Monte Carlo Track Structure Simulations Research Articles

Comparison of two methods simulating inter-track interactions using the radiobiological Monte Carlo toolkit TOPAS-nBio

Objective. To compare two independently developed methods that enable modelling inter-track interactions in TOPAS-nBio by examining the yield of radiolytic species in radiobiological Monte Carlo track structure simulations. One method uses a phase space file to assign more than one primary to one event, allowing for inter-track interaction between these primary particles. This method has previously been developed by this working group and published earlier. Using the other method, chemical reactions are simulated based on a new version of the independent reaction time approach to allow inter-track interactions. Approach. G-values were calculated and compared using both methods for different numbers of tracks able to undergo inter-track interactions. Main results. Differences in the G-values simulated with the two methods strongly depend on the molecule type, and deviations can range up to 3.9% (H2O2), although, on average, the deviations are smaller than 1.5%. Significance. Both methods seem to be suitable for simulating inter-track interactions, as they provide comparable G-values even though both techniques were developed independently of each other.

Cellular lethal damage of 64Cu incorporated in mammalian genome evaluated with Monte Carlo methods.

Targeted Radionuclide Therapy (TRT) with Auger Emitters (AE) is a technique that allows targeting specific sites on tumor cells using radionuclides. The toxicity of AE is critically dependent on its proximity to the DNA. The aim of this study is to quantify the DNA damage and radiotherapeutic potential of the promising AE radionuclide copper-64 (64Cu) incorporated into the DNA of mammalian cells using Monte Carlo track-structure simulations. A mammalian cell nucleus model with a diameter of 9.3 μm available in TOPAS-nBio was used. The cellular nucleus consisted of double-helix DNA geometrical model of 2.3 nm diameter surrounded by a hydration shell with a thickness of 0.16 nm, organized in 46 chromosomes giving a total of 6.08 giga base-pairs (DNA density of 14.4 Mbp/μm3). The cellular nucleus was irradiated with monoenergetic electrons and radiation emissions from several radionuclides including 111In, 125I, 123I, and 99mTc in addition to 64Cu. For monoenergetic electrons, isotropic point sources randomly distributed within the nucleus were modeled. The radionuclides were incorporated in randomly chosen DNA base pairs at two positions near to the central axis of the double-helix DNA model at (1) 0.25 nm off the central axis and (2) at the periphery of the DNA (1.15 nm off the central axis). For all the radionuclides except for 99mTc, the complete physical decay process was explicitly simulated. For 99mTc only total electron spectrum from published data was used. The DNA Double Strand Breaks (DSB) yield per decay from direct and indirect actions were quantified. Results obtained for monoenergetic electrons and radionuclides 111In, 125I, 123I, and 99mTc were compared with measured and calculated data from the literature for verification purposes. The DSB yields per decay incorporated in DNA for 64Cu are first reported in this work. The therapeutic effect of 64Cu (activity that led 37% cell survival after two cell divisions) was determined in terms of the number of atoms incorporated into the nucleus that would lead to the same DSBs that 100 decays of 125I. Simulations were run until a 2% statistical uncertainty (1 standard deviation) was achieved. The behavior of DSBs as a function of the energy for monoenergetic electrons was consistent with published data, the DSBs increased with the energy until it reached a maximum value near 500 eV followed by a continuous decrement. For 64Cu, when incorporated in the genome at evaluated positions (1) and (2), the DSB were 0.171 ± 0.003 and 0.190 ± 0.003 DSB/decay, respectively. The number of initial atoms incorporated into the genome (per cell) for 64Cu that would cause a therapeutic effect was estimated as 3,107 ± 28, that corresponds to an initial activity of 47.1 ± 0.4 × 10-3 Bq. Our results showed that TRT with 64Cu has comparable therapeutic effects in cells as that of TRT with radionuclides currently used in clinical practice.

Calculation of the DNA damage yield and relative biological effectiveness in boron neutron capture therapy via the Monte Carlo track structure simulation.

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.

A method to implement inter-track interactions in Monte Carlo simulations with TOPAS-nBio and their influence on simulated radical yields following water radiolysis

Objective. In FLASH radiotherapy (dose rates ≥40 Gy s−1), a reduced normal tissue toxicity has been observed, while maintaining the same tumor control compared to conventional radiotherapy (dose rates ≤0.03 Gy s−1). This protecting effect could not be fully explained yet. One assumption is that interactions between the chemicals of different primary ionizing particles, so-called inter-track interactions, trigger this outcome. In this work, we included inter-track interactions in Monte Carlo track structure simulations and investigated the yield of chemicals (G-value) produced by ionizing particles. Approach. For the simulations, we used the Monte Carlo toolkit TOPAS, in which inter-track interactions cannot be implemented without further effort. Thus, we developed a method enabling the simultaneous simulation of N original histories in one event allowing chemical species to interact with each other. To investigate the effect of inter-track interactions we analyzed the G-value of different chemicals using various radiation sources. We used electrons with an energy of 60 eV in different spatial arrangements as well as a 10 MeV and 100 MeV proton source. For electrons we set N between 1 and 60, for protons between 1 and 100. Main results. In all simulations, the total G-value decreases with increasing N. In detail, the G-value for •OH , H3O and eaq decreases with increasing N, whereas the G-value of OH− , H2O2 and H2 increases slightly. The reason is that with increasing N, the concentration of chemical radicals increases allowing for more chemical reactions between the radicals resulting in a change of the dynamics of the chemical stage. Significance. Inter-track interactions resulting in a variation of the yield of chemical species, may be a factor explaining the FLASH effect. To verify this hypothesis, further simulations are necessary in order to evaluate the impact of varying G-values on the yield of DNA damages.

An integrated Monte Carlo track-structure simulation framework for modeling inter and intra-track effects on homogenous chemistry

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 10 μM to 1 mM with [H2O2] yields calculated for 100 MeV protons at conventional and FLASH dose rates of 0.286 Gy s−1 and 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.

Biological modeling of gadolinium-based nanoparticles radio-enhancement for kilovoltage photons: a Monte Carlo study

BackgroundGadolinium-based nanoparticles (GdNPs) are clinically used agents to increase the radiosensitivity of tumor cells. However, studies on the mechanisms and biological modeling of GdNP radio-enhancement are still preliminary. This study aims to investigate the mechanism of radio-enhancement of GdNPs for kilovoltage photons using Monte Carlo (MC) simulations, and to establish local effect model (LEM)-based biological model of GdNP radiosensitization.MethodsThe spectrum and yield of secondary electrons and dose enhancement around a single GdNP and clustered GdNPs were calculated in a water cube phantom by MC track-structure simulations using TOPAS code. We constructed a partial shell-like cell geometry model of pancreatic cancer cell based on transmission electron microscope (TEM) observations. LEM-based biological modeling of GdNP radiosensitization was established based on the MC-calculated nano-scale dose distributions in the cell model to predict the cell surviving fractions after irradiation.ResultsThe yield of secondary electrons for GdNP was 0.16% of the yield for gold nanoparticle (GNP), whereas the average electron energy was 12% higher. The majority of the dose enhancement came from the contribution of Auger electrons. GdNP clusters had a larger range and extent of dose enhancement than single GdNPs, although GdNP clustering reduced radial dose per interacting photon significantly. For the dose range between 0 and 8 Gy, the surviving fraction predicted using LEM-based biological model laid within one standard deviation of the published experimental results, and the deviations between them were all within 25%.ConclusionsThe mechanism of radio-enhancement of GdNPs for kilovoltage photons was investigated using MC simulations. The prediction results of the established LEM-based biological model for GdNP radiosensitization showed good agreement with published experimental results, although the deviation of simulation parameters can lead to large disparity in the results. To our knowledge, this was the first LEM-based biological model for GdNP radiosensitization.

Microdosimetric analysis for boron neutron capture therapy via Monte Carlo track structure simulation with modified lithium cross-sections

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.

Track Structure of Light Ions: The Link to Radiobiology.

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.

An Analytical Method for Quantifying the Yields of DNA Double-Strand Breaks Coupled with Strand Breaks by γ-H2AX Focus Formation Assay Based on Track-Structure Simulation.

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.

Parathyroid Hormone Reduces Persistent Proton Induced DNA Double-Strand Breaks in Osteocytes

<h3>Purpose/Objective(s)</h3> Healthy bone is commonly irradiated during radiotherapy for many cancers, and bone fractures can be a late complication. A recent study revealed a higher incidence of rib fractures after breast irradiation with protons (7%) compared to photons (1%) at the same dose, but the underlying biological mechanisms are unknown. Here we used <i>in vitro</i> experiments, supported by Monte Carlo track structure simulations, to investigate differences in bone cell responses to proton and photon radiation, and to identify potential therapeutic interventions. <h3>Materials/Methods</h3> We used TOPAS-nBio, a radiobiology simulation toolkit, to simulate a segment of bone using geometric models of bone cells (osteoblasts, osteoclasts, and osteocytes). Photon and proton tracks were simulated through bone matrix to investigate energy distributions received by each cell. For <i>in vitro</i> experiments, we utilized the murine osteocytic cell line Ocy454. Cells were irradiated with different doses of protons or photons. Surviving fraction as a function of dose was determined using colony formation assays. DNA double-strand breaks were assessed by 53BP1 foci assay. For PTH treatments, cells were treated with 10 nM human PTH(1-34) for 24 hours prior to irradiation. All experiments were repeated independently three or more times. Statistical analysis was performed by unpaired t-test with Bonferroni correction. <h3>Results</h3> Monte Carlo track simulations showed osteocytes are the bone cell most likely to receive radiation damage, particularly with protons. In the case of large multi-nucleated osteoclasts, both photons and protons spared some of the nuclei, suggesting functional sparing of osteoclasts from radiation damage. We therefore focused our <i>in vitro</i> experiments on Ocy454 osteocytes. Interestingly, the surviving fraction of osteocytes was significantly lower after protons compared to photons for all investigated doses of 1 to 8 Gy. The dose for 10% surviving fraction was 5.38 Gy for protons and 7.46 Gy for photons (Relative Biological Effect 1.39). Although protons and photons induced similar numbers of 53BP1 foci at 1 hour (79% vs. 72% cells with foci), a significantly higher number of foci was observed at 24 hours after protons compared to photons (22% vs. 6.5%, p=0.0078), suggestive of persistent DNA damage after protons. Remarkably, we found that pre-treatment with parathyroid hormone (PTH) decreased 53BP1 foci at 24 hours in proton-irradiated cells to levels comparable to that of non-irradiated cells (22% without PTH vs. 6.3% with PTH, p=0.014). <h3>Conclusion</h3> Surviving fraction of osteocytes was lower after proton compared to photon irradiation, suggesting a greater sensitivity of osteocytes to protons. Protons result in greater DNA damage in osteocytes, but this damage may be mitigated with the addition of PTH. Further study is needed to investigate the potential of PTH to reduce bone damage induced by proton irradiation.

Modeling of DNA Damage Repair and Cell Response in Relation to p53 System Exposed to Ionizing Radiation.

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 TGFβ. 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.

Microdosimetry Study of Proton Quality Factor Using Analytic Model Calculations

The quality factor (Q) is formally linked to the stochastic (e.g., carcinogenic) risk of diverse ionizing radiations at low doses and/or low dose rates. Q can be a function of the non-stochastic physical quantity Linear Energy Transfer (LET) or the microdosimetric parameter lineal energy (y). These two physical quantities can be calculated either by Monte Carlo (MC) track-structure simulations or by analytic models. In this work, various generalized analytical models were utilized and combined to determine the proton lineal energy spectra in liquid water spheres of various sizes (i.e., 10–3000 nm diameter) over the proton energy range of 1–250 MeV. The calculated spectra were subsequently used within the Theory of Dual Radiation Action (TDRA) and the ICRU Report 40 microdosimetric methodologies to determine the variation of Q¯ with proton energy. The results revealed that the LET-based Q values underestimated the microdosimetric-based Q¯ values for protons with energy below ~100 MeV. At energies relevant to the Bragg peak region (&lt;20–30 MeV), the differences were larger than 20–50%, while reaching 200–500% at ~5 MeV. It was further shown that the microdosimetric-based Q¯ values for protons below ~100 MeV were sensitive to the sphere size. Finally, condensed-phase effects had a very small (&lt;5%) influence on the calculated microdosimetric-based Q¯ over the proton energy range considered here.

A computational approach to quantifying miscounting of radiation-induced double-strand break immunofluorescent foci

Immunofluorescent tagging of DNA double-strand break (DSB) markers, such as γ-H2AX and other DSB repair proteins, are powerful tools in understanding biological consequences following irradiation. However, whilst the technique is widespread, there are many uncertainties related to its ability to resolve and reliably deduce the number of foci when counting using microscopy. We present a new tool for simulating radiation-induced foci in order to evaluate microscope performance within in silico immunofluorescent images. Simulations of the DSB distributions were generated using Monte Carlo track-structure simulation. For each DSB distribution, a corresponding DNA repair process was modelled and the un-repaired DSBs were recorded at several time points. Corresponding microscopy images for both a DSB and (γ-H2AX) fluorescent marker were generated and compared for different microscopes, radiation types and doses. Statistically significant differences in miscounting were found across most of the tested scenarios. These inconsistencies were propagated through to repair kinetics where there was a perceived change between radiation-types. These changes did not reflect the underlying repair rate and were caused by inconsistencies in foci counting. We conclude that these underlying uncertainties must be considered when analysing images of DNA damage markers to ensure differences observed are real and are not caused by non-systematic miscounting.

Impact of DNA Geometry and Scoring on Monte Carlo Track-Structure Simulations of Initial Radiation-Induced Damage.

Track structure Monte Carlo simulations are a useful tool to investigate the damage induced to DNA by ionizing radiation. These simulations usually rely on simplified geometrical representations of the DNA subcomponents. DNA damage is determined by the physical and physicochemical processes occurring within these volumes. In particular, damage to the DNA backbone is generally assumed to result in strand breaks. DNA damage can be categorized as direct (ionization of an atom part of the DNA molecule) or indirect (damage from reactive chemical species following water radiolysis). We also consider quasi-direct effects, i.e., damage originated by charge transfers after ionization of the hydration shell surrounding the DNA. DNA geometries are needed to account for the damage induced by ionizing radiation, and different geometry models can be used for speed or accuracy reasons. In this work, we use the Monte Carlo track structure tool TOPAS-nBio, built on top of Geant4-DNA, for simulation at the nanometer scale to evaluate differences among three DNA geometrical models in an entire cell nucleus, including a sphere/spheroid model specifically designed for this work. In addition to strand breaks, we explicitly consider the direct, quasi-direct, and indirect damage induced to DNA base moieties. We use results from the literature to determine the best values for the relevant parameters. For example, the proportion of hydroxyl radical reactions between base moieties was 80%, and between backbone, moieties was 20%, the proportion of radical attacks leading to a strand break was 11%, and the expected ratio of base damages and strand breaks was 2.5-3. Our results show that failure to update parameters for new geometric models can lead to significant differences in predicted damage yields.

Geant4 track structure simulation of electron beam interaction with a gold nanoparticle

Application of nanoparticles as radiosensitizer in various radiation therapy modalities have recently attracted considerable interest. Although experimental findings have shown radiosensitization effect of gold nanoparticles (GNPs) when combining with electron irradiations, observing the recent literature reveals the lack of a standard analysis regarding the modification effects caused by the presence of GNP on physical energy deposition pattern in electron fields. The aim of the current study is to evaluate and verify radioenhancement effects of GNPs under electron beams. Monte Carlo track structure simulation that is the generally accepted approach for investigation of radiation effects in the nanometer scale was conducted by the use of Geant4-DNA code to track electrons down to the 7.4 eV energy. Macroscopic megavoltage energy electron spectrum from an intraoperative electron radiation source was used to irradiate a water phantom while particles were tracked to score the microscopic (nanometer) beam spectrum. Then, a single 50 nm gold nanoparticle was irradiated with the nanobeam where secondary electrons and energy deposition were scored. The results reveal a non-negligible dose escalation of up to 12% at close vicinities of the nanoparticle gradually decreasing at further distances that is caused by low energy electrons originated in the NP. Although, the amount of calculated dose enhancement show dependence on the parameters of the microscopic simulation, the current result provides a theoretical evidence in support of the physical dose enhancement in GNP aided electron radiotherapy.

The effect of non-ionizing excitations on the diffusion of ion species and inter-track correlations in FLASH ultra-high dose rate radiotherapy

Purpose. We present a microscopic mechanism that accounts for the outward burst of ‘cold’ ion species (IS) in a high-energy particle track due to coupling with ‘hot’ non-ion species (NIS). IS refers to radiolysis products of ionized molecules, whereas NIS refers to non-ionized excitations of molecules in a medium. The interaction is mediated by a quantized field of acoustic phonons, a channel that allows conversion of thermal energy of NIS to kinetic energy of IS, a flow of heat from the outer to the inner core of the track structure. Methods. We perform step-by-step Monte Carlo (MC) simulations of ionizing radiation track structures in water to score the spatial coordinates and energy depositions that form IS and NIS at atto-second time scales. We subsequently calculate the resulting temperature profiles of the tracks with MC track structure simulations and verify the results analytically using the Rutherford scattering formulation. These temperature profiles are then used as boundary conditions in a series of multi-scale atomistic molecular dynamic (MD) simulations that describe the sudden expansion and enhanced diffusive broadening of tracks initiated by the non-equilibrium spectrum of high-energy IS. We derive a stochastic coarse-grained Langevin equation of motion for IS from first-principle MD to describe the irreversible femto-second flow of thermal energy pumping from NIS to IS, mediated by quantized fields of acoustic phonons. A pair-wise Lennard-Jones potential implemented in a classical MD is then employed to validate the results calculated from the Langevin equation. Results. We demonstrate the coexistence of ‘hot’ NIS with ‘cold’ IS in the radiation track structures right after their generation. NIS, concentrated within nano-scale volumes wrapping around IS, are the main source of intensive heat-waves and the outward burst of IS due to femto-second time scale IS-NIS coupling. By comparing the transport of IS coupled to NIS with identical configurations of non-interacting IS in thermal equilibrium at room temperature, we demonstrate that the energy gain of IS due to the surrounding hot nanoscopic volumes of NIS significantly increases their effective diffusion constants. Comparing the average track separation and the time scale calculated for a deposited dose of 10 Gy and a dose rate of 40 Gy s−1, typical values used in FLASH ultra high dose rate (UHDR) experiments, we find that the sudden expansion of tracks and ballistic transport proposed in this work strengthens the hypothesis of inter-track correlations recently introduced to interpret mitigation of the biological responses at the FLASH-UHDR (Abolfath et al 2020 Med. Phys. 47, 6551–6561). Conclusions. The much higher diffusion constants predicted in the present model suggest higher inter-track chemical reaction rates at FLASH-UHDR, as well as lower intra-track reaction rates. This study explains why research groups relying on the current Monte Carlo frameworks have reported negligible inter-track overlaps, simply because of underestimation of the diffusion constants. We recommend incorporation of the IS-NIS coupling and heat exchange in all MC codes to enable these tool-kits to appropriately model reaction-diffusion rates at FLASH-UHDR. Novelty. To introduce a hypothetical pathway of outward burst of radiolysis products driven by highly localized thermal spikes wrapping around them and to investigate the interplay of the non-equilibrium spatio-temporal distribution of the chemical activities of diffusive high-energy particle tracks on inter-track correlations at FLASH-UHDR.

Inelastic scattering of electrons in water from first principles: cross sections and inelastic mean free path for use in Monte Carlo track-structure simulations of biological damage.

Modelling the inelastic scattering of electrons in water is fundamental, given their crucial role in biological damage. In Monte Carlo track-structure (MC-TS) codes used to assess biological damage, the energy loss function (ELF), from which cross sections are extracted, is derived from different semi-empirical optical models. Only recently have first ab initio results for the ELF and cross sections in water become available. For benchmarking purpose, in this work, we present ab initio linear-response time-dependent density functional theory calculations of the ELF of liquid water. We calculated the inelastic scattering cross sections, inelastic mean free paths, and electronic stopping power and compared our results with recent calculations and experimental data showing a good agreement. In addition, we provide an in-depth analysis of the contributions of different molecular orbitals, species and orbital angular momenta to the total ELF. Moreover, we present single-differential cross sections computed for each molecular orbital channel, which should prove useful for MC-TS simulations.

TOPAS-nBio validation for simulating water radiolysis and DNA damage under low-LET irradiation

The chemical stage of the Monte Carlo track-structure simulation code Geant4-DNA has been revised and validated. The root-mean-square (RMS) empirical parameter that dictates the displacement of water molecules after an ionization and excitation event in Geant4-DNA has been shortened to better fit experimental data. The pre-defined dissociation channels and branching ratios were not modified, but the reaction rate coefficients for simulating the chemical stage of water radiolysis were updated. The evaluation of Geant4-DNA was accomplished with TOPAS-nBio. For that, we compared predicted time-dependent G values in pure liquid water for ·OH, e– aq, and H2 with published experimental data. For H2O2 and H·, simulation of added scavengers at different concentrations resulted in better agreement with measurements. In addition, DNA geometry information was integrated with chemistry simulation in TOPAS-nBio to realize reactions between radiolytic chemical species and DNA. This was used in the estimation of the yield of single-strand breaks (SSB) induced by 137Cs γ-ray radiolysis of supercoiled pUC18 plasmids dissolved in aerated solutions containing DMSO. The efficiency of SSB induction by reaction between radiolytic species and DNA used in the simulation was chosen to provide the best agreement with published measurements. An RMS displacement of 1.24 nm provided agreement with measured data within experimental uncertainties for time-dependent G values and under the presence of scavengers. SSB efficiencies of 24% and 0.5% for ·OH and H·, respectively, led to an overall agreement of TOPAS-nBio results within experimental uncertainties. The efficiencies obtained agreed with values obtained with published non-homogeneous kinetic model and step-by-step Monte Carlo simulations but disagreed by 12% with published direct measurements. Improvement of the spatial resolution of the DNA damage model might mitigate such disagreement. In conclusion, with these improvements, Geant4-DNA/TOPAS-nBio provides a fast, accurate, and user-friendly tool for simulating DNA damage under low linear energy transfer irradiation.

Investigating the feasibility of TOPAS-nBio for Monte Carlo track structure simulations by adapting GEANT4-DNA examples application

Purpose. The purpose of this work is to investigate the feasibility of TOPAS-nBio for track structure simulations using tuple scoring and ROOT/Python-based post-processing. Materials and methods. There are several example applications implemented in GEANT4-DNA demonstrating track structure simulations. These examples are not implemented by default in TOPAS-nBio. In this study, the tuple scorer was used to re-simulate these examples. The simulations contained investigations of different physics lists, calculation of energy-dependent range, stopping power, mean free path and W-value. Additionally, further applications of the TOPAS-nBio tool were investigated, focusing on physical interactions and deposited energies of electrons with initial energies in the range of 10–60 eV, not covered in the recently published GEANT4-DNA simulations. Low-energetic electrons are currently of great interest in the radiobiology research community due to their high effectiveness towards the induction of biological damage. Results. The quantities calculated with TOPAS-nBio show a good agreement with the simulations of GEANT4-DNA with deviations of 5% at maximum. Thus, we have presented a feasible way to implement the example applications included in GEANT4-DNA in TOPAS-nBio. With the extended simulations, an insight could be given, which further tracking information can be gained with the track structure code and how cross sections and physics models influence a particle’s fate. Conclusion. With our results, we could show the potentials of applying the tuple scorer in TOPAS-nBio Monte Carlo track structure simulations. Using this scorer, a large amount of information about the track structure can be accessed, which can be analyzed as preferred after the simulation.

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.