- Volume 43 Issue 1
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Analysis of Dose Distribution According to the Initial Electron Beam of the Linear Accelerator: A Monte Carlo Study
- Park, Hyojun (Department of Radiation Convergence Engineering, Yonsei University) ;
- Choi, Hyun Joon (Department of Radiation Convergence Engineering, Yonsei University) ;
- Kim, Jung-In (Department of Radiation Oncology, Seoul National University Hospital) ;
- Min, Chul Hee (Department of Radiation Convergence Engineering, Yonsei University)
- Received : 2018.02.14
- Accepted : 2018.03.22
- Published : 2018.03.31
Background: Monte Carlo (MC) simulation is the most accurate for calculating radiation dose distribution and determining patient dose. In MC simulations of the therapeutic accelerator, the characteristics of the initial electron must be precisely determined in order to achieve accurate simulations. However, It has been computation-, labor-, and time-intensive to predict the beam characteristics through predominantly empirical approach. The aim of this study was to analyze the relationships between electron beam parameters and dose distribution, with the goal of simplifying the MC commissioning process. Materials and Methods: The Varian Clinac 2300 IX machine was modeled with the Geant4 MC-toolkit. The percent depth dose (PDD) and lateral beam profiles were assessed according to initial electron beam parameters of mean energy, radial intensity distribution, and energy distribution. Results and Discussion: The PDD values increased on average by 4.36% when the mean energy increased from 5.6 MeV to 6.4 MeV. The PDD was also increased by 2.77% when the energy spread increased from 0 MeV to 1.019 MeV. In the lateral dose profile, increasing the beam radial width from 0 mm to 4 mm at the full width at half maximum resulted in a dose decrease of 8.42% on the average. The profile also decreased by 4.81% when the mean energy was increased from 5.6 MeV to 6.4 MeV. Of all tested parameters, electron mean energy had the greatest influence on dose distribution. The PDD and profile were calculated using parameters optimized and compared with the golden beam data. The maximum dose difference was assessed as less than 2%. Conclusion: The relationship between the initial electron and treatment beam quality investigated in this study can be used in Monte Carlo commissioning of medical linear accelerator model.
Supported by : National Research Foundation of Korea (NRF)
- Ma CM, et al. Monte Carlo verification of IMRT dose distributions from a commercial treatment planning optimization system. Phys. Med. Biol. 2000;45(9):2483-2495. https://doi.org/10.1088/0031-9155/45/9/303
- da Rosa LA, Cardoso SC, Campos LT, Alves VGL, Batista DVS, Facure A. Percentage depth dose evaluation in heterogeneous media using thermoluminescent dosimetry. J Appl. Clin. Med. Phys. 2010;11(1):117-127. https://doi.org/10.1120/jacmp.v11i1.2947
- Sterpin E, Tomsej M, De Smedt B, Reynaert N, Vynckier S. Monte Carlo evaluation of the AAA treatment planning algorithm in a heterogeneous multilayer phantom and IMRT clinical treatments for an Elekta SL25 linear accelerator. Medical Physics. 2007;34(5):1665-1677. https://doi.org/10.1118/1.2727314
- Chetty IJ, et al. Report of the AAPM Task Group No. 105: Issues associated with clinical implementation of Monte Carlo-based photon and electron external beam treatment planning. Medical Physics. 2007;34(12):4818-4853. https://doi.org/10.1118/1.2795842
- Verhaegen F, Seuntjens J. Monte Carlo modelling of external radiotherapy photon beams. Phys. Med. Biol. 2003;48(21):R107-R164. https://doi.org/10.1088/0031-9155/48/21/R01
- Francescon P, Cora S, Chiovati P. Dose verification of an IMRT treatment planning system with the BEAM EGS4-based Monte Carlo code. Medical Physics. 2003;30(2):144-157. https://doi.org/10.1118/1.1538236
- Bush K, Gagne IM, Zavgorodni S, Ansbacher W, Beckham W. Dosimetric validation of Acuros XB with Monte Carlo methods for photon dose calculations. Medical Physics. 2011;38(4):2208-2221. https://doi.org/10.1118/1.3567146
- Han T, Mikell JK, Salehpour M, Mourtada F. Dosimetric comparison of Acuros XB deterministic radiation transport method with Monte Carlo and model-based convolution methods in heterogeneous media. Medical Physics. 2011;38(5):2651-2664. https://doi.org/10.1118/1.3582690
- Bjork P, Knoos K, Nilsson P. Influence of initial electron beam characteristics on Monte Carlo calculated absorbed dose distributions for linear accelerator electron beams. Phys. Med. Biol. 2002;47(22):4019-4041. https://doi.org/10.1088/0031-9155/47/22/308
- Tzedakis A, Damilakis JE, Mazonakis M, Stratakis J, Varveris H, Gourtsoyiannis N. Influence of initial electron beam parameters on Monte Carlo calculated absorbed dose distributions for radiotherapy photon beams. Medical Physics. 2004;31(4):907-913. https://doi.org/10.1118/1.1668551
- Maskani R, Tahmasebibirgani MJ, HoseiniGhahfarokhi M, Fatahiasl J. Determination of Initial Beam Parameters of Varian 2100 CD LINAC for Various Therapeutic Electrons Using PRIMO. Asian Pac. J Cancer Prev. 2014;16(17):7795-7801. https://doi.org/10.7314/APJCP.2015.16.17.7795
- Grevillot L, Frisson T, Maneval D, Zahra N, Badel JN, D Sarrut D. Simulation of a 6 MV Elekta Precise LINAC photon beam using GATE/GEANT4. Phys. Med. Biol. 2011;56(4):903-918. https://doi.org/10.1088/0031-9155/56/4/002
- Oliveria ACH, Vieira JW, Santana MG, Lima FR. Monte Carlo simulation of a medical linear accelerator for generation of phase spaces. 2013 International Nuclear Atlantic Conference. Recife, Brazil. November 24-29, 2013.
- Aljarrah K, Sharp GC, Neicu T, Jiang SB. Determination of the initial beam parameters in Monte Carlo linac simulation. Medical Physics. 2006;33(4):850-858. https://doi.org/10.1118/1.2168433
- Carrier J, Archambault L, Beaulieu L, Roy R. Validation of Geant4, and object-oriented Monte Carlo toolkit, for simulations in medical physics. Medical Physics. 2004;31(3):484-492. https://doi.org/10.1118/1.1644532
- Murakami K, et al. Systematic comparison of electromagnetic physics between Geant4 and EGS4 with respect to protocol data. 2004 IEEE Nuclear Science Symposium Conference. Rome, Italy. October 4, 2004.
- Keall P, Siebers JV, Libby B, Mohan R. Determining the incident electron fluence for Monte Carlo-based photon treatment planning using a standard measured data set. Medical Physics. 2003; 30(4):574-582. https://doi.org/10.1118/1.1561623
- Tanabe E, Hamm RW. Compact multi-energy electron linear accelerators. Nucl. Instrum. Methods Phys. Res., Sect. B. 1985;10: 871-876.
- Ivanchenko V, et al. Recent improvements in Geant4 electromagnetic physics models and interfaces. Prog. Nucl. Sci. Technol. 2011;2:898-903.
- Pandola L, Andenna C, Caccia B. Validation of the Geant4 simulation of bremsstrahlung from thick targets below 3MeV. Nucl. Instrum. Methods Phys. Res., Sect. B. 2015;350:41-48.
- Almond PR, Biggs PJ, Coursey BM, Hanson WF, Huq MS, Nath R, Rogers DWO. AAPM's TG-51 protocol for clinical reference dosimetry of high-energy photon and electron beams. Medical Physics. 1999;26(9):1847-1870. https://doi.org/10.1118/1.598691
- Development of a Geant4-based independent patient dose validation system with an elaborate multileaf collimator simulation model vol.20, pp.2, 2019, https://doi.org/10.1002/acm2.12530