Vol 26, No 6 (2021)
Research paper
Published online: 2021-10-04

open access

Page views 6096
Article views/downloads 345
Get Citation

Connect on Social Media

Connect on Social Media

Monte Carlo evaluation of particle interactions within the patient-dependent part of Elekta 6 MV photon beam applying IAEA phase space data

Deae-eddine Krim1, Dikra Bakari2, Mustapha Zerfaoui3, Abdeslem Rrhioua3, Yassine Oulhouq3
Rep Pract Oncol Radiother 2021;26(6):928-938.


Background: This work aims to provide a simulated method to be used by designers of medical accelerators and in clinical centers to manage and minimize particles' interaction in the patient-dependent part of a 6 MV X-Ray Beam generated by the Elekta linear accelerator system, based on the latest GATE software version 9.0 Monte Carlo simulation, IAEA phase space data, and the last version of “Slurm” computing cluster.

Materials and methods: The experimental results are obtained using the Elekta 6 MV accelerator. The simulation MC developed includes the majority of the patient-dependent segments, such as Multi-Leaf Collimator (MLC), Tongue and Groove T&G, Rounded leaf Part, including the Jaws (XY). This model is used, with a simulated Iba Blue Phantom 2 homogeneous water phantom with dimensions 480 x 480 x 410 mm3, positioned at a Source-to-Surface-Distance (SSD) of 100 cm, all of the interactions of the mega voltage 6 MV radiations in water are simulated. The IAEA phase space (PS) provided by the International Atomic Energy Agency database and cluster computing (Slurm HPC-MARWAN, CNRST, Morocco) are employed to reduce our simulation time.

Results: The results confirm that there are many interactions in all areas and the patient-dependent part’s internal structures. Thus, electrons and positrons participation appear in the generated field previously designed to be an X-ray beam. Besides, to validate our implementation geometry, the PDD's and transverse profiles, at a depth ranging from 1.5 to 20 cm, for a field size of 10 × 10 cm2, the beam quality such as D1o%, dmax (cm), d80 (cm), TPR(20/10), the two relative differences in dose were derived on  and  are calculated, respectively. Additionally, gamma index formalism for 2%/2 mm criteria is used. Once and for all, we typically take a good agreement between simulation MC GATE 9.0 and the experiment data with an error less than 2%/2 mm.

Conclusions: In the field of X-ray photons, a significant contribution of electrons and positrons has been found. This contribution could be enough to be essential or affect the delivered dose. A good agreement of 98% between this new approach of simulation MC GATE 9.0 software based on IAEA phase space and experimental dose distributions is observed regarding the validation tests used in this task.


Article available in PDF format

View PDF Download PDF file


  1. Zheng Yu, Qiu Y, Lu P, et al. An improved on-the-fly global variance reduction technique by automatically updating weight window values for Monte Carlo shielding calculation. Fusion Engineer Design. 2019; 147: 111238.
  2. Junior JPR, Salmon H, Menezes AF, et al. Simulation of Siemens ONCOR™ Expression linear accelerator using phase space in the MCNPX code. Progress in Nuclear Energy. 2014; 70: 64–70.
  3. Papadimitroulas P. Dosimetry applications in GATE Monte Carlo toolkit. Phys Med. 2017; 41: 136–140.
  4. Gardner M, McNabb A, Seppi K. A speculative approach to parallelization in particle swarm optimization. Swarm Intellig. 2011; 6(2): 77–116.
  5. Ahnesjö A, Aspradakis MM. Dose calculations for external photon beams in radiotherapy. Phys Med Biol. 1999; 44(11): R99–155.
  6. Jenkins TM, and Ro. Monte Carlo Transport of Electron and Photons. Plenum, New York 1988: 453–468.
  7. Almond PR, Biggs PJ, Coursey BM, et al. AAPM's TG-51 protocol for clinical reference dosimetry of high-energy photon and electron beams. Med Phys. 1999; 26(9): 1847–1870.
  8. Jan S, Santin G, Strul D. GATE: a simulation toolkit for PET and SPECT. Phys Med Biol. 2004; 49(19): 4543–4561.
  9. Antcheva I, Ballintijn M, Bellenot B, et al. ROOT — A C++ framework for petabyte data storage, statistical analysis and visualization. Comp Phys Communicat. 2011; 182(6): 1384–1385.
  10. Agostinelli S, Allisonas J, Amako K. Geant4 — a simulation toolkit. Nucl Instrum Methods Phys Res Sect A. 2003; 506(3): 250–303.
  11. Li J, Zhang XZ, Gui LG, et al. Clinical Feasibility of Leakage and Transmission Radiation Dosimetry Using Multileaf Collimator of ELEKTA Synergy-S Accelerator During Conventional Radiotherapy. Journal of Medical Imaging and Health Informatics. 2016; 6(2): 409–415.
  12. Low DA, Dempsey JF. Evaluation of the gamma dose distribution comparison method. Med Phys. 2003; 30(9): 2455–2464.
  13. Van Dyk J, Barnett RB, Cygler JE, et al. Commissioning and quality assurance of treatment planning computers. Int J Radiat Oncol Biol Phys. 1993; 26(2): 261–273.
  14. Low DA, Harms WB, Mutic S, et al. A technique for the quantitative evaluation of dose distributions. Med Phys. 1998; 25(5): 656–661.
  15. Teixeira MS, Batista D, Braz D, et al. Monte Carlo simulation of Novalis Classic 6 MV accelerator using phase space generation in GATE/Geant4 code. Progr Nucl Energy. 2019; 110: 142–147.
  16. Tuğrul T, Eroğul O. Determination of initial electron parameters by means of Monte Carlo simulations for the Siemens Artiste Linac 6 MV photon beam. Rep Pract Oncol Radiother. 2019; 24(4): 331–337.
  17. Grevillot L, Frisson T, Maneval D, et al. Simulation of a 6 MV Elekta Precise Linac photon beam using GATE/GEANT4. Phys Med Biol. 2011; 56(4): 903–918.
  18. Efendi MA, Funsian A, Chittrakarn T, et al. Monte Carlo simulation using PRIMO code as a tool for checking the credibility of commissioning and quality assurance of 6 MV TrueBeam STx varian LINAC. Rep Pract Oncol Radiother. 2020; 25(1): 125–132.

Reports of Practical Oncology and Radiotherapy