Track Structure Simulations Research Articles

Optimized neuron models for estimation of charged particle energy deposition in hippocampus

The study of evaluating radiation risk on the central nervous system induced by space-born charged particles is very complex and challenging task in space radiobiology and radiation protection. To overcome computational difficulties in this field, we developed simplified neuron models with properties equivalent to realistic neuron morphology. Three-dimensional structure and parameters of simplified and complex neuron models with realistic morphology were obtained from the experimental data. The models implement uniform random distribution of spines along the dendritic branches in typical hippocampal neurons. Both types of models were implemented and tested using Geant4 Monte Carlo radiation transport code. Track structure simulations were performed for ion beams with typical fluxes of galactic cosmic rays expected for long-term interplanetary missions. The distribution of energy deposition events and percentage of irradiated volumes were obtained to be similar in both simplified and realistic models of pyramidal and granule cells of the rat hippocampus following irradiation. Significant increase of computational efficiency for detailed microdosimetry simulations of hippocampus using simplified neuron models was achieved. Using designed neuron models we have constructed 3D model of the rat hippocampus, including pyramidal cells, mature and immature granular cells, mossy cells, and neural stem cells. Computed energy deposition in irradiated hippocampal neurons following a track of iron ion suggests that most of energy is accumulated by dense population of granular cells in the dentate gyrus. Proposed approach could serve as a complementary computation technique for studying radiation-induced effects in large scale brain networks.

Monte Carlo track structure simulation in studies of biological effects induced by accelerated charged particles in the central nervous system

Simulating the biological damage induced by charged particles trajectories (tracks) in the central nervous system (CNS) at different levels of its organization (molecular, cellular, and tissue) is a challenge of modern radiobiology studies. According to the recent experimental studies at particle accelerators, the most radiation-sensitive area of the CNS is the hippocampus. In this regards, the development of measurement-based Monte Carlo simulation of radiation-induced alterations in the hippocampus is of great interest to understand the radiobiological effects on the CNS. The present work investigates the influence of charged particles on the hippocampal cells of the rat brain using the Geant4 Monte Carlo radiation transport code. The applied computer simulation provides a method to simulate physics processes and chemical reactions in the developed model of the rat hippocampus, which contains different types of neural cells - pyramidal cells, mature and immature granular cells, mossy cells, and neural stem cells. The distribution of stochastic energy depositions has been obtained and analyzed in critical structures of the hippocampal neurons after irradiation with 600 MeV/u iron particles. The computed energy deposition in irradiated hippocampal neurons following a track of iron ion suggests that most of the energy is accumulated by granular cells. The obtained quantities at the level of molecular targets also assume that NMDA and GABA receptors belong to the most probable targets in the irradiated neural cells.

Development of a new Geant4-DNA electron elastic scattering model for liquid-phase water using the ELSEPA code

This paper presents the calculation of new elastic scattering cross sections for the simulation of electron interactions in liquid water. The calculations are based on the “ELastic Scattering of Electrons and Positrons by neutral Atoms” code, which adopts a Dirac partial wave analysis. A Muffin-tin potential was used in order to account for the liquid-phase of water, and the optical parameters of the correlation-polarization and the inelastic absorption potentials were optimized against vapour-phase water data. The differential and total elastic scattering cross sections calculated in the present work show a global agreement with the experimental data. The impact of these elastic scattering cross sections on the transport of electrons in liquid water was evaluated by track-structure simulations of range, dose-point-kernel, microdosimetric spectra, and ionization clustering using the Geant4-DNA simulation toolkit. The results are compared against those obtained with the elastic scattering models already available in Geant4-DNA and are discussed.

Fast calculation of nanodosimetric quantities in treatment planning of proton and ion therapy

Details of the pattern of ionization formed by particle tracks extends knowledge of dose effects on the nanometer scale. Ionization detail (ID), frequently characterized by ionization cluster size distributions (ICSD), is obtained through time-consuming Monte Carlo (MC) track-structure simulations. In this work, TOPAS-nBio was used to generate a highly precise database of biologically significant ID quantities, sampled with randomly oriented 2.3 nm diameter cylinders, 3.4 nm (10 base pairs) long, inside a chromatin-size cylinder, irradiated by 1–1000 MeV/u ions of Z = 1–8. A macroscopic method developed to utilize the database using condensed-history MC was used to calculate distributions of the ICSD first moment and cumulative probability in a 20 × 20 × 40 cm3 water phantom irradiated with proton and carbon spread-out Bragg peak (SOBP) of 10.5 cm range, 2 cm width. Results were verified against detailed MC track-structure simulations using phase space scored at several depths. ID distributions were then obtained for intensity modulated proton and carbon radiotherapy plans in a digitized anthropomorphic phantom of a base of skull tumor to demonstrate clinical application of this approach.The database statistical uncertainties were 0.5% (3 standard deviations). Fluence-averaged ID as implemented proved unsuitable for macroscopic calculation. Edep-averaged ID agreed with track-structure results within 0.8% for protons. For carbon, maximum absolute differences of 2.9% ± 1.6% and 5.6% ± 1.9% for , 1.7% ± 0.8% and 1.9% ± 0.4% (1 standard deviation) for , were found in the plateau and SOBP, respectively, up to 11.5% ± 5.6% in the tail region. Macroscopic ID calculation was demonstrated for a realistic treatment plan. Computation times with or without ID calculation were comparable in all cases.Pre-calculated nanodosimetric data may be used for condensed-history MC for nanodosimetric ID-based treatment planning in ion radiotherapy in the future. The macroscopic approach developed has the calculation speed of condensed-history MC while approaching the accuracy of full track structure simulations.

Track structure simulation of low energy electron damage to DNA using Geant4-DNA

Due to the physical and chemical processes that are involved, interactions of ionizing radiations with cells lead to single- and double-strand breaks (SSB and DSB) and base damage to DNA cells. The damage may kill the cells or may be mis-repaired and lead to genetic diseases and cancers. Track structure Monte Carlo simulation of the DNA damage provides types of the damage and their frequencies. In the present work, to derive initial DNA damage, we used the Geant4-DNA code to simulate the physical, physico-chemical and chemical stages of interactions of incident beams of 100 eV–4.5 keV electrons. By considering the direct damage of electrons and also the indirect hydroxyl radical damage to the DNA, in a simulation, simple and complex damages to SSB and DSB were investigated. Moreover, the yield of damage and the probability of types of DNA damage were evaluated. The results of these calculations were compared with the existing experimental data and the other simulations. For electrons with energies lower than 500 eV, there were differences between our results and published data which are basically due to the existing differences in the physical (electron ionization, excitation cross sections) and chemical models of Geant4-DNA, the chemical processes considered in the simulations, DNA geometry, and the selected parameters for damage threshold as compared to the other codes. In the present work, the effect of the threshold energy of the strand breaks was also evaluated.

Geometrical structures for radiation biology research as implemented in the TOPAS-nBio toolkit

Computational simulations, such as Monte Carlo track structure simulations, offer a powerful tool for quantitatively investigating radiation interactions within cells. The modelling of the spatial distribution of energy deposition events as well as diffusion of chemical free radical species, within realistic biological geometries, can help provide a comprehensive understanding of the effects of radiation on cells. Track structure simulations, however, generally require advanced computing skills to implement. The TOPAS-nBio toolkit, an extension to TOPAS (TOol for PArticle Simulation), aims to provide users with a comprehensive framework for radiobiology simulations, without the need for advanced computing skills. This includes providing users with an extensive library of advanced, realistic, biological geometries ranging from the micrometer scale (e.g. cells and organelles) down to the nanometer scale (e.g. DNA molecules and proteins). Here we present the geometries available in TOPAS-nBio.

Analysis of scintillation light intensity by microscopic radiation transport calculation and Förster quenching model.

The scintillation light yield of plastic scintillator considering the quenching effect is reproduced by a calculation model based on a track-structure simulation code and the Förster effect. Energy deposition and its nm-scale spatial arrangement in the irradiation by electrons, protons, and heavy ions (4He to 81Br) in an NE-102A scintillator were simulated by a track-structure simulation code. The spatial arrangements of the excited molecules emitting scintillation light and those dissipating the excitation energy were then obtained to calculate the strength of the quenching effect. Light emission from the excited molecules was integrated to finally obtain the observable light yield. The calculated light yields are in good agreement with the earlier measurement data. Moreover, in the case of low-LET particle incidence, a statistical micro-dosimetric model can substitute the track-structure simulation code for reproducing the light yield.

Geant4-DNA example applications for track structure simulations in liquid water: A report from the Geant4-DNA Project.

This Special Report presents a description of Geant4-DNA user applications dedicated to the simulation of track structures (TS) in liquid water and associated physical quantities (e.g., range, stopping power, mean free path…). These example applications are included in the Geant4 Monte Carlo toolkit and are available in open access. Each application is described and comparisons to recent international recommendations are shown (e.g., ICRU, MIRD), when available. The influence of physics models available in Geant4-DNA for the simulation of electron interactions in liquid water is discussed. Thanks to these applications, the authors show that the most recent sets of physics models available in Geant4-DNA (the so-called "option4" and "option 6" sets) enable more accurate simulation of stopping powers, dose point kernels, and W-values in liquid water, than the default set of models ("option 2") initially provided in Geant4-DNA. They also serve as reference applications for Geant4-DNA users interested in TS simulations.

Monte Carlo simulation of chemistry following radiolysis with TOPAS-nBio

Simulation of water radiolysis and the subsequent chemistry provides important information on the effect of ionizing radiation on biological material. The Geant4 Monte Carlo toolkit has added chemical processes via the Geant4-DNA project. The TOPAS tool simplifies the modeling of complex radiotherapy applications with Geant4 without requiring advanced computational skills, extending the pool of users. Thus, a new extension to TOPAS, TOPAS-nBio, is under development to facilitate the configuration of track-structure simulations as well as water radiolysis simulations with Geant4-DNA for radiobiological studies. In this work, radiolysis simulations were implemented in TOPAS-nBio. Users may now easily add chemical species and their reactions, and set parameters including branching ratios, dissociation schemes, diffusion coefficients, and reaction rates. In addition, parameters for the chemical stage were re-evaluated and updated from those used by default in Geant4-DNA to improve the accuracy of chemical yields. Simulation results of time-dependent and LET-dependent primary yields Gx (chemical species per 100 eV deposited) produced at neutral pH and 25 °C by short track-segments of charged particles were compared to published measurements. The LET range was 0.05–230 keV µm−1. The calculated Gx values for electrons satisfied the material balance equation within 0.3%, similar for protons albeit with long calculation time. A smaller geometry was used to speed up proton and alpha simulations, with an acceptable difference in the balance equation of 1.3%. Available experimental data of time-dependent G-values for agreed with simulated results within 7% ± 8% over the entire time range; for over the full time range within 3% ± 4%; for H2O2 from 49% ± 7% at earliest stages and 3% ± 12% at saturation. For the LET-dependent Gx, the mean ratios to the experimental data were 1.11 ± 0.98, 1.21 ± 1.11, 1.05 ± 0.52, 1.23 ± 0.59 and 1.49 ± 0.63 (1 standard deviation) for , , H2, H2O2 and , respectively. In conclusion, radiolysis and subsequent chemistry with Geant4-DNA has been successfully incorporated in TOPAS-nBio. Results are in reasonable agreement with published measured and simulated data.

Track-structure simulations of energy deposition patterns to mitochondria and damage to their DNA

Purpose: Mitochondria have been implicated in initiating and/or amplifying the biological effects of ionizing radiation not mediated via damage to nuclear DNA. To help elucidate the underlying mechanisms, energy deposition patterns to mitochondria and radiation damage to their DNA have been modelled.Methods: Track-structure simulations have been performed with PARTRAC biophysical tool for 60Co γ-rays and 5 MeV α-particles. Energy deposition to the cell’s mitochondria has been analyzed. A model of mitochondrial DNA reflecting experimental information on its structure has been developed and used to assess its radiation-induced damage.Results: Energy deposition to mitochondria is highly inhomogeneous, especially at low doses. Although a dose-dependent fraction of mitochondria sees no energy deposition at all, the hit ones receive rather high amounts of energy. Nevertheless, only little damage to mitochondrial DNA occurs, even at large doses.Conclusion: Mitochondrial DNA does not represent a critical target for radiation effects. Likely, the key role of mitochondria in radiation-induced biological effects arises from the communication between mitochondria and/or with the nucleus. Through this signaling, initial modifications in a few heavily hit mitochondria seem to be amplified to a massive long-term effect manifested in the whole cell or even tissue.

Geant4-DNA track-structure simulations for gold nanoparticles: The importance of electron discrete models in nanometer volumes.

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 10eV. The present work describes how such specialized physics models impact simulation-based studies on GNP-radioenhancement in a context of x-ray radiotherapy. 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. The new physics models show similar backscattering coefficients with the existing Geant4 Livermore and Penelope models in large volumes for 100keV 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. 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 10eV 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.

Modeling Radiation Effects of Ultrasoft X Rays on the Basis of Amorphous Track Structure.

There is experimental evidence that ultrasoft X rays (0.1-5 keV) show a higher biological effectiveness than high-energy photons. Similar to high-LET radiation, this is attributed to a rather localized dose distribution associated with a considerably smaller range of secondary electrons, which results in an increasing yield of double-strand breaks (DSBs) and potentially more complex lesions. We previously reported on the application of the Giant LOop Binary LEsion (GLOBLE) model to ultrasoft X rays, in which experimental values of the relative biological effectiveness (RBE) for DSB induction were used to show that this increasing DSB yield was sufficient to explain the enhanced effectiveness in the cell inactivation potential of ultrasoft X rays. Complementary to GLOBLE, we report here on a modeling approach to predict the increased DSB yield of ultrasoft X rays on the basis of amorphous track structure formed by secondary electrons, which was derived from Monte Carlo track structure simulations. This procedure is associated with increased production of single-strand break (SSB) clusters, which are caused by the highly localized energy deposition pattern induced by low-energy photons. From this, the RBE of ultrasoft X rays can be determined and compared to experimental data, showing that the inhomogeneity of the energy deposition pattern represents the key variable to describe the increased biological effectiveness of ultrasoft X rays. Thus, this work demonstrates an extended applicability of the amorphous track structure concept and tests its limits with respect to its predictive power. The employed model mechanism offers a possible explanation for how the cellular response to ultrasoft X rays is directly linked to the energy deposition properties on the nanometric scale.

Measurement of track structure parameters of low and medium energy helium and carbon ions in nanometric volumes

Ionization cluster size distributions produced in the sensitive volume of an ion-counting wall-less nanodosimeter by monoenergetic carbon ions with energies between 45 MeV and 150 MeV were measured at the TANDEM-ALPI ion accelerator facility complex of the LNL-INFN in Legnaro. Those produced by monoenergetic helium ions with energies between 2 MeV and 20 MeV were measured at the accelerator facilities of PTB and with a 241Am alpha particle source. C3H8 was used as the target gas. The ionization cluster size distributions were measured in narrow beam geometry with the primary beam passing the target volume at specified distances from its centre, and in broad beam geometry with a fan-like primary beam. By applying a suitable drift time window, the effective size of the target volume was adjusted to match the size of a DNA segment. The measured data were compared with the results of simulations obtained with the PTB Monte Carlo code PTra. Before the comparison, the simulated cluster size distributions were corrected with respect to the background of additional ionizations produced in the transport system of the ionized target gas molecules. Measured and simulated characteristics of the particle track structure are in good agreement for both types of primary particles and for both types of the irradiation geometry. As the range in tissue of the ions investigated is within the typical extension of a spread-out Bragg peak, these data are useful for benchmarking not only ‘general purpose’ track structure simulation codes, but also treatment planning codes used in hadron therapy. Additionally, these data sets may serve as a data base for codes modelling the induction of radiation damages at the DNA-level as they almost completely characterize the ionization component of the nanometric track structure.

Flagged uniform particle splitting for variance reduction in proton and carbon ion track-structure simulations

Flagged uniform particle splitting was implemented with two methods to improve the computational efficiency of Monte Carlo track structure simulations with TOPAS-nBio by enhancing the production of secondary electrons in ionization events. In method 1 the Geant4 kernel was modified. In method 2 Geant4 was not modified. In both methods a unique flag number assigned to each new split electron was inherited by its progeny, permitting reclassification of the split events as if produced by independent histories.Computational efficiency and accuracy were evaluated for simulations of 0.5–20 MeV protons and 1–20 MeV u−1 carbon ions for three endpoints: (1) mean of the ionization cluster size distribution, (2) mean number of DNA single-strand breaks (SSBs) and double-strand breaks (DSBs) classified with DBSCAN, and (3) mean number of SSBs and DSBs classified with a geometry-based algorithm.For endpoint (1), simulation efficiency was 3 times lower when splitting electrons generated by direct ionization events of primary particles than when splitting electrons generated by the first ionization events of secondary electrons. The latter technique was selected for further investigation. The following results are for method 2, with relative efficiencies about 4.5 times lower for method 1. For endpoint (1), relative efficiency at 128 split electrons approached maximum, increasing with energy from 47.2 ± 0.2 to 66.9 ± 0.2 for protons, decreasing with energy from 51.3 ± 0.4 to 41.7 ± 0.2 for carbon. For endpoint (2), relative efficiency increased with energy, from 20.7 ± 0.1 to 50.2 ± 0.3 for protons, 15.6 ± 0.1 to 20.2 ± 0.1 for carbon. For endpoint (3) relative efficiency increased with energy, from 31.0 ± 0.2 to 58.2 ± 0.4 for protons, 23.9 ± 0.1 to 26.2 ± 0.2 for carbon. Simulation results with and without splitting agreed within 1% (2 standard deviations) for endpoints (1) and (2), within 2% (1 standard deviation) for endpoint (3).In conclusion, standard particle splitting variance reduction techniques can be successfully implemented in Monte Carlo track structure codes.

Monte Carlo Electron Track Structure Calculations in Liquid Water Using a New Model Dielectric Response Function.

Monte Carlo track structure codes provide valuable information for understanding radiation effects down to the DNA level, where experimental measurements are most difficult or unavailable. It is well recognized that the performance of such codes, especially at low energies and/or subcellular level, critically depends on the reliability of the interaction cross sections that are used as input in the simulation. For biological media such as liquid water, one of the most challenging issues is the role of condensed-phase effects. For inelastic scattering, such effects can be conveniently accounted for through the complex dielectric response function of the media. However, for this function to be useful it must fulfill some important sum rules and have a simple analytic form for arbitrary energy- and momentum-transfer. The Emfietzoglou-Cucinotta-Nikjoo (ECN) model offers a practical, self-consistent and fully analytic parameterization of the dielectric function of liquid water based on the best available experimental data. An important feature of the ECN model is that it includes, in a phenomenological manner, exchange and correlation effects among the screening electrons, thus, going beyond the random-phase approximation implicit in earlier models. In this work, inelastic cross sections beyond the plane wave Born approximation are calculated for low-energy electrons (10 eV-10 keV) based on the ECN model, and used for Monte Carlo track structure simulations of physical quantities relevant to the microdosimetry of low-energy electrons in liquid water. Important new developments in the physics of inelastic scattering are discussed and their effect on electron track structure is investigated by a comparison against simulations (under otherwise identical conditions) using the Born approximation and a simpler form of the dielectric function based on the Oak Ridge National Laboratory model. The results reveal that both the dielectric function and the corrections to the Born approximation may have a sizeable effect on track structure calculations at the nanometer scale (DNA level), where the details of inelastic scattering and the role of low-energy electrons are most critical.

Monte Carlo simulation of proton track structure in biological matter

Understanding the radiation-induced effects at the cellular and subcellular levels remains crucial for predicting the evolution of irradiated biological matter. In this context, Monte Carlo track-structure simulations have rapidly emerged among the most suitable and powerful tools. However, most existing Monte Carlo track-structure codes rely heavily on the use of semi-empirical cross sections as well as water as a surrogate for biological matter. In the current work, we report on the up-to-date version of our homemade Monte Carlo code TILDA-V – devoted to the modeling of the slowing-down of 10 keV–100 MeV protons in both water and DNA – where the main collisional processes are described by means of an extensive set of ab initio differential and total cross sections.

Geant4-DNA simulation of electron slowing-down spectra in liquid water

This work presents the simulation of monoenergetic electron slowing-down spectra in liquid water by the Geant4-DNA extension of the Geant4 Monte Carlo toolkit (release 10.2p01). These spectra are simulated for several incident energies using the most recent Geant4-DNA physics models, and they are compared to literature data. The influence of Auger electron production is discussed. For the first time, a dedicated Geant4-DNA example allowing such simulations is described and is provided to Geant4 users, allowing further verification of Geant4-DNA track structure simulation capabilities.

A comparison between track-structure, condensed-history Monte Carlo simulations and MIRD cellular S-values

The S-value is a standard measure in cellular dosimetry. S-values are calculated by applying analytical methods or by Monte Carlo simulation. In Monte Carlo simulation, particles are either tracked individually event-by-event or close events are condensed and processed collectively in different steps. Both of these methods have been employed for estimation of cellular S-values, but there is no consistency between the published results. In the present paper, we used the Geant4-DNA track-structure physics model as the reference to estimate the cellular S-values. We compared the results with the corresponding values obtained from the following three condensed-history physics models of Geant4: Penelope, Livermore and standard. The geometry and source were exactly the same in all the simulations. We utilized mono-energetic electrons with an initial kinetic energy in the range 1–700 keV as the source of radiation. We also compared our results with the MIRD S-values. We first drew an overall comparison between different data series and then compared the dependence of results on the energy of particles and the size of scoring compartments. The overall comparison indicated a very good linear correlation (R2 > 91%) and small bias (3%) between the results of the track-structure model and the condensed-history physics model. The bias between MIRD and the results of Monte Carlo track-structure simulation was considerable (−8%). However, the point-by-point comparison revealed differences of up to 28% between the condensed-history and the track-structure MC codes for self-absorption S-values in the 10–50 keV energy range. For the cross-absorption S-values, the difference was up to 34%. In this energy range, the difference between the MIRD S-values and the Geant4-DNA results was up to 68%. Our findings suggest that the consistency/inconsistency of the results obtained with different MC simulations depends on the size of the scoring volumes, the energy of the particles, the step-size in electron tracking and the energy cutoff used in the MC codes.

Validation of the radiobiology toolkit TOPAS-nBio in simple DNA geometries

Computational simulations offer a powerful tool for quantitatively investigating radiation interactions with biological tissue and can help bridge the gap between physics, chemistry and biology. The TOPAS collaboration is tackling this challenge by extending the current Monte Carlo tool to allow for sub-cellular in silico simulations in a new extension, TOPAS-nBio. TOPAS wraps and extends the Geant4 Monte Carlo simulation toolkit and the new extension allows the modeling of particles down to vibrational energies (∼2eV) within realistic biological geometries. Here we present a validation of biological geometries available in TOPAS-nBio, by comparing our results to two previously published studies. We compare the prediction of strand breaks in a simple linear DNA strand from TOPAS-nBio to a published Monte Carlo track structure simulation study. While TOPAS-nBio confirms the trend in strand break generation, it predicts a higher frequency of events below an energy of 17.5eV compared to the alternative Monte Carlo track structure study. This is due to differences in the physics models used by each code. We also compare the experimental measurement of strand breaks from incident protons in DNA plasmids to TOPAS-nBio simulations. Our results show good agreement of single and double strand breaks predicting a similar increase in the strand break yield with increasing LET.

Multi-Scale Modeling of the Gamma Radiolysis of Nitrate Solutions.

A multiscale modeling approach has been developed for the extended time scale long-term radiolysis of aqueous systems. The approach uses a combination of stochastic track structure and track chemistry as well as deterministic homogeneous chemistry techniques and involves four key stages: radiation track structure simulation, the subsequent physicochemical processes, nonhomogeneous diffusion-reaction kinetic evolution, and homogeneous bulk chemistry modeling. The first three components model the physical and chemical evolution of an isolated radiation chemical track and provide radiolysis yields, within the extremely low dose isolated track paradigm, as the input parameters for a bulk deterministic chemistry model. This approach to radiation chemical modeling has been tested by comparison with the experimentally observed yield of nitrite from the gamma radiolysis of sodium nitrate solutions. This is a complex radiation chemical system which is strongly dependent on secondary reaction processes. The concentration of nitrite is not just dependent upon the evolution of radiation track chemistry and the scavenging of the hydrated electron and its precursors but also on the subsequent reactions of the products of these scavenging reactions with other water radiolysis products. Without the inclusion of intratrack chemistry, the deterministic component of the multiscale model is unable to correctly predict experimental data, highlighting the importance of intratrack radiation chemistry in the chemical evolution of the irradiated system.