K Henkner et al 2009 Phys. Med. Biol. 54 N509 doi:10.1088/0031-9155/54/22/N01
K Henkner1,3, N Sobolevsky2, O Jäkel1,3 and H Paganetti4
Show affiliationsMonte Carlo codes are widely used to simulate dose distributions in ion radiotherapy. The benchmark of the implemented physical models against experimental data plays an important role in improving the accuracy of the simulations. To estimate the accuracy of the inelastic cross sections in SHIELD-HIT, the simulated charge is compared to measured data from a Multi Layer Faraday Cup. In addition, the results are compared to GEANT4, which are already published. Furthermore, energy distributions are simulated with SHIELD-HIT07 and GEANT4.8.1. From a comparison of depth distributions and beam profiles of 100 and 200 MeV protons, we estimate the level of agreement of the two codes. Nuclear interactions predicted by SHIELD-HIT underestimate the total amount of measured charge. The energy distributions from SHIELD-HIT and GEANT4 show differences exceeding the statistical uncertainties of 2%. Due to a difference of the Bragg curve of 0.5 ± 0.3 mm on average, the mean difference in dose is 3.5% with a maximum deviation of 7% for the simulated cases.
General scientific summary. To apply Monte Carlo (MC) in proton therapy treatment planning, the MC codes are benchmarked to experimental data to adjust the physical models which are implemented. In this work, the nuclear interaction model in SHIELD-HIT is compared to measurements from a Multi Layer Faraday Cup for 160 MeV protons. Furthermore, energy distributions simulated with SHIELD-HIT07 and GEANT4.8.1 are compared for 100 MeV and 200 MeV protons downstream of different material interfaces. Nuclear interactions simulated with SHIELD-HIT underestimate the total amount of measured charge, but this has no major influence on the depth-dose curve. Bragg curves from SHIELD-HIT are shifted on average 0.5 ± 0.3 mm towards lower depth as compared to GEANT4. This leads to a 7% difference in deposited energy for the simulated profiles. The shift is explained by differences in the stopping power simulations and benchmarks to different experimental data for both codes.
87.53.Bn Dosimetry/exposure assessment
Issue 22 (21 November 2009)
Received 18 March 2009, in final form 25 June 2009
Published 28 October 2009
K Henkner et al 2009 Phys. Med. Biol. 54 N509
Y.-M. Wang and N. R. Sheeley, Jr. 2006 ApJ 653 708
G. J. Wasserburg and Y.-Z. Qian 2000 ApJ 529 L21
Letizia Stanghellini et al. 2002 ApJ 575 178
Gioel Calabrese et al 2004 Class. Quantum Grav. 21 5735
Teng Hao et al 2009 Chinese Phys. Lett. 26 113201
Itzhak Bars 2001 Class. Quantum Grav. 18 3113
Subhanjoy Mohanty et al. 2005 ApJ 626 498
P Mason et al 2005 J. Phys. G: Nucl. Part. Phys. 31 S1729
K. L. Luhman et al 2005 ApJ 635 L93