Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-23T16:35:52.690Z Has data issue: false hasContentIssue false
  • English
  • Français

Bragg peak characteristics of proton beams within therapeutic energy range and the comparison of stopping power using the GATE Monte Carlo simulation and the NIST data

Published online by Cambridge University Press:  31 July 2019

Shiva Zarifi Open the ORCID record for Shiva Zarifi [Opens in a new window] ,
Hadi Taleshi Ahangari Open the ORCID record for Hadi Taleshi Ahangari [Opens in a new window] ,
Sayyed Bijan Jia ,
Mohammad Ali Tajik-Mansoury ,
Milad Najafzadeh  and
Milad Peer Firouzjaei
Shiva Zarifi
Affiliation:
Department of Medical Physics, Faculty of Medicine, Semnan University of Medical Sciences, Semnan, Iran
Hadi Taleshi Ahangari*
Affiliation:
Department of Medical Physics, Faculty of Medicine, Semnan University of Medical Sciences, Semnan, Iran
Sayyed Bijan Jia
Affiliation:
Department of Physics, University of Bojnord, Bojnord, Iran
Mohammad Ali Tajik-Mansoury
Affiliation:
Department of Medical Physics, Faculty of Medicine, Semnan University of Medical Sciences, Semnan, Iran
Milad Najafzadeh
Affiliation:
Department of Radiology, Faculty of Para-Medicine, Hormozgan University of Medical Sciences, Bandare-Abbas, Iran
Milad Peer Firouzjaei
Affiliation:
Department of Medical Physics, Faculty of Medicine, Semnan University of Medical Sciences, Semnan, Iran
*
Author for correspondence: Hadi Taleshi Ahangari, Department of Medical Physics, Faculty of Medicine, Semnan University of Medical Sciences, Semnan, Iran. Tel: +98 9127101772. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Purpose:

To examine detail depth dose characteristics of ideal proton beams using the GATE Monte Carlo technique.

Methods:

In this study, in order to improve simulation efficiency, we used pencil beam geometry instead of parallel broad-field geometry. Depth dose distributions for beam energies from 5 to 250 MeV in a water phantom were obtained. This study used parameters named Rpeak, R90, R80, R73, R50, full width at half maximum (FWHM), width of 80–20% distal fall-off (W(80–20)) and peak-to-entrance ratio to represent Bragg peak characteristics. The obtained energy–range relationships were fitted into third-order polynomial formulae. The present study also used the GATE Monte Carlo code to calculate the stopping power of proton pencil beams in a water cubic phantom and compared results with the National Institute of Standards and Technology (NIST) standard reference database.

Results:

The study results revealed deeper penetration, broader FWHM and distal fall-off and decreased peak-to-entrance dose ratio with increasing beam energy. Study results for monoenergetic proton beams showed that R73 can be a good indicator to characterise a range of incident beams. These also suggest FWHM is more sensitive than W(80–20) distal fall-off in finding initial energy spread. Furthermore, the difference between the obtained stopping power from simulation and NIST data almost in all energies was lower than 1%.

Conclusion:

Detail depth dose characteristics for monoenergetic proton beams within therapeutic energy ranges were reported. These results can serve as a good reference for clinical practitioners in their daily practice.

Keywords

Bragg peakdepth-doseGATE codeproton therapystopping power
Type
Original Article
Information
Journal of Radiotherapy in Practice , Volume 19 , Issue 2 , June 2020 , pp. 173 - 181
Copyright
© Cambridge University Press 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Haberer, T (ed.). Advances in charged particle therapy. AIP Conference Proceedings, Berkeley, United States: AIP, 2002.CrossRefGoogle Scholar
IAEA. Relative Biological Effectiveness in Ion Beam Therapy. Vienna, Austria: International Atomic Energy Agency Vienna IAEA, 2008.Google Scholar
Wilson, RR.Radiological use of fast protons. Radiology 1946; 47 (5): 487–491.CrossRefGoogle ScholarPubMed
Paganetti, H.Proton Therapy Physics. Boca Raton, USA: CRC Press, 2016.CrossRefGoogle Scholar
Newhauser, WD, Zhang, R.The physics of proton therapy. Phys Med Biol 2015; 60 (8): R155–R209.CrossRefGoogle ScholarPubMed
Berger, M, Coursey, J, Zucker, M, Chang, J. Stopping-power and range tables for electrons, protons, and helium ions. http://physics nist gov. Online: October 1998. Last update: July 2017. doi: 10.18434/T4NC7P.CrossRefGoogle Scholar
Peterson, S, Polf, J, Bues, M, Ciangaru, G, Archambault, L, Beddar, Set al. Experimental validation of a Monte Carlo proton therapy nozzle model incorporating magnetically steered protons. Phys Med Biol 2009; 54 (10): 3217–3229.CrossRefGoogle ScholarPubMed
Andreo, P.Monte Carlo techniques in medical radiation physics. Phys Med Biol 1991; 36 (7): 861–920.CrossRefGoogle ScholarPubMed
Agostinelli, S, Allison, J, Amako, K, Apostolakis, J, Araujo, H, Arce, Pet al. GEANT4—a simulation toolkit. Nucl Instrum Methods Phys Res 2003; 506 (3): 250–303.CrossRefGoogle Scholar
Jan, S, Benoit, D, Becheva, E, Carlier, T, Cassol, F, Descourt, Pet al. GATE V6: a major enhancement of the GATE simulation platform enabling modelling of CT and radiotherapy. Phys Med Biol 2011; 56(4): 881–901.CrossRefGoogle Scholar
Gonias, P, Bertsekas, N, Karakatsanis, N, Saatsakis, G, Gaitanis, A, Nikolopoulos, Det al. Validation of a GATE model for the simulation of the Siemens biograph™ 6 PET scanner. Nucl Instrum Methods Phys Res A 2007; 571 (1–2): 263–266.CrossRefGoogle Scholar
Lamare, F, Turzo, A, Bizais, Y, Le Rest, CC, Visvikis, D.Validation of a Monte Carlo simulation of the Philips Allegro/GEMINI PET systems using GATE. Phys Med Biol 2006; 51 (4): 943–962.CrossRefGoogle ScholarPubMed
Karakatsanis, N, Sakellios, N, Tsantilas, N, Dikaios, N, Tsoumpas, C, Lazaro, D, et al. Comparative evaluation of two commercial PET scanners, ECAT EXACT HR+ and Biograph 2, using GATE. Nucl Instrum Methods Phys Res A 2006; 569 (2): 368–372.CrossRefGoogle Scholar
Bruyndonckx, P, Lemaître, C, Schaart, D, Maas, M, Krieguer, M, Devroede, Oet al. Towards a continuous crystal APD-based PET detector design. Nucl Instrum Methods Phys Res A 2007; 571 (1–2): 182–186.CrossRefGoogle Scholar
Jan, S, Santin, G, Strul, D, Staelens, S, Assie, K, Autret, Det al. GATE: a simulation toolkit for PET and SPECT. Phys Med Biol 2004; 49 (19): 4543–4561.CrossRefGoogle ScholarPubMed
Zarifi, S, Ahangari, H T, Jia, S B, Tajik-Mansoury, M A.Validation of GATE Monte Carlo code for simulation of proton therapy using National Institute of Standards and Technology library data. J Radiother Pract 2019; 18 (1): 38–45.CrossRefGoogle Scholar
Geant4-Collaboration. GEANT4-A Simulation Toolkit-Guide for Physics Lists. CERN, Geant4. 2019; Release 10.5. Available: http://geant4-userdoc.web.cern.ch/geant4-userdoc/UsersGuides/PhysicsListGuide/fo/PhysicsListGuide.pdfGoogle Scholar
Jia, SB, Romano, F, Cirrone, GA, Cuttone, G, Hadizadeh, M, Mowlavi, A, et al. Designing a range modulator wheel to spread-out the Bragg peak for a passive proton therapy facility. Nucl Instrum Methods Phys Res A 2016; 806: 101–108.CrossRefGoogle Scholar
ICRU. Stopping powers for electrons and positrons. Report No 37, Bethesda, MD: International Commission on Radiation Units and Measurements, 1984.Google Scholar
Berger, MJ, Inokuti, M, Andersen, HH, Bichsel, H, Powers, D, Seltzer, SM, et al. Report 49. J ICRU 1993; os25 (2): NP–NP.Google Scholar
Grevillot, L, Frisson, T, Zahra, N, Bertrand, D, Stichelbaut, F, Freud, N, et al. Optimization of GEANT4 settings for proton pencil beam scanning simulations using GATE. Nucl Instrum Methods Phys Res A 2010; 268 (20): 3295–3305.CrossRefGoogle Scholar
Paganetti, H.Range uncertainties in proton therapy and the role of Monte Carlo simulations. Phys Med Biol 2012; 57 (11): R99–R117.CrossRefGoogle ScholarPubMed
Gottschalk, B. Passive beam spreading in proton radiation therapy. Unpublished Book. 2004. Available: https://gray.mgh.harvard.edu/attachments/article/212/pbs.pdfGoogle Scholar
Nichiporov, D, Hsi, W, Farr, J.Beam characteristics in two different proton uniform scanning systems: a side-by-side comparison. Med Phys 2012; 39 (5): 2559–2568.CrossRefGoogle ScholarPubMed
McAuley, GA, Slater, JM, Wroe, AJ.Single-plane magnetically focused elongated small field proton beams. Technol Cancer Res Treat 2015; 14 (4): 447–458.CrossRefGoogle ScholarPubMed
McAuley, GA, Heczko, SL, Nguyen, TT, Slater, JM, Slater, JD, Wroe, AJ.Monte Carlo evaluation of magnetically focused proton beams for radiosurgery. Phys Med Biol 2018; 63 (5): 055010.CrossRefGoogle ScholarPubMed
Bozkurt, A (ed.). Monte Carlo calculation of proton stopping power and ranges in water for therapeutic energies. EPJ Web of Conferences, Les Ulis, France: EDP Sciences, 2017.CrossRefGoogle Scholar