Implementation of new physics models for low energy electrons in liquid water in Geant4-DNA

Results of a Geant4 benchmarking study for bio-medical applications, performed with the G4-Med system

BACKGROUND

Geant4, a Monte Carlo Simulation Toolkit extensively used in bio-medical physics, is in continuous evolution to include newest research findings to improve its accuracy and to respond to the evolving needs of a very diverse user community. In 2014, the G4-Med benchmarking system was born from the effort of the Geant4 Medical Simulation Benchmarking Group, to benchmark and monitor the evolution of Geant4 for medical physics applications. The G4-Med system was first described in our Medical Physics Special Report published in 2021. Results of the tests were reported for Geant4 10.5.

PURPOSE

In this work, we describe the evolution of the G4-Med benchmarking system.

METHODS

The G4-Med benchmarking suite currently includes 23 tests, which benchmark Geant4 from the calculation of basic physical quantities to the simulation of more clinically relevant set-ups. New tests concern the benchmarking of Geant4-DNA physics and chemistry components for regression testing purposes, dosimetry for brachytherapy with a125 I $^{125}I$ source, dosimetry for external x-ray and electron FLASH radiotherapy, experimental microdosimetry for proton therapy, and in vivo PET for carbon and oxygen beams. Regression testing has been performed between Geant4 10.5 and 11.1. Finally, a simple Geant4 simulation has been developed and used to compare Geant4 EM physics constructors and physics lists in terms of execution times.

RESULTS

In summary, our EM tests show that the parameters of the multiple scattering in the Geant4 EM constructor G4EmStandardPhysics_option3 in Geant4 11.1, while improving the modeling of the electron backscattering in high atomic number targets, are not adequate for dosimetry for clinical x-ray and electron beams. Therefore, these parameters have been reverted back to those of Geant4 10.5 in Geant4 11.2.1. The x-ray radiotherapy test shows significant differences in the modeling of the bremsstrahlung process, especially between G4EmPenelopePhysics and the other constructors under study (G4EmLivermorePhysics, G4EmStandardPhysics_option3, and G4EmStandardPhysics_option4). These differences will be studied in an in-depth investigation within our Group. Improvement in Geant4 11.1 has been observed for the modeling of the proton and carbon ion Bragg peak with energies of clinical interest, thanks to the adoption of ICRU90 to calculate the low energy proton stopping powers in water and of the Linhard-Sorensen ion model, available in Geant4 since version 11.0. Nuclear fragmentation tests of interest for carbon ion therapy show differences between Geant4 10.5 and 11.1 in terms of fragment yields. In particular, a higher production of boron fragments is observed with Geant4 11.1, leading to a better agreement with reference data for this fragment.

CONCLUSIONS

Based on the overall results of our tests, we recommend to use G4EmStandardPhysics_option4 as EM constructor and QGSP_BIC_HP with G4EmStandardPhysics_option4, for hadrontherapy applications. The Geant4-DNA physics lists report differences in modeling electron interactions in water, however, the tests have a pure regression testing purpose so no recommendation can be formulated.

Investigating ultra-high dose rate water radiolysis using the Geant4-DNA toolkit and a Geant4 model of the Oriatron eRT6 electron linac

Ultra-high dose rate FLASH radiotherapy, a promising cancer treatment approach, offers the potential to reduce healthy tissue damage during radiotherapy. As the mechanisms underlying this process remain unknown, several hypotheses have been proposed, including the altered production of radio-induced species under ultra-high dose rate (UHDR) conditions. This study explores realistic irradiation scenarios with various dose-per-pulse and investigates the role of pulse temporal structure. Using the Geant4 toolkit and its Geant4-DNA extension, we modeled the Oriatron eRT6 linac, a FLASH-validated electron beam, and conducted simulations covering four distinct dose-per-pulse scenarios - 0.17 Gy, 1 Gy, 5 Gy, and 10 Gy - all featuring a 1.8 µs pulse duration. Results show close agreement between simulated and experimental dose profiles in water, validating the eRT6 model for Geant4-DNA simulations. We observed important changes in the temporal evolution of certain species, such as the earlier fall in hydroxyl radicals ([Formula: see text]) and reduced production and lifetime of superoxide ([Formula: see text]) with higher dose-per-pulse levels. The pulse temporal structure did not influence the long-term evolution of species. Our findings encourage further investigation into different irradiation types, such as multi-pulse configurations, and emphasize the need to add components in water to account for relevant cellular processes.

Monte Carlo simulations of microdosimetry and radiolytic species production at long time post proton irradiation using GATE and Geant4-DNA

BACKGROUND

Radiobiological effectiveness of radiation in cancer treatment can be studied at different scales (molecular till organ scale) and different time post irradiation. The production of free radicals and reactive oxygen species during water radiolysis is particularly relevant to understand the fundamental mechanisms playing a role in observed biological outcomes. The development and validation of Monte Carlo tools integrating the simulation of physical, physico-chemical and chemical stages after radiation is very important to maintain with experiments.

PURPOSE

Therefore, in this study, we propose to validate a new Geant4-DNA chemistry module through the simulation of water radiolysis and Fricke dosimetry experiments on a proton preclinical beam line.

MATERIAL AND METHODS

In this study, we used the GATE Monte Carlo simulation platform (version 9.3) to simulate a 67.5 MeV proton beam produced with the ARRONAX isochronous cyclotron (IBA Cyclone 70XP) at conventional dose rate (0.2 Gy/s) to simulate the irradiation of ultra-pure liquid water samples and Fricke dosimeter. We compared the depth dose profile with measurements performed with a plane parallel Advanced PTW 34045 Markus ionization chamber. Then, a new Geant4-DNA chemistry application proposed from Geant4 version 11.2 has been used to assess the evolution ofHO • ${\mathrm{HO}}^ \bullet $ ,e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ ,H 3 O + ${{\mathrm{H}}}_3{{\mathrm{O}}}^ + $ ,H 2 O 2 ${{\mathrm{H}}}_2{{\mathrm{O}}}_2$ ,H 2 ${{\mathrm{H}}}_2$ ,HO 2 • ${\mathrm{HO}}_2^ \bullet $ ,HO 2 - , O 2 • - ${\mathrm{HO}}_2^ - ,{\mathrm{\ O}}_2^{ \bullet - }$ andHO - ${\mathrm{HO}}^ - $ reactive species along time until 1-h post-irradiation. In particular, the effect of oxygen and pH has been investigated through comparisons with experimental measurements of radiolytic yields forH 2 O 2 ${{\mathrm{H}}}_2{{\mathrm{O}}}_2$ and Fe3+.

RESULTS

GATE simulations reproduced, within 4%, the depth dose profile in liquid water. With Geant4-DNA, we were able to reproduce experimentalH 2 O 2 ${{\mathrm{H}}}_2{{\mathrm{O}}}_2$ radiolytic yields 1-h post-irradiation in aerated and deaerated conditions, showing the impact of small changes in oxygen concentrations on species evolution along time. For the Fricke dosimeter, simulated G(Fe3+) is 15.97 ± 0.2 molecules/100 eV which is 11% higher than the measured value (14.4 ± 04 molecules/100 eV).

CONCLUSIONS

These results aim to be consolidated by new comparisons involving other radiolytic species, such ase aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ or, O 2 • - $,{\mathrm{\ O}}_2^{ \bullet - }$ to further study the mechanisms underlying the FLASH effect observed at ultra-high dose rates (UHDR).

A mechanistic simulation of induced DNA damage in a bacterial cell by X- and gamma rays: a parameter study

Mechanistic Monte Carlo simulations calculating DNA damage caused by ionizing radiation are highly dependent on the simulation parameters. In the present study, using the Geant4-DNA toolkit, the impact of different parameters on DNA damage induced in a bacterial cell by X- and gamma-ray irradiation was investigated. Three geometry configurations, including the simple (without DNA details), the random (a random multiplication of identical DNA segments), and the fractal (a regular replication of DNA segments using fractal Hilbert curves), were simulated. Also, three physics constructors implemented in Geant4-DNA, i.e., G4EmDNAPhysics_option2, G4EmDNAPhysics_option4, and G4EmDNAPhysics_option6, with two energy thresholds of 17.5 eV and 5-37.5 eV were compared for direct DNA damage calculations. Finally, a previously developed mathematical model of cell repair called MEDRAS (Mechanistic DNA Repair and Survival) was employed to compare the impact of physics constructors on the cell survival curve. The simple geometry leads to undesirable results compared to the random and fractal ones, highlighting the importance of simulating complex DNA structures in mechanistic simulation studies. Under the same conditions, the DNA damage calculated in the fractal geometry was more consistent with the experimental data. All physics constructors can be used alternatively with the fractal geometry, provided that an energy threshold of 17.5 eV is considered for recording direct DNA damage. All physics constructors represent a similar behavior in generating cell survival curves, although the slopes of the curves are different. Since the inverse of the slope of a bacterial cell survival curve (i.e., the D10-value) is highly sensitive to the simulation parameters, it is not logical to determine an optimal set of parameters for calculating the D10-value by Monte Carlo simulation.

Effects of Differing Underlying Assumptions in In Silico Models on Predictions of DNA Damage and Repair

The induction and repair of DNA double-strand breaks (DSBs) are critical factors in the treatment of cancer by radiotherapy. To investigate the relationship between incident radiation and cell death through DSB induction many in silico models have been developed. These models produce and use custom formats of data, specific to the investigative aims of the researchers, and often focus on particular pairings of damage and repair models. In this work we use a standard format for reporting DNA damage to evaluate combinations of different, independently developed, models. We demonstrate the capacity of such inter-comparison to determine the sensitivity of models to both known and implicit assumptions. Specifically, we report on the impact of differences in assumptions regarding patterns of DNA damage induction on predicted initial DSB yield, and the subsequent effects this has on derived DNA repair models. The observed differences highlight the importance of considering initial DNA damage on the scale of nanometres rather than micrometres. We show that the differences in DNA damage models result in subsequent repair models assuming significantly different rates of random DSB end diffusion to compensate. This in turn leads to disagreement on the mechanisms responsible for different biological endpoints, particularly when different damage and repair models are combined, demonstrating the importance of inter-model comparisons to explore underlying model assumptions.

Sub-keV corrections to binary encounter cross section models for electron ionization of liquid water with application to the Geant4-DNA Monte Carlo code

INTRODUCTION

The electron ionization cross section of water is one of the most important input in Monte Carlo studies of cellular radiobiological effects. Analytical cross section models of the binary-encounter type have the potential of reducing simulation time and facilitate application to a variety of biological materials (other than water). The Binary-Encounter-Bethe (BEB) and Binary-Encounter-Dipole (BED) models of NIST are perhaps the most popular of such models giving reliable results for atoms and molecules in the gas-phase over a wide energy range. However, the use of such models to sub-keV electron energies in liquid water raises concerns due to the neglect of condensed phase effects that leads to a significant overestimation when compared to medium-specific dielectric models.

PURPOSE

To modify the BEB and BED models towards better agreement with the recommended low-energy dielectric model of Geant4-DNA (Option 4). To implement the new modifications to the existing BEB model of the Option 6 physics constructor of Geant4-DNA and re-evaluate fundamental transport quantities for sub-keV electrons.

METHODS

In analogy to a Yukawa potential a simple, yet physically-motivated, modification of the Burgess correction term is proposed to account for the reduction of the Coulomb interaction due to the polarizability of the target. The magnitude of the correction is guided by the dielectric-based ionization cross section implemented in Option 4.

RESULTS

Differential, total and stopping ionization cross sections for low-energy electrons in liquid water are presented. When combined with the Vriens correction (which is not included in Option 6), the proposed modification to the BEB and BED models brings the ionization and stopping cross sections in much better agreement against those used in the Option 4 dielectric model of Geant4-DNA, with up to 30% and 10% deviation, respectively. Implementation of the new correction to the Option 6 constructor of Geant4-DNA and re-evaluation of fundamental transport quantities, such as electron penetration ranges and dose-point-kernels, reduced the discrepancies from Option 4 at sub-keV energies from 20 to 100% (or more) to well below 10% in most cases.

CONCLUSIONS

A simple modification to the BEB and BED analytic models was found to improve their performance for sub-keV electrons in liquid water medium. Implementation of the new modification to the Option 6 constructor of Geant4-DNA significantly improved the agreement with the recommended low-energy Option 4 constructor for a variety of fundamental quantities related to electron transport.

Modeling of scavenging systems in water radiolysis with Geant4-DNA

PURPOSE

This paper presents the capabilities of the Geant4-DNA Monte Carlo toolkit to simulate water radiolysis with scavengers using the step-by-step (SBS) or the independent reaction times (IRT) methods. It features two examples of application areas: (1) computing the escape yield of H₂O₂ following a ⁶⁰Co γ-irradiation and (2) computing the oxygen depletion in water irradiated with 1 MeV electrons.

METHODS

To ease the implementation of the chemical stage in Geant4-DNA, we developed a user interface that helps define the chemical reactions and set the concentration of scavengers. The first application area example required two computational steps to perform water radiolysis using NO₂^- and NO₃^- as scavengers and a ⁶⁰Co irradiation. The oxygen depletion computation technique for the second application area example consisted of simulating track segments of 1 MeV electrons and determining the radio-induced loss and gain of oxygen molecules.

RESULTS

The production of H₂O₂ under variable scavenging levels is consistent with the literature; the mean relative difference between the SBS and IRT methods is 7.2 % ± 0.5 %. For the oxygen depletion 1 µs post-irradiation, the mean relative difference between both methods is equal to 9.8 % ± 0.3 %. The results in the microsecond scale depend on the initial partial pressure of oxygen in water. In addition, the computed oxygen depletions agree well with the literature.

CONCLUSIONS

The Geant4-DNA toolkit makes it possible to simulate water radiolysis in the presence of scavengers. This feature offers perspectives in radiobiology, with the possibility of simulating cell-relevant scavenging mechanisms.

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.

The Role of Molecular Structure in Monte Carlo Simulations of the Secondary Electron Yield and Backscattering Coefficient from Methacrylic Acid

In this paper, we show the influence of the chemical structure of four different conformers on the secondary electron emission and backscattering of an electron beam from a gel of methacrylic acid. The conformers have different permanent dipole moments, which determines the cross sections for elastic collisions with electrons. The cross sections are used in Monte Carlo simulations of an electron beam, which enters the gel of methacrylic acid. The secondary electron yield and the backscattering coefficient are computed as a function of the beam energy.

Exploiting active nuclear import for efficient delivery of Auger electron emitters into the cell nucleus

BACKGROUND

The most attractive features of Auger electrons (AEs) in cancer therapy are their extremely short range and sufficiently high linear energy transfer (LET) for a majority of them. The cytotoxic effects of AE emitters can be realized only in close vicinity to sensitive cellular targets and they are negligible if the emitters are located outside the cell. The nucleus is considered the compartment most sensitive to high LET particles. Therefore, the use of AE emitters could be most useful in specific recognition of a cancer cell and delivery of AE emitters into its nucleus.

PURPOSE

This review describes the studies aimed at developing effective anticancer agents for the delivery of AE emitters to the nuclei of target cancer cells. The use of peptide-based conjugates, nanoparticles, recombinant proteins, and other constructs for AE emitter targeted intranuclear delivery as well as their advantages and limitations are discussed.

CONCLUSION

Transport from the cytoplasm to the nucleus along with binding to the cancer cell is one of the key stages in the delivery of AE emitters; therefore, several constructs for exploitation of this transport have been developed. The transport is carried out through a nuclear pore complex (NPC) with the use of specific amino acid nuclear localization sequences (NLS) and carrier proteins named importins, which are located in the cytosol. Therefore, the effectiveness of NLS-containing delivery constructs designed to provide energy-dependent transport of AE emitter into the nuclei of cancer cells also depends on their efficient entry into the cytosol of the target cell.

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.

Processes Induced by Electrons at Sub-Ionization Energies Studied by the Correlated Ions-(Ions/Neutrals) Mass Spectrometry

Sub-ionization energy electrons play a substantial role in the early time of (radiation/photo-) chemistry by generating reactive ions and neutral radicals. As the ions can be easily identified by mass spectrometry methods, information on the neutral species produced in correlation relies mainly on theoretical calculations. Here we show that coupling a double counter-propagative electron beams with a dual (+/-) time-of-flight mass spectrometer is probably the most versatile instrument for studying processes induced by low energy electrons, by providing correlated information between (ion and ion) and (ion and neutral) species. We demonstrate the feasibility of this technique for the prototypical case of carbon tetrachloride, but this method is generally applicable as shown for nitromethane.

Research on the proximity functions of microdosimetry of low energy electrons in liquid water based on different Monte Carlo codes

PURPOSE

The proximity function is an important index in microdosimetry for describing the spatial distribution of energy, which is closely related to the biological effects of organs or tissues in the target area. In this work, the impact of parameters, such as physic models, cut-off energy, and initial energy, on the proximity function are quantitated and compared.

METHODS

According to the track structure (TS) and condensed history (CH) low-energy electromagnetic models, this paper chooses a variety of Monte Carlo (Monte Carlo, MC) codes (Geant4-DNA, PHITS, and Penelope) to simulate the track structure of low-energy electrons in liquid water and evaluates the influence of the electron initial energy, cut-off energy, energy spectrum, and physical model factors on the differential proximity function.

RESULTS

The results show that the initial energy of electrons in the low-energy part (especially less than 1 keV) has a greater impact on the differential proximity function, and the choice of cut-off energy has a greater impact on the differential proximity function corresponding to small radius sites (generally less than 10 nm). The difference in the electronic energy spectrum has little effect on the result, and the proximity functions of different physics models show better consistency under large radius sites.

CONCLUSIONS

This work comprehensively compares the differential proximity functions under different codes by setting a variety of simulation conditions and has basic guiding significance for helping users simulate and analyze the deposition characteristics of microscale electrons according to the selection of an appropriate methodology and cut-off energy.

Perspectives of Gas Phase Ion Chemistry: Spectroscopy and Modeling

The study of ions in the gas phase has a long history and has involved both chemists and physicists. The interplay of their competences with the use of very sophisticated commercial and/or homemade instrumentations and theoretical models has improved the knowledge of thermodynamics and kinetics of many chemical reactions, even if still many stages of these processes need to be fully understood. The new technologies and the novel free-electron laser facilities based on plasma acceleration open new opportunities to investigate the chemical reactions in some unrevealed fundamental aspects. The synchrotron light source can be put beside the FELs, and by mass spectrometric techniques and spectroscopies coupled with versatile ion sources it is possible to really change the state of the art of the ion chemistry in different areas such as atmospheric and astro chemistry, plasma chemistry, biophysics, and interstellar medium (ISM). In this manuscript we review the works performed by a joint combination of the experimental studies of ion–molecule reactions with synchrotron radiation and theoretical models adapted and developed to the experimental evidence. The review concludes with the perspectives of ion–molecule reactions by using FEL instrumentations as well as pump probe measurements and the initial attempt in the development of more realistic theoretical models for the prospective improvement of our predictive capability.

Dosimetry assessment of theranostic Auger-emitting radionuclides in a micron-sized multicellular cluster model: A Monte Carlo study using Geant4-DNA simulations

The present work is aimed at improving the multicellular dosimetry of several Auger radionuclides of interest for targeted cancer therapy, including ^99mTc, ¹¹¹In, ¹²³I, ¹²⁵I, and ²⁰¹Tl. For this purpose, using the Geant4-DNA Monte Carlo code, a cluster of 13 similar spherical cells with a hexagonal packed arrangement was modeled, and the mean absorbed doses per unit cumulated activity (S-values) were calculated by considering two target←source configurations, cell←cell and nucleus←nucleus. The obtained ratios of cross-dose to self-dose S-value in terms of the distance between the source and target regions were evaluated and also compared to those estimated by the Medical Internal Radiation Dose (MIRD) method. Besides, the contribution of the Coster-Kronig, Auger and internal conversion electrons to the S-values was provided for each radionuclide. According to the results, it can be concluded that in contrast to self-absorption, the cross-absorption due to the Auger-emitters has not a significant role in the total energy deposition within a cell in the cluster.

Nanoscale Calculation of Proton-Induced DNA Damage Using a Chromatin Geometry Model with Geant4-DNA

Monte Carlo simulations can quantify various types of DNA damage to evaluate the biological effects of ionizing radiation at the nanometer scale. This work presents a study simulating the DNA target response after proton irradiation. A chromatin fiber model and new physics constructors with the ELastic Scattering of Electrons and Positrons by neutral Atoms (ELSEPA) model were used to describe the DNA geometry and the physical stage of water radiolysis with the Geant4-DNA toolkit, respectively. Three key parameters (the energy threshold model for strand breaks, the physics model and the maximum distance to distinguish DSB clusters) of scoring DNA damage were studied to investigate the impact on the uncertainties of DNA damage. On the basis of comparison of our results with experimental data and published findings, we were able to accurately predict the yield of various types of DNA damage. Our results indicated that the difference in physics constructor can cause up to 56.4% in the DNA double-strand break (DSB) yields. The DSB yields were quite sensitive to the energy threshold for strand breaks (SB) and the maximum distance to classify the DSB clusters, which were even more than 100 times and four times than the default configurations, respectively.

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.

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.

Monte Carlo simulations of nanodosimetry and radiolytic species production for monoenergetic proton and electron beams: Benchmarking of GEANT4-DNA and LPCHEM codes

PURPOSE

In hadrontherapy, biophysical models can be used to predict the biological effect received by cancerous tissues and organs at risk. The input data of these models generally consist of information on nano/micro dosimetric quantities and, concerning some models, reactive species produced in water radiolysis. In order to fully account for the radiation stochastic effects, these input data have to be provided by Monte Carlo track structure (MCTS) codes allowing to estimate physical, physico-chemical, and chemical effects of radiation at the molecular scale. The objective of this study is to benchmark two MCTS codes, Geant4-DNA and LPCHEM, that are useful codes for estimating the biological effects of ions during radiation therapy treatments.

MATERIAL AND METHODS

In this study we considered the simulation of specific energy spectra for monoenergetic proton beams (10 MeV) as well as radiolysis species production for both electron (1 MeV) and proton (10 MeV) beams with Geant4-DNA and LPCHEM codes. Options 2, 4, and 6 of the Geant4-DNA physics lists have been benchmarked against LPCHEM. We compared probability distributions of energy transfer points in cylindrical nanometric targets (10 nm) positioned in a liquid water box. Then, radiochemical species (· OH, e aq - ${\rm{e}}_{{\rm{aq}}}^ - $ , H 3 O + , H 2 O 2 ${{\rm{H}}_3}{{\rm{O}}^ + },{\rm{\;}}{{\rm{H}}_2}{{\rm{O}}_2}$ , H₂ , and O H - ) ${\rm{O}}{{\rm{H}}^ - }){\rm{\;}}$ yields simulated between 10^-12 and 10^-6 s after irradiation are compared.

RESULTS

Overall, the specific energy spectra and the chemical yields obtained by the two codes are in good agreement considering the uncertainties on experimental data used to calibrate the parameters of the MCTS codes. For 10 MeV proton beams, ionization and excitation processes are the major contributors to the specific energy deposition (larger than 90%) while attachment, solvation, and vibration processes are minor contributors. LPCHEM simulates tracks with slightly more concentrated energy depositions than Geant4-DNA which translates into slightly faster recombination than Geant4-DNA. Relative deviations (C_EV ) with respect to the average of evolution rates of the radical yields between 10^-12 and 10^-6 s remain below 10%. When comparing execution times between the codes, we showed that LPCHEM is faster than Geant4-DNA by a factor of about four for 1000 primary particles in all simulation stages (physical, physico-chemical, and chemical). In multi-thread mode (four threads), Geant4-DNA computing times are reduced but remain slower than LPCHEM by ∼20% up to ∼50%.

CONCLUSIONS

For the first time, the entire physical, physico-chemical, and chemical models of two track structure Monte Carlo codes have been benchmarked along with an extensive analysis on the effects on the water radiolysis simulation. This study opens up new perspectives in using specific energy distributions and radiolytic species yields from monoenergetic ions in biophysical models integrated to Monte Carlo software.

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

Simple Summary

A brief description of the methodologies to simulate ionizing radiation transport in biologically relevant matter is presented. Emphasis is given to the physical, chemical, and biological models of Geant4-DNA that enable mechanistic radiobiological modeling at the cellular and DNA level, important to improve the efficacy of existing and novel radiotherapeutic modalities for the treatment of cancer.

Abstract

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 β^±-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.

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 andW-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.

Recent Developments on gMicroMC: Transport Simulations of Proton and Heavy Ions and Concurrent Transport of Radicals and DNA

Mechanistic Monte Carlo (MC) simulation of radiation interaction with water and DNA is important for the understanding of biological responses induced by ionizing radiation. In our previous work, we employed the Graphical Processing Unit (GPU)-based parallel computing technique to develop a novel, highly efficient, and open-source MC simulation tool, gMicroMC, for simulating electron-induced DNA damages. In this work, we reported two new developments in gMicroMC: the transport simulation of protons and heavy ions and the concurrent transport of radicals in the presence of DNA. We modeled these transports based on electromagnetic interactions between charged particles and water molecules and the chemical reactions between radicals and DNA molecules. Various physical properties, such as Linear Energy Transfer (LET) and particle range, from our simulation agreed with data published by NIST or simulation results from other CPU-based MC packages. The simulation results of DNA damage under the concurrent transport of radicals and DNA agreed with those from nBio-Topas simulation in a comprehensive testing case. GPU parallel computing enabled high computational efficiency. It took 41 s to simultaneously transport 100 protons with an initial kinetic energy of 10 MeV in water and 470 s to transport 105 radicals up to 1 µs in the presence of DNA.

Ultrahigh dose-rate (FLASH) x-ray irradiator for pre-clinical laboratory research

FLASH irradiation has been shown to reduce significantly normal tissue toxicity compared to conventional irradiation, while maintaining tumor control probability at similar level. Clinical translation of FLASH irradiation necessitates comprehensive laboratory studies to elucidate biological effects as well as pertinent technological and physical requirements. At present, FLASH research employs complex accelerator technologies of limited accessibilities. Here, we study the feasibility of a novel self-shielded x-ray irradiation cabinet system, as an enabling technology to enhance the preclinical research capabilities. The proposed system employs two commercially available high capacity 150 kVp fluoroscopy x-ray sources with rotating anode technology in a parallel-opposed arrangement. Simulation was performed with the GEANT4 Monte-Carlo platform. Simulated dosimetric properties of the x-ray beam for both FLASH and conventional dose-rate irradiations were characterized. Dose and dose rate from a single kV x-ray fluoroscopy source in solid water phantom were verified with measurements using Gafchromic films. The parallel-opposed x-ray sources can deliver over 50 Gy doses to a 20 mm thick water equivalent medium at ultrahigh dose-rates of 40-240 Gy s^-1. A uniform depth-dose rate (±5%) is achieved over 8-12 mm in the central region of the phantom. Mirrored beams minimize heel effect of the source and achieve reasonable cross-beam uniformity (±3%). Conventional dose-rate irradiation (≤0.1 Gy s^-1) can also be achieved by reducing the tube current and increasing the distance between the phantom and tubes. The rotating anode x-ray source can be used to deliver both FLASH and conventional dose-rate irradiations with the field dimensions well suitable for small animal and cell-culture irradiations. For FLASH irradiation using parallel-opposed sources, entrance and exit doses can be higher by 30% than the dose at the phantom center. Beam angling can be employed to minimize the high surface doses. Our proposed system is amendable to self-shielding and enhance research in regular laboratory setting.

Microdosimetric investigation of the radiation quality of low-medium energy electrons using Geant4-DNA

The increasing clinical use of low-energy photon and electron sources (below few tens of keV) has raised concerns on the adequacy of the existing approximation of an energy-independent radiobiological effectiveness. In this work, the variation of the quality factor (Q) and relative biological effectiveness (RBE) of electrons over the low-medium energy range (0.1 keV-1 MeV) is examined using several microdosimetry-based Monte Carlo methodologies with input data obtained from Geant4-DNA track-structure simulations. The sensitivity of the results to the different methodologies, Geant4-DNA physics models, and target sizes is examined. Calculations of Q and RBE are based on the ICRU Report 40 recommendations, the Kellerer-Hahn approximation, the site version of the theory of dual radiation action (TDRA), the microdosimetric kinetic model (MKM) of cell survival, and the calculated yield of DNA double strand breaks (DSB). The stochastic energy deposition spectra needed as input in the above approaches have been calculated for nanometer spherical volumes using the different electron physics models of Geant4-DNA. Results are normalized at 100 keV electrons which is here considered the reference radiation. It is shown that in the energy range ~50 keV-1 MeV, the calculated Q and RBE are approximately unity (to within 1-2%) irrespective of the methodology, Geant4-DNA physics model, and target size. At lower energies, Q and RBE become energy-dependent reaching a maximum value of ~1.5-2.5 between ~200 and 700 eV. The detailed variation of Q and RBE at low energies depends mostly upon the adopted methodology and target size, and less so upon the Geant4-DNA physics model. Overall, the DSB yield predicts the highest RBE values (with RBE_max≈2.5) whereas the MKM the lowest RBE values (with RBE_max≈1.5). The ICRU Report 40, Kellerer-Hahn, and TDRA methods are in excellent agreement (to within 1-2%) over the whole energy range predicting a Q_max≈2. In conclusion, the approximation Q=RBE=1 was found to be valid only above ~50 keV whereas at lower energies both Q and RBE become strongly energy-dependent. It is envisioned that the present work will contribute towards establishing robust methodologies to determine theoretically the energy-dependence of radiation quality of individual electrons which may then be used in subsequent calculations involving practical electron and photon radiation sources.

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.

Monte Carlo dosimetry of a realistic multicellular model of follicular lymphoma in a context of radioimmunotherapy

PURPOSE

Small-scale dosimetry studies generally consider an artificial environment where the tumors are spherical and the radionuclides are homogeneously biodistributed. However, tumor shapes are irregular and radiopharmaceutical biodistributions are heterogeneous, impacting the energy deposition in targeted radionuclide therapy. To bring realism, we developed a dosimetric methodology based on a three-dimensional in vitro model of follicular lymphoma incubated with rituximab, an anti-CD20 monoclonal antibody used in the treatment of non-Hodgkin lymphomas, which might be combined with a radionuclide. The effects of the realistic geometry and biodistribution on the absorbed dose were highlighted by comparison with literature data. Additionally, to illustrate the possibilities of this methodology, the effect of different radionuclides on the absorbed dose distribution delivered to the in vitro tumor were compared.

METHODS

The starting point was a model named multicellular aggregates of lymphoma cells (MALC). Three MALCs of different dimensions and their rituximab biodistribution were considered. Geometry, antibody location and concentration were extracted from selective plane illumination microscopy. Assuming antibody radiolabeling with Auger electron (¹²⁵ I and ¹¹¹ In) and β^- particle emitters (¹⁷⁷ Lu, ¹³¹ I and ⁹⁰ Y), we simulated energy deposition in MALCs using two Monte Carlo codes: Geant4-DNA with "CPA100" physics models for Auger electron emitters and Geant4 with "Livermore" physics models for β^- particle emitters.

RESULTS

MALCs had ellipsoid-like shapes with major radii, r, of ~0.25, ~0.5 and ~1.3 mm. Rituximab was concentrated in the periphery of the MALCs. The absorbed doses delivered by ¹⁷⁷ Lu, ¹³¹ I and ⁹⁰ Y in MALCs were compared with literature data for spheres with two types of homogeneous biodistributions (on the surface or throughout the volume). Compared to the MALCs, the mean absorbed doses delivered in spheres with surface biodistributions were between 18% and 38% lower, while with volume biodistribution they were between 15% and 29% higher. Regarding the radionuclides comparison, the relationship between MALC dimensions, rituximab biodistribution and energy released per decay impacted the absorbed doses. Despite releasing less energy, ¹²⁵ I delivered a greater absorbed dose per decay than ¹¹¹ In in the r ~ 0.25 mm MALC (6.78·10^-2 vs 6.26·10^-2  µGy·Bq^-1 ·s^-1 ). Similarly, the absorbed doses per decay in the r ~ 0.5 mm MALC for ¹⁷⁷ Lu (2.41·10^-2  µGy·Bq^-1 ·s^-1 ) and ¹³¹ I (2.46·10^-2  µGy·Bq^-1 ·s^-1 ) are higher than for ⁹⁰ Y (1.98·10^-2  µGy·Bq^-1 ·s^-1 ). Furthermore, radionuclides releasing more energy per decay delivered absorbed dose more uniformly through the MALCs. Finally, when considering the radiopharmaceutical effective half-life, due to the biological half-life of rituximab being best matched by the physical half-life of ¹⁷⁷ Lu and ¹³¹ I compared to ⁹⁰ Y, the first two radionuclides delivered higher absorbed doses.

CONCLUSION

In the simulated configurations, β^- emitters delivered higher and more uniform absorbed dose than Auger electron emitters. When considering radiopharmaceutical half-lives, ¹⁷⁷ Lu and ¹³¹ I delivered absorbed doses higher than ⁹⁰ Y. In view of real irradiation of MALCs, such a work may be useful to select suited radionuclides and to help explain the biological effects.

A parameter sensitivity study for simulating DNA damage after proton irradiation using TOPAS-nBio

Monte Carlo (MC) track structure simulation tools are commonly used for predicting radiation induced DNA damage by modeling the physical and chemical reactions at the nanometer scale. However, the outcome of these MC simulations is particularly sensitive to the adopted parameters which vary significantly across studies. In this study, a previously developed full model of nuclear DNA was used to describe the DNA geometry. The TOPAS-nBio MC toolkit was used to investigate the impact of physics and chemistry models as well as three key parameters (the energy threshold for direct damage, the chemical stage time length, and the probability of damage between hydroxyl radical reactions with DNA) on the induction of DNA damage. Our results show that the difference in physics and chemistry models alone can cause differences up to 34% and 16% in the DNA double strand break (DSB) yield, respectively. Additionally, changing the direct damage threshold, chemical stage length, and hydroxyl damage probability can cause differences of up to 28%, 51%, and 71% in predicted DSB yields, respectively, for the configurations in this study.

Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations

Ionizing radiation is a common tool in medical procedures. Monte Carlo (MC) techniques are widely used when dosimetry is the matter of investigation. The scientific community has invested, over the last 20 years, a lot of effort into improving the knowledge of radiation biology. The present article aims to summarize the understanding of the field of DNA damage response (DDR) to ionizing radiation by providing an overview on MC simulation studies that try to explain several aspects of radiation biology. The need for accurate techniques for the quantification of DNA damage is crucial, as it becomes a clinical need to evaluate the outcome of various applications including both low- and high-energy radiation medical procedures. Understanding DNA repair processes would improve radiation therapy procedures. Monte Carlo simulations are a promising tool in radiobiology studies, as there are clear prospects for more advanced tools that could be used in multidisciplinary studies, in the fields of physics, medicine, biology and chemistry. Still, lot of effort is needed to evolve MC simulation tools and apply them in multiscale studies starting from small DNA segments and reaching a population of cells.

A new open-source GPU-based microscopic Monte Carlo simulation tool for the calculations of DNA damages caused by ionizing radiation --- Part I: Core algorithm and validation

PURPOSE

Monte Carlo (MC) simulation of radiation interactions with water medium at physical, physicochemical, and chemical stages, as well as the computation of biologically relevant quantities such as DNA damages, are of critical importance for the understanding of microscopic basis of radiation effects. Due to the large problem size and many-body simulation problem in the chemical stage, existing CPU-based computational packages encounter the problem of low computational efficiency. This paper reports our development on a GPU-based microscopic Monte Carlo simulation tool gMicroMC using advanced GPU-acceleration techniques.

METHODS

gMicroMC simulated electron transport in the physical stage using an interaction-by-interaction scheme to calculate the initial events generating radicals in water. After the physicochemical stage, initial positions of all radicals were determined. Simulation of radicals' diffusion and reactions in the chemical stage was achieved using a step-by-step model using GPU-accelerated parallelization together with a GPU-enabled box-sorting algorithm to reduce the computations of searching for interaction pairs and therefore improve efficiency. A multi-scale DNA model of the whole lymphocyte cell nucleus containing ~6.2 Gbp of DNA was built.

RESULTS

Accuracy of physical stage simulation was demonstrated by computing stopping power and track length. The results agreed with published data and the data produced by GEANT4-DNA (version 10.3.3) simulations with 10 -20% difference in most cases. Difference of yield values of major radiolytic species from GEANT4-DNA results was within 10%. We computed DNA damages caused by monoenergetic 662 keV photons, approximately representing ¹³⁷ Cs decay. Single-strand break (SSB) and double-strand break (DSB) yields were 196 ± 8 SSB/Gy/Gbp and 7.3 ± 0.7 DSB/Gy/Gbp, respectively, which agreed with the result of 188 SSB/Gy/Gbp and 8.4 DSB/Gy/Gbp computed by Hsiao et al. Compared to computation using a single CPU, gMicroMC achieved a speedup factor of ~540x using an NVidia TITAN Xp GPU card.

CONCLUSIONS

The achieved accuracy and efficiency demonstrated that gMicroMC can facilitate research on microscopic radiation transport simulation and DNA damage calculation. gMicroMC is an open-source package available to the research community.

Microdosimetric calculations of the direct DNA damage induced by low energy electrons using the Geant4-DNA Monte Carlo code

To calculate the yield of direct DNA damage induced by low energy electrons using Monte Carlo generated microdosimetric spectra at the nanometer scale and examine the influence of various simulation inputs. The potential of classical microdosimetry to offer a viable and simpler alternative to more elaborate mechanistic approaches for practical applications is discussed. Track-structure simulations with the Geant4-DNA low-energy extension of the Geant4 Monte Carlo toolkit were used for calculating lineal energy spectra in spherical volumes with dimensions relevant to double-strand-break (DSB) induction. The microdosimetric spectra were then used to calculate the yield of simple and clustered DSB based on literature values of the threshold energy of DNA damage. The influence of the different implementations of the dielectric function of liquid water available in Geant4-DNA (Option 2 and Option 4 constructors), as well as the effect of particle tracking cutoff energy and target size are examined. Frequency- and dose-mean lineal energies in liquid-water spheres of 2, 2.3, 2.6, and 3.4 nm diameter, as well as, number of simple and clustered DSB/Gy/cell are presented for electrons over the 100 eV to 100 keV energy range. Results are presented for both the 'default' (Option 2) and 'Ioannina' (Option 4) physics models of Geant4-DNA applying several commonly used tracking cutoff energies (10, 20, 50, 100 eV). Overall, the choice of the physics model and target diameter has a moderate effect (up to ~10%-30%) on the DSB yield whereas the effect of the tracking cutoff energy may be significant (>100%). Importantly, the yield of both simple and clustered DSB was found to vary significantly (by a factor of 2 or more) with electron energy over the examined range. The yields of electron-induced simple and clustered DSB exhibit a strong energy dependence over the 100 eV-100 keV range with implications to radiation quality issues. It is shown that a classical microdosimetry approach for the calculation of DNA damage based on lineal energy spectra in nanometer-size targets predicts comparable results to computationally intensive mechanistic approaches which use detailed atomistic DNA geometries, thus, offering a relatively simple and robust alternative for some practical applications.

The influence of Geant4-DNA toolkit parameters on electron microdosimetric track structure

The influence of different physical process factors on tracks of low-energy electrons in liquid water was analyzed and evaluated based on the Geant4-DNA toolkit of Geant4 version 10.4, and it provides theoretical support for obtaining the basic parameters of microdosimetry concerned with radiotherapy and radiation protection. According to the characteristics of different models, five physics constructors of Geant4-DNA toolkit were selected to simulate monoenergetic electrons in microscopic scale. Details of track structure of different Geant4-DNA physics constructors were compared, including total number of interaction processes, number and energy percentage of excitation and ionization; analyzing the impacts of mean lineal energy of several factors, including Geant4-DNA physics constructors, initial energy, radius of scoring spheres, interaction processes and cut-off energy. Firstly, 'G4EmDNAPhysics' (hereinafter referred to as 'dna') is well consistent with 'G4EmDNAPhysics_option 2' (hereinafter referred to as 'option 2'), and 'G4EmDNAPhysics_option 4' (hereinafter referred to as 'option 4') is well consistent with 'G4EmDNAPhysics_option 5' (hereinafter referred to as 'option 5'); secondly, there are differences for the information of track structure and mean lineal energy between 'option 2' 'option 4' and 'G4EmDNAPhysics_option 6' (hereinafter referred to as 'option 6'); thirdly, the influence of the model on the mean lineal energy decreases with the increase of the radius of the scoring spheres, whereas mean lineal energy increases as the tracking cut increases. Several alternative discrete physics constructors of Geant4-DNA are comprehensively discussed overlaying multiple perspectives under different conditions in this work.

TOPAS-nBio: An Extension to the TOPAS Simulation Toolkit for Cellular and Sub-cellular Radiobiology

The TOPAS Monte Carlo (MC) system is used in radiation therapy and medical imaging research, having played a significant role in making Monte Carlo simulations widely available for proton therapy related research. While TOPAS provides detailed simulations of patient scale properties, the fundamental unit of the biological response to radiation is a cell. Thus, our goal was to develop TOPAS-nBio, an extension of TOPAS dedicated to advance understanding of radiobiological effects at the (sub-)cellular, (i.e., the cellular and sub-cellular) scale. TOPAS-nBio was designed as a set of open source classes that extends TOPAS to model radiobiological experiments. TOPAS-nBio is based on and extends Geant4-DNA, which extends the Geant4 toolkit, the basis of TOPAS, to include very low-energy interactions of particles down to vibrational energies, explicitly simulates every particle interaction (i.e., without using condensed histories) and propagates radiolysis products. To further facilitate the use of TOPAS-nBio, a graphical user interface was developed. TOPAS-nBio offers full track-structure Monte Carlo simulations, integration of chemical reactions within the first millisecond, an extensive catalogue of specialized cell geometries as well as sub-cellular structures such as DNA and mitochondria, and interfaces to mechanistic models of DNA repair kinetics. We compared TOPAS-nBio simulations to measured and published data of energy deposition patterns and chemical reaction rates (G values). Our simulations agreed well within the experimental uncertainties. Additionally, we expanded the chemical reactions and species provided in Geant4-DNA and developed a new method based on independent reaction times (IRT), including a total of 72 reactions classified into 6 types between neutral and charged species. Chemical stage simulations using IRT were a factor of 145 faster than with step-by-step tracking. Finally, we applied the geometric/chemical modeling to obtain initial yields of double-strand breaks (DSBs) in DNA fibers for proton irradiations of 3 and 50 MeV and compared the effect of including chemical reactions on the number and complexity of DSB induction. Over half of the DSBs were found to include chemical reactions with approximately 5% of DSBs caused only by chemical reactions. In conclusion, the TOPAS-nBio extension to the TOPAS MC application offers access to accurate and detailed multiscale simulations, from a macroscopic description of the radiation field to microscopic description of biological outcome for selected cells. TOPAS-nBio offers detailed physics and chemistry simulations of radiobiological experiments on cells simulating the initially induced damage and links to models of DNA repair kinetics.

Clinically relevant nanodosimetric simulation of DNA damage complexity from photons and protons

Relative Biological Effectiveness (RBE), the ratio of doses between radiation modalities to produce the same biological endpoint, is a controversial and important topic in proton therapy. A number of phenomenological models incorporate variable RBE as a function of Linear Energy Transfer (LET), though a lack of mechanistic description limits their applicability. In this work we take a different approach, using a track structure model employing fundamental physics and chemistry to make predictions of proton and photon induced DNA damage, the first step in the mechanism of radiation-induced cell death. We apply this model to a proton therapy clinical case showing, for the first time, predictions of DNA damage on a patient treatment plan. Our model predictions are for an idealised cell and are applied to an ependymoma case, at this stage without any cell specific parameters. By comparing to similar predictions for photons, we present a voxel-wise RBE of DNA damage complexity. This RBE of damage complexity shows similar trends to the expected RBE for cell kill, implying that damage complexity is an important factor in DNA repair and therefore biological effect.

Relative Biological Effectiveness (RBE) is a controversial and important topic in proton therapy. This work uses Monte Carlo simulations of DNA damage for protons and photons to probe this phenomenon, providing a plausible mechanistic understanding.

Validation and investigation of reactive species yields of Geant4-DNA chemistry models

PURPOSE

Indirect biological damage due to reactive species produced in water radiolysis reactions is responsible for the majority of biological effect for low linear energy transfer (LET) radiation. Modeling water radiolysis and the subsequent interactions of reactive species, as well as track structures, is essential to model radiobiology on the microscale. Recently, chemistry models have been developed for Geant4-DNA to be used in combination with the comprehensive existing physics models. In the current work, the first detailed, independent, in silico validation of all species yields with published experimental observations and comparison with other radiobiological simulations is presented. Additionally, the effect of LET of protons and heavier ions on reactive species yield in the model was examined, as well as the completeness of the chemical reactions following the radiolysis within the time after physical interactions simulated in the model.

METHODS

Yields over time of reactive species were simulated for water radiolysis by incident electrons, protons, alpha particles, and ions with various LETs using Geant4 and RITRACKS simulation tools. Water dissociation and recombination was simulated using Geant4 to determine the completeness of chemical reactions at the end of the simulation. Yield validation was performed by comparing yields simulated using Geant4 with experimental observations and other simulations. Validation was performed for all species for low LET radiation and the solvated electron and hydroxyl radical for high LET ions.

RESULTS

It was found that the Geant4-DNA chemistry yields were generally in good agreement with experimental observations and other simulations. However, the Geant4-DNA yields for the hydroxyl radical and hydrogen peroxide at the end of the chemistry stage were found to be respectively considerably higher and lower than the experimentally observed yields. Increasing the LET of incident hadrons increased the yield of secondary species and decreased the yield of primary species. The effect of LET on the yield of the hydroxyl radical at 100 ns simulated with Geant4 was in good agreement with experimental measurements. Additionally, by the end of the simulation only 40% of dissociated water molecules had been recombined and the rate of recombination was slowing.

CONCLUSIONS

The yields simulated using Geant4 are within reasonable agreement with experimental observations. Higher LET radiation corresponds with increased yields of secondary species and decreased yields of primary species. These trends combined with the LET having similar effects on the 100 ns hydroxyl radical yield for Geant4 and experimental measurements indicate that Geant4 accurately models the effect of LET on radiolysis yields. The limited recombination within the modeled chemistry stage and the slowing rate of recombination at the end of the stage indicate potential long-range indirect biological damage.

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

The use of Monte Carlo (MC) simulations remains a powerful tool to study the biological effects induced by ionizing radiation on living beings. Several MC codes are commonly used in research fields such as nanodosimetry, radiotherapy, radiation protection, and space radiation. This work presents an enhancement of an existing model [1] for radiobiological purposes, to account for the indirect DNA damage induced by ionizing particles. The Geant4-DNA simulation toolkit was used to simulate the physical, pre-chemical, and chemical stages of early DNA damage induced by protons and α-particles. Liquid water was used as the medium for simulations. Two phase-space files were generated, one containing the energy deposition events and another with the position of chemical species produced by water radiolysis from 0.1 ps up to 1 ns. These files were used as input in the radiobiological code that contains the genetic material model with atomic resolution, consisting of several copies of 30 nm chromatin fibers. The B-DNA configuration was used. This work focused on the indirect damage produced by the hydroxyl radical (OH) attack on the sugar-phosphate group. The approach followed to account for the indirect DNA damage was the same as those used by other radiobiological codes [2,3]. The critical parameter considered here was the reaction radius, which was calculated from the Smoluchowski's diffusion equation. Single, double, and total strand break yields produced by direct, indirect, and mixed mechanisms are reported. The obtained results are consistent with experimental and calculation data sets published in the literature.

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

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

Targeted alpha therapy with 212Pb or 225Ac: Change in RBE from daughter migration

Targeted α-therapy (TAT) could be delivered early to patients who are at a high-risk for developing brain metastases, targeting the areas of the vasculature where tumor cells are penetrating into the brain. We have utilized a Monte Carlo model representing brain vasculature to calculate physical dose and DNA damage from the α-emitters ²²⁵Ac and ²¹²Pb. The micron-scale dose distributions from all radioactive decay products were modeled in Geant4, including the eV-scale interactions using the Geant4-DNA models. These interactions were then superimposed on an atomic-scale DNA model to estimate strand break yields. In addition to ²²⁵Ac having a higher dose per decay than ²¹²Pb, it also has a double strand break yield per decay that is 4.7 ± 0.5 times that of ²¹²Pb. However, the efficacy of both nuclides depends on retaining the daughter nuclei at the target location in the brain vasculature. The relative biological effectiveness (RBE) of ²²⁵Ac and ²¹²Pb are similar when the entire decay chains are included, with maxima of 2.7 ± 0.6 and 2.5 ± 0.5 (respectively), and RBE values of about 2 to a depth of 80 μm. If the initial daughter is lost, the RBE of ²¹²Pb is completely reduced to 1 or lower and the RBE of ²²⁵Ac is approximately 2 only for the first 40 μm.

Mechanistic DNA damage simulations in Geant4-DNA part 1: A parameter study in a simplified geometry

Mechanistic modelling of DNA damage in Monte Carlo simulations is highly sensitive to the parameters that define DNA damage. In this work, we use a simple testing geometry to investigate how different choices of physics models and damage model parameters can change the estimation of DNA damage in a mechanistic DNA damage simulation built in Geant4-DNA. The choice of physics model can lead to variations by up to a factor of two in the yield of physically induced strand breaks, and the parameters that determine scavenging, and physical and chemical single strand break induction can have even larger consequences. Using low energy electrons as primary particles, a variety of parameters are tested in this geometry in order to arrive at a parameter set consistent with past simulation studies. We find that the modelling of scavenging can play an important role in determining results, and speculate that high-scavenging regimes, where only chemical radicals within 1 nm of DNA are simulated, could provide a good means of testing mechanistic DNA simulations.

Mechanistic DNA damage simulations in Geant4-DNA Part 2: Electron and proton damage in a bacterial cell

We extended a generic Geant4 application for mechanistic DNA damage simulations to an Escherichia coli cell geometry, finding electron damage yields and proton damage yields largely in line with experimental results. Depending on the simulation of radical scavenging, electrons double strand breaks (DSBs) yields range from 0.004 to 0.010 DSB Gy-1 Mbp-1, while protons have yields ranging from 0.004 DSB Gy-1 Mbp-1 at low LETs and with strict assumptions concerning scavenging, up to 0.020 DSB Gy-1 Mbp-1 at high LETs and when scavenging is weakest. Mechanistic DNA damage simulations can provide important limits on the extent to which physical processes can impact biology in low background experiments. We demonstrate the utility of these studies for low dose radiation biology calculating that in E. coli, the median rate at which the radiation background induces double strand breaks is 2.8 × 10-8 DSB day-1, significantly less than the mutation rate per generation measured in E. coli, which is on the order of 10-3.

Average stopping powers for electron and photon sources for radiobiological modeling and microdosimetric applications

This study concerns calculation of the average electronic stopping power for photon and electron sources. It addresses two problems that have not yet been fully resolved. The first is defining the electron spectrum used for averaging in a way that is most suitable for radiobiological modeling. We define it as the spectrum of electrons entering the sensitive to radiation volume (SV) within the cell nucleus, at the moment they enter the SV. For this spectrum we derive a formula that combines linearly the fluence spectrum and the source spectrum. The latter is the distribution of initial energies of electrons produced by a source. Previous studies used either the fluence or source spectra, but not both, thereby neglecting a part of the complete spectrum. Our derived formula reduces to these two prior methods in the case of high and low energy sources, respectively. The second problem is extending electron spectra to low energies. Previous studies used an energy cut-off on the order of 1 keV. However, as we show, even for high energy sources, such as 60Co, electrons with energies below 1 keV contribute about 30% to the dose. In this study all the spectra were calculated with Geant4-DNA code and a cut-off energy of only 11 eV. We present formulas for calculating frequency- and dose-average stopping powers, numerical results for several important electron and photon sources, and tables with all the data needed to use our formulas for arbitrary electron and photon sources producing electrons with initial energies up to  ∼1 MeV.

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.