An assessment on the use of RadCalc to verify Raystation Electron Monte Carlo plans

  • Yunfei Hu
  • Ben Archibald-Heeren
  • Mikel Byrne
  • Yang Wang
Scientific Paper
First Online:
Received:
Accepted:
  • 111 Downloads

Abstract

Large differences in monitor units have been observed when RadCalc, a pencil-beam-algorithm based software, is used to verify clinical electron plans from Raystation, a Monte-Carlo-algorithm based planning system. To investigate the problem, a number of clinical plans as well as test plans were created and calculated in both systems, with the resultant monitor units compared. The results revealed that differences between the two systems are significant when the geometry includes inhomogeneities and curved surfaces. The RadCalc pencil-beam-algorithm fails to handle such complexities, particularly in the presence of surface curvature. The error is not negligible and cannot be easily corrected for. It is concluded that RadCalc is not adequate to verify electron Monte Carlo plans from Raystation when complex geometry is involved and alternative methods should be developed.

Keywords

Electron Monte Carlo Pencil beam Curvature Inhomogeneity 
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References

  1. 1.
    Chetty IJ, Curran B, Cygler JE, DeMarco JJ, Ezzell G, Faddegon BA, Kawrakow I, Keall PJ, Liu H, Ma CM, Rogers DWO, Seuntjens J, Sheikh-Bagheri D, Siebers JV (2007) Report of the AAPM Task Group Report No. 105: issues associated with clinical implementation of Monte Carlo-based photon and electron external beam treatment planning. Med Phys 34:4818CrossRefPubMedGoogle Scholar
  2. 2.
    Andreo P (1991) Monte Carlo techniques in medical radiation physics. Phys Med Biol 36:861CrossRefPubMedGoogle Scholar
  3. 3.
    Ma CM, Jiang SB (1999) Monte Carlo modelling of electron beams from medical accelerators. Phys Med Biol 44:R157CrossRefPubMedGoogle Scholar
  4. 4.
    Mzenda B, Mugabe KV, Sims R, Godwin G, Loria D (2014) Modeling and dosimetric performance evaluation of the Raystation treatment planning system. J Appl Clin Med Phys 15(5):29Google Scholar
  5. 5.
    Fragoso M, Pillai S, Solberg TD, Chetty IJ (2008) Experimental verification and clinical implementation of a commercial Monte Carlo electron beam dose calculation algorithm. Med Phys 35(3):1028CrossRefPubMedGoogle Scholar
  6. 6.
    Archibald-Heeren B, Liu G (2016) Raystation Monte Carlo application: evaluation of electron calculations with entry obliquity. Australas Phys Eng Sci Med 39:441–452CrossRefPubMedGoogle Scholar
  7. 7.
    Kawrakow I (2001) VMC++, electron and photon Monte Carlo calculations optimised for radiation treatment planning. In: Kling A, Barao FJC, Nakagawa M, Tavora L, Vaz P (eds) Advanced Monte Carlo for radiation physics, particle transport simulation and applications: proceedings of the Monte Carlo 2000 conference, Lisbon, 23–26 October 2000. Springer, Berlin, pp 229–236Google Scholar
  8. 8.
    Gibbons JP, Antolak JA, Followill DS, Huq MS, Klein EE, Lam KL, Palta JR, Roback DM, Reid M, Khan FM (2014) Report of the AAPM Therapy Physics Committee Taks Group No. 71: monitor unit calculations for external photon and electron beams. Med Phys 41(3):031501CrossRefPubMedGoogle Scholar
  9. 9.
    Cygler JE, Daskalov G, Chan GH (2004) Evaluation of the first commercial Monte Carlo dose calculation engine for electron beam treatment planning. Med Phys 31:142CrossRefPubMedGoogle Scholar
  10. 10.
    Ding GX, Cygler JE, Yu CW, Kalach NI, Daskalov G (2005) A comparison of electron beam dose calculation accuracy between treatment planning systems using either a pencil beam or a Monte Carlo algorithm. Int J Radiat Oncol Biol Phys 63(2):622CrossRefPubMedGoogle Scholar
  11. 11.
    Edimo P, Clermont C, Kwato MG, Vyncker S (2009) Evaluation of a commercial VMC++ Monte Carlo based treatment planning system for electron beam using EGSnrc/BEAMnrc simulations and measurements. Phys Med 25(3):111CrossRefPubMedGoogle Scholar
  12. 12.
    RaySearch Laboratories AB (2014) RayStation5: user manual, version 4.6.073. StockholmGoogle Scholar
  13. 13.
    Khan FM, Doppke KP, Hogstrom KR, Kutcher GJ, Nath R, Prasad SC, Purdy JA, Rozenfeld M, Werner BL (1991) Report of the AAPM Task Group No. 25, clinical electron-beam dosimetry. Med Phys 18(1):73CrossRefPubMedGoogle Scholar
  14. 14.
    Jursinic PA, Mueller R (1997) A sector-integration method for calculating the output factors of irregularly shaped electron fields. Med Phys 24:1765CrossRefPubMedGoogle Scholar
  15. 15.
    Ding GX, Rogers DWO, Cygler JE, Mackie TR (1997) Electron fluence correction factors for conversion of dose in plastic to dose in water. Med Phys 24:161CrossRefPubMedGoogle Scholar
  16. 16.
    Andreo P, Burns DT, Hohlfeld K, Huq MS, Kanai T, Laitano F, Smith VG, Vynckier S (2000) Absorbed dose determination in external beam radiotherapy: an international code of practice for dosimetry based on standards of absorbed dose to water IAEA Technical Reports Series No. 398. International Atomic Energy Agency, ViennaGoogle Scholar
  17. 17.
    Zarza-Moreno M, Carreira P, Madureira L, Miras del Rio H, Salguero FJ, Leal A, Teixeira N, Jesus AP, More G (2014) Dosimetric effect by shallow air cavities in high energy electron beams. Phys Med 30:234CrossRefPubMedGoogle Scholar
  18. 18.
    Khan FM (2003) The physics of radiation therapy, 3rd edn. Lippincott Williams and Wilkins, PhiladelphiaGoogle Scholar
  19. 19.
    Ritenour ER, Cacak RK, Hendee WR (1983) Ionization produced by electron beams beneath curved surfaces. Med Phys 10(5):669CrossRefPubMedGoogle Scholar

Copyright information

© Australasian College of Physical Scientists and Engineers in Medicine 2016

Authors and Affiliations

  1. 1.Radiation Oncology Centres GosfordGosfordAustralia
  2. 2.Radiation Oncology Centres WahroongaWahroongaAustralia

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