Document Type : Original Research

Authors

1 Ionizing and Non-Ionizing Radiation Protection Research Center (INIRPRC), Shiraz University of Medical Sciences, Shiraz, Iran

2 Department of Physics, University of Bojnord, Bojnord, Iran

3 Quchan Technical and Vocational University of Iran, Quchan, Iran

Abstract

Background: The assessment of RBE quantity in the treatment of cancer tumors with proton beams in treatment planning systems (TPS) is of high significance. Given the significance of the issue and the studies conducted in the literature, this quantity is fixed and is taken as equal to 1.1.Objective: The main objective of this study was to assess RBE quantity of proton beams and their variations in different depths of the tumor. This dependency makes RBE values used in TPS no longer be fixed as they depend on the depth of the tumor and therefore this dependency causes some changes in the physical dose profile.Materials and Methods: The energy spectrum of protons was measured at various depths of the tumor using proton beam simulations and well as the complete simulation of a cell to a pair of DNA bases through Monte Carlo GEANT4. The resulting energy spectrum was used to estimate the number of double-strand breaks generated in cells. Finally, RBE values were calculated in terms of the penetration depth in the tumor.Results and Conclusion: The simulation results show that the RBE value not fixed terms of the depth of the tumor and it differs from the clinical value of 1.1 at the end of the dose profile and this will lead to a non-uniform absorbed dose profile. Therefore, to create a uniform impact dose area, deep-finishing systems need to be designed by taking into account deep RBE values.

Keywords

  1. Relative biological effectivness in ion beam therapy. IAEA; 2008. p. 461.
  2. Weights IBo, Measures, Taylor BN, Thompson A. The international system of units (SI). 2001.
  3. Protection ICoR. ICRP Publication 60: 1990 Recommendations of the International Commission on Radiological Protection: Elsevier Health Sciences; 1991.
  4. Agostinelli S, Allison J, Amako Ka, Apostolakis J, Araujo H, Arce P, et al. Geant4—a simulation toolkit. Nuclear instruments and methods in physics research section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2003;506:250-303. doi.org/10.1016/S0168-9002(03)01368-8.
  5. Allison J, Amako K, Apostolakis Jea, Araujo H, Dubois PA, Asai M, et al. Geant4 developments and applications. Nuclear Science, IEEE Transactions on. 2006;53:270-8. doi.org/10.1109/TNS.2006.869826.
  6. Incerti S, Baldacchino G, Bernal M, Capra R, Champion C, Francis Z, et al. The Geant4-DNA project. International Journal of Modeling, Simulation, and Scientific Computing. 2010;1:157-78. doi.org/10.1142/S1793962310000122.
  7. Incerti S, Ivanchenko A, Karamitros M, Mantero A, Moretto P, Tran HN, et al. Comparison of GEANT4 very low energy cross section models with experimental data in water. Med Phys. 2010;37:4692-708. doi.org/10.1118/1.3476457. PubMed PMID: 20964188.
  8. Bernal MA, Bordage MC, Brown JM, Davidkova M, Delage E, El Bitar Z, et al. Track structure modeling in liquid water: A review of the Geant4-DNA very low energy extension of the Geant4 Monte Carlo simulation toolkit. Phys Med. 2015;31:861-74. doi.org/10.1016/j.ejmp.2015.10.087. PubMed PMID: 26653251.
  9. Bernal M, Sikansi D, Cavalcante F, Incerti S, Champion C, Ivanchenko V, et al. An atomistic geometrical model of the B-DNA configuration for DNA–radiation interaction simulations. Computer Physics Communications. 2013;184:2840-7. doi.org/10.1016/j.cpc.2013.07.015.
  10. Jia SB, Hadizadeh MH, Mowlavi AA, Loushab ME. Evaluation of energy deposition and secondary particle production in proton therapy of brain using a slab head phantom. Rep Pract Oncol Radiother. 2014;19:376-84. doi.org/10.1016/j.rpor.2014.04.008. PubMed PMID: 25337410. PubMed PMCID: 4201772.