Inter-comparison of Dose Distributions Calculated by FLUKA, GEANT4, MCNP, and PHITS for Proton Therapy

Abstract

Abstract. The dose distributions from proton pencil beam scanning were calculated by FLUKA, GEANT4, MCNP, and PHITS, in order to investigate their applicability in proton radiotherapy. The first studied case was the integrated depth dose curves (IDDCs), respectively from a 100 and a 226-MeV proton pencil beam impinging a water phantom. The calculated IDDCs agree with each other as long as each code employs 75 eV for the ionization potential of water. The second case considered a similar condition of the first case but with proton energies in a Gaussian distribution. The comparison to the measurement indicates the inter-code differences might not only due to different stopping power but also the nuclear physics models. How the physics parameter setting affect the computation time was also discussed. In the third case, the applicability of each code for pencil beam scanning was confirmed by delivering a uniform volumetric dose distribution based on the treatment plan, and the results showed general agreement between each codes, the treatment plan, and the measurement, except that some deviations were found in the penumbra region. This study has demonstrated that the selected codes are all capable of performing dose calculations for therapeutic scanning proton beams with proper physics settings.

Comparison of penh, fluka, and Geant4/topas for absorbed dose calculations in air cavities representing ionization chambers in high‐energy photon and proton beams

“…fluka could reproduce both the electronic and the nuclear buildup quite well, with a maximum underestimation of ∼1% at large depths. In another study by Yang et al, depth–dose curves were calculated with both fluka and Geant4 and compared to measurements. Yang et al concluded that fluka and Geant4 are “capable of performing dose calculations for therapeutic scanning proton beams with proper physics settings.” Furthermore, Monte Carlo codes like, for example, fluka are already used to generate basic data for treatment‐planning systems and are hence intensively validated against experimental dose measurements …”

“…FLUKA could reproduce both the electronic and the nuclear buildup quite well, with a maximum underestimation of $ 1% at large depths. In another study by Yang et al 69 , depth-dose curves were calculated with both FLUKA and Geant4 and compared to measurements. Yang et al concluded that FLUKA and Geant4 are "capable of performing dose calculations for therapeutic scanning proton beams with proper physics settings."…”

“…Yang et al concluded that FLUKA and Geant4 are "capable of performing dose calculations for therapeutic scanning proton beams with proper physics settings." 69 Furthermore, Monte Carlo codes like, for example, FLUKA are already used to generate basic data for treatment-planning systems and are hence intensively validated against experimental dose measurements. 70,71 We also showed that the ranges of protons in water agree within $ 0.1 mm between the codes [see Fig 6(b)].…”

Modelling and measurements of distributions in an adult human phantom undergoing proton scanning beam radiotherapy: lung- and prostate-located tumours

“…Numerical simulations were performed with the general purpose MC particle transport code PHITS, v.3.10 (Sato et al 2018 ), that has been already benchmarked for radiotherapy applications in several studies, showing a reasonable agreement with measurements and with other MC codes (e.g. Yang et al 2017 ; Takada et al 2018 ). The PHITS code is a multi-purpose 3D Monte Carlo code dealing with particle transport via continuous energy loss, collisions and decays via reaction models and cross-section data libraries.…”

“…The same assumption was adopted for the lung case a reasonable agreement with measurements and with other MC codes (e.g. Yang et al 2017;Takada et al 2018). The PHITS code is a multi-purpose 3D Monte Carlo code dealing with particle transport via continuous energy loss, collisions and decays via reaction models and cross-section data libraries.…”