Accounting for radiation-induced indirect damage on DNA with the Geant 4-DNA code

Radiation-induced DNA damage by proton, helium and carbon ions in human fibroblast cell: Geant4-DNA and MCDS-based study

Background. Radiation-induced DNA damages such as Single Strand Break (SSB), Double Strand Break (DSB) and Complex DSB (cDSB) are critical aspects of radiobiology with implications in radiotherapy and radiation protection applications.Materials and Methods. This study presents a thorough investigation into the effects of protons (0.1-100 MeV/u), helium ions (0.13-100 MeV/u) and carbon ions (0.5-480 MeV/u) on DNA of human fibroblast cells using Geant4-DNA track structure code coupled with DBSCAN algorithm and Monte Carlo Damage Simulations (MCDS) code. Geant4-DNA-based simulations consider 1μm × 1μm × 0.5μm water box as the target to calculate energy deposition on event-by-event basis and the three-dimensional coordinates of the interaction location, and then DBSCAN algorithm is used to calculate yields of SSB, DSB and cDSB in human fibroblast cell. The study investigated the influence of Linear Energy Transfer (LET) of protons, helium ions and carbon ions on the yields of DNA damages. Influence of cellular oxygenation on DNA damage patterns is investigated using MCDS code.Results. The study shows that DSB and SSB yields are influenced by the LET of the particles, with distinct trends observed for different particles. The cellular oxygenation is a key factor, with anoxic cells exhibiting reduced SSB and DSB yields, underscoring the intricate relationship between cellular oxygen levels and DNA damage. The study introduced DSB/SSB ratio as an informative metric for evaluating the severity of radiation-induced DNA damage, particularly in higher LET regions.Conclusions. The study highlights the importance of considering particle type, LET, and cellular oxygenation in assessing the biological effects of ionizing radiation.

Monte Carlo-Based Nanoscale Dosimetry Holds Promise for Radiopharmaceutical Therapy Involving Auger Electron Emitters

Radiopharmaceutical therapy (RPT) is evolving as a promising strategy for treating cancer. As interest grows in short-range particles, like Auger electrons, understanding the dose-response relationship at the deoxyribonucleic acid (DNA) level has become essential. In this study, we used the Geant4-DNA toolkit to evaluate DNA damage caused by the Auger-electron-emitting isotope I-125. We compared the energy deposition and single strand break (SSB) yield at each base pair location in a short B-form DNA (B-DNA) geometry with existing simulation and experimental data, considering both physical direct and chemical indirect hits. Additionally, we evaluated dosimetric differences between our high-resolution B-DNA target and a previously published simple B-DNA geometry. Overall, our benchmarking results for SSB yield from I-125 decay exhibited good agreement with both simulation and experimental data. Using this simulation, we then evaluated the SSB and double strand break (DSB) yields caused by a theranostic Br-77-labeled poly ADP ribose polymerase (PARP) inhibitor radiopharmaceutical. The results indicated a predominant contribution of chemical indirect hits over physical direct hits in generating SSB and DSB. This study lays the foundation for future investigations into the nano-dosimetric properties of RPT.

In-silico calculations of DNA damage induced by α-particles in the 224Ra DaRT decay chain for a better understanding of the radiobiological effectiveness of this treatment

Diffusing alpha-emitters radiation Therapy (DaRT) is an interstitial brachytherapy technique using 224Ra seeds. For accurate treatment planning a good understanding of the early DNA damage due to α-particles is required. Geant4-DNA was used to calculate the initial DNA damage and radiobiological effectiveness due to α-particles with linear energy transfer (LET) values in the range 57.5-225.9 keV/μm from the 224Ra decay chain. The impact of DNA base pair density on DNA damage has been modelled, as this parameter varies between human cell lines. Results show that the quantity and complexity of DNA damage changes with LET as expected. Indirect damage, due to water radical reactions with the DNA, decreases and becomes less significant at higher LET values as shown in previous studies. As expected, the yield of complex double strand breaks (DSBs), which are harder for a cell to repair, increases approximately linearly with LET. The level of complexity of DSBs and radiobiological effectiveness have been found to increase with LET as expected. The quantity of DNA damage has been shown to increase for increased DNA density in the expected base pair density range of human cells. The change in damage yield as a function of base pair density is largest for higher LET α-particles, an increase of over 50% for individual strand breaks between 62.7 and 127.4 keV/μm. This change in yield shows that the DNA base pair density is an important parameter for modelling DNA damage particularly at higher LET where the DNA damage is greatest and most complex.

Computational modeling and a Geant4-DNA study of the rejoining of direct and indirect DNA damage induced by low energy electrons and carbon ions

PURPOSE

DNA double-strand breaks (DSBs) created by ionizing radiations are considered as the most detrimental lesion, which could result in the cell death or sterilization. As the empirical evidence gathered from the cellular and molecular radiation biology has demonstrated significant correlations between the initial and lasting levels of DSBs, gaining knowledge into the DSB repair mechanisms proves vital. Much effort has been invested into understanding the mechanisms triggering the repair and processes engaged after irradiation of cells. Given a mechanistic model, we performed - to our knowledge - the first Monte Carlo study of the expected repair kinetics of carbon ions and electrons using on the one hand Geant4-DNA simulations of electrons for benchmarking purposes and on the other hand quantifying the influence of direct and indirect damage. Our objective was to calculate the DSB repair rates using a repair mechanism for G1 and early S phases of the cell cycle in conjunction with simulations of the DNA damage.

MATERIALS AND METHODS

Based on Geant4-DNA simulations of DSB damage caused by electrons and carbon ions - using a B-DNA model and a water sphere of 3 μm radius resembling the mean size of human cells - we derived the kinetics of various biochemical repair processes.

RESULTS

The overall repair times of carbon ions increased with the DSB complexity. Comparison of the DSB complexity (DSBc) and repair times as a function of carbon-ion energy suggested that the repair time of no specific fraction of DSBs could solely be explained as a function of DSB complexity.

CONCLUSION

Analysis of the carbon-ion repair kinetics indicated that, given a fraction of DSBs, decreasing the energy would result in an increase of the repair time. The disagreements of the calculated and experimental repair kinetics for electrons could, among others, be due to larger damage complexity predicted by simulations or created actually by electrons of comparable energies to x-rays. They are also due to the employed repair mechanisms, which introduce no inherent dependence on the radiation type but make direct use of the simulated DSBs.

Radical Production with Pulsed Beams: Understanding the Transition to FLASH

Ultra-high dose rate (UHDR) irradiation regimes have the potential to spare normal tissue while keeping equivalent tumoricidal capacity than conventional dose rate radiotherapy (CONV-RT). This has been called the FLASH effect. In this work, we present a new simulation framework aiming to study the production of radical species in water and biological media under different irradiation patterns. The chemical stage (heterogeneous phase) is based on a nonlinear reaction-diffusion model, implemented in GPU. After the first 1 μs, no further radical diffusion is assumed, and radical evolution may be simulated over long periods of hundreds of seconds. Our approach was first validated against previous results in the literature and then employed to assess the influence of different temporal microstructures of dose deposition in the expected biological damage. The variation of the Normal Tissue Complication Probability (NTCP), assuming the model of Labarbe et al., where the integral of the peroxyl radical concentration over time (AUC-ROO) is taken as surrogate for biological damage, is presented for different intra-pulse dose rate and pulse frequency configurations, relevant in the clinical scenario. These simulations yield that overall, mean dose rate and the dose per pulse are the best predictors of biological effects at UHDR.

A TD-DFT-Based Study on the Attack of the OH· Radical on a Guanine Nucleotide

Heavy charged particles induce severe damage in DNA, which is a radiobiological advantage when treating radioresistant tumors. However, these particles can also induce cancer in humans exposed to them, such as astronauts in space missions. This damage can be directly induced by the radiation or indirectly by the attack of free radicals mainly produced by water radiolysis. We previously studied the impact of a proton on a DNA base pair, using the Time Dependent-Density Functional Theory (TD-DFT). In this work, we go a step further and study the attack of the OH· radical on the Guanine nucleotide to unveil how this molecule subsequently dissociates. The OH· attack on the H1', H2', H3', and H5' atoms in the guanine was investigated using the Ehrenfest dynamics within the TD-DFT framework. In all cases, the hydrogen abstraction succeeded, and the subsequent base pair dissociation was observed. The DNA dissociates in three major fragments: the phosphate group, the deoxyribose sugar, and the nitrogenous base, with slight differences, no matter which hydrogen atom was attacked. Hydrogen abstraction occurs at about 6 fs, and the nucleotide dissociation at about 100 fs, which agrees with our previous result for the direct proton impact on the DNA. These calculations may be a reference for adjusting reactive force fields so that more complex DNA structures can be studied using classical molecular dynamics, including both direct and indirect DNA damage.

DNA damage and microdosimetry for carbon ions: Track structure simulations as the key to quantitative modeling of radiation-induced damage

PURPOSE

Dose distribution in carbon-ion irradiations is generally envisaged to have therapeutic advantages over protons, primarily due to the carbon-ion's comparatively higher relative biological effectiveness (RBE) in the tumor than in the encompassing healthy tissues. The objective of this work was to simulate the overall physical and chemical reactions of primary carbon ions impinging on liquid water and, as such, to investigate the DNA-damage yields in the form of strand breaks (SBs) and in connection with the expected microdosimetric quantities.

MATERIALS AND METHODS

Using a B-DNA model and Geant4-DNA, we simulated the primary and secondary interactions in a spherical medium of water. Subsequently, we categorized DNA damages based on their complexity utilizing the concept of μ-randomness. We assumed a threshold of 17.5 eV for a direct SB and a probability of 0.13 for an indirect SB triggered by chemical reactions of hydroxyl radicals. Microdosimetric quantities were extracted for three cylindrical volumes representing typical sub-cellular organisms.

RESULTS

For fully-ionized carbons of 8 to 256 MeV/u, the yield results appeared to be considerably influenced by the chemical reactions - indicating the important role of secondary electrons in inflicting damage. However, it was mostly the direct-damage spectrum that determined the overall shape of the damage spectrum. At all primary energies, it was more probable to break each DNA strand at one point - the two points being less than 10 bp apart - than to break only one strand at two random points. Unlike proton's mean-specific-energy results, which showed more sensitivity to the volume increase of the smallest cylinder than of the larger ones, carbon-ion results showed no such sensitivity.

CONCLUSION

The growth of the yield ratio of the single- and double-strand breaks (SSB and DSB) with the particle energy was estimated for protons to be about two times that of alphas and 92 times that of carbon ions. Unlike the proton results, which suggested significant correlations between the DSB yields and mean specific (and lineal) energies, carbon ions exhibited no such correlations. This article is protected by copyright. All rights reserved.

DNA damage modeled with Geant4-DNA: effects of plasmid DNA conformation and experimental conditions

The chemical stage of the Monte Carlo track-structure (MCTS) code Geant4-DNA was extended for its use in DNA strand break (SB) simulations and compared against published experimental data. Geant4-DNA simulations were performed using pUC19 plasmids (2686 base pairs) in a buffered solution of DMSO irradiated by⁶⁰Co or¹³⁷Csγ-rays. A comprehensive evaluation of SSB yields was performed considering DMSO, DNA concentration, dose and plasmid supercoiling. The latter was measured using the super helix density value used in a Brownian dynamics plasmid generation algorithm. The Geant4-DNA implementation of the independent reaction times method (IRT), developed to simulate the reaction kinetics of radiochemical species, allowed to score the fraction of supercoiled, relaxed and linearized plasmid fractions as a function of the absorbed dose. The percentage of the number of SB after •OH + DNA and H• + DNA reactions, referred as SSB efficiency, obtained using MCTS were 13.77% and 0.74% respectively. This is in reasonable agreement with published values of 12% and 0.8%. The SSB yields as a function of DMSO concentration, DNA concentration and super helix density recreated the expected published experimental behaviors within 5%, one standard deviation. The dose response of SSB and DSB yields agreed with published measurements within 5%, one standard deviation. We demonstrated that the developed extension of IRT in Geant4-DNA, facilitated the reproduction of experimental conditions. Furthermore, its calculations were strongly in agreement with experimental data. These two facts will facilitate the use of this extension in future radiobiological applications, aiding the study of DNA damage mechanisms with a high level of detail.

Quantification of gold nanoparticle photon radiosensitization from direct and indirect effects using a complete human genome single cell model based on Geant4

PURPOSE

To investigate the radiosensitization properties of gold nanoparticles (GNPs) and better understand the intricate deoxyribonucleic acid (DNA) damage induction mechanisms involved in GNP-aided radiotherapy, a single cell model with complete human genome based on the Geant4 Monte Carlo toolkit was applied.

MATERIALS AND METHODS

A Geant4-DNA model was implemented to simulate direct and indirect DNA damage generated in the physical and chemical stages. In the physical stage, a mixed-physics approach was taken by using Geant4-DNA in water and Livermore in gold. Water radiolysis was created posteriorly in the physicochemical and chemical stages to simulate indirect damage from reactions between DNA molecules and OH• radicals. A mono-energetic photon beam (100 keV) and two clinical photon sources (250-kVp, 6-MV flattening-filter free) were simulated for modeling the irradiation of a single cell with or without GNPs. In order to study the effects of GNP size on radiosensitization, 15, 30, and 100 nm GNPs were simulated. The effects of intracellular distribution were simulated using 90-nm GNPs with different characteristics of distribution within the cell. The time dependence of DNA damage enhancement was also studied with chemistry stage simulation end-time no larger than 10 ns.

RESULTS

Double strand break (DSB) enhancement due to direct and indirect action was quantified under different scenarios. Under realistic cellular uptake condition, the 100-nm GNPs had the most significant increase in DSBs: 40.9% and 28.5% for 100 keV and 250-kVp photon irradiation, respectively. The intracellular localization showed differing levels of radiosensitization with a maximum of 64%, 27%, and 6% DSB enhancements for 100 keV, 250-kVp, and 6-MV respectively, when 90-nm GNPs congregate around the nucleus.

CONCLUSION

The results indicate that photon energy, GNP size, and intracellular distribution play an important role in the enhancement of DSB from direct and indirect damage under scenarios close to cell experiments. The radiosensitization effects due to indirect damage are significant and should be considered carefully.

Effect of spatial distribution of boron and oxygen concentration on DNA damage induced from boron neutron capture therapy using Monte Carlo simulations

PURPOSE

This paper aims to investigate how the spatial distribution of boron in cells and oxygen concentration affect the DNA damage induced by charged particles in boron neutron capture therapy (BNCT) by Monte Carlo simulations, and further to evaluate the relative biological effectiveness (RBE) of DNA double-strand breaks (DSBs) induction.

MATERIALS AND METHODS

The kinetic energy spectra of α, 7Li particles in BNCT arriving at the nucleus surface were obtained from GEANT4 (Geant4 10.05.p01). The DNA damage caused by BNCT was then evaluated using MCDS (MCDS 3.10A).

RESULTS

When α or 7Li particles were distributed in the cytomembrane or cytoplasm, the difference in DNA damage of the same types was less than 0.5%. Taking the 137Cs photons as the reference radiation, when the oxygen concentration varied from 0% to 50%, the RBE of 0.54MeV protons and recoil protons varied from 5 to 2, whereas it decreased from 10 to 3 for α or 7Li particles.

CONCLUSION

The RBE of DSB induction all charged particles in BNCT decreased with the increase of oxygen concentration. This work indicated that the RBE of different radiation particles of BNCT might be affected by many factors, which should be paid attention to in theoretical research or clinical application.

Multi-scaled Monte Carlo calculation for radon-induced cellular damage in the bronchial airway epithelium

Radon is a leading cause of lung cancer in indoor public and mining workers. Inhaled radon progeny releases alpha particles, which can damage cells in the airway epithelium. The extent and complexity of cellular damage vary depending on the alpha particle's kinetic energy and cell characteristics. We developed a framework to quantitate the cellular damage on the nanometer and micrometer scales at different intensities of exposure to radon progenies Po-218 and Po-214. Energy depositions along the tracks of alpha particles that were slowing down were simulated on a nanometer scale using the Monte Carlo code Geant4-DNA. The nano-scaled track histories in a 5 μm radius and 1 μm-thick cylindrical volume were integrated into the tracking scheme of alpha trajectories in a micron-scale bronchial epithelium segment in the user-written SNU-CDS program. Damage distribution in cellular DNA was estimated for six cell types in the epithelium. Deep-sited cell nuclei in the epithelium would have less chance of being hit, but DNA damage from a single hit would be more serious, because low-energy alpha particles of high LET would hit the nuclei. The greater damage in deep-sited nuclei was due to the 7.69 MeV alpha particles emitted from Po-214. From daily work under 1 WL of radon concentration, basal cells would respond with the highest portion of complex DSBs among the suspected progenitor cells in the most exposed regions of the lung epithelium.

Fast neutron energy based modelling of biological effectiveness with implications for proton and ion beams

A practical neutron energy dependent RBE model has been developed, based on the relationship between a mono-energetic neutron energy and its likely recoil proton energy. Essentially, the linear energy transfer (LET) values of the most appropriate recoil proton energies are then used to modify the linear quadratic model radiosensitivities (α and β) from their reference LET radiation values to provide the RBE estimates. Experimental neutron studies published by Hall (including some mono-energetic beams ranging from 0.2 to 15 MeV), Broerse, Berry, and data from the Clatterbridge and Detroit clinical neutron beams, which all contain some data from a spectrum of neutron energies, are used to derive single effective neutron energies (NE_eff) for each spectral beam. These energies yield a recoil proton spectrum, but with an effective mean proton energy (being around 50% of NE_eff). The fractional increase in LET is given by the recoil proton LET divided by the proton (LET_U) value which provides the highest RBE. This ratio is then used to determine the change in the linear-quadratic model α and β parameters, from those of the reference radiation, to estimate the RBE. The predicted proton recoil RBE is then reasonably close to the experimental neutron RBE values found when taking into account the variation inherent in biological experiments. The work has some important consequences. The data of Hall et al (1975 Radiat. Res. 64 245-55) shows that the highest RBE values are found with neutron energies around 0.3-0.4 MeV, but this energy cannot possibly generate recoil proton energies which are higher, as necessary for a 0.68 MeV proton with a 30.5 keV μm^-1 LET_U (the LET value which provides the maximum obtainable RBE for a specified ion). For 0.4 MeV neutrons with proton recoil energies of around 0.2 MeV, the latter have a LET of around 62.88 keV μm^-1. This could have an impact on proton beam RBE modelling. However, this is compensated by finding that the maximum radiosensitivity for mono-energetic neutrons was around 1.7 times larger than previously suggested from experimental ion beam studies, probably due to the necessary spreading out of Bragg peaks for ion beam experimental purposes, sampling errors and particle range considerations. This semi-empirical model can be used with minimal computer support and could have applications in ionic beams and in radioprotection.

Fully integrated Monte Carlo simulation for evaluating radiation induced DNA damage and subsequent repair using Geant4-DNA

Ionising radiation induced DNA damage and subsequent biological responses to it depend on the radiation’s track-structure and its energy loss distribution pattern. To investigate the underlying biological mechanisms involved in such complex system, there is need of predicting biological response by integrated Monte Carlo (MC) simulations across physics, chemistry and biology. Hence, in this work, we have developed an application using the open source Geant4-DNA toolkit to propose a realistic “fully integrated” MC simulation to calculate both early DNA damage and subsequent biological responses with time. We had previously developed an application allowing simulations of radiation induced early DNA damage on a naked cell nucleus model. In the new version presented in this work, we have developed three additional important features: (1) modeling of a realistic cell geometry, (2) inclusion of a biological repair model, (3) refinement of DNA damage parameters for direct damage and indirect damage scoring. The simulation results are validated with experimental data in terms of Single Strand Break (SSB) yields for plasmid and Double Strand Break (DSB) yields for plasmid/human cell. In addition, the yields of indirect DSBs are compatible with the experimental scavengeable damage fraction. The simulation application also demonstrates agreement with experimental data of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\gamma$$\end{document}γ-H2AX yields for gamma ray irradiation. Using this application, it is now possible to predict biological response along time through track-structure MC simulations.

Combined effects of cisplatin and photon or proton irradiation in cultured cells: radiosensitization, patterns of cell death and cell cycle distribution

The purpose of the current study was to investigate the biological effects of protons and photons in combination with cisplatin in cultured cells and elucidate the mechanisms responsible for their combined effects. To evaluate the sensitizing effects of cisplatin against X-rays and proton beams in HSG, EMT6 and V79 cells, the combination index, a simple measure for quantifying synergism, was estimated from cell survival curves using software capable of performing the Monte Carlo calculation. Cell death and apoptosis were assessed using live cell fluorescence imaging. HeLa and HSG cells expressing the fluorescent ubiquitination-based cell cycle indicator system (Fucci) were irradiated with X-rays and protons with cisplatin. Red and green fluorescence in the G1 and S/G2/M phases, respectively, were evaluated and changes in the cell cycle were assessed. The sensitizing effects of ≥1.5 μM cisplatin were observed for both X-ray and proton irradiation (P < 0.05). In the three cell lines, the average combination index was 0.82-1.00 for X-rays and 0.73-0.89 for protons, indicating stronger effects for protons. In time-lapse imaging, apoptosis markedly increased in the groups receiving ≥1.5 μM cisplatin + protons. The percentage of green S/G2/M phase cells at that time was higher when cisplatin was combined with proton beams than with X-rays (P < 0.05), suggesting more significant G2 arrest. Proton therapy plus ≥1.5 μM cisplatin is considered to be very effective. When combined with cisplatin, proton therapy appeared to induce greater apoptotic cell death and G2 arrest, which may partly account for the difference observed in the combined effects.

Simulation of Proton-Induced DNA Damage Patterns Using an Improved Clustering Algorithm

Simulations of deoxyribonucleic acid (DNA) molecular damage use the traversal algorithm that has the disadvantages of being time-consuming, slowly converging, and requiring high-performance computer clusters. This work presents an improved version of the algorithm, "density-based spatial clustering of applications with noise" (DBSCAN), using a KD-tree approach to find neighbors of each point for calculating clustered DNA damage. The resulting algorithm considers the spatial distributions for sites of energy deposition and hydroxyl radical attack, yielding the statistical probability of (single and double) DNA strand breaks. This work achieves high accuracy and high speed at calculating clustered DNA damage that has been induced by proton treatment at the molecular level while running on an i7 quad-core CPU. The simulations focus on the indirect effect generated by hydroxyl radical attack on DNA. The obtained results are consistent with those of other published experiments and simulations. Due to the array of chemical processes triggered by proton treatment, it is possible to predict the effects that different track structures of various energy protons produce on eliciting direct and indirect damage of DNA.

Challenges in the quantification approach to a radiation relevant adverse outcome pathway for lung cancer

PURPOSE

Adverse outcome pathways (AOPs) provide a modular framework for describing sequences of biological key events (KEs) and key event relationships (KERs) across levels of biological organization. Empirical evidence across KERs can support construction of quantified AOPs (qAOPs). Using an example AOP of energy deposition from ionizing radiation onto DNA leading to lung cancer incidence, we investigate the feasibility of quantifying data from KERs supported by all types of stressors. The merits and challenges of this process in the context of AOP construction are discussed.

MATERIALS AND METHODS

Empirical evidence across studies of dose-response from four KERs of the AOP were compiled independently for quantification. Three upstream KERs comprised of evidence from various radiation types in line with AOP guidelines. For these three KERs, a focused analysis of data from alpha-particle studies was undertaken to better characterize the process to the adverse outcome (AO) for a radon gas stressor. Numerical information was extracted from tables and graphs to plot and tabulate the response of KEs. To complement areas of the AOP quantification process, Monte Carlo (MC) simulations in TOPAS-nBio were performed to model exposure conditions relevant to the AO for an example bronchial compartment of the lung with secretory cell nuclei targets.

RESULTS

Quantification of AOP KERs highlighted the relevance of radiation types under the stressor-agnostic intent of AOP design, motivating a focus on specific types. For a given type, significant differences of KE response indicate meaningful data to derive linkages from the MIE to the AO is lacking and that better response-response focused studies are required. The MC study estimates the linear energy transfer (LET) of alpha-particles emitted by radon-222 and its progeny in the secretory cell nuclei of the example lung compartment to range from 94 - 5 + 5 to 192 - 18 + 15 keV/µm.

CONCLUSION

Quantifying AOP components provides a means to assemble empirical evidence across different studies. This highlights challenges in the context of studies examining similar endpoints using different radiation types. Data linking KERs to a MIE of 'deposition of energy' is shown to be non-compatible with the stressor-agnostic principles of AOP design. Limiting data to that describing response-response relationships between adjacent KERs may better delineate studies relevant to the damage that drives a pathway to the next KE and still support an 'all hazards' approach. Such data remains limited and future investigations in the radiation field may consider this approach when designing experiments and reporting their results and outcomes.

A new open-source GPU-based microscopic Monte Carlo simulation tool for the calculations of DNA damages caused by ionizing radiation - Part II: sensitivity and uncertainty analysis

PURPOSE

Calculations of deoxyribonucleic acid (DNA) damages involve many parameters in the computation process. As these parameters are often subject to uncertainties, it is of central importance to comprehensively quantify their impacts on DNA single-strand break (SSB) and double-strand break (DSB) yields. This has been a challenging task due to the required large number of simulations and the relatively low computational efficiency using CPU-based MC packages. In this study, we present comprehensive evaluations on sensitivities and uncertainties of DNA SSB and DSB yields on 12 parameters using our GPU-based MC tool, gMicroMC.

METHODS

We sampled one electron at a time in a water sphere containing a human lymphocyte nucleus and transport the electrons and generated radicals until 2 Gy dose was accumulated in the nucleus. We computed DNA damages caused by electron energy deposition events in the physical stage and the hydroxyl radicals at the end of the chemical stage. We repeated the computations by varying 12 parameters: (a) physics cross section, (b) cutoff energy for electron transport, (c)-(e) three branching ratios of hydroxyl radicals in the de-excitation of excited water molecules, (f) temporal length of the chemical stage, (g)-(h) reaction radii for direct and indirect damages, (i) threshold energy defining the threshold damage model to generate a physics damage, (j)-(k) minimum and maximum energy values defining the linear-probability damage model to generate a physics damage, and (l) probability to generate a damage by a radical. We quantified sensitivity of SSB and DSB yields with respect to these parameters for cases with 1.0 and 4.5 keV electrons. We further estimated uncertainty of SSB and DSB yields caused by uncertainties of these parameters.

RESULTS

Using a threshold of 10% uncertainty as a criterion, threshold energy in the threshold damage model, maximum energy in the linear-probability damage model, and probability for a radical to generate a damage were found to cause large uncertainties in both SSB and DSB yields. The scaling factor of the cross section, cutoff energy, physics reaction radius, and minimum energy in the linear-probability damage model were found to generate large uncertainties in DSB yields.

CONCLUSIONS

We identified parameters that can generate large uncertainties in the calculations of SSB and DSB yields. Our study could serve as a guidance to reduce uncertainties of parameters and hence uncertainties of the simulation results.

Enhancing low-dose risk assessment using mechanistic mathematical models of radiation effects

Mechanistic mathematical modeling of ionizing radiation (IR) effects has a long history spanning several decades. Models that mathematically represent current knowledge and hypotheses about how radiation damages cells and organs, leading to deleterious outcomes such as carcinogenesis, are particularly useful for estimating radiation risks at doses that are relevant for radiation protection, but are too low to provide a strong 'signal-to-noise ratio' in epidemiological or experimental studies with realistic sample sizes. Here, I discuss examples of models in several relevant areas, including radionuclide biokinetics, non-targeted IR effects, DNA double-strand break (DSB) rejoining and radiation carcinogenesis. I do not provide a detailed review of the vast modeling literature in these fields, but focus on concepts that we have implemented, such as using continuous probability distributions of exponential rates to model radionuclide biokinetics and DSB rejoining, and combining short and long time scales in carcinogenesis models. Improvements in models, including the ability to generate new hypotheses based on model predictions, may come from the introduction of additional novel concepts and from integrating multiple data types.

MPEXS-DNA, a new GPU-based Monte Carlo simulator for track structures and radiation chemistry at subcellular scale

Purpose

Track structure simulation codes can accurately reproduce the stochastic nature of particle–matter interactions in order to evaluate quantitatively radiation damage in biological cells such as DNA strand breaks and base damage. Such simulations handle large numbers of secondary charged particles and molecular species created in the irradiated medium. Every particle and molecular species are tracked step‐by‐step using a Monte Carlo method to calculate energy loss patterns and spatial distributions of molecular species inside a cell nucleus with high spatial accuracy. The Geant4‐DNA extension of the Geant4 general‐purpose Monte Carlo simulation toolkit allows for such track structure simulations and can be run on CPUs. However, long execution times have been observed for the simulation of DNA damage in cells. We present in this work an improvement of the computing performance of such simulations using ultraparallel processing on a graphical processing unit (GPU).

Methods

A new Monte Carlo simulator named MPEXS‐DNA, allowing high computing performance by using a GPU, has been developed for track structure and radiolysis simulations at the subcellular scale. MPEXS‐DNA physics and chemical processes are based on Geant4‐DNA processes available in Geant4 version 10.02 p03. We have reimplemented the Geant4‐DNA process codes of the physics stage (electromagnetic processes of charged particles) and the chemical stage (diffusion and chemical reactions for molecular species) for microdosimetry simulation by using the CUDA language. MPEXS‐DNA can calculate a distribution of energy loss in the irradiated medium caused by charged particles and also simulate production, diffusion, and chemical interactions of molecular species from water radiolysis to quantitatively assess initial damage to DNA. The validation of MPEXS‐DNA physics and chemical simulations was performed by comparing various types of distributions, namely the radial dose distributions for the physics stage, and the G‐value profiles for each chemical product and their linear energy transfer dependency for the chemical stage, to existing experimental data and simulation results obtained by other simulation codes, including PARTRAC.

Results

For physics validation, radial dose distributions calculated by MPEXS‐DNA are consistent with experimental data and numerical simulations. For chemistry validation, MPEXS‐DNA can also reproduce G‐value profiles for each molecular species with the same tendency as existing experimental data. MPEXS‐DNA also agrees with simulations by PARTRAC reasonably well. However, we have confirmed that there are slight discrepancies in G‐value profiles calculated by MPEXS‐DNA for molecular species such as H₂ and H₂O₂ when compared to experimental data and PARTRAC simulations. The differences in G‐value profiles between MPEXS‐DNA and PARTRAC are caused by the different chemical reactions considered. MPEXS‐DNA can drastically boost the computing performance of track structure and radiolysis simulations. By using NVIDIA's GPU devices adopting the Volta architecture, MPEXS‐DNA has achieved speedup factors up to 2900 against Geant4‐DNA simulations with a single CPU core.

Conclusion

The MPEXS‐DNA Monte Carlo simulation achieves similar accuracy to Monte Carlo simulations performed using other codes such as Geant4‐DNA and PARTRAC, and its predictions are consistent with experimental data. Notably, MPEXS‐DNA allows calculations that are, at maximum, 2900 times faster than conventional simulations using a CPU.

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

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