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

"dsbandrepair" - An updated Geant4-DNA simulation tool for evaluating the radiation-induced DNA damage and its repair

PURPOSE

Interdisciplinary scientific communities have shown large interest to achieve a mechanistic description of radiation-induced biological damage, aiming to predict biological results produced by different radiation quality exposures. Monte Carlo track-structure simulations are suitable and reliable for the study of early DNA damage induction used as input for assessing DNA damage. This study presents the most recent improvements of a Geant4-DNA simulation tool named "dsbandrepair".

METHODS

"dsbandrepair" is a Monte Carlo simulation tool based on a previous code (FullSim) that estimates the induction of early DNA single-strand breaks (SSBs) and double-strand breaks (DSBs). It uses DNA geometries generated by the DNAFabric computational tool for simulating the induction of early single-strand breaks (SSBs) and double-strand breaks (DSBs). Moreover, the new tool includes some published radiobiological models for survival fraction and un-rejoined DSB. Its application for a human fibroblast cell and human umbilical vein endothelial cell containing both heterochromatin and euchromatin was conducted. In addition, this new version offers the possibility of using the new IRT-syn method for computing the chemical stage.

RESULTS

The direct and indirect strand breaks, SSBs, DSBs, and damage complexity obtained in this work are equivalent to those obtained with the previously published simulation tool when using the same configuration in the physical and chemical stages. Simulation results on survival fraction and un-rejoined DSB are in reasonable agreement with experimental data.

CONCLUSIONS

"dsbandrepair" is a tool for simulating DNA damage and repair, benchmarked against experimental data. It has been released as an advanced example in Geant4.11.2.

Physics and small-scale dosimetry of α $\alpha$ -emitters for targeted radionuclide therapy: The case of 211 At $^{211}{\rm At}$

BACKGROUND

Monte Carlo simulations have been considered for a long time the gold standard for dose calculations in conventional radiotherapy and are currently being applied for the same purpose in innovative radiotherapy techniques such as targeted radionuclide therapy (TRT).

PURPOSE

We present in this work a benchmarking study of the latest version of the Transport d'Ions Lourds Dans l'Aqua & Vivo (TILDA-V ) Monte Carlo track structure code, highlighting its capabilities for describing the full slowing down of α $\alpha$ -particles in water and the energy deposited in cells by α $\alpha$ -emitters in the context of TRT.

METHODS

We performed radiation transport simulations of α $\alpha$ -particles (10 keVu - 1 ${\rm u}^{-1}$ -100 MeVu - 1 ${\rm u}^{-1}$ ) in water with TILDA-V and the Particle and Heavy Ion Transport code System (PHITS) version 3.33. We compared the predictions of each code in terms of track parameters (stopping power, range and radial dose profiles) and cellular S-values of the promising radionuclide astatine-211 (211 At $^{211}{\rm At}$ ). Additional comparisons were made with available data in the literature.

RESULTS

The stopping power, range and radial dose profiles of α $\alpha$ -particles computed with TILDA-V were in excellent agreement with other calculations and available data. Overall, minor differences with PHITS were ascribed to phase effects, that is, related to the use of interaction cross sections computed for water vapor or liquid water. However, important discrepancies were observed in the radial dose profiles of monoenergetic α $\alpha$ -particles, for which PHITS results showed a large underestimation of the absorbed dose compared to other codes and experimental data. The cellular S-values of211 At $^{211}{\rm At}$ computed with TILDA-V  agreed within 4% with the values predicted by PHITS and MIRDcell.

CONCLUSIONS

The validation of the TILDA-V code presented in this work opens the possibility to use it as an accurate simulation tool for investigating the interaction of α $\alpha$ -particles in biological media down to the nanometer scale in the context of medical research. The code may help nuclear medicine physicians in their choice of α $\alpha$ -emitters for TRT. Further research will focus on the application of TILDA-V for quantifying radioinduced damage on the deoxyribonucleic acid (DNA) molecule.

Future Perspectives of Artificial Intelligence in Bone Marrow Dosimetry and Individualized Radioligand Therapy

Radioligand therapy is an emerging and effective treatment option for various types of malignancies, but may be intricately linked to hematological side effects such as anemia, lymphopenia or thrombocytopenia. The safety and efficacy of novel theranostic agents, targeting increasingly complex targets, can be well served by comprehensive dosimetry. However, optimization in patient management and patient selection based on risk-factors predicting adverse events and built upon reliable dose-response relations is still an open demand. In this context, artificial intelligence methods, especially machine learning and deep learning algorithms, may play a crucial role. This review provides an overview of upcoming opportunities for integrating artificial intelligence methods into the field of dosimetry in nuclear medicine by improving bone marrow and blood dosimetry accuracy, enabling early identification of potential hematological risk-factors, and allowing for adaptive treatment planning. It will further exemplify inspirational success stories from neighboring disciplines that may be translated to nuclear medicine practices, and will provide conceptual suggestions for future directions. In the future, we expect artificial intelligence-assisted (predictive) dosimetry combined with clinical parameters to pave the way towards truly personalized theranostics in radioligand therapy.

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.

Review of chemical models and applications in Geant4-DNA: Report from the ESA BioRad III Project

A chemistry module has been implemented in Geant4-DNA since Geant4 version 10.1 to simulate the radiolysis of water after irradiation. It has been used in a number of applications, including the calculation of G-values and early DNA damage, allowing the comparison with experimental data. Since the first version, numerous modifications have been made to the module to improve the computational efficiency and extend the simulation to homogeneous kinetics in bulk solution. With these new developments, new applications have been proposed and released as Geant4 examples, showing how to use chemical processes and models. This work reviews the models implemented and application developments for modeling water radiolysis in Geant4-DNA as reported in the ESA BioRad III Project.

Simulation of Radiation-Induced DNA Damage and Protection by Histones Using the Code RITRACKS

(1) Background: DNA damage is of great importance in the understanding of the effects of ionizing radiation. Various types of DNA damage can result from exposure to ionizing radiation, with clustered types considered the most important for radiobiological effects. (2) Methods: The code RITRACKS (Relativistic Ion Tracks), a program that simulates stochastic radiation track structures, was used to simulate DNA damage by photons and ions spanning a broad range of linear energy transfer (LET) values. To perform these simulations, the transport code was modified to include cross sections for the interactions of ions or electrons with DNA and amino acids for ionizations, dissociative electron attachment, and elastic collisions. The radiochemistry simulations were performed using a step-by-step algorithm that follows the evolution of all particles in time, including reactions between radicals and DNA structures and amino acids. Furthermore, detailed DNA damage events, such as base pair positions, DNA fragment lengths, and fragment yields, were recorded. (3) Results: We report simulation results using photons and the ions 1H+, 4He2+, 12C6+, 16O8+, and 56Fe26+ at various energies, covering LET values from 0.3 to 164 keV/µm, and performed a comparison with other codes and experimental results. The results show evidence of DNA protection from damage at its points of contacts with histone proteins. (4) Conclusions: RITRACKS can provide a framework for studying DNA damage from a variety of ionizing radiation sources with detailed representations of DNA at the atomic scale, DNA-associated proteins, and resulting DNA damage events and statistics, enabling a broader range of future comparisons with experiments such as those based on DNA sequencing.

A Critical Look at Heavy Ion Beam Irradiation for Vaccine Development

Recent studies offer valuable insights into viral inactivation for vaccine development. Schulze et al. have demonstrated the potential of heavy ion beam irradiation to create effective vaccines, which is particularly relevant in the context of airborne pandemics. Notably, the success in immunizing mice via intranasal administration with the inactivated influenza virus is encouraging, especially given the genetic similarities between influenza and SARS-CoV-2. However, the study raises important considerations. While heavy ion treatment shows advantages, there are concerns about viral inactivation completeness and the potential for surviving viruses, albeit at extremely low levels. Prolonged irradiation times and the risk of selective pressure leading to the evolution of resistant variants are highlighted. Biosafety concerns regarding accidental lab escape of resistant strains are crucial, emphasizing the need for caution during experiments. Moreover, limitations in Monte Carlo simulations of virus irradiation are discussed, pointing out the need for more comprehensive studies to assess the impact of secondary particles on virus inactivation under realistic irradiation conditions. Given these considerations, while the study presents a promising approach for vaccine development, further research is essential to address potential drawbacks and optimize the method for safe and effective application.

Estimation of the relative biological effectiveness for double strand break induction of clinical kilovoltage beams using Monte Carlo simulations

BACKGROUND

The Relative Biological Effectiveness (RBE) of kilovoltage photon beams has been previously investigated in vitro and in silico using analytical methods. The estimated values range from 1.03 to 1.82 depending on the methodology and beam energies examined.

PURPOSE

The focus of this work was to independently estimate RBE values for a range of clinically used kilovoltage beams (70-200 kVp) while investigating the suitability of using TOPAS-nBio for this task.

METHODS

Previously validated spectra of clinical beams were used to generate secondary electron spectra at several depths in a water tank phantom via TOPAS Monte Carlo (MC) simulations. Cell geometry was irradiated with the secondary electrons in TOPAS-nBio MC simulations. The deposited dose and the calculated number of DNA strand breaks were used to estimate RBE values.

RESULTS

Monoenergetic secondary electron simulations revealed the highest direct and indirect double strand break yield at approximately 20 keV. The average RBE value for the kilovoltage beams was calculated to be 1.14.

CONCLUSIONS

TOPAS-nBio was successfully used to estimate the RBE values for a range of clinical radiotherapy beams. The calculated value was in agreement with previous estimates, providing confidence in its clinical use in the future.

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.

Proton relative biological effectiveness for the induction of DNA double strand breaks based on Geant4

Uncertainties in the relative biological effectiveness (RBE) of proton remains a major barrier to the biological optimization of proton therapy. A large amount of experimental data suggest that proton RBE is variable. As an evolving Monte Carlo code toolkit, Geant4-DNA is able to simulate the initial DNA damage caused by particle beams through physical and chemical interactions at the nanometer scale over a short period of time. This contributes to evaluating the radiobiological effects induced by ionizing radiation. Based on the Geant4-DNA toolkit, this study constructed a DNA geometric model containing 6.32Gbp, simulated the relationship between radiochemical yields (G-values) and their corresponding chemical constructors, and calculated a detailed calculation of the sources of damage and the complexity of damage in DNA strand breaks. The damage model constructed in this study can simulate the relative biological effectiveness (RBE) in the proton Bragg peak region. The results indicate that: (1) When the electron energy is below 400 keV, the yield of OH·account for 18.1% to 25.3% of the total water radiolysis yields. (2) Under the influence of histone clearance function, the yield of indirect damage account for over 72.93% of the yield of DNA strand breaks (SBs). When linear energy transfer (LET) increased from 29.79 (keV/μm) to 64.29 (keV/μm), the yield of double strand breaks (DSB) increased from 17.27% to 32.65%. (3) By investigating the effect of proton Bragg peak depth on the yield of direct DSB (DSBdirect) and total DSB (DSBtotal), theRBEDSBtotandRBEDSBdirlevels of cells show that the RBE value of protons reaches 2.2 in the Bragg peak region.

The Effects of Particle LET and Fluence on the Complexity and Frequency of Clustered DNA Damage

Motivation

Clustered DNA-lesions are predominantly induced by ionizing radiation, particularly by high-LET particles, and considered as lethal damage. Quantification of this specific type of damage as a function of radiation parameters such as LET, dose rate, dose, and particle type can be informative for the prediction of biological outcome in radiobiological studies. This study investigated the induction and complexity of clustered DNA damage for three different types of particles at an LET range of 0.5-250 keV/μm.

Methods

Nanometric volumes (36.0 nm3) of 15 base-pair DNA with its hydration shell was modeled. Electron, proton, and alpha particles at various energies were simulated to irradiate the nanometric volumes. The number of ionization events, low-energy electron spectra, and chemical yields for the formation of °OH, H°, e aq - , and H2O2 were calculated for each particle as a function of LET. Single- and double-strand breaks (SSB and DSB), base release, and clustered DNA-lesions were computed from the Monte-Carlo based quantification of the reactive species and measured yields of the species responsible for the DNA lesion formation.

Results

The total amount of DNA damage depends on particle type and LET. The number of ionization events underestimates the quantity of DNA damage at LETs higher than 10 keV/μm. Minimum LETs of 9.4 and 11.5 keV/μm are required to induce clustered damage by a single track of proton and alpha particles, respectively. For a given radiation dose, an increase in LET reduces the number of particle tracks, leading to more complex clustered DNA damage, but a smaller number of separated clustered damage sites.

Conclusions

The dependency of the number and the complexity of clustered DNA damage on LET and fluence suggests that the quantification of this damage can be a useful method for the estimation of the biological effectiveness of radiation. These results also suggest that medium-LET particles are more appropriate for the treatment of bulk targets, whereas high-LET particles can be more effective for small targets.

A simulation study on the radiosensitization properties of gold nanorods

Objective. Gold nanorods (GNRs) have emerged as versatile nanoparticles with unique properties, holding promise in various modalities of cancer treatment through drug delivery and photothermal therapy. In the rapidly evolving field of nanoparticle radiosensitization (NPRS) for cancer therapy, this study assessed the potential of gold nanorods as radiosensitizing agents by quantifying the key features of NPRS, such as secondary electron emission and dose enhancement, using Monte Carlo simulations.Approach. Employing the TOPAS track structure code, we conducted a comprehensive evaluation of the radiosensitization behavior of spherical gold nanoparticles and gold nanorods. We systematically explored the impact of nanorod geometry (in particular size and aspect ratio) and orientation on secondary electron emission and deposited energy ratio, providing validated results against previously published simulations.Main results. Our findings demonstrate that gold nanorods exhibit comparable secondary electron emission to their spherical counterparts. Notably, nanorods with smaller surface-area-to-volume ratios (SA:V) and alignment with the incident photon beam proved to be more efficient radiosensitizing agents, showing superiority in emitted electron fluence. However, in the microscale, the deposited energy ratio (DER) was not markedly influenced by the SA:V of the nanorod. Additionally, our findings revealed that the geometry of gold nanoparticles has a more significant impact on the emission of M-shell Auger electrons (with energies below 3.5 keV) than on higher-energy electrons.Significance. This research investigated the radiosensitization properties of gold nanorods, positioning them as promising alternatives to the more conventionally studied spherical gold nanoparticles in the context of cancer research. With increasing interest in multimodal cancer therapy, our findings have the potential to contribute valuable insights into the perspective of gold nanorods as effective multipurpose agents for synergistic photothermal therapy and radiotherapy. Future directions may involve exploring alternative metallic nanorods as well as further optimizing the geometry and coating materials, opening new possibilities for more effective cancer treatments.

A spatial measure-valued model for radiation-induced DNA damage kinetics and repair under protracted irradiation condition

In the present work, we develop a general spatial stochastic model to describe the formation and repair of radiation-induced DNA damage. The model is described mathematically as a measure-valued particle-based stochastic system and extends in several directions the model developed in Cordoni et al. (Phys Rev E 103:012412, 2021; Int J Radiat Biol 1-16, 2022a; Radiat Res 197:218-232, 2022b). In this new spatial formulation, radiation-induced DNA damage in the cell nucleus can undergo different pathways to either repair or lead to cell inactivation. The main novelty of the work is to rigorously define a spatial model that considers the pairwise interaction of lesions and continuous protracted irradiation. The former is relevant from a biological point of view as clustered lesions are less likely to be repaired, leading to cell inactivation. The latter instead describes the effects of a continuous radiation field on biological tissue. We prove the existence and uniqueness of a solution to the above stochastic systems, characterizing its probabilistic properties. We further couple the model describing the biological system to a set of reaction-diffusion equations with random discontinuity that model the chemical environment. At last, we study the large system limit of the process. The developed model can be applied to different contexts, with radiotherapy and space radioprotection being the most relevant. Further, the biochemical system derived can play a crucial role in understanding an extremely promising novel radiotherapy treatment modality, named in the community FLASH radiotherapy, whose mechanism is today largely unknown.

Radioactive Molecules 2021-2022

In 2020 I was invited to write an editorial review on radioactive molecules published in Molecules in 2019 and 2020 [...].

Computational model of radiation oxygen effect with Monte Carlo simulation: effects of antioxidants and peroxyl radicals

PURPOSE

Oxygen plays a crucial role in radiation biology. Antioxidants and peroxyl radicals affect the oxygen effect greatly. This study aims to establish a computational model of the oxygen effect and explore the effect attributed to antioxidants and peroxyl radicals.

MATERIALS AND METHODS

Oxygen-related reactions are added to our track-structure Monte Carlo code NASIC, including oxygen fixation, chemical repair by antioxidants and damage migration from base-derived peroxyl radicals. Then the code is used to simulate the DNA damage under various oxygen, antioxidant and damage migration rate conditions. The oxygen enhancement ratio(OER) is calculated quantifying by the number of double-strand breaks for each condition. The roles of antioxidants and peroxyl radicals are examined by manipulating the relevant parameters.

RESULTS AND CONCLUSIONS

Our results indicate that antioxidants are capable of rapidly restoring DNA radicals through chemical reactions, which compete with natural and oxygen fixation processes. Additionally, antioxidants can react with peroxyl radicals derived from bases, thereby preventing the damage from migrating to DNA strands. By quantitatively accounting for the impact of peroxyl radicals and antioxidants on the OER curves, our study establishes a more precise and comprehensive model of the radiation oxygen effect.

An inter-comparison between radiobiological characteristics of a commercial low-energy IORT system by Geant4-DNA and MCDS Monte Carlo codes

INTRODUCTION

The need for accurate relative biological effectiveness (RBE) estimation for low energy therapeutic X-rays (corresponding to 50 kV nominal energy of a commercial low-energy IORT system (INTRABEAM)) is a crucial issue due to increased radiobiological effects, respect to high energy photons. Modeling of radiation-induced DNA damage through Monte Carlo (MC) simulation approaches can give useful information. Hence, this study aimed to evaluate and compare RBE of low energy therapeutic X-rays using Geant4-DNA toolkit and Monte Carlo damage simulation (MCDS) code.

MATERIALS AND METHODS

RBE calculations were performed considering the emitted secondary electron spectra through interactions of low energy X-rays inside the medium. In Geant4-DNA, the DNA strand breaks were obtained by employing a B-DNA model in physical stage with 10.79 eV energy-threshold and the probability of hydroxyl radical's chemical reactions of about 0.13%. Furthermore, RBE estimations by MCDS code were performed under fully aerobic conditions.

RESULTS

Acquired results by two considered MC codes showed that the same trend is found for RBEDSB and RBESSB variations. Totally, a reasonable agreement between the calculated RBE values (both RBESSB and RBEDSB) existed between the two considered MC codes. The mean differences of 9.2% and 1.8% were obtained between the estimated RBESSB and RBEDSB values by two codes, respectively.

CONCLUSION

Based on the obtained results, it can be concluded that a tolerable accordance is found between the calculated RBEDSB values through MCDS and Geant4-DNA, a fact which appropriates both codes for RBE evaluations of low energy therapeutic X-rays, especially in the case of RBEDSB where lethal damages are regarded.

First-principles simulation of an ejected electron produced by monochromatic deposition energy to water at the femtosecond order

This study uses a time-dependent first-principles simulation code to investigate the transient dynamics of an ejected electron produced in the monochromatic deposition energy from 11 to 19 eV in water. The energy deposition forms a three-body single spur comprising a hydroxyl radical (OH˙), hydronium ion (H3O+), and hydrated electron (eaq-). The earliest formation involves electron thermalization and delocalization dominated by the molecular excitation of water. Our simulation results show that the transient electron dynamics primarily depends on the amount of deposition energy to water; the thermalization time varies from 200 to 500 fs, and the delocalization varies from 3 to 10 nm in this energy range. These features are crucial for determining the earliest single-spur formation and facilitating a sequential simulation from an energy deposition to a chemical reaction in water photolysis or radiolysis. The spur radius obtained from the simulation correlates reasonably with the experimental-based estimations. Our results should provide universalistic insights for analysing ultrafast phenomena dominated by the molecular excitation of water in the femtosecond order.

Study of Nuclear Reactions in Therapy of Tumors with Proton Beams

This paper presents an assessment of nuclear reaction yields of protons, α-particles, and neutrons in human tissue-equivalentmaterial in proton therapy using a simulation with Geant 4. In this study, we also check an enhancement of nuclear reactions due to the presence of Bi, Au, 11B, and 10B radiosensitizer nanoparticles. We demonstrate that a proton beam induces a noticeable amount of nuclear reactions in the tissue. Nevertheless, the enhancement of nuclear reaction products due to radiosensitizer nanoparticles is found to be negligible.

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

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

Microdosimetric Analysis for Boron Neutron Capture Therapy via Monte Carlo Track Structure Simulation with Modified Lithium Cross-sections

Boron neutron capture therapy (BNCT) is a cellular-level hadron therapy achieving therapeutic effects via the synergistic action of multiple particles, including Lithium, alpha, proton, and photon. However, evaluating the relative biological effectiveness (RBE) in BNCT remains challenging. In this research, we performed a microdosimetric calculation for BNCT using the Monte Carlo track structure (MCTS) simulation toolkit, TOPAS-nBio. This paper reports the first attempt to derive the ionization cross-sections of low-energy (>0.025 MeV/u) Lithium for MCTS simulation based on the effective charge cross-section scalation method and phenomenological double-parameter modification. The fitting parameters λ 1 = 1.101 , λ 2 = 3.486 were determined to reproduce the range and stopping power data from the ICRU report 73. Besides, the lineal energy spectra of charged particles in BNCT were calculated, and the influence of sensitive volume (SV) size was discussed. Condensed history simulation obtained similar results with MCTS when using Micron-SV while overestimating the lineal energy when using Nano-SV. Furthermore, we found that the microscopic boron distribution can significantly affect the lineal energy for Lithium, while the effect for alpha is minimal. Similar results to the published data by PHITS simulation were observed for the compound particles and monoenergetic protons when using micron-SV. Spectra with nano-SV reflected that the different track densities and absorbed doses in the nucleus together result in the dramatic difference in the macroscopic biological response of BPA and BSH. This work and the developed methodology could impact the research fields in BNCT where understanding radiation effects is crucial, such as the treatment planning system, source evaluation, and new boron drug development.

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.

Monte Carlo study of the free radical yields in minibeam radiation therapy

BACKGROUND

Minibeam radiation therapy (MBRT) is a novel technique which has been shown to widen the therapeutic window through significant normal tissue sparing. Despite the heterogeneous dose distributions, tumor control is still ensured. Nevertheless the exact radiobiological mechanisms responsible for MBRT efficacy are not fully understood.

PURPOSE

Reactive oxygen species (ROS) resulting from water radiolysis were investigated given their implications not only on targeted DNA damage, but also for their role in the immune response and non-targeted cell signalling effects: two potential drivers of MBRT efficacy.

METHODS

Monte Carlo simulations were performed using TOPAS-nBio to carry out the irradiation of a water phantom with beams of protons (pMBRT), photons (xMBRT), 4 He ions (HeMBRT), and 12 C ions (CMBRT). Primary yields at the end of the chemical stage were calculated in spheres of 20 μm diameter, located in the peaks and valleys at various depths up to the Bragg peak. The chemical stage was limited to 1 ns to approximate biological scavenging, and the yield of · OH, H2 O2 , ande aq - ${\rm e}^{-}_{\rm aq}$ was recorded.

RESULTS

Beyond 10 mm, there were no substantial differences in the primary yields between peaks and valleys of the pMBRT and HeMBRT modalities. For xMBRT, there was a lower primary yield of the radical species · OH ande aq - ${\rm e}^{-}_{\rm aq}$ at all depths in the valleys compared to the peaks, and a higher primary yield of H2 O2 . Compared to the peaks, the valleys of the CMBRT modality were subject to a higher · OH ande aq - ${\rm e}^{-}_{\rm aq}$ yield, and lower H2 O2 yield. This difference between peaks and valleys became more severe in depth. Near the Bragg peak, the increase in the primary yield of the valleys over the peaks was 6% and 4% for · OH ande aq - ${\rm e}^{-}_{\rm aq}$ respectively, while there was a decrease in the yield of H2 O2 by 16%. Given the similar ROS primary yields in the peaks and valleys of pMBRT and HeMBRT, the level of indirect DNA damage is expected to be directly proportional to the peak to valley dose ratio (PVDR). The difference in the primary yields implicates a lower level of indirect DNA damage in the valleys compared to the peaks than what would be suggested by the PVDR for xMBRT, and a higher level for CMBRT.

CONCLUSIONS

These results highlight the notion that depending on the particle chosen, one can expect different levels of ROS in the peaks and valley that goes beyond what would be expected by the macroscopic PVDR. The combination of MBRT with heavier ions is shown to be particularly interesting as the primary yield in the valleys progressively diverges from the level observed in the peaks as the LET increases. While differences in the reported · OH yields of this work implicated the indirect DNA damage, H2 O2 yields particularly implicate non-targeted cell signalling effects, and therefore this work provides a point of reference for future simulations in which the distribution of this species at more biologically relevant timescales could be investigated.

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.

Application of Geant4-DNA for simulating water radiolysis induced by Auger electron-emitting radionuclides

Auger-emitting radionuclides have potential application in targeted radiotherapy, particularly for metastatic cancers. This possibility, especially, is stemmed from their characteristic short-range (a few μm) in biological systems allowing localization of high dose within small tumours. To explore this potential application, a Geant4 Monte Carlo toolkit has been employed to simulate the energy deposition of different radionuclides in a water model. The Geant4 Monte Carlo toolkit has model packages to simulate the interaction of radiation with matter and with diverse applications such as studies in science and medicine. In this study, the Geant4-DNA package was used to simulate the radiolytic yields induced by some Auger electron-emitting (AE) radionuclides including; I-131, I-125 and Pd-103, In-111, Ru-97 and Rh-103 m in water model. The results showed that the transient yield of the radiolytic species is characterized by the kinetic energies of the emitted electrons. It was observed that almost all the radionuclides, except I-131, deposited more energy in their proximity thereby inducing a high density of spurs to interact in a short time. It is, therefore, important to consider the kinetic energies of the emitted particles in choosing a radionuclide for specified targeted radiotherapy. This means that apart from their toxicity, compatibility with chelator and carrier molecules, and method of production, we can predict radionuclides such as In-111, Ru-97, Pb-103 m and I-125 could be relevant for targeted radiotherapy for the treatment of metastasis lesions, or tiny tumours at the cellular level, and tumours after surgical resection.

Electronic Excitation Response of DNA to High-Energy Proton Radiation in Water

The lack of molecular-level understanding for the electronic excitation response of DNA to charged particle radiation, such as high-energy protons, remains a fundamental scientific bottleneck in advancing proton and other ion beam cancer therapies. In particular, the dependence of different types of DNA damage on high-energy protons represents a significant knowledge void. Here we employ first-principles real-time time-dependent density functional theory simulation, using a massively parallel supercomputer, to unravel the quantum-mechanical details of the energy transfer from high-energy protons to DNA in water. The calculations reveal that protons deposit significantly more energy onto the DNA sugar-phosphate side chains than onto the nucleobases, and greater energy transfer is expected onto the DNA side chains than onto water. As a result of this electronic stopping process, highly energetic holes are generated on the DNA side chains as a source of oxidative damage.

The Cellular Response to Complex DNA Damage Induced by Ionising Radiation

Radiotherapy (ionising radiation; IR) is utilised in the treatment of ~50% of all human cancers, and where the therapeutic effect is largely achieved through DNA damage induction. In particular, complex DNA damage (CDD) containing two or more lesions within one to two helical turns of the DNA is a signature of IR and contributes significantly to the cell killing effects due to the difficult nature of its repair by the cellular DNA repair machinery. The levels and complexity of CDD increase with increasing ionisation density (linear energy transfer, LET) of the IR, such that photon (X-ray) radiotherapy is deemed low-LET whereas some particle ions (such as carbon ions) are high-LET radiotherapy. Despite this knowledge, there are challenges in the detection and quantitative measurement of IR-induced CDD in cells and tissues. Furthermore, there are biological uncertainties with the specific DNA repair proteins and pathways, including components of DNA single and double strand break mechanisms, that are engaged in CDD repair, which very much depends on the radiation type and associated LET. However, there are promising signs that advancements are being made in these areas and which will enhance our understanding of the cellular response to CDD induced by IR. There is also evidence that targeting CDD repair, particularly through inhibitors against selected DNA repair enzymes, can exacerbate the impact of higher LET, which could be explored further in a translational context.

Enhanced astaxanthin production of Haematococcus pluvialis strains induced salt and high light resistance with gamma irradiation

This study was conducted to increase the productivity of biomass that contains high astaxanthin content by developing a mutant Haematococcus pluvialis strain with strong environmental tolerance. H. pluvialis has a low cell-growth rate and is vulnerable to stressors such as salinity or light intensity, which may hinder large-scale commercial cultivation. A mutant M5 strain selected through 5000-Gy gamma irradiation showed improved biomass and astaxanthin production under high-salinity and high-light intensity conditions. With enhanced SOD activity and overexpressed astaxanthin biosynthesis genes (lyc, crtR-b, bkt2), M5 demonstrated an increase in biomass and astaxanthin productivity by 86.70 % and 66.15 %, respectively compared to those of untreated cells. Also, the omega-3 content of M5 increased by 149.44 % under 40 mM CaCl₂ compared to the untreated cells. Finally, even when subjected to high-intensity light irradiation for the whole life cycle, the biomass and astaxanthin concentration increased by 84.99 % and 241 %, respectively, compared to the wild-type cells.

Monte-Carlo techniques for radiotherapy applications II: equipment and source modelling, dose calculations and radiobiology

Introduction:

This is the second of two papers giving an overview of the use of Monte-Carlo techniques for radiotherapy applications.

Methods:

The first paper gave an introduction and introduced some of the codes that are available to the user wishing to model the different aspects of radiotherapy treatment. It also aims to serve as a useful companion to a curated collection of papers on Monte-Carlo that have been published in this journal.

Results and Conclusions:

This paper focuses on the application of Monte-Carlo to specific problems in radiotherapy. These include radiotherapy and imaging beam production, brachytherapy, phantom and patient dosimetry, detector modelling and track structure calculations for micro-dosimetry, nano-dosimetry and radiobiology.

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.

Development and implementation of a metaphase DNA model for ionizing radiation induced DNA damage calculation

Objective. To develop a metaphase chromosome model representing the complete genome of a human lymphocyte cell to support microscopic Monte Carlo (MMC) simulation-based radiation-induced DNA damage studies.Approach. We first employed coarse-grained polymer physics simulation to obtain a rod-shaped chromatid segment of 730 nm in diameter and 460 nm in height to match Hi-C data. We then voxelized the segment with a voxel size of 11 nm per side and connected the chromatid with 30 types of pre-constructed nucleosomes and 6 types of linker DNAs in base pair (bp) resolutions. Afterward, we piled different numbers of voxelized chromatid segments to create 23 pairs of chromosomes of 1-5μm long. Finally, we arranged the chromosomes at the cell metaphase plate of 5.5μm in radius to create the complete set of metaphase chromosomes. We implemented the model in gMicroMC simulation by denoting the DNA structure in a four-level hierarchical tree: nucleotide pairs, nucleosomes and linker DNAs, chromatid segments, and chromosomes. We applied the model to compute DNA damage under different radiation conditions and compared the results to those obtained with G0/G1 model and experimental measurements. We also performed uncertainty analysis for relevant simulation parameters.Main results. The chromatid segment was successfully voxelized and connected in bps resolution, containing 26.8 mega bps (Mbps) of DNA. With 466 segments, we obtained the metaphase chromosome containing 12.5 Gbps of DNA. Applying it to compute the radiation-induced DNA damage, the obtained results were self-consistent and agreed with experimental measurements. Through the parameter uncertainty study, we found that the DNA damage ratio between metaphase and G0/G1 phase models was not sensitive to the chemical simulation time. The damage was also not sensitive to the specific parameter settings in the polymer physics simulation, as long as the produced metaphase model followed a similar contact map distribution.Significance. Experimental data reveal that ionizing radiation induced DNA damage is cell cycle dependent. Yet, DNA chromosome models, except for the G0/G1 phase, are not available in the state-of-the-art MMC simulation. For the first time, we successfully built a metaphase chromosome model and implemented it into MMC simulation for radiation-induced DNA damage computation.

Multiple levels of stochasticity accounted for in different radiation biophysical models: from physics to biology

PURPOSE

In the present paper we investigate how some stochastic effects are included in a class of radiobiological models with particular emphasis on how such randomnesses reflect into the predicted cell survival curve.

MATERIALS AND METHODS

We consider four different models, namely the Generalized Stochastic Microdosimetric Model GSM², in its original full form, the Dirac GSM² the Poisson GSM² and the Repair-Misrepair Model (RMR). While GSM² and the RMR models are known in literature, the Dirac and the Poisson GSM²  have been newly introduced in this work. We further numerically investigate via Monte Carlo simulation of four different particle beams, how the proposed stochastic approximations reflect into the predicted survival curves. To achieve these results, we consider different ion species at energies of interest for therapeutic applications, also including a mixed field scenario.

RESULTS

We show how the Dirac GSM², the Poisson GSM² and the RMR can be obtained from the GSM² under suitable approximations on the stochasticity considered. We analytically derive the cell survival curve predicted by the four models, characterizing rigorously the high and low dose limits. We further study how the theoretical findings emerge also using Monte Carlo numerical simulations.

CONCLUSIONS

We show how different models include different levels of stochasticity in the description of cellular response to radiation. This translates into different cell survival predictions depending on the radiation quality.

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.

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.

A double-strand-break model for the relative biological effectiveness of electrons based on ionization clustering

BACKGROUND

The effectiveness of ionizing radiation regarding DNA damage induction depends on its spatial energy deposition pattern. For electrons an increased effectiveness is observed at low kinetic energies due to the enhanced density of energy deposition events at electron track ends.

PURPOSE

A model is presented, which enables the calculation of the double-strand-break (DSB) yield and the relative biological effectiveness (RBE) for DSB induction of electrons.

METHODS

The model applies the mean free path between two ionizations and the assumption that two ionizations within a certain threshold distance are necessary to potentially lead to a DSB. Next to an expression for the electron RBE according to its common definition, a local RBE is determined, which describes the electrons' local effectiveness at a defined point on their track.

RESULTS

This local RBE allows a better understanding of microscopic processes resulting from radiation and can be used, for instance, to describe the mean effectiveness of the mixed electron radiation field as a function of the radial distance to the center of an ion track.

CONCLUSIONS

The presented model reflects the experimentally observed increased effectiveness of low-energetic electrons. It will be used in a future work to improve RBE predictions for ions performed with the local effect model.

On the calculation of the relative biological effectiveness of ion radiation therapy using a biological weighting function, the microdosimetric kinetic model (MKM) and subsequent corrections (non-Poisson MKM and modified MKM)

Objective. To investigate similarities and differences in the formalism, processing, and the results of relative biological effectiveness (RBE) calculations with a biological weighting function (BWF), the microdosimetric kinetic model (MKM) and subsequent modifications (non-Poisson MKM, modified MKM). This includes: (a) the extension of the V79-RBE10% BWF to model the RBE for other clonogenic survival levels; (b) a novel implementation of MKMs as weighting functions; (c) a benchmark against Chinese Hamster lung fibroblast (V79) in vitro data; (d) a study on the effect of pre- or post- processing the average biophysical quantities used for the RBE calculations; (e) a possible modification of the modified MKM parameters to improve the model accuracy at high linear energy transfer (LET). Methodology. Lineal energy spectra were simulated for two spherical targets (diameter = 0.464 or 1.0 μm) using PHITS for 1H, 4He, 12C, 20Ne, 40Ar, 56Fe and 132Xe ions. The results of the in silico calculations were compared with published in vitro data. Main results. All models appear to underestimate the RBE α of hydrogen ions. All MKMs generally overestimate the RBE50%, RBE10% and RBE1% for ions with an LET greater than ∼200 keV μm−1. This overestimation is greater for small surviving fractions and is likely due to the assumption of a radiation-independent quadratic term of clonogenic survival (ß). The overall RBE trends seem to be best described by the novel ‘post-processing average’ implementation of the non-Poisson MKM. In case of calculations with the non-Poisson MKM, pre- or post- processing the average biophysical quantities affects the computed RBE values significantly. Significance. This study presents a systematic analysis of the formalism and results of widely used microdosimetric models of clonogenic survival for ions relevant for cancer particle therapy and space radiation protection. Points for improvements were highlighted and will contribute to the development of upgraded biophysical models.

Estimate of the Biological Dose in Hadrontherapy Using GATE

Simple Summary

This study presents the implementation of a biological dose module using the Monte Carlo software, GATE. Both mMKM and NanOx biophysics models of cell survival predictions were used as input. The code was validated in terms of biological dose, relative biological effectiveness and cell survival against experimental data from the HIMBC (Hyogo, Japan) ion beam line.

Abstract

For the evaluation of the biological effects, Monte Carlo toolkits were used to provide an RBE-weighted dose using databases of survival fraction coefficients predicted through biophysical models. Biophysics models, such as the mMKM and NanOx models, have previously been developed to estimate a biological dose. Using the mMKM model, we calculated the saturation corrected dose mean specific energy z1D* (Gy) and the dose at 10% D₁₀ for human salivary gland (HSG) cells using Monte Carlo Track Structure codes LPCHEM and Geant4-DNA, and compared these with data from the literature for monoenergetic ions. These two models were used to create databases of survival fraction coefficients for several ion types (hydrogen, carbon, helium and oxygen) and for energies ranging from 0.1 to 400 MeV/n. We calculated α values as a function of LET with the mMKM and the NanOx models, and compared these with the literature. In order to estimate the biological dose for SOBPs, these databases were used with a Monte Carlo toolkit. We considered GATE, an open-source software based on the GEANT4 Monte Carlo toolkit. We implemented a tool, the BioDoseActor, in GATE, using the mMKM and NanOx databases of cell survival predictions as input, to estimate, at a voxel scale, biological outcomes when treating a patient. We modeled the HIBMC 320 MeV/u carbon-ion beam line. We then tested the BioDoseActor for the estimation of biological dose, the relative biological effectiveness (RBE) and the cell survival fraction for the irradiation of the HSG cell line. We then tested the implementation for the prediction of cell survival fraction, RBE and biological dose for the HIBMC 320 MeV/u carbon-ion beamline. For the cell survival fraction, we obtained satisfying results. Concerning the prediction of the biological dose, a 10% relative difference between mMKM and NanOx was reported.

DNA Damage Clustering after Ionizing Radiation and Consequences in the Processing of Chromatin Breaks

Charged-particle radiotherapy (CPRT) utilizing low and high linear energy transfer (low-/high-LET) ionizing radiation (IR) is a promising cancer treatment modality having unique physical energy deposition properties. CPRT enables focused delivery of a desired dose to the tumor, thus achieving a better tumor control and reduced normal tissue toxicity. It increases the overall radiation tolerance and the chances of survival for the patient. Further improvements in CPRT are expected from a better understanding of the mechanisms governing the biological effects of IR and their dependence on LET. There is increasing evidence that high-LET IR induces more complex and even clustered DNA double-strand breaks (DSBs) that are extremely consequential to cellular homeostasis, and which represent a considerable threat to genomic integrity. However, from the perspective of cancer management, the same DSB characteristics underpin the expected therapeutic benefit and are central to the rationale guiding current efforts for increased implementation of heavy ions (HI) in radiotherapy. Here, we review the specific cellular DNA damage responses (DDR) elicited by high-LET IR and compare them to those of low-LET IR. We emphasize differences in the forms of DSBs induced and their impact on DDR. Moreover, we analyze how the distinct initial forms of DSBs modulate the interplay between DSB repair pathways through the activation of DNA end resection. We postulate that at complex DSBs and DSB clusters, increased DNA end resection orchestrates an increased engagement of resection-dependent repair pathways. Furthermore, we summarize evidence that after exposure to high-LET IR, error-prone processes outcompete high fidelity homologous recombination (HR) through mechanisms that remain to be elucidated. Finally, we review the high-LET dependence of specific DDR-related post-translational modifications and the induction of apoptosis in cancer cells. We believe that in-depth characterization of the biological effects that are specific to high-LET IR will help to establish predictive and prognostic signatures for use in future individualized therapeutic strategies, and will enhance the prospects for the development of effective countermeasures for improved radiation protection during space travel.