Prediction of DNA rejoining kinetics and cell survival after proton irradiation for V79 cells using Geant4-DNA.

PURPOSE: Track structure Monte Carlo (MC) codes have achieved successful outcomes in the quantitative investigation of radiation-induced initial DNA damage. The aim of the present study is to extend a Geant4-DNA radiobiological application by incorporating a feature allowing for the prediction of DNA rejoining kinetics and corresponding cell surviving fraction along time after irradiation, for a Chinese hamster V79 cell line, which is one of the most popular and widely investigated cell lines in radiobiology. METHODS: We implemented the Two-Lesion Kinetics (TLK) model, originally proposed by Stewart, which allows for simulations to calculate residual DNA damage and surviving fraction along time via the number of initial DNA damage and its complexity as inputs. RESULTS: By optimizing the model parameters of the TLK model in accordance to the experimental data on V79, we were able to predict both DNA rejoining kinetics at low linear energy transfers (LET) and cell surviving fraction. CONCLUSION: This is the first study to demonstrate the implementation of both the cell surviving fraction and the DNA rejoining kinetics with the estimated initial DNA damage, in a realistic cell geometrical model simulated by full track structure MC simulations at DNA level and for various LET. These simulation and model make the link between mechanistic physical/chemical damage processes and these two specific biological endpoints.

A matter of space: how the spatial heterogeneity in energy deposition determines the biological outcome of radiation exposure.

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.

Intercomparison of nanodosimetric distributions in nitrogen simulated with Geant4 and PTra track structure codes.

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.

Nanodosimetric Calculations of Radiation-Induced DNA Damage in a New Nucleus Geometrical Model Based on the Isochore Theory.

Double-strand breaks (DSBs) in nuclear DNA represents radiation-induced damage that has been identified as particularly deleterious. Calculating this damage using Monte Carlo track structure modeling could be a suitable indicator to better assess and anticipate the side-effects of radiation therapy. However, as already demonstrated in previous work, the geometrical description of the nucleus and the DNA content used in the simulation significantly influence damage calculations. Therefore, in order to obtain accurate results, this geometry must be as realistic as possible. In this study, a new geometrical model of an endothelial cell nucleus and DNA distribution according to the isochore theory are presented and used in a Monte Carlo simulation chain based on the Geant4-DNA toolkit. In this theory, heterochromatin and euchromatin compaction are distributed along the genome according to five different families (L1, L2, H1, H2, and H3). Each of these families is associated with a different hetero/euchromatin rate related to its compaction level. In order to compare the results with those obtained using a previous nuclear geometry, simulations were performed for protons with linear energy transfers (LETs) of 4.29 keV/µm, 19.51 keV/µm, and 43.25 keV/µm. The organization of the chromatin fibers at different compaction levels linked to isochore families increased the DSB yield by 6-10%, and it allowed the most affected part of the genome to be identified. These new results indicate that the genome core is more radiosensitive than the genome desert, with a 3-8% increase in damage depending on the LET. This work highlights the importance of using realistic distributions of chromatin compaction levels to calculate radio-induced damage using Monte Carlo simulation methods.

Modeling Early Radiation DNA Damage Occurring During 177Lu-DOTATATE Radionuclide Therapy.

The aim of this study was to build a simulation framework to evaluate the number of DNA double-strand breaks (DSBs) induced by in vitro targeted radionuclide therapy (TRT). This work represents the first step toward exploring underlying biologic mechanisms and the influence of physical and chemical parameters to enable a better response prediction in patients. We used this tool to characterize early DSB induction by 177Lu-DOTATATE, a commonly used TRT for neuroendocrine tumors. Methods: A multiscale approach was implemented to simulate the number of DSBs produced over 4 h by the cumulated decays of 177Lu distributed according to the somatostatin receptor binding. The approach involves 2 sequential simulations performed with Geant4/Geant4-DNA. The radioactive source is sampled according to uptake experiments on the distribution of activities within the medium and the planar cellular cluster, assuming instant and permanent internalization. A phase space is scored around the nucleus of the central cell. Then, the phase space is used to generate particles entering the nucleus containing a multiscale description of the DNA in order to score the number of DSBs per particle source. The final DSB computations are compared with experimental data, measured by immunofluorescent detection of p53-binding protein 1 foci. Results: The probability of electrons reaching the nucleus was significantly influenced by the shape of the cell compartment, causing a large variance in the induction pattern of DSBs. A significant difference was found in the DSBs induced by activity distributions in cell and medium, as is explained by the specific energy ([Formula: see text]) distributions. The average number of simulated DSBs was 14 DSBs per cell (range, 7-24 DSBs per cell), compared with 13 DSBs per cell (range, 2-30 DSBs per cell) experimentally determined. We found a linear correlation between the mean absorbed dose to the nucleus and the number of DSBs per cell: 0.014 DSBs per cell mGy-1 for internalization in the Golgi apparatus and 0.017 DSBs per cell mGy-1 for internalization in the cytoplasm. Conclusion: This simulation tool can lead to a more reliable absorbed-dose-to-DNA correlation and help in prediction of biologic response.

A Geant4-DNA Evaluation of Radiation-Induced DNA Damage on a Human Fibroblast.

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.

Geant4-DNA simulation of the pre-chemical stage of water radiolysis and its impact on initial radiochemical yields.

This paper demonstrates the impact of the pre-chemical stage, especially the dissociation scheme and the associated probabilities, on water radiolysis simulation using the Geant4-DNA Monte Carlo track structure simulation toolkit. The models and parameters provided by TRACs have been collected and implemented into Geant4-DNA. In order to evaluate their influence on water radiolysis simulation, the radiochemical yields (G-values) are evaluated as a function of time and LET using the "chem6" Geant4-DNA example, and they are compared with published experimental and calculated data. The new pre-chemical models lead to a better agreement with literature data than the default pre-chemical models of Geant4-DNA, especially for OH radicals and H2O2. The revised chemistry constructor "G4EmDNAChemistry_option3" is available in Geant4-DNA version 10.7.

Radiation Enhancer Effect of Platinum Nanoparticles in Breast Cancer Cell Lines: In Vitro and In Silico Analyses.

High-Z metallic nanoparticles (NPs) are new players in the therapeutic arsenal against cancer, especially radioresistant cells. Indeed, the presence of these NPs inside malignant cells is believed to enhance the effect of ionizing radiation by locally increasing the dose deposition. In this context, the potential of platinum nanoparticles (PtNPs) as radiosensitizers was investigated in two breast cancer cell lines, T47D and MDA-MB-231, showing a different radiation sensitivity. PtNPs were internalized in the two cell lines and localized in lysosomes and multivesicular bodies. Analyses of cell responses in terms of clonogenicity, survival, mortality, cell-cycle distribution, oxidative stress, and DNA double-strand breaks did not reveal any significant enhancement effect when cells were pre-exposed to PtNPs before being irradiated, as compared to radiation alone. This result is different from that reported in a previous study performed, under the same conditions, on cervical cancer HeLa cells. This shows that the efficacy of radio-enhancement is strongly cell-type-dependent. Simulation of the early stage ionization processes, taking into account the irradiation characteristics and realistic physical parameters in the biological sample, indicated that PtNPs could weakly increase the dose deposition (by 3%) in the immediate vicinity of the nanoparticles. Some features that are potentially responsible for the biological effect could not be taken into account in the simulation. Thus, chemical and biological effects could explain this discrepancy. For instance, we showed that, in these breast cancer cell lines, PtNPs exhibited ambivalent redox properties, with an antioxidant potential which could counteract the radio-enhancement effect. This work shows that the efficacy of PtNPs for enhancing radiation effects is strongly cell-dependent and that no effect is observed in the case of the breast cancer cell lines T47D and MDA-MB-231. Thus, more extensive experiments using other relevant biological models are needed in order to evaluate such combined strategies, since several clinical trials have already demonstrated the success of combining nanoagents with radiotherapy in the treatment of a range of tumor types.

Review of the Geant4-DNA Simulation Toolkit for Radiobiological Applications at the Cellular and DNA Level.

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 ß±-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.

Assessment of DNA damage with an adapted independent reaction time approach implemented in Geant4-DNA for the simulation of diffusion-controlled reactions between radio-induced reactive species and a chromatin fiber.

PURPOSE: Simulation of indirect damage originating from the attack of free radical species produced by ionizing radiation on biological molecules based on the independent pair approximation is investigated in this work. In addition, a new approach, relying on the independent pair approximation that is at the origin of the independent reaction time (IRT) method, is proposed in the chemical stage of Geant4-DNA. METHODS: This new approach has been designed to respect the current Geant4-DNA chemistry framework while proposing a variant IRT method. Based on the synchronous algorithm, this implementation allows us to access the information concerning the position of radicals and may make it more convenient for biological damage simulations. Estimates of the evolution of free species as well as biological hits in a segment of DNA chromatin fiber in Geant4-DNA were compared for the dynamic time step approach of the step-by-step (SBS) method, currently used in Geant4-DNA, and this newly implemented IRT. RESULTS: Results show a gain in computation time of a factor of 30 for high LET particle tracks with a better than 10% agreement on the number of DNA hits between the value obtained with the IRT method as implemented in this work and the SBS method currently available in Geant4-DNA. CONCLUSION: Offering in Geant4-DNA more efficient methods for the chemical step based on the IRT method is a task in progress. For the calculation of biological damage, information on the position of chemical species is a crucial point. This can be achieved using the method presented in this paper.

Independent reaction times method in Geant4-DNA: Implementation and performance.

PURPOSE: The simulation of individual particle tracks and the chemical stage following water radiolysis in biological tissue is an effective means of improving our knowledge of the physico-chemical contribution to the biological effect of ionizing radiation. However, the step-by-step simulation of the reaction kinetics of radiolytic species is the most time-consuming task in Monte Carlo track-structure simulations, with long simulation times that are an impediment to research. In this work, we present the implementation of the independent reaction times (IRT) method in Geant4-DNA Monte Carlo toolkit to improve the computational efficiency of calculating G-values, defined as the number of chemical species created or lost per 100 eV of deposited energy. METHODS: The computational efficiency of IRT, as implemented, is compared to that from available Geant4-DNA step-by-step simulations for electrons, protons and alpha particles covering a wide range of linear energy transfer (LET). The accuracy of both methods is verified using published measured data from fast electron irradiations for • OH and e aq - for time-dependent G-values. For IRT, simulations in the presence of scavengers irradiated by cobalt-60 γ-ray and 2 MeV protons are compared with measured data for different scavenging capacities. In addition, a qualitative assessment comparing measured LET-dependent G-values with Geant4-DNA calculations in pure liquid water is presented. RESULTS: The IRT improved the computational efficiency by three orders of magnitude relative to the step-by-step method while differences in G-values by 3.9% at 1 µs were found. At 7 ps, • OH and e aq - yields calculated with IRT differed from recent published measured data by 5% ± 4% and 2% ± 4%, respectively. At 1 µs, differences were 9% ± 5% and 6% ± 7% for • OH and e aq - , respectively. Uncertainties are one standard deviation. Finally, G-values at different scavenging capacities and LET-dependent G-values reproduced the behavior of measurements for all radiation qualities. CONCLUSION: The comprehensive validation of the Geant4-DNA capabilities to accurately simulate the chemistry following water radiolysis is an ongoing work. The implementation presented in this work is a necessary step to facilitate performing such a task.

Assessment of Radio-Induced Damage in Endothelial Cells Irradiated with 40 kVp, 220 kVp, and 4 MV X-rays by Means of Micro and Nanodosimetric Calculations.

The objective of this work was to study the differences in terms of early biological effects that might exist between different X-rays energies by using a mechanistic approach. To this end, radiobiological experiments exposing cell monolayers to three X-ray energies were performed in order to assess the yields of early DNA damage, in particular of double-strand breaks (DSBs). The simulation of these irradiations was set in order to understand the differences in the obtained experimental results. Hence, simulated results in terms of microdosimetric spectra and early DSB induction were analyzed and compared to the experimental data. Human umbilical vein endothelial cells (HUVECs) were irradiated with 40, 220 kVp, and 4 MV X-rays. The Geant4 Monte Carlo simulation toolkit and its extension Geant4-DNA were used for the simulations. Microdosimetric calculations aiming to determine possible differences in the variability of the energy absorbed by the irradiated cell population for those photon spectra were performed on 10,000 endothelial cell nuclei representing a cell monolayer. Nanodosimetric simulations were also carried out using a computation chain that allowed the simulation of physical, physico-chemical, and chemical stages on a single realistic endothelial cell nucleus model including both heterochromatin and euchromatin. DNA damage was scored in terms of yields of prompt DSBs per Gray (Gy) and per giga (109) base pair (Gbp) and DSB complexity was derived in order to be compared to experimental data expressed as numbers of histone variant H2AX (γ-H2AX) foci per cell. The calculated microdosimetric spread in the irradiated cell population was similar when comparing between 40 and 220 kVp X-rays and higher when comparing with 4 MV X-rays. Simulated yields of induced DSB/Gy/Gbp were found to be equivalent to those for 40 and 220 kVp but larger than those for 4 MV, resulting in a relative biological effectiveness (RBE) of 1.3. Additionally, DSB complexity was similar between the considered photon spectra. Simulated results were in good agreement with experimental data obtained by IRSN (Institut de radioprotection et de sûreté nucléaire) radiobiologists. Despite differences in photon energy, few differences were observed when comparing between 40 and 220 kVp X-rays in microdosimetric and nanodosimetric calculations. Nevertheless, variations were observed when comparing between 40/220 kVp and 4 MV X-rays. Thanks to the simulation results, these variations were able to be explained by the differences in the production of secondary electrons with energies below 10 keV.

Determining dose enhancement factors of high-Z nanoparticles from simulations where lateral secondary particle disequilibrium exists.

Nanoparticles (NPs) containing high atomic number (high-Z) materials have been shown to enhance the radiobiological effectiveness of ionizing radiation. This effect is often attributed to an enhancement of the absorbed dose in the vicinity of the NPs, based on Monte Carlo simulations that show a significant local enhancement of the energy deposition on the microscopic scale. The results of such simulations may be significantly biased and lead to a severe overestimation of the dose enhancement if the condition of secondary particle equilibrium is not met in the simulation setup. This current work shows an approach to estimate a 'realistic' dose enhancement from the results of such biased simulations which is based on published photon interaction data and provides a way for correcting biased results.

Evaluation of early radiation DNA damage in a fractal cell nucleus model using Geant4-DNA.

The advancement of multidisciplinary research fields dealing with ionising radiation induced biological damage - radiobiology, radiation physics, radiation protection and, in particular, medical physics - requires a clear mechanistic understanding of how cellular damage is induced by ionising radiation. Monte Carlo (MC) simulations provide a promising approach for the mechanistic simulation of radiation transport and radiation chemistry, towards the in silico simulation of early biological damage. We have recently developed a fully integrated MC simulation that calculates early single strand breaks (SSBs) and double strand breaks (DSBs) in a fractal chromatin based human cell nucleus model. The results of this simulation are almost equivalent to past MC simulations when considering direct/indirect strand break fraction, DSB yields and fragment distribution. The simulation results agree with experimental data on DSB yields within 13.6% on average and fragment distributions agree within an average of 34.8%.

From Energy Deposition of Ionizing Radiation to Cell Damage Signaling: Benchmarking Simulations by Measured Yields of Initial DNA Damage after Ion Microbeam Irradiation.

Advances in accelerator technology, which have enabled conforming radiotherapy with charged hadronic species, have brought benefits as well as potential new risks to patients. To better understand the effects of ionizing radiation on tumor and surrounding tissue, it is important to investigate and quantify the relationship between energy deposition at the nanometric scale and the initial biological events. Monte Carlo track structure simulation codes provide a powerful tool for investigating this relationship; however, their success and reliability are dependent on their improvement and development accordingly to the dedicated biological data to which they are challenged. For this aim, a microbeam facility that allows for fluence control, down to one ion per cell nucleus, was used to evaluate relative frequencies of DNA damage after interaction between the incoming ion and DNA according to radiation quality. Primary human cells were exposed to alpha particles of three different energies with respective linear energy transfers (LETs) of approximately 36, 85 or 170 keV·µm-1 at the cells' center position, or to protons (19 keV·µm-1). Statistical evaluation of nuclear foci formation (53BP1/γ-H2AX), observed using immunofluorescence and related to a particle traversal, was undertaken in a large population of cell nuclei. The biological results were adjusted to consider the factors that drive the experimental uncertainties, then challenged with results using Geant4-DNA code modeling of the ionizing particle interactions on a virtual phantom of the cell nucleus with the same mean geometry and DNA density as the cells used in our experiments. Both results showed an increase of relative frequencies of foci (or simulated DNA damage) in cell nuclei as a function of increasing LET of the traversing particles, reaching a quasi-plateau when the LET exceeded 80-90 keV·µm-1. For the LET of an alpha particle ranging from 80-90 to 170 keV·µm-1, 10-30% of the particle hits did not lead to DNA damage inducing 53BP1 or γ-H2AX foci formation.

SIMULATION OF EARLY RADIATION-INDUCED DNA DAMAGE ON DIFFERENT TYPES OF CELL NUCLEI.

This work presents a comparison of simulated early radiation-induced DNA damage represented by yields of double-strand breaks (DSB) in three different human cell nuclei geometries representing fibroblasts, lymphocytes and endothelial cells for protons and alpha particles of different energies and for different irradiation configurations. Each cell nucleus model includes a multi-scale description of the DNA target from the molecular level to the whole human genome representation (6 Gbp) in the G0/G1 phase of the cell cycle and was generated with the DnaFabric software. The three nuclei differ in shape, volume, and therefore DNA density. A calculation chain based on Geant4-DNA that takes into account the physical, physico-chemical and chemical stages was used to simulate the irradiation of the different cell nuclei. Results show an increase of DSB/primary/µm with an increase of DNA density and an increase of DSB/Gy/Gbp with an increase of the cell nucleus volume which indicates that the cell nucleus shape and size have an impact on early DNA damage, which may play a role in latter effects.

Relation between DNA double-strand breaks and energy spectra of secondary electrons produced by different X-ray energies.

Purpose: In a radiological examination, low-energy X-radiation is used (<100 keV). For other radiological procedures, the energy used is several MeV. ICRP in publication 103 has currently considered that photons irrespective of their energy have the same radiation weighting factor. Nevertheless, there are topological differences at the nanoscale of X-ray energy deposition as a function of its energy spectrum, meaning that the different interactions with living matter could vary in biological efficacy. Materials and methods: To study these differences, we characterized our irradiation conditions in terms of initial photon energies, but especially in terms of energy spectra of secondary electrons at the cell nucleus level, using Monte Carlo simulations. We evaluated signaling of DNA damage by monitoring a large number of γH2A.X foci after exposure of G0/G1-phase synchronized human primary endothelial cells from 0.25 to 5 Gy at 40 kV, 220 kV and 4 MV X-rays. Number and spatial distribution of γH2A.X foci were explored. In parallel, we investigated cell behavior through cell death and ability of a mother cell to produce two daughter cells. We also studied the missegregation rate after cell division. Results: We report a higher number of DNA double-strand breaks signaled by γH2A.X for 40 kVp and/or 220 kVp compared to 4 MVp for the highest tested doses of 2 and 5 Gy. We observed no difference between the biological endpoint studies with 40 kVp and 220 kVp X-ray spectra. This lack of difference could be explained by the relative similarity of the calculated energy spectra of secondary electrons at the cell monolayer. Conclusion: The energy spectrum of secondary electrons seems to be more closely related to the level of DNA damage measured by γH2A.X than the initial spectrum of photon energy or voltage settings. Our results indicate that as the energy spectrum of secondary electrons increases, the DNA damage signaled by γH2A.X decreases and this effect is observable beyond 220 kVp.

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.

Simulation of early DNA damage after the irradiation of a fibroblast cell nucleus using Geant4-DNA.

In order to improve the understanding of the mechanisms involved in the generation of early DNA damage, a new calculation chain based on the Geant4-DNA toolkit was developed. This work presents for the first time the simulation of the physical, physicochemical and chemical stages of early radiation damage at the scale of an entire human genome (fibroblast, male) and using Geant4-DNA models. The DnaFabric software was extended to generate and export this nucleus model to a text file with a specific format that can be read by Geant4 user applications. This calculation chain was used to simulate the irradiation of the nucleus by primary protons of different energies (0,5; 0,7; 0,8; 1; 1,5; 2; 3; 4; 5; 10; 20 MeV) and the results, in terms of DNA double strand breaks, agree with experimental data found in the literature (pulsed field electrophoresis technique). These results show that the simulation is consistent and that its parameters are well balanced. Among the different parameters that can be adjusted, our results demonstrate that the criterion used to select direct strand break appears to have a very significant role on the final number of simulated double strand breaks.