Shogo Okada

Monte Carlo track structure simulation is a powerful method for estimating damage induced by water radiolysis products for cell killing. To investigate the influence of multiple ionization for the formation of water radiolysis products under ¹H⁺, ⁴He²⁺, and ¹²C⁶⁺ ion beams, a Monte Carlo simulation based on Geant4-DNA was carried out. The G-value of H₂O₂ increased monotonically with increasing linear energy transfer up to 200 eV/nm. Above 200 eV/nm, the G-value of H₂O₂ began dropping, but only when the influence of multiple ionization was considered. This trend is in good agreement with the experimental results. Furthermore, we successfully reproduce the experimental results of G-values of HO₂^• + O₂^•−. The role of the multiple ionization in the production of H₂O₂, HO₂^•, O₂^•−, and O₂ is also discussed.

This paper presents the influence of electron elastic scattering models, electron thermalization models, and chemical parameters on Geant4-DNA simulations of liquid water radiolysis under mega-electron-volt electron irradiation. The radiochemical yields are simulated using a new Geant4-DNA example. In particular, the influence of the new elastic scattering model recently developed is presented as well as the influence of improved electron thermalization models. The influence of a new chemistry constructor using parameters of another Monte Carlo track structure code is also described. The results calculated using these different models are compared with each other and with experimental data. For sub-mega-electron-volt electron simulations, the combination of the “G4EmDNAPhysics_option2” physics constructor with the recently developed elastic scattering model, the Meesungnoen electron thermalization model, and the “G4EmDNAChemistry_option1” chemistry constructor is recommended.

Purpose: Track structure simulation codes can accurately reproduce the stochastic nature of particle–matter interactions in order to evaluate quantitatively radiation damage in biological cells such as DNA strand breaks and base damage. Such simulations handle large numbers of secondary charged particles and molecular species created in the irradiated medium. Every particle and molecular species are tracked step‐by‐step using a Monte Carlo method to calculate energy loss patterns and spatial distributions of molecular species inside a cell nucleus with high spatial accuracy. The Geant4‐DNA extension of the Geant4 general‐purpose Monte Carlo simulation toolkit allows for such track structure simulations and can be run on CPUs. However, long execution times have been observed for the simulation of DNA damage in cells. We present in this work an improvement of the computing performance of such simulations using ultraparallel processing on a graphical processing unit (GPU).Methods: A new Monte Carlo simulator named MPEXS‐DNA, allowing high computing performance by using a GPU, has been developed for track structure and radiolysis simulations at the subcellular scale. MPEXS‐DNA physics and chemical processes are based on Geant4‐DNA processes available in Geant4 version 10.02 p03. We have reimplemented the Geant4‐DNA process codes of the physics stage (electromagnetic processes of charged particles) and the chemical stage (diffusion and chemical reactions for molecular species) for microdosimetry simulation by using the CUDA language. MPEXS‐DNA can calculate a distribution of energy loss in the irradiated medium caused by charged particles and also simulate production, diffusion, and chemical interactions of molecular species from water radiolysis to quantitatively assess initial damage to DNA. The validation of MPEXS‐DNA physics and chemical simulations was performed by comparing various types of distributions, namely the radial dose distributions for the physics stage, and the G‐value profiles for each chemical product and their linear energy transfer dependency for the chemical stage, to existing experimental data and simulation results obtained by other simulation codes, including PARTRAC.Results: For physics validation, radial dose distributions calculated by MPEXS‐DNA are consistent with experimental data and numerical simulations. For chemistry validation, MPEXS‐DNA can also reproduce G‐value profiles for each molecular species with the same tendency as existing experimental data. MPEXS‐DNA also agrees with simulations by PARTRAC reasonably well. However, we have confirmed that there are slight discrepancies in G‐value profiles calculated by MPEXS‐DNA for molecular species such as H₂ and H₂O₂ when compared to experimental data and PARTRAC simulations. The differences in G‐value profiles between MPEXS‐DNA and PARTRAC are caused by the different chemical reactions considered. MPEXS‐DNA can drastically boost the computing performance of track structure and radiolysis simulations. By using NVIDIA's GPU devices adopting the Volta architecture, MPEXS‐DNA has achieved speedup factors up to 2900 against Geant4‐DNA simulations with a single CPU core.Conclusion: The MPEXS‐DNA Monte Carlo simulation achieves similar accuracy to Monte Carlo simulations performed using other codes such as Geant4‐DNA and PARTRAC, and its predictions are consistent with experimental data. Notably, MPEXS‐DNA allows calculations that are, at maximum, 2900 times faster than conventional simulations using a CPU.

Purpose: Gold nanoparticles (GNPs) are known to enhance the absorbed dose in their vicinity following photon‐based irradiation. To investigate the therapeutic effectiveness of GNPs, previous Monte Carlo simulation studies have explored GNP dose enhancement using mostly condensed‐history models. However, in general, such models are suitable for macroscopic volumes and for electron energies above a few hundred electron volts. We have recently developed, for the Geant4‐DNA extension of the Geant4 Monte Carlo simulation toolkit, discrete physics models for electron transport in gold which include the description of the full atomic de‐excitation cascade. These models allow event‐by‐event simulation of electron tracks in gold down to 10 eV. The present work describes how such specialized physics models impact simulation‐based studies on GNP‐radioenhancement in a context of x‐ray radiotherapy.Methods: The new discrete physics models are compared to the Geant4 Penelope and Livermore condensed‐history models, which are being widely used for simulation‐based NP radioenhancement studies. An ad hoc Geant4 simulation application has been developed to calculate the absorbed dose in liquid water around a GNP and its radioenhancement, caused by secondary particles emitted from the GNP itself, when irradiated with a monoenergetic electron beam. The effect of the new physics models is also quantified in the calculation of secondary particle spectra, when originating in the GNP and when exiting from it.Results: The new physics models show similar backscattering coefficients with the existing Geant4 Livermore and Penelope models in large volumes for 100 keV incident electrons. However, in submicron sized volumes, only the discrete models describe the high backscattering that should still be present around GNPs at these length scales. Sizeable differences (mostly above a factor of 2) are also found in the radial distribution of absorbed dose and secondary particles between the new and the existing Geant4 models. The degree to which these differences are due to intrinsic limitations of the condensed‐history models or to differences in the underling scattering cross sections requires further investigation.Conclusions: Improved physics models for gold are necessary to better model the impact of GNPs in radiotherapy via Monte Carlo simulations. We implemented discrete electron transport models for gold in Geant4 that is applicable down to 10 eV including the modeling of the full de‐excitation cascade. It is demonstrated that the new model has a significant positive impact on particle transport simulations in gold volumes with submicron dimensions compared to the existing Livermore and Penelope condensed‐history models of Geant4.

Gold nanoparticle (GNP) boosted radiation therapy can enhance the biological effectiveness of radiation treatments by increasing the quantity of direct and indirect radiation-induced cellular damage. As the physical effects of GNP boosted radiotherapy occur across energy scales that descend down to 10 eV, Monte Carlo simulations require discrete physics models down to these very low energies in order to avoid underestimating the absorbed dose and secondary particle generation. Discrete physics models for electron transportation down to 10 eV have been implemented within the Geant4-DNA low energy extension of Geant4. Such models allow the investigation of GNP effects at the nanoscale. At low energies, the new models have better agreement with experimental data on the backscattering coefficient, and they show similar performance for transmission coefficient data as the Livermore and Penelope models already implemented in Geant4. These new models are applicable in simulations focussed towards estimating the relative biological effectiveness of radiation in GNP boosted radiotherapy applications with photon and electron radiation sources.