 2021, 87 : 1 - 10