The Geant4-DNA low energy extension of the Geant4 Monte Carlo (MC) toolkit is a continuously evolving MC simulation code permitting mechanistic studies of cellular radiobiological effects. Geant4-DNA considers the physical, chemical, and biological stages of the action of ionizing radiation (in the form of x- and γ-ray photons, electrons and β^±-rays, hadrons, α-particles, and a set of heavier ions) in living cells towards a variety of applications ranging from predicting radiotherapy outcomes to radiation protection both on earth and in space. In this work, we provide a brief, yet concise, overview of the progress that has been achieved so far concerning the different physical, physicochemical, chemical, and biological models implemented into Geant4-DNA, highlighting the latest developments. Specifically, the “dnadamage1” and “molecularDNA” applications which enable, for the first time within an open-source platform, quantitative predictions of early DNA damage in terms of single-strand-breaks (SSBs), double-strand-breaks (DSBs), and more complex clustered lesions for different DNA structures ranging from the nucleotide level to the entire genome. These developments are critically presented and discussed along with key benchmarking results. The Geant4-DNA toolkit, through its different set of models and functionalities, offers unique capabilities for elucidating the problem of radiation quality or the relative biological effectiveness (RBE) of different ionizing radiations which underlines nearly the whole spectrum of radiotherapeutic modalities, from external high-energy hadron beams to internal low-energy gamma and beta emitters that are used in brachytherapy sources and radiopharmaceuticals, respectively.

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.

Accurately modeling the radiobiological mechanisms responsible for the induction of DNA damage remains a major scientific challenge, particularly for understanding the effects of low doses of ionizing radiation on living beings, such as the induction of carcinogenesis. A computational approach based on the Monte Carlo technique to simulate track structures in a biological medium is currently the most reliable method for calculating the early effects induced by ionizing radiation on DNA, the primary cellular target of such effects. The Geant4-DNA Monte Carlo toolkit can simulate not only the physical, but also the physico-chemical and chemical stages of water radiolysis. These stages can be combined with simplified geometric models of biological targets, such as DNA, to assess direct and indirect early DNA damage. In this study, DNA damage induced in a human fibroblast cell was evaluated using Geant4-DNA as a function of incident particle type (gammas, protons, and alphas) and energy. The resulting double-strand break yields as a function of linear energy transfer closely reproduced recent experimental data. Other quantities, such as fragment length distribution, scavengeable damage fraction, and time evolution of damage within an analytical repair model also supported the plausibility of predicting DNA damage using Geant4-DNA.The complete simulation chain application “molecularDNA”, an example for users of Geant4-DNA, will soon be distributed through Geant4.

In this work, we use the next sub-volume method (NSM) to investigate the possibility of using the compartment-based (“on-lattice”) model to simulate water radiolysis. We, first, start with a brief description of the reaction-diffusion master equation (RDME) in a spatially discretized simulation volume (“mesh”), which is divided into sub-volumes (or “voxels”). We then discuss the choice of voxel size and merging technique of a given mesh, along with the evolution of the system using the hierarchical algorithm for the RDME (“hRDME”). Since the compartment-based model cannot describe high concentration species of early radiation-induced spurs, we propose a combination of the particle-based step-by-step (“SBS”) Brownian dynamics model and the compartment-based model (“SBS-RDME model”) for the simulation. We, finally, use the particle-based SBS Brownian dynamics model of Geant4-DNA as a reference to test the model implementation through several benchmarks. We find that the compartment-based model can efficiently simulate the system with a large number of species and for longer timescales, beyond the microsecond, with a reasonable computing time. Our aim in developing this model is to study the production and evolution of reactive oxygen species generated under irradiation with different dose rate conditions, such as in FLASH and conventional radiotherapy.