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At the Heidelberg Ion-Beam Therapy Center, the track structure of carbon ions of therapeutic energy after penetrating layers of simulated tissue was investigated for the first time. Measurements were conducted with carbon ion beams of different energies and polymethyl methacrylate (PMMA) absorbers of different thicknesses to realize different depths in the phantom along the pristine Bragg peak. Ionization cluster size (ICS) distributions resulting from the mixed radiation field behind the PMMA absorbers were measured using an ion-counting nanodosimeter. Two different measurements were carried out: (i) variation of the PMMA absorber thickness with constant carbon ion beam energy and (ii) combined variation of PMMA absorber thickness and carbon ion beam energy such that the kinetic energy of the carbon ions in the target volume is constant. The data analysis revealed unexpectedly high mean ICS values compared to stopping power calculations and the data measured at lower energies in earlier work. This suggests that in the measurements the carbon ion kinetic energies behind the PMMA absorber may have deviated considerably from the expected values obtained by the calculations. In addition, the results indicate the presence of a marked contribution of nuclear fragments to the measured ICS distributions, especially if the carbon ion does not cross the target volume.

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Objective.To present a new set of lithium-ion cross-sections for (i) ionization and excitation processes down to 700 eV, and (ii) charge-exchange processes down to 1 keV u-1. To evaluate the impact of the use of these cross-sections on micro a nano dosimetric quantities in the context of boron neutron capture (BNC) applications/techniques.Approach.The Classical Trajectory Monte Carlo method was used to calculate Li ion charge-exchange cross sections in the energy range of 1 keV u-1to 10 MeV u-1. Partial Li ion charge states ionization and excitation cross-sections were calculated using a detailed charge screening factor. The cross-sections were implemented in Geant4-DNA v10.07 and simulations and verified using TOPAS-nBio by calculating stopping power and continuous slowing down approximation (CSDA) range against data from ICRU and SRIM. Further microdosimetric and nanodosimetric calculations were performed to quantify differences against other simulation approaches for low energy Li ions. These calculations were: lineal energy spectra (yf(y) andyd(y)), frequency mean lineal energyyF-, dose mean lineal energyyD-and ionization cluster size distribution analysis. Microdosimetric calculations were compared against a previous MC study that neglected charge-exchange and excitation processes. Nanodosimetric results were compared against pure ionization scaled cross-sections calculations.Main results.Calculated stopping power differences between ICRU and Geant4-DNA decreased from 33.78% to 6.9%. The CSDA range difference decreased from 621% to 34% when compared against SRIM calculations. Geant4-DNA/TOPAS calculated dose mean lineal energy differed by 128% from the previous Monte Carlo. Ionization cluster size frequency distributions for Li ions differed by 76%-344.11% for 21 keV and 2 MeV respectively. With a decrease in theN1within 9% at 10 keV and agreeing after the 100 keV. With the new set of cross-sections being able to better simulate low energy behaviors of Li ions.Significance.This work shows an increase in detail gained from the use of a more complete set of low energy cross-sections which include charge exchange processes. Significant differences to previous simulation results were found at the microdosimetric and nanodosimetric scales that suggest that Li ions cause less ionizations per path length traveled but with more energy deposits. Microdosimetry results suggest that the BNC's contribution to cellular death may be mainly due to alpha particle production when boron-based drugs are distributed in the cellular membrane and beyond and by Li when it is at the cell cytoplasm regions.

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Details of excitation and ionization acts hide a description of the biological effects of charged particle traversal through living tissue. Nanodosimetry enables the introduction of novel quantities that characterize and quantify the particle track structure while also serving as a foundation for assessing biological effects based on this quantification. This presents an opportunity to enhance the planning of charged particle radiotherapy by taking into account the ionization detail. This work uses Monte Carlo simulations with Geant4-DNA code for a wide variety of charged particles and their radiation qualities to analyze the distribution of ionization cluster sizes within nanometer-scale volumes, similar to DNA diameter. By correlating these results with biological parameters extracted from the PIDE database for the V79 cell line, a novel parameter R2 based on ionization details is proposed for the evaluation of radiation quality in terms of biological consequences, i.e., radiobiological cross section for inactivation. By incorporating the probability p of sub-lethal damage caused by a single ionization, we address limitations associated with the usually proposed nanodosimetric parameter Fk for characterizing the biological effects of radiation. We show that the new parameter R2 correlates well with radiobiological data and can be used to predict biological outcomes.

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The major part of energy deposition of ionizing radiation is caused by secondary electrons, independent of the primary radiation type. However, their spatial concentration and their spectral properties strongly depend on the primary radiation type and finally determine the pattern of molecular damage e.g. to biological targets as the DNA, and thus the final effect of the radiation exposure. To describe the physical and to predict the biological consequences of charged ion irradiation, amorphous track structure approaches have proven to be pragmatic and helpful. There, the local dose deposition in the ion track is equated by considering the emission and slowing down of the secondary electrons from the primary particle track. In the present work we exploit the model of Kiefer and Straaten and derive the spectral composition of secondary electrons as function of the distance to the track center. The spectral composition indicates differences to spectra of low linear energy transfer (LET) photon radiation, which we confirm by a comparison with Monte Carlo studies. We demonstrate that the amorphous track structure approach provides a simple tool for evaluating the spectral electron properties within the track structure. Predictions of the LET of electrons across the track structure as well as the electronic dose build-up effect are derived. Implications for biological effects and corresponding predicting models based on amorphous track structure are discussed.

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Cosmic rays have the potential to significantly affect the atmospheric composition by increasing the rate and changing the types of chemical reactions through ion production. The amount and states of ionization, and the spatial distribution of ions produced are still open questions for atmospheric models. To precisely estimate these quantities, it is necessary to simulate particle-molecule interactions, down to very low energies. Models enabling such simulations require interaction probabilities over a broad energy range and for all energetically allowed scattering processes. In this paper, we focus on electron interaction with the two most abundant molecules in the atmosphere, i.e., N2 and O2, as an initial step. A set of elastic and inelastic cross section models for electron transportation in oxygen and nitrogen molecules valid in the energy range 10 eV - 1 MeV, is presented. Comparison is made with available theoretical and experimental data and a reasonable good agreement is observed. Stopping power is calculated and compared with published data to assess the general consistency and reliability of our results. Good overall agreement is observed, with relative differences lower than 6% with the ESTAR database.

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Objective. To propose a mathematical model for applying ionization detail (ID), the detailed spatial distribution of ionization along a particle track, to proton and ion beam radiotherapy treatment planning (RTP).Approach. Our model provides for selection of preferred ID parameters (Ip) for RTP, that associate closest to biological effects. Cluster dose is proposed to bridge the large gap between nanoscopicIpand macroscopic RTP. Selection ofIpis demonstrated using published cell survival measurements for protons through argon, comparing results for nineteenIp:Nk,k= 2, 3, …, 10, the number of ionizations in clusters ofkor more per particle, andFk,k= 1, 2, …, 10, the number of clusters ofkor more per particle. We then describe application of the model to ID-based RTP and propose a path to clinical translation.Main results. The preferredIpwereN4andF5for aerobic cells,N5andF7for hypoxic cells. Significant differences were found in cell survival for beams having the same LET or the preferredNk. Conversely, there was no significant difference forF5for aerobic cells andF7for hypoxic cells, regardless of ion beam atomic number or energy. Further, cells irradiated with the same cluster dose for theseIphad the same cell survival. Based on these preliminary results and other compelling results in nanodosimetry, it is reasonable to assert thatIpexist that are more closely associated with biological effects than current LET-based approaches and microdosimetric RBE-based models used in particle RTP. However, more biological variables such as cell line and cycle phase, as well as ion beam pulse structure and rate still need investigation.Significance. Our model provides a practical means to select preferredIpfrom radiobiological data, and to convertIpto the macroscopic cluster dose for particle RTP.

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Objective.Boron neutron capture therapy (BNCT) is an advanced cellular-level hadron therapy that has exhibited remarkable therapeutic efficacy in the treatment of locally invasive malignancies. Despite its clinical success, the intricate nature of relative biological effectiveness (RBE) and mechanisms responsible for DNA damage remains elusive. This work aims to quantify the RBE of compound particles (i.e. alpha and lithium) in BNCT based on the calculation of DNA damage yields via the Monte Carlo track structure (MCTS) simulation.Approach. The TOPAS-nBio toolkit was employed to conduct MCTS simulations. The calculations encompassed four steps: determination of the angle and energy spectra on the nuclear membrane, quantification of the database containing DNA damage yields for ions with specific angle and energy, accumulation of the database and spectra to obtain the DNA damage yields of compound particles, and calculation of the RBE by comparison yields of double-strand break (DSB) with the reference gamma-ray. Furthermore, the impact of cell size and microscopic boron distribution was thoroughly discussed.Main results. The DSB yields induced by compound particles in three types of spherical cells (radius equal to 10, 8, and 6µm) were found to be 13.28, 17.34, 22.15 Gy Gbp-1for boronophenylalanine (BPA), and 1.07, 3.45, 8.32 Gy Gbp-1for sodium borocaptate (BSH). The corresponding DSB-based RBE values were determined to be 1.90, 2.48, 3.16 for BPA and 0.15, 0.49, 1.19 for BSH. The calculated DSB-based RBE showed agreement with experimentally values of compound biological effectiveness for melanoma and gliosarcoma. Besides, the DNA damage yield and DSB-based RBE value exhibited an increasing trend as the cell radius decreased. The impact of the boron concentration ratio on RBE diminished once the drug enrichment surpasses a certain threshold.Significance. This work is potential to provide valuable guidance for accurate biological-weighted dose evaluation in BNCT.

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The indirect effect of radiation plays an important role in radio-induced biological damages. Monte Carlo codes have been widely used in recent years to study the chemical evolution of particle tracks. However, due to the large computational efforts required, their applicability is typically limited to simulations in pure water targets and to temporal scales up to the µs. In this work, a new extension of TRAX-CHEM is presented, namely TRAX-CHEMxt, able to predict the chemical yields at longer times, with the capability of exploring the homogeneous biochemical stage. Based on the species coordinates produced around one track, the set of reaction-diffusion equations is solved numerically with a computationally light approach based on concentration distributions. In the overlapping time scale (500 ns-1 µs), a very good agreement to standard TRAX-CHEM is found, with deviations below 6% for different beam qualities and oxygenations. Moreover, an improvement in the computational speed by more than three orders of magnitude is achieved. The results of this work are also compared with those from another Monte Carlo-based algorithm and a fully homogeneous code (Kinetiscope). TRAX-CHEMxt will allow for studying the variation in chemical endpoints at longer timescales with the introduction, as the next step, of biomolecules, for more realistic assessments of biological response under different radiation and environmental conditions.

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Objective. Estimation of the probability density of the microdosimetric quantities in macroscopic matter is indispensable for applying the concept of microdosimetry to medical physics and radiological protection. The Particle and Heavy Ion Transport code System (PHITS) enables estimating the microdosimetric probability densities due to its unique hybrid modality between the Monte Carlo and analytical approaches called the microdosimetric function. It can convert the deposition energies calculated by the macroscopic Monte Carlo radiation transport simulation to microdosimetric probability densities in water using an analytical function based on the track-structure simulations.Approach. In this study, we improved this function using the latest track-structure simulation codes implemented in PHITS. The improved function is capable of calculating the probability densities of not only the conventional microdosimetric quantities such as lineal energy but also the number of ionization events occurring in a target site, the so-called ionization cluster size distribution, for arbitrary site diameters from 3 nm to 1µm.Main results. The accuracy of the improved function was well verified by comparing the microdosimetric probability densities measured by tissue-equivalent proportional counters with the corresponding data calculated in this study. Test calculations for clonogenic cell survival using the improved function coupled with the modified microdosimetric kinetic model suggested a slight increase of its relative biological effectiveness compared with our previous estimations. As a new application of the improved function, we calculated the relative biological effectiveness of the single-strand break and double-strand break yields for proton irradiations using the updated PHITS coupled with the simplified DNA damage estimation model, and confirmed its equivalence in accuracy and its superiority in computational time compared to our previously proposed method based on the track-structure simulation.Significance. From these features, we concluded that the improved function could expand the application fields of PHITS by bridging the gap between microdosimetry and macrodosimetry.

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Boron neutron capture therapy (BNCT) is a cellular-level hadron therapy achieving therapeutic effects via the synergistic action of multiple particles, including Lithium, alpha, proton, and photon. However, evaluating the relative biological effectiveness (RBE) in BNCT remains challenging. In this research, we performed a microdosimetric calculation for BNCT using the Monte Carlo track structure (MCTS) simulation toolkit, TOPAS-nBio. This paper reports the first attempt to derive the ionization cross-sections of low-energy (>0.025 MeV/u) Lithium for MCTS simulation based on the effective charge cross-section scalation method and phenomenological double-parameter modification. The fitting parameters λ1=1.101,λ2=3.486 were determined to reproduce the range and stopping power data from the ICRU report 73. Besides, the lineal energy spectra of charged particles in BNCT were calculated, and the influence of sensitive volume (SV) size was discussed. Condensed history simulation obtained similar results with MCTS when using Micron-SV while overestimating the lineal energy when using Nano-SV. Furthermore, we found that the microscopic boron distribution can significantly affect the lineal energy for Lithium, while the effect for alpha is minimal. Similar results to the published data by PHITS simulation were observed for the compound particles and monoenergetic protons when using micron-SV. Spectra with nano-SV reflected that the different track densities and absorbed doses in the nucleus together result in the dramatic difference in the macroscopic biological response of BPA and BSH. This work and the developed methodology could impact the research fields in BNCT where understanding radiation effects is crucial, such as the treatment planning system, source evaluation, and new boron drug development.

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Objective. The TOPAS-nBio Monte Carlo track structure simulation code, a wrapper of Geant4-DNA, was extended for its use in pulsed and longtime homogeneous chemistry simulations using the Gillespie algorithm.Approach. Three different tests were used to assess the reliability of the implementation and its ability to accurately reproduce published experimental results: (1) a simple model with a known analytical solution, (2) the temporal evolution of chemical yields during the homogeneous chemistry stage, and (3) radiolysis simulations conducted in pure water with dissolved oxygen at concentrations ranging from 10µM to 1 mM with [H2O2] yields calculated for 100 MeV protons at conventional and FLASH dose rates of 0.286 Gy s-1and 500 Gy s-1, respectively. Simulated chemical yield results were compared closely with data calculated using the Kinetiscope software which also employs the Gillespie algorithm.Main results. Validation results in the third test agreed with experimental data of similar dose rates and oxygen concentrations within one standard deviation, with a maximum of 1% difference for both conventional and FLASH dose rates. In conclusion, the new implementation of TOPAS-nBio for the homogeneous long time chemistry simulation was capable of recreating the chemical evolution of the reactive intermediates that follow water radiolysis.Significance. Thus, TOPAS-nBio provides a reliable all-in-one chemistry simulation of the physical, physico-chemical, non-homogeneous, and homogeneous chemistry and could be of use for the study of FLASH dose rate effects on radiation chemistry.

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It is generally recognized that the biological response to irradiation by light ions is initiated by complex damages at the DNA level. In turn, the occurrence of complex DNA damages is related to spatial and temporal distribution of ionization and excitation events, i.e., the particle track structure. It is the aim of the present study to investigate the correlation between the distribution of ionizations at the nanometric scale and the probability to induce biological damage. By means of Monte Carlo track structure simulations, the mean ionization yield M1 and the cumulative probabilities F1, F2, and F3 of at least one, two and three ionizations, respectively, were calculated in spherical volumes of water-equivalent diameters equal to 1, 2, 5 and 10 nm. When plotted as a function of M1, the quantities F1, F2 and F3 are distributed along almost unique curves, largely independent of particle type and velocity. However, the shape of the curves depends on the size of the sensitive volume. When the site size is 1 nm, biological cross sections are strongly correlated to combined probabilities of F2 and F3 calculated in the spherical volume, and the proportionality factor is the saturation value of biological cross sections.

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In hydrated electron (e-aq) dosimetry, absorbed radiation dose to water is measured by monitoring the concentration of radiation-induced e-aq. However, to obtain accurate dose, the radiation chemical yield of e-aq, G(e-aq), is needed for the radiation quality/setup under investigation. The aim of this study was to investigate the time-evolution of the G-values for the main generated reactive species during water radiolysis using GEANT4-DNA. The effects of cluster size and linear energy transfer (LET) on G(e-aq) were examined. Validity of GEANT4-DNA for calculation of G(e-aq) for clinically relevant energies was studied. Three scenarios were investigated with different phantom sizes and incoming electron energies (1 keV to 1 MeV). The time evolution of G(e-aq) was in good agreement with published data and did not change with decreasing phantom size. The time-evolution of the G-values increases with increasing LET for all radiolytic species. The particle tracks formed with high-energy electrons are separated and the resulting reactive species develop independently in time. With decreasing energy, the mean separation distance between reactive species decreases. The particle tracks might not initially overlap but will overlap shortly thereafter due to diffusion of reactive species, increasing the probability of e-aq recombination with other species. This also explains the decrease of G(e-aq) with cluster size and LET. Finally, if all factors are kept constant, as the incoming electron energy increases to clinically relevant energies, G(e-aq) remains similar to its value at 1 MeV, hence GEANT4-DNA can be used for clinically relevant energies.

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Complex DNA double-strand break (DSB), which is defined as a DSB coupled with additional strand breaks within 10 bp in this study, induced after ionizing radiation or X-rays, is recognized as fatal damage which can induce cell death with a certain probability. In general, a DSB site inside the nucleus of live cells can be experimentally detected using the γ-H2AX focus formation assay. DSB complexity is believed to be detected by analyzing the focus size using such an assay. However, the relationship between focus size and DSB complexity remains uncertain. In this study, using Monte Carlo (MC) track-structure simulation codes, i.e., an in-house WLTrack code and a Particle and Heavy Ion Transport code System (PHITS), we developed an analytical method for qualifying the DSB complexity induced by photon irradiation from the microscopic image of γ-H2AX foci. First, assuming that events (i.e., ionization and excitation) potentially induce DNA strand breaks, we scored the number of events in a water cube (5.03 × 5.03 × 5.03 nm3) along electron tracks. Second, we obtained the relationship between the number of events and the foci size experimentally measured by the γ-H2AX focus formation assay. Third, using this relationship, we evaluated the degree of DSB complexity induced after photon irradiation for various X-ray spectra using the foci size, and the experimental DSB complexity was compared to the results estimated by the well-verified DNA damage estimation model in the PHITS code. The number of events in a water cube was found to be proportional to foci size, suggesting that the number of events intrinsically related to DSB complexity at the DNA scale. The developed method was applicable to focus data measured for various X-ray spectral situations (i.e., diagnostic kV X-rays and therapeutic MV X-rays). This method would contribute to a precise understanding of the early biological impacts of photon irradiation by means of the γ-H2AX focus formation assay.

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In this work, the induction and repair of radiation-induced 53BP1 foci were studied in human umbilical vein endothelial cells irradiated at the PTB microbeam with protons and α-particles of different energies. The data were analyzed in terms of the mean number of 53BP1 foci induced by the different ion beams. The number of 53BP1 foci found at different times post-irradiation suggests that the disappearance of foci follows first order kinetics. The mean number of initially produced foci shows the expected increase with LET. The most interesting finding of this work is that the absolute number of persistent foci increases with LET but not their fraction. Furthermore, protons seem to produce more persistent foci as compared to α-particles of even higher LET. This may be seen as experimental evidence that protons may be more effective in producing severe DNA lesions, as was already shown in other work, and that LET may not be the best suited parameter to characterize radiation quality.

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Diverse isotopes such as 2H, 3He, 10Be, 11C and 14C occur in nuclear reactions in ion beam radiotherapy, in cosmic ray shielding, or are intentionally accelerated in dating techniques. However, only a few studies have specifically addressed the biological effects of diverse isotopes and were limited to energies of several MeV/u. A database of simulations with the PARTRAC biophysical tool is presented for H, He, Li, Be, B and C isotopes at energies from 0.5 GeV/u down to stopping. The doses deposited to a cell nucleus and also the yields per unit dose of single- and double-strand breaks and their clusters induced in cellular DNA are predicted to vary among diverse isotopes of the same element at energies < 1 MeV/u, especially for isotopes of H and He. The results may affect the risk estimates for astronauts in deep space missions or the models of biological effectiveness of ion beams and indicate that radiation protection in 14C or 10Be dating techniques may be based on knowledge gathered with 12C or 9Be.

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Repair of DNA damage induced by ionizing radiation plays an important role in the cell response to ionizing radiation. Radiation-induced DNA damage also activates the p53 system, which determines the fate of cells. The kinetics of repair, which is affected by the cell itself and the complexity of DNA damage, influences the cell response and fate via affecting the p53 system. To mechanistically study the influences of the cell response to different LET radiations, we introduce a new repair module and a p53 system model with NASIC, a Monte Carlo track structure code. The factors determining the kinetics of the double-strand break (DSB) repair are modeled, including the chromosome environment and complexity of DSB. The kinetics of DSB repair is modeled considering the resection-dependent and resection-independent compartments. The p53 system is modeled by simulating the interactions among genes and proteins. With this model, the cell responses to low- and high-LET irradiation are simulated, respectively. It is found that the kinetics of DSB repair greatly affects the cell fate and later biological effects. A large number of DSBs and a slow repair process lead to severe biological consequences. High-LET radiation induces more complex DSBs, which can be repaired by slow processes, subsequently resulting in a longer cycle arrest and, furthermore, apoptosis and more secreting of TGFß. The Monte Carlo track structure simulation with a more realistic repair module and the p53 system model developed in this study can expand the functions of the NASIC code in simulating mechanical radiobiological effects.

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The outcome of the exposure of living organisms to ionizing radiation is determined by the distribution of the associated energy deposition at different spatial scales. Radiation proceeds through ionizations and excitations of hit molecules with an ~ nm spacing. Approaches such as nanodosimetry/microdosimetry and Monte Carlo track-structure simulations have been successfully adopted to investigate radiation quality effects: they allow to explore correlations between the spatial clustering of such energy depositions at the scales of DNA or chromosome domains and their biological consequences at the cellular level. Physical features alone, however, are not enough to assess the entity and complexity of radiation-induced DNA damage: this latter is the result of an interplay between radiation track structure and the spatial architecture of chromatin, and further depends on the chromatin dynamic response, affecting the activation and efficiency of the repair machinery. The heterogeneity of radiation energy depositions at the single-cell level affects the trade-off between cell inactivation and induction of viable mutations and hence influences radiation-induced carcinogenesis. In radiation therapy, where the goal is cancer cell inactivation, the delivery of a homogenous dose to the tumour has been the traditional approach in clinical practice. However, evidence is accumulating that introducing heterogeneity with spatially fractionated beams (mini- and microbeam therapy) can lead to significant advantages, particularly in sparing normal tissues. Such findings cannot be explained in merely physical terms, and their interpretation requires considering the scales at play in the underlying biological mechanisms, suggesting a systemic response to radiation.

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Proton beam therapy allows irradiating tumor volumes with reduced side effects on normal tissues with respect to conventional x-ray radiotherapy. Biological effects such as cell killing after proton beam irradiations depend on the proton kinetic energy, which is intrinsically related to early DNA damage induction. As such, DNA damage estimation based on Monte Carlo simulations is a research topic of worldwide interest. Such simulation is a mean of investigating the mechanisms of DNA strand break formations. However, past modellings considering chemical processes and DNA structures require long calculation times. Particle and heavy ion transport system (PHITS) is one of the general-purpose Monte Carlo codes that can simulate track structure of protons, meanwhile cannot handle radical dynamics simulation in liquid water. It also includes a simple model enabling the efficient estimation of DNA damage yields only from the spatial distribution of ionizations and excitations without DNA geometry, which was originally developed for electron track-structure simulations. In this study, we investigated the potential application of the model to protons without any modification. The yields of single-strand breaks, double-strand breaks (DSBs) and the complex DSBs were assessed as functions of the proton kinetic energy. The PHITS-based estimation showed that the DSB yields increased as the linear energy transfer (LET) increased, and reproduced the experimental and simulated yields of various DNA damage types induced by protons with LET up to about 30 keVµm-1. These results suggest that the current DNA damage model implemented in PHITS is sufficient for estimating DNA lesion yields induced after protons irradiation except at very low energies (below 1 MeV). This model contributes to evaluating early biological impacts in radiation therapy.

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To facilitate the use of Geant4-DNA for radiation transport simulations in micro- and nanodosimeters, which are physically operated with tissue-equivalent gases such as nitrogen (and propane), this work aims to extend the cross section data available in Geant4-DNA to include those of nitrogen for electron energies ranging from 1 MeV down to the ionisation threshold. To achieve this, interaction cross section data for nitrogen that have been used with the in-house PTB PTra track structure code have been implemented in the current state-of-the-art Geant4-DNA simulation toolkit. An intercomparison has been performed between the two codes to validate this implementation. To quantify the agreement between the cross section models for nitrogen adopted in PTra and those implemented in Geant4-DNA, the simulation results of both codes were analysed using three physical parameters describing the ionisation cluster size distribution (ICSD): mean ionisation cluster size, variance of the cluster size and the probability to obtain a single ionisation within the target. Statistical analysis of the results indicates that the interaction cross section models for nitrogen used in PTra (elastic scattering, impact ionisations and electronic excitations) have been successfully implemented in Geant4-DNA. In addition, simulated ICSDs were compared to those measured with the Jet Counter nanodosimeter for energies between 100 and 2000 eV. For greater energies, the ICRP data for LET and particle range were used as a reference. The modified Geant4-DNA code and data successfully passed all these benchmarks fulfilling the requirement for their public release in the next version of the Geant4 toolkit.

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