Track structures, DNA targets and radiation effects in the biophysical Monte Carlo simulation code PARTRAC

Development of a novel computational technique to create DNA and cell geometrical models for Geant4-DNA

BACKGROUND

This study aimed to develop a novel human cell geometry for the Geant4-DNA simulation toolkit that explicitly incorporates all 23 chromosome pairs of the human cell. This approach contrasts with the existing, default human cell, geometrical model, which utilizes a continuous Hilbert curve.

METHODS

A Python-based tool named "complexDNA" was developed to facilitate the design of both simple and complex DNA geometries. This tool was employed to construct a human cell geometry with individual pairs of chromosomes. Subsequently, the performance of this chromosomal model was compared to the standard human cell model provided in the "molecularDNA" Geant4-DNA example.

RESULTS

Simulations using the new chromosomal model revealed minimal discrepancies in DNA damage yield and fragment size distribution compared to the default human cell model. Notably, the chromosomal model demonstrated significant computational efficiency, requiring approximately three times less simulation time to achieve equivalent results.

CONCLUSIONS

This work highlights the importance of incorporating chromosomal structure into human cell models for radiation biology research. The "complexDNA" tool offers a valuable resource for creating intricate DNA structures for future studies. Further refinements, such as implementing smaller voxels for euchromatin regions, are proposed to enhance the model's accuracy.

Significant role of secondary electrons in the formation of a multi-body chemical species spur produced by water radiolysis

Scientific insights into water photolysis and radiolysis are essential for estimating the direct and indirect effects of deoxyribonucleic acid (DNA) damage. Secondary electrons from radiolysis intricately associated with both effects. In our previous paper, we simulated the femtosecond (1 × 10- 15 s) dynamics of secondary electrons ejected by energy depositions of 11-19 eV into water via high-energy electron transport using a time-dependent simulation code. The results contribute to the understanding of simple "intra-spur" chemical reactions of tree-body chemical species (hydrated electrons, hydronium ion and OH radical) in subsequent chemical processes. Herein, we simulate the dynamics of the electrons ejected by energy depositions of 20-30 eV. The present results contribute to the understanding of complex "inter-spur" chemical reactions of the multi-body chemical species as well as for the formation of complex DNA damage with redox site and strand break on DNA. The simulation results present the earliest formation mechanism of an unclear multi-body chemical species spur when secondary electrons induce further ionisations or electronic excitations. The formation involves electron-water collisions, i.e. ionisation, electronic excitation, molecular excitation and elastic scattering. Our simulation results indicate that (1) most secondary electrons delocalise to ~ 12 nm, and multiple collisions are sometimes induced in a water molecule at 22 eV deposition energy. (2) The secondary electrons begin to induce diffuse band excitation of water around a few nm from the initial energy deposition site and delocalise to ~ 8 nm at deposition energies ~ 25 eV. (3) The secondary electron can cause one additional ionisation or electronic excitation at deposition energies > 30 eV, forming a multi-body chemical species spur. Thus, we propose that the type and density of chemical species produced by water radiolysis strongly depend on the deposition energy. From our results, we discuss formation of complex DNA damage.

Liquid water radiolysis induced by secondary electrons generated from MeV-energy carbon ions

Fast ion beams induce damage to deoxyribonucleic acid (DNA) by chemical products, including secondary electrons, produced from interaction with liquid water in living cells. However, the production process of these chemical products in the Bragg peak region used in particle therapy is not fully understood. To investigate this process, we conducted experiments to evaluate the radiolytic yields produced when a liquid water jet in vacuum is irradiated with MeV-energy carbon beams. We used secondary ion mass spectrometry to measure the products, such as hydronium cations (H3O+) and hydroxyl anions (OH-), produced along with ·OH radicals, which are significant inducers of DNA damage formation. In addition, we simulated the ionization process in liquid water by incident ions and secondary electrons using a Monte Carlo code for radiation transport. Our results showed that secondary electrons, rather than incident ions, are the primary cause of ionization in water. We found that the production yield of H3O+ or OH- was linked to the frequency of ionization by secondary electrons in water, with these electrons having energies between 10.9 and 550 eV. These electrons are responsible for ionizing the outer-shell electrons of water molecules. Finally, we present that the elementary processes contribute to advancing radiation biophysics and biochemistry, which study the formation mechanism of DNA damage.

Monte Carlo investigation of the nucleus size effect and cell's oxygen content on the damage efficiency of protons

Living tissues could suffer different types of DNA damage as a result of being exposed to ionizing radiations. Monte Carlo simulations of the underlying interactions have been instrumental in predicting the damage types and the processes involved. In this work, we employed Geant4-DNA and MCDS for extracting the initial DNA damage and investigating the dependence of damage efficiency on the cell's oxygen content. The frequency-mean lineal (y¯F) and specific (z¯F) energies were derived for a spherical volume of water of various diameters between 2 and 11.1 μm. This sphere would serve as the nucleus of a cell of 100 μm diameter, engulfed by a homogeneous beam of protons. These microdosimetric quantities were calculated assuming spherical samples of 1 μm diameter in MCDS. The simulation results showed that for 230 MeV protons, an increase in the oxygen content from 0 by 10% raised the frequency of single- and double-strand breaks and lowered the base damage frequency. The resulting damage frequencies appeared to be independent of nucleus diameter. For proton energies between 2 and 230 MeV,y¯Fshowed no dependence on the cell diameter and an increase of the cell size resulted in a decrease inz¯F.An increase in the proton energy slowed down the decreasing rate ofz¯Fas a function of nucleus diameter. However, the ratio ofy¯Fvalues corresponding to two proton energies of choice showed no dependence on the nucleus size and were equal to the ratio of the correspondingz¯Fvalues. Furthermore, the oxygen content of the cell did not affect these microdosimetric quantities. Contrary to damage frequencies, these quantities appeared to depend only on direct interactions due to deposited energies. Our calculations showed the near independence of DNA damages on the nucleus size of the human cells. The probabilities of different types of single and double-strand breaks increase with the oxygen content.

Modelling radiobiology

Radiotherapy has played an essential role in cancer treatment for over a century, and remains one of the best-studied methods of cancer treatment. Because of its close links with the physical sciences, it has been the subject of extensive quantitative mathematical modelling, but a complete understanding of the mechanisms of radiotherapy has remained elusive. In part this is because of the complexity and range of scales involved in radiotherapy-from physical radiation interactions occurring over nanometres to evolution of patient responses over months and years. This review presents the current status and ongoing research in modelling radiotherapy responses across these scales, including basic physical mechanisms of DNA damage, the immediate biological responses this triggers, and genetic- and patient-level determinants of response. Finally, some of the major challenges in this field and potential avenues for future improvements are also discussed.

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.

Modelling DNA damage-repair and beyond

The paper presents a review of mechanistic modelling studies of DNA damage and DNA repair, and consequences to follow in mammalian cell nucleus. We hypothesize DNA deletions are consequences of repair of double strand breaks leading to the modifications of genome that play crucial role in long term development of genetic inheritance and diseases. The aim of the paper is to review formation mechanisms underlying naturally occurring DNA deletions in the human genome and their potential relevance for bridging the gap between induced DNA double strand breaks and deletions in damaged human genome from endogenous and exogenous events. The model of the cell nucleus presented enables simulation of DNA damage at molecular level identifying the spectrum of damage induced in all chromosomal territories and loops. Our mechanistic modelling of DNA repair for double stand breaks (DSB), single strand breaks (SSB) and base damage (BD), shows the complexity of DNA damage is responsible for the longer repair times and the reason for the biphasic feature of mammalian cells repair curves. In the absence of experimentally determined data, the mechanistic model of repair predicts the in vivo rate constants for the proteins involved in the repair of DSB, SSB, and of BD.

Clustered DNA Damage and its Complexity: Tracking the History

The concept of radiation-induced clustered damage in DNA has grown over the past several decades to become a topic of considerable interest across the scientific disciplines involved in studies of the biological effects of ionizing radiation. This paper, prepared for the 70th anniversary issue of Radiation Research, traces historical development of the three main threads of physics, chemistry, and biochemical/cellular responses that led to the hypothesis and demonstration that a key component of the biological effectiveness of ionizing radiation is its characteristic of producing clustered DNA damage of varying complexities. The physics thread has roots that started as early as the 1920s, grew to identify critical nanometre-scale clusterings of ionizations relevant to biological effectiveness, and then, by the turn of the century, had produced an extensive array of quantitative predictions on the complexity of clustered DNA damage from different radiations. Monte Carlo track structure simulation techniques played a key role through these developments, and they are now incorporated into many recent and ongoing studies modelling the effects of radiation. The chemistry thread was seeded by water-radiolysis descriptions of events in water as radical-containing "spurs," demonstration of the important role of the hydroxyl radical in radiation-inactivation of cells and the difficulty of protection by radical scavengers. This led to the concept and description of locally multiply damaged sites (LMDS) for DNA double-strand breaks and other combinations of DNA base damage and strand breakage that could arise from a spur overlapping, or created in very close proximity to, the DNA. In these ways, both the physics and the chemistry threads, largely in parallel, put out the challenge to the experimental research community to verify these predictions of clustered DNA damage from ionizing radiations and to investigate their relevance to DNA repair and subsequent cellular effects. The third thread, biochemical and cell-based research, responded strongly to the challenge by demonstrating the existence and biological importance of clustered DNA damage. Investigations have included repair of a wide variety of defined constructs of clustered damage, evaluation of mutagenic consequences, identification of clustered base-damage within irradiated cells, and identification of co-localization of repair complexes indicative of complex clustered damage after high-LET irradiation, as well as extensive studies of the repair pathways involved in repair of simple double-strand breaks. There remains, however, a great deal more to be learned because of the diversity of clustered DNA damage and of the biological responses.

"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.

Modelling Cellular Response to Ionizing Radiation: Mechanistic, Semi-Mechanistic, and Phenomenological Approaches - A Historical Perspective

Radiation research is a multidisciplinary field, and among its many branches, mathematical and computational modelers have played a significant role in advancing boundaries of knowledge. A fundamental contribution is modelling cellular response to ionizing radiation as that is the key to not only understanding how radiation can kill cancer cells, but also cause cancer and other health issues. The invention of microdosimetry in the 1950s by Harold Rossi paved the way for brilliant scientists to study the mechanism of radiation at cellular and sub-cellular scales. This paper reviews some snippets of ingenious mathematical and computational models published in microdosimetry symposium proceedings and publications of the radiation research community. Among these are simulations of radiation tracks at atomic and molecular levels using Monte Carlo methods, models of cell survival, quantification of the amount of energy required to create a single strand break, and models of DNA-damage-repair. These models can broadly be categorized into mechanistic, semi-mechanistic, and phenomenological approaches, and this review seeks to provide historical context of their development. We salute pioneers of the field and great teachers who supported and educated the younger members of the community and showed them how to build upon their work.

Lithium inelastic cross-sections and their impact on micro and nano dosimetry of boron neutron capture

Objective.To present a new set of lithium-ion cross-sections for (i) ionization and excitation processes down to 700 eV, and (ii) charge-exchange processes down to 1 keV u-1. To evaluate the impact of the use of these cross-sections on micro a nano dosimetric quantities in the context of boron neutron capture (BNC) applications/techniques.Approach.The Classical Trajectory Monte Carlo method was used to calculate Li ion charge-exchange cross sections in the energy range of 1 keV u-1to 10 MeV u-1. Partial Li ion charge states ionization and excitation cross-sections were calculated using a detailed charge screening factor. The cross-sections were implemented in Geant4-DNA v10.07 and simulations and verified using TOPAS-nBio by calculating stopping power and continuous slowing down approximation (CSDA) range against data from ICRU and SRIM. Further microdosimetric and nanodosimetric calculations were performed to quantify differences against other simulation approaches for low energy Li ions. These calculations were: lineal energy spectra (yf(y) andyd(y)), frequency mean lineal energyyF-, dose mean lineal energyyD-and ionization cluster size distribution analysis. Microdosimetric calculations were compared against a previous MC study that neglected charge-exchange and excitation processes. Nanodosimetric results were compared against pure ionization scaled cross-sections calculations.Main results.Calculated stopping power differences between ICRU and Geant4-DNA decreased from 33.78% to 6.9%. The CSDA range difference decreased from 621% to 34% when compared against SRIM calculations. Geant4-DNA/TOPAS calculated dose mean lineal energy differed by 128% from the previous Monte Carlo. Ionization cluster size frequency distributions for Li ions differed by 76%-344.11% for 21 keV and 2 MeV respectively. With a decrease in theN1within 9% at 10 keV and agreeing after the 100 keV. With the new set of cross-sections being able to better simulate low energy behaviors of Li ions.Significance.This work shows an increase in detail gained from the use of a more complete set of low energy cross-sections which include charge exchange processes. Significant differences to previous simulation results were found at the microdosimetric and nanodosimetric scales that suggest that Li ions cause less ionizations per path length traveled but with more energy deposits. Microdosimetry results suggest that the BNC's contribution to cellular death may be mainly due to alpha particle production when boron-based drugs are distributed in the cellular membrane and beyond and by Li when it is at the cell cytoplasm regions.

Condensed Matter Systems Exposed to Radiation: Multiscale Theory, Simulations, and Experiment

This roadmap reviews the new, highly interdisciplinary research field studying the behavior of condensed matter systems exposed to radiation. The Review highlights several recent advances in the field and provides a roadmap for the development of the field over the next decade. Condensed matter systems exposed to radiation can be inorganic, organic, or biological, finite or infinite, composed of different molecular species or materials, exist in different phases, and operate under different thermodynamic conditions. Many of the key phenomena related to the behavior of irradiated systems are very similar and can be understood based on the same fundamental theoretical principles and computational approaches. The multiscale nature of such phenomena requires the quantitative description of the radiation-induced effects occurring at different spatial and temporal scales, ranging from the atomic to the macroscopic, and the interlinks between such descriptions. The multiscale nature of the effects and the similarity of their manifestation in systems of different origins necessarily bring together different disciplines, such as physics, chemistry, biology, materials science, nanoscience, and biomedical research, demonstrating the numerous interlinks and commonalities between them. This research field is highly relevant to many novel and emerging technologies and medical applications.

14-3-3σ downregulation sensitizes pancreatic cancer to carbon ions by suppressing the homologous recombination repair pathway

This study explored the role of 14-3-3σ in carbon ion-irradiated pancreatic adenocarcinoma (PAAD) cells and xenografts and clarified the underlying mechanism. The clinical significance of 14-3-3σ in patients with PAAD was explored using publicly available databases. 14-3-3σ was silenced or overexpressed and combined with carbon ions to measure cell proliferation, cell cycle, and DNA damage repair. Immunoblotting and immunofluorescence (IF) assays were used to determine the underlying mechanisms of 14-3-3σ toward carbon ion radioresistance. We used the BALB/c mice to evaluate the biological behavior of 14-3-3σ in combination with carbon ions. Bioinformatic analysis revealed that PAAD expressed higher 14-3-3σ than normal pancreatic tissues; its overexpression was related to invasive clinicopathological features and a worse prognosis. Knockdown or overexpression of 14-3-3σ demonstrated that 14-3-3σ promoted the survival of PAAD cells after carbon ion irradiation. And 14-3-3σ was upregulated in PAAD cells during DNA damage (carbon ion irradiation, DNA damaging agent) and promotes cell recovery. We found that 14-3-3σ resulted in carbon ion radioresistance by promoting RPA2 and RAD51 accumulation in the nucleus in PAAD cells, thereby increasing homologous recombination repair (HRR) efficiency. Blocking the HR pathway consistently reduced 14-3-3σ overexpression-induced carbon ion radioresistance in PAAD cells. The enhanced radiosensitivity of 14-3-3σ depletion on carbon ion irradiation was also demonstrated in vivo. Altogether, 14-3-3σ functions in tumor progression and can be a potential target for developing biomarkers and treatment strategies for PAAD along with incorporating carbon ion irradiation.

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.

Radium deposition in human brain tissue: A Geant4-DNA Monte Carlo toolkit study

NASA has encouraged studies on 226Ra deposition in the human brain to investigate the effects of exposure to alpha particles with high linear energy transfer, which could mimic some of the exposure astronauts face during space travel. However, this approach was criticized, noting that radium is a bone-seeker and accumulates in the skull, which means that the radiation dose from alpha particles emitted by 226Ra would be heavily concentrated in areas close to cranial bones rather than uniformly distributed throughout the brain. In the high background radiation areas of Ramsar, Iran, extremely high levels of 226Ra in soil contribute to a large proportion of the inhabitants' radiation exposure. A prospective study on Ramsar residents with a calcium-rich diet was conducted to improve the dose uniformity due to 226Ra throughout the cerebral and cerebellar parenchyma. The study found that exposure of the human brain to alpha particles did not significantly affect working memory but was significantly associated with increased reaction times. This finding is crucial because astronauts on deep space missions may face similar cognitive impairments due to exposure to high charge and energy particles. The current study was aimed to evaluate the validity of the terrestrial model using the Geant4 Monte Carlo toolkit to simulate the interactions of alpha particles and representative cosmic ray particles, acknowledging that these radiation types are only a subset of the complete space radiation environment.

Enhanced RBE of Particle Radiation Depends on Beam Size in the Micrometer Range

High-linear energy transfer (LET) radiation, such as heavy ions is associated with a higher relative biological effectiveness (RBE) than low-LET radiation, such as photons. Irradiation with low- and high-LET particles differ in the interaction with the cellular matter and therefore in the spatial dose distribution. When a single high-LET particle interacts with matter, it results in doses of up to thousands of gray (Gy) locally concentrated around the ion trajectory, whereas the mean dose averaged over the target, such as a cell nucleus is only in the range of a Gy. DNA damage therefore accumulates in this small volume. In contrast, up to hundreds of low-LET particle hits are required to achieve the same mean dose, resulting in a quasi-homogeneous damage distribution throughout the cell nucleus. In this study, we investigated the dependence of RBE from different spatial dose depositions using different focused beam spot sizes of proton radiation with respect to the induction of chromosome aberrations and clonogenic cell survival. Human-hamster hybrid (AL) as well as Chinese hamster ovary cells (CHO-K1) were irradiated with focused low LET protons of 20 MeV (LET = 2.6 keV/µm) beam energy with a mean dose of 1.7 Gy in a quadratic matrix pattern with point spacing of 5.4 × 5.4 µm2 and 117 protons per matrix point at the ion microbeam SNAKE using different beam spot sizes between 0.8 µm and 2.8 µm (full width at half maximum). The dose-response curves of X-ray reference radiation were used to determine the RBE after a 1.7 Gy dose of radiation. The RBE for the induction of dicentric chromosomes and cell inactivation was increased after irradiation with the smallest beam spot diameter (0.8 µm for chromosome aberration experiments and 1.0 µm for cell survival experiments) compared to homogeneous proton radiation but was still below the RBE of a corresponding high LET single ion hit. By increasing the spot size to 1.6-1.8 µm, the RBE decreased but was still higher than for homogeneously distributed protons. By further increasing the spot size to 2.7-2.8 µm, the RBE was no longer different from the homogeneous radiation. Our experiments demonstrate that varying spot size of low-LET radiation gradually modifies the RBE. This underlines that a substantial fraction of enhanced RBE originates from inhomogeneous energy concentrations on the µm scale (mean intertrack distances of low-LET particles below 0.1 µm) and quantifies the link between such energy concentration and RBE. The missing fraction of RBE enhancement when comparing with high-LET ions is attributed to the high inner track energy deposition on the nanometer scale. The results are compared with model results of PARTRAC and LEM for chromosomal aberration and cell survival, respectively, which suggest mechanistic interpretations of the observed radiation effects.

Mechanistic modelling of relative biological effectiveness of carbon ion beams and comparison with experiments

Objective.Relative biological effectiveness (RBE) plays a vital role in carbon ion radiotherapy, which is a promising treatment method for reducing toxic effects on normal tissues and improving treatment efficacy. It is important to have an effective and precise way of obtaining RBE values to support clinical decisions. A method of calculating RBE from a mechanistic perspective is reported.Approach.Ratio of dose to obtain the same number of double strand breaks (DSBs) between different radiation types was used to evaluate RBE. Package gMicroMC was used to simulate DSB yields. The DSB inductions were then analyzed to calculate RBE. The RBE values were compared with experimental results.Main results.Furusawa's experiment yielded RBE values of 1.27, 2.22, 3.00 and 3.37 for carbon ion beam with dose-averaged LET of 30.3 keVμm-1, 54.5 keVμm-1, 88 keVμm-1and 137 keVμm-1, respectively. RBE values computed from gMicroMC simulations were 1.75, 2.22, 2.87 and 2.97. When it came to a more sophisticated carbon ion beam with 6 cm spread-out Bragg peak, RBE values were 1.61, 1.63, 2.19 and 2.36 for proximal, middle, distal and distal end part, respectively. Values simulated by gMicroMC were 1.50, 1.87, 2.19 and 2.34. The simulated results were in reasonable agreement with the experimental data.Significance.As a mechanistic way for the evaluation of RBE for carbon ion radiotherapy by combining the macroscopic simulation of energy spectrum and microscopic simulation of DNA damages, this work provides a promising tool for RBE calculation supporting clinical applications such as treatment planning.

DNA break clustering as a predictor of cell death across various radiation qualities: influence of cell size, cell asymmetry, and beam orientation

Cosmic radiation, composed of high charge and energy (HZE) particles, causes cellular DNA damage that can result in cell death or mutation that can evolve into cancer. In this work, a cell death model is applied to several cell lines exposed to HZE ions spanning a broad range of linear energy transfer (LET) values. We hypothesize that chromatin movement leads to the clustering of multiple double strand breaks (DSB) within one radiation-induced foci (RIF). The survival probability of a cell population is determined by averaging the survival probabilities of individual cells, which is function of the number of pairwise DSB interactions within RIF. The simulation code RITCARD was used to compute DSB. Two clustering approaches were applied to determine the number of RIF per cell. RITCARD outputs were combined with experimental data from four normal human cell lines to derive the model parameters and expand its predictions in response to ions with LET ranging from ~0.2 keV/μm to ~3000 keV/μm. Spherical and ellipsoidal nuclear shapes and two ion beam orientations were modeled to assess the impact of geometrical properties on cell death. The calculated average number of RIF per cell reproduces the saturation trend for high doses and high-LET values that is usually experimentally observed. The cell survival model generates the recognizable bell shape of LET dependence for the relative biological effectiveness (RBE). At low LET, smaller nuclei have lower survival due to increased DNA density and DSB clustering. At high LET, nuclei with a smaller irradiation area-either because of a smaller size or a change in beam orientation-have a higher survival rate due to a change in the distribution of DSB/RIF per cell. If confirmed experimentally, the geometric characteristics of cells would become a significant factor in predicting radiation-induced biological effects. Insight Box: High-charge and energy (HZE) ions are characterized by dense linear energy transfer (LET) that induce unique spatial distributions of DNA damage in cell nuclei that result in a greater biological effect than sparsely ionizing radiation like X-rays. HZE ions are a prominent component of galactic cosmic ray exposure during human spaceflight and specific ions are being used for radiotherapy. Here, we model DNA damage clustering at sub-micrometer scale to predict cell survival. The model is in good agreement with experimental data for a broad range of LET. Notably, the model indicates that nuclear geometry and ion beam orientation affect DNA damage clustering, which reveals their possible role in mediating cell radiosensitivity.

A step-by-step simulation code for estimating yields of water radiolysis species based on electron track-structure mode in the PHITS code

Objective. Time-dependent yields of chemical products resulting from water radiolysis play a great role in evaluating DNA damage response after exposure to ionizing radiation. Particle and Heavy Ion Transport code System (PHITS) is a general-purpose Monte Carlo simulation code for radiation transport, which simulates atomic interactions originating from discrete energy levels of ionizations and electronic excitations as well as molecular excitations as physical stages. However, no chemical code for simulating water radiolysis products exists in the PHITS package.Approach.Here, we developed a chemical simulation code dedicated to the PHITS code, hereafter calledPHITS-Chemcode, which enables the calculation of theGvalues of water radiolysis species (•OH, eaq-, H2, H2O2etc) by electron beams.Main results.The estimatedGvalues during 1 μs are in agreement with the experimental ones and other simulations. ThisPHITS-Chemcode also simulates the radiolysis in the presence of OH radical scavengers, such as tris(hydroxymethyl)aminomethane and dimethyl sulfoxide. Thank to this feature, the contributions of direct and indirect effects on DNA damage induction under various scavenging capacities can be analyzed.Significance.This chemical code coupled with PHITS could contribute to elucidating the mechanism of radiation effects by connecting physical, physicochemical, and chemical processes.

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.

Use of Gaussian-Type Functions for Describing Fast Ion-Matter Irradiation with Time-Dependent Density Functional Theory

The electronic stopping power is an observable property that quantifies the ability of swift ions to penetrate matter to transfer energy to the electron cloud. The recent literature has proven the value of Real-Time Time-Dependent Density Functional Theory to accurately evaluate this property from first-principles, but questions remain regarding the capability of computer codes relying on atom-centered basis functions to capture the physics at play. In this Perspective, we draw attention to the fact that irradiation by swift ions triggers electron emission into the continuum, especially at the Bragg peak. We investigate the ability of Gaussian atomic orbitals (AOC), which were fitted to mimic continuum wave functions, to improve electronic stopping power predictions. AOC are added to standard correlation-consistent basis sets or STO minimal basis sets. Our benchmarks for water irradiation by fast protons clearly advocate for the use of AOC, especially near the Bragg peak. We show that AOC only need to be placed on the molecules struck by the ion. The number of AOC that are added to the usual basis set is relatively small compared to the total number of atomic orbitals, making the use of such a basis set an excellent choice from a computational cost point of view. The optimum basis set combination is applied for the calculation of the stopping power of a proton in water with encouraging agreement with experimental data.

DNA damage by radiation as a function of electron energy and interaction at the atomic level with Monte Carlo simulation

In radiotherapy, X-ray or heavy ion beams target tumors to cause damage to their cell DNA. This damage is mainly induced by secondary low energy electrons. In this paper, we report the DNA molecular breaks at the atomic level as a function of electron energy and types of electron interactions using of Monte Carlo simulation. The number of DNA single and double strand breaks are compared to those from experimental results based on electron energies. In recent years, DNA atomistic models were introduced but still the simulations consider energy deposition in volumes of DNA or water equivalent material. We simulated a model of atomistic B-DNA in vacuum, forming 1122 base pairs of 30 nm in length. Each atom has been represented by a sphere whose radius equals the radius of van der Waals. We repeatedly simulated 10 million electrons for each energy from 4 eV to 500 eV and counted each interaction type with its position x, y, z in the volume of DNA. Based on the number and types of interactions at the atomic level, the number of DNA single and double strand breaks were calculated. We found that the dissociative electron attachment has the dominant effect on DNA strand breaks at energies below 10 eV compared to excitation and ionization. In addition, it is straightforward with our simulation to discriminate the strand and base breaks as a function of radiation interaction type and energy. In conclusion, the knowledge of DNA damage at the atomic level helps design direct internal therapeutic agents of cancer treatment.

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.

Estimation of relative biological effectiveness of 225Ac compared to 177Lu during [225Ac]Ac-PSMA and [177Lu]Lu-PSMA radiopharmaceutical therapy using TOPAS/TOPAS-nBio/MEDRAS

AIM

Over recent years, [225Ac]Ac-PSMA and [177Lu]Lu-PSMA radiopharmaceutical therapy have evolved as a promising treatment option for advanced prostate cancer. Especially for alpha particle emitter treatments, there is still a need for improving dosimetry, which requires accurate values of relative biological effectiveness (RBE). To achieve that, consideration of DNA damages in the cell nucleus and knowledge of the energy deposition in the location of the DNA at the nanometer scale are required. Monte Carlo particle track structure simulations provide access to interactions at this level. The aim of this study was to estimate the RBE of 225Ac compared to 177Lu. The initial damage distribution after radionuclide decay and the residual damage after DNA repair were considered.

METHODS

This study employed the TOol for PArtcile Simulation (TOPAS) based on the Geant4 simulation toolkit. Simulation of the nuclear DNA and damage scoring were performed using the TOPAS-nBio extension of TOPAS. DNA repair was modeled utilizing the Python-based program MEDRAS (Mechanistic DNA Repair and Survival). Five different cell geometries of equal volume and two radionuclide internalization assumptions as well as two cell arrangement scenarios were investigated. The radionuclide activity (number of source points) was adopted based on SPECT images of patients undergoing the above-mentioned therapies.

RESULTS

Based on the simulated dose-effect curves, the RBE of 225Ac compared to 177Lu was determined in a wide range of absorbed doses to the nucleus. In the case of spherical geometry, 3D cell arrangement and full radionuclide internalization, the RBE based on the initial damage had a constant value of approximately 2.14. Accounting for damage repair resulted in RBE values ranging between 9.38 and 1.46 for 225Ac absorbed doses to the nucleus between 0 and 50 Gy, respectively.

CONCLUSION

In this work, the consideration of DNA repair of the damage from [225Ac]Ac-PSMA and [177Lu]Lu-PSMA revealed a dose dependency of the RBE. Hence, this work suggested that DNA repair is an important aspect to understand response to different radiation qualities.

Evaluation of the Yield of DNA Double-Strand Breaks for Carbon Ions Using Monte Carlo Simulation and DNA Fragment Distribution

PURPOSE

The aim of this work was to provide a method to evaluate the yield of DNA double-strand breaks (DSBs) for carbon ions, overcoming the bias in existing methods due to the nonrandom distribution of DSBs.

METHODS AND MATERIALS

A previously established biophysical program based on the radiation track structure and a multilevel chromosome model was used to simulate DNA damage induced by x-rays and carbon ions. The fraction of activity retained (FAR) as a function of absorbed dose or particle fluence was obtained by counting the fraction of DNA fragments larger than 6 Mbp. Simulated FAR curves for the 250 kV x-rays and carbon ions at various energies were compared with measurements using constant-field gel electrophoresis. The doses or fluences at the FAR of 0.7 based on linear interpolation were used to estimate the simulation error for the production of DSBs.

RESULTS

The relative difference of doses at the FAR of 0.7 between simulation and experiment was -8.5% for the 250 kV x-rays. The relative differences of fluences at the FAR of 0.7 between simulations and experiments were -17.5%, -42.2%, -18.2%, -3.1%, 10.8%, and -14.5% for the 34, 65, 130, 217, 2232, and 3132 MeV carbon ions, respectively. In comparison, the measurement uncertainty was about 20%. Carbon ions produced remarkably more DSBs and DSB clusters per unit dose than x-rays. The yield of DSBs for carbon ions, ranging from 10 to 16 Gbp-1Gy-1, increased with linear energy transfer (LET) but plateaued in the high-LET end. The yield of DSB clusters first increased and then decreased with LET. This pattern was similar to the relative biological effectiveness for cell survival for heavy ions.

CONCLUSIONS

The estimated yields of DSBs for carbon ions increased from 10 Gbp-1Gy-1 in the low-LET end to 16 Gbp-1Gy-1 in the high-LET end with 20% uncertainty.

A new approach for simulating inhomogeneous chemical kinetics

In this paper, inhomogeneous chemical kinetics are simulated by describing the concentrations of interacting chemical species by a linear expansion of basis functions in such a manner that the coupled reaction and diffusion processes are propagated through time efficiently by tailor-made numerical methods. The approach is illustrated through modelling [Formula: see text]- and [Formula: see text]-radiolysis in thin layers of water and at their solid interfaces from the start of the chemical phase until equilibrium was established. The method's efficiency is such that hundreds of such systems can be modelled in a few hours using a single core of a typical laptop, allowing the investigation of the effects of the underlying parameter space. Illustrative calculations showing the effects of changing dose-rate and water-layer thickness are presented. Other simulations are presented which show the approach's capability to solve problems with spherical symmetry (an approximation to an isolated radiolytic spur), where the hollowing out of an initial Gaussian distribution is observed, in line with previous calculations. These illustrative simulations show the generality and the computational efficiency of this approach to solving reaction-diffusion problems. Furthermore, these example simulations illustrate the method's suitability for simulating solid-fluid interfaces, which have received a lot of experimental attention in contrast to the lack of computational studies.

Kinetics of radiation-induced DNA double-strand breaks through coarse-grained simulations

Double-strand breaks (DSBs), i.e., the covalent cut of the DNA backbone over both strands, are a detrimental outcome of cell irradiation, bearing chromosomal aberrations and leading to cell apoptosis. In the early stages of the evolution of a DSB, the disruption of the residual interactions between the DNA moieties drives the fracture of the helical layout; in spite of its biological significance, the details of this process are still largely uncertain. Here, we address the mechanical rupture of DNA by DSBs via coarse-grained molecular dynamics simulations: the setup involves a 3855-bp DNA filament and diverse DSB motifs, i.e., within a range of distances between strand breaks (or DSB distance). By employing a coarse-grained model of DNA, we access the molecular details and characteristic timescales of the rupturing process. A sequence-nonspecific, linear correlation is observed between the DSB distance and the internal energy contribution to the disruption of the residual (Watson-Crick and stacking) contacts between DNA moieties, which is seemingly driven by an abrupt, cooperative process. Moreover, we infer an exponential dependence of the characteristic rupture times on the DSB distances, which we associate to an Arrhenius-like law of thermally-activated processes. This work lays the foundations of a detailed, mechanistic assessment of DSBs in silico as a benchmark to both numerical simulations and data from single-molecule experiments.

The complexity of DNA damage by radiation follows a Gamma distribution: insights from the Microdosimetric Gamma Model

Introduction

DNA damage is the main predictor of response to radiation therapy for cancer. Its Q8 quantification and characterization are paramount for treatment optimization, particularly in advanced modalities such as proton and alpha-targeted therapy.

Methods

We present a novel approach called the Microdosimetric Gamma Model (MGM) to address this important issue. The MGM uses the theory of microdosimetry, specifically the mean energy imparted to small sites, as a predictor of DNA damage properties. MGM provides the number of DNA damage sites and their complexity, which were determined using Monte Carlo simulations with the TOPAS-nBio toolkit for monoenergetic protons and alpha particles. Complexity was used together with a illustrative and simplistic repair model to depict the differences between high and low LET radiations.

Results

DNA damage complexity distributions were were found to follow a Gamma distribution for all monoenergetic particles studied. The MGM functions allowed to predict number of DNA damage sites and their complexity for particles not simulated with microdosimetric measurements (yF) in the range of those studied.

Discussion

Compared to current methods, MGM allows for the characterization of DNA damage induced by beams composed of multi-energy components distributed over any time configuration and spatial distribution. The output can be plugged into ad hoc repair models that can predict cell killing, protein recruitment at repair sites, chromosome aberrations, and other biological effects, as opposed to current models solely focusing on cell survival. These features are particularly important in targeted alpha-therapy, for which biological effects remain largely uncertain. The MGM provides a flexible framework to study the energy, time, and spatial aspects of ionizing radiation and offers an excellent tool for studying and optimizing the biological effects of these radiotherapy modalities.

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.

Initial yield of hydrated electron production from water radiolysis based on first-principles calculation

Many scientific insights into water radiolysis have been applied for developing life science, including radiation-induced phenomena, such as DNA damage and mutation induction or carcinogenesis. However, the generation mechanism of free radicals due to radiolysis remains to be fully understood. Consequently, we have encountered a crucial problem in that the initial yields connecting radiation physics to chemistry must be parameterized. We have been challenged in the development of a simulation tool that can unravel the initial free radical yields, from physical interaction by radiation. The presented code enables the first-principles calculation of low energy secondary electrons resulting from the ionization, in which the secondary electron dynamics are simulated while considering dominant collision and polarization effects in water. In this study, using this code, we predicted the yield ratio between ionization and electronic excitation from a delocalization distribution of secondary electrons. The simulation result presented a theoretical initial yield of hydrated electrons. In radiation physics, the initial yield predicted from parameter analysis of radiolysis experiments in radiation chemistry was successfully reproduced. Our simulation code helps realize a reasonable spatiotemporal connection from radiation physics to chemistry, which would contribute to providing new scientific insights for precise understanding of underlying mechanisms of DNA damage induction.

Modeling of dose and linear energy transfer homogeneity in cell nuclei exposed to alpha particles under various setup conditions

PURPOSE

Different alpha exposure setups are often used to study the relation between biological responses and LET. This study aimed to estimate the dose heterogeneity and uncertainty in four exposure setups using Geant4 and PARTRAC codes. The importance of the irradiation system characteristics was shown in the context of reporting experimental results, especially in radiobiological studies at the molecular level.

MATERIALS AND METHODS

Geant4 was used to estimate the dose distributions in cells grown on a disk exposed to alpha particles penetrating from above and below. The latter setup was simulated without and with a collimator. PARTRAC was used for the validation of Geant4 simulations based on distributions of the number of alpha particles penetrating a round nucleus and the deposited energy.

RESULTS

The LET distributions obtained for simulated setups excluding the collimator were wide and non-Gaussian. Using a collimator resulted in a Gaussian LET distribution, but strongly reduced dose rate and dose homogeneity. Comparison between PARTRAC and Geant4 calculations for the cell nucleus exposed to alpha radiation showed an excellent agreement.

CONCLUSIONS

The interpretation of results from radiobiological experiments with alpha particles should always cover the characteristics of the experimental setup, which can be done precisely with computational methods.

Tritiated Steel Micro-Particles: Computational Dosimetry and Prediction of Radiation-Induced DNA Damage for In Vitro Cell Culture Exposures

Biological effects of radioactive particles can be experimentally investigated in vitro as a function of particle concentration, specific activity and exposure time. However, a careful dosimetric analysis is needed to elucidate the role of radiation emitted by radioactive products in inducing cyto- and geno-toxicity: the quantification of radiation dose is essential to eventually inform dose-risk correlations. This is even more fundamental when radioactive particles are short-range emitters and when they have a chemical speciation that might further concur to the heterogeneity of energy deposition at the cellular and sub-cellular level. To this aim, we need to use computational models. In this work, we made use of a Monte Carlo radiation transport code to perform a computational dosimetric reconstruction for in vitro exposure of cells to tritiated steel particles of micrometric size. Particles of this kind have been identified as worth of attention in nuclear power industry and research: tritium easily permeates in steel elements of nuclear reactor machinery, and mechanical operations on these elements (e.g., sawing) during decommissioning of old facilities can result in particle dispersion, leading to human exposure via inhalation. Considering the software replica of a representative in vitro setup to study the effect of such particles, we therefore modelled the radiation field due to the presence of particles in proximity of cells. We developed a computational approach to reconstruct the dose range to individual cell nuclei in contact with a particle, as well as the fraction of "hit" cells and the average dose for the whole cell population, as a function of particle concentration in the culture medium. The dosimetric analysis also provided the basis to make predictions on tritium-induced DNA damage: we estimated the dose-dependent expected yield of DNA double strand breaks due to tritiated steel particle radiation, as an indicator of their expected biological effectiveness.

Generation of Radioresistant Prostate Cancer Cells

The development of in vitro isogenic models of radioresistance through exposure to fractionated radiation is an increasingly used approach to investigate the mechanisms of radioresistance in cancer cells. Owing to the complex nature of the biological effect of ionizing radiation, the generation and validation of these models requires the careful consideration of radiation exposure protocols and cellular endpoints. This chapter presents a protocol we used to derive and characterize an isogenic model of radioresistant prostate cancer cells. This protocol may be applicable to other cancer cell lines.

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.

Electron tracks simulation in water: Performance comparison between GPU CPU and the EUMED grid installation

PURPOSE

We explored different technologies to minimize simulation time of the Monte-Carlo method for track generation following the Geant4-DNA processes for electrons in water.

METHODS

A GPU software tool is developed for electron track simulations. A similar CPU version is also developed using the same collision models. CPU simulations were carried out on a single user desktop computer and on the computing grid France Grilles using 10 and 100 computing nodes. Computing time results for CPU, GPU, and grid simulations are compared with those using Geant4-DNA processes.

RESULTS

The CPU simulations better performs when the number of electrons is less than 10⁴ with 100 eV initial energy, this number decreases as the energy increases. The GPU simulations gives better results when the number of electrons is more than 10⁴ with initial energy of 100 eV, this number decreases to 10³ for electrons with 10KeV and increases back with higher energy. The use of the grid introduces an additional queuing time which slows down the overall simulation performance. Thus, the Grid gives better performance when the number of electrons is over 10⁵ with initial energy of 10KeV, and this number decreases as the energy increases.

CONCLUSIONS

The CPU is best suited for small numbers of primary incident electrons. The GPU is best suited when the number of primary incident particles occupies sufficient resources on GPU card in order to get an important computing power. The grid is best suited for simulations with high number of primary incident electrons with high initial energy.

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.

Track Structure-Based Simulations on DNA Damage Induced by Diverse Isotopes

Diverse isotopes such as 2H, 3He, 10Be, 11C and 14C occur in nuclear reactions in ion beam radiotherapy, in cosmic ray shielding, or are intentionally accelerated in dating techniques. However, only a few studies have specifically addressed the biological effects of diverse isotopes and were limited to energies of several MeV/u. A database of simulations with the PARTRAC biophysical tool is presented for H, He, Li, Be, B and C isotopes at energies from 0.5 GeV/u down to stopping. The doses deposited to a cell nucleus and also the yields per unit dose of single- and double-strand breaks and their clusters induced in cellular DNA are predicted to vary among diverse isotopes of the same element at energies < 1 MeV/u, especially for isotopes of H and He. The results may affect the risk estimates for astronauts in deep space missions or the models of biological effectiveness of ion beams and indicate that radiation protection in 14C or 10Be dating techniques may be based on knowledge gathered with 12C or 9Be.

Application of a simple DNA damage model developed for electrons to proton irradiation

Proton beam therapy allows irradiating tumor volumes with reduced side effects on normal tissues with respect to conventional x-ray radiotherapy. Biological effects such as cell killing after proton beam irradiations depend on the proton kinetic energy, which is intrinsically related to early DNA damage induction. As such, DNA damage estimation based on Monte Carlo simulations is a research topic of worldwide interest. Such simulation is a mean of investigating the mechanisms of DNA strand break formations. However, past modellings considering chemical processes and DNA structures require long calculation times. Particle and heavy ion transport system (PHITS) is one of the general-purpose Monte Carlo codes that can simulate track structure of protons, meanwhile cannot handle radical dynamics simulation in liquid water. It also includes a simple model enabling the efficient estimation of DNA damage yields only from the spatial distribution of ionizations and excitations without DNA geometry, which was originally developed for electron track-structure simulations. In this study, we investigated the potential application of the model to protons without any modification. The yields of single-strand breaks, double-strand breaks (DSBs) and the complex DSBs were assessed as functions of the proton kinetic energy. The PHITS-based estimation showed that the DSB yields increased as the linear energy transfer (LET) increased, and reproduced the experimental and simulated yields of various DNA damage types induced by protons with LET up to about 30 keV μm−1. These results suggest that the current DNA damage model implemented in PHITS is sufficient for estimating DNA lesion yields induced after protons irradiation except at very low energies (below 1 MeV). This model contributes to evaluating early biological impacts in radiation therapy.

Exosome secretion and cellular response of DU145 and PC3 after exposure to alpha radiation

Exosomes are spherical membrane nanovesicles secreted from cells, and they play an important role in tumor immune response, metastasis, angiogenesis, and survival. Studies investigating exosomes isolated from cells exposed to photon radiation commonly used in conventional radiotherapy demonstrate the influence of this type of radiation on exosome characteristics and secretion. There is currently no research investigating the effects of densely ionizing particles such as protons and alpha radiation on exosomes. Thus we have evaluated the cellular response of human prostate cancer cells exposed to 0, 2, and 6 Gy of alpha radiation emitted from the Am-241 source. Irradiated PC3 and DU145 cell lines, characterized by differences in radiosensitivity, were studied using apoptosis, LDH, and IL-6 assays. Additionally, the corresponding concentration and size of isolated exosomes were measured using NTA. We found that exposure to ionizing radiation resulted in gross changes in viability and cell damage. There were increased amounts of apoptotic or necrotic cells as a function of radiation dose. We demonstrated that irradiated PC3 cells secrete higher quantities of exosomes compared to DU145 cells. Additionally, we also found no statistical difference in exosome size for control and irradiated cells.

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

The outcome of the exposure of living organisms to ionizing radiation is determined by the distribution of the associated energy deposition at different spatial scales. Radiation proceeds through ionizations and excitations of hit molecules with an ~ nm spacing. Approaches such as nanodosimetry/microdosimetry and Monte Carlo track-structure simulations have been successfully adopted to investigate radiation quality effects: they allow to explore correlations between the spatial clustering of such energy depositions at the scales of DNA or chromosome domains and their biological consequences at the cellular level. Physical features alone, however, are not enough to assess the entity and complexity of radiation-induced DNA damage: this latter is the result of an interplay between radiation track structure and the spatial architecture of chromatin, and further depends on the chromatin dynamic response, affecting the activation and efficiency of the repair machinery. The heterogeneity of radiation energy depositions at the single-cell level affects the trade-off between cell inactivation and induction of viable mutations and hence influences radiation-induced carcinogenesis. In radiation therapy, where the goal is cancer cell inactivation, the delivery of a homogenous dose to the tumour has been the traditional approach in clinical practice. However, evidence is accumulating that introducing heterogeneity with spatially fractionated beams (mini- and microbeam therapy) can lead to significant advantages, particularly in sparing normal tissues. Such findings cannot be explained in merely physical terms, and their interpretation requires considering the scales at play in the underlying biological mechanisms, suggesting a systemic response to radiation.

The high toxicity of DSB-clusters modelling high-LET-DNA damage derives from inhibition of c-NHEJ and promotion of alt-EJ and SSA despite increases in HR

Heavy-ion radiotherapy utilizing high linear energy transfer (high-LET) ionizing radiation (IR) is a promising cancer treatment modality owing to advantageous physical properties of energy deposition and associated toxicity over X-rays. Therapies utilizing high-LET radiation will benefit from a better understanding of the molecular mechanisms underpinning their increased biological efficacy. Towards this goal, we investigate here the biological consequences of well-defined clusters of DNA double-strand breaks (DSBs), a form of DNA damage, which on theoretical counts, has often been considered central to the enhanced toxicity of high-LET IR. We test clonal cell lines harboring in their genomes constructs with appropriately engineered I-SceI recognition sites that convert upon I-SceI expression to individual DSBs, or DSB-clusters comprising known numbers of DSBs with defined DNA-ends. We find that, similarly to high-LET IR, DSB-clusters of increasing complexity, i.e. increasing numbers of DSBs, with compatible or incompatible ends, compromise classical non-homologous end-joining, favor DNA end-resection and promote resection-dependent DSB-processing. Analysis of RAD51 foci shows increased engagement of error-free homologous recombination on DSB-clusters. Multicolor fluorescence in situ hybridization analysis shows that complex DSB-clusters markedly increase the incidence of structural chromosomal abnormalities (SCAs). Since RAD51-knockdown further increases SCAs-incidence, we conclude that homologous recombination suppresses SCAs-formation. Strikingly, CtIP-depletion inhibits SCAs-formation, suggesting that it relies on alternative end-joining or single-strand annealing. Indeed, ablation of RAD52 causes a marked reduction in SCAs, as does also inhibition of PARP1. We conclude that increased DSB-cluster formation that accompanies LET-increases, enhances IR-effectiveness by promoting DNA end-resection, which suppresses c-NHEJ and enhances utilization of alt-EJ or SSA. Although increased resection also favors HR, on balance, error-prone processing dominates, causing the generally observed increased toxicity of high-LET radiation. These findings offer new mechanistic insights into high-LET IR-toxicity and have translational potential in the clinical setting that may be harnessed by combining high-LET IR with inhibitors of PARP1 or RAD52.

Impact of the Lorentz force on electron track structure and early DNA damage yields in magnetic resonance-guided radiotherapy

Magnetic resonance-guided radiotherapy (MRgRT) has been developed and installed in recent decades for external radiotherapy in several clinical facilities. Lorentz forces modulate dose distribution by charged particles in MRgRT; however, the impact of Lorentz forces on low-energy electron track structure and early DNA damage induction remain unclear. In this study, we estimated features of electron track structure and biological effects in a static magnetic field (SMF) using a general-purpose Monte Carlo code, particle and heavy ion transport code system (PHITS) that enables us to simulate low-energy electrons down to 1 meV by track-structure mode. The macroscopic dose distributions by electrons above approximately 300 keV initial energy in liquid water are changed by both perpendicular and parallel SMFs against the incident direction, indicating that the Lorentz force plays an important role in calculating dose within tumours. Meanwhile, DNA damage estimation based on the spatial patterns of atomic interactions indicates that the initial yield of DNA double-strand breaks (DSBs) is independent of the SMF intensity. The DSB induction is predominantly attributed to the secondary electrons below a few tens of eV, of which energy deposition patterns are not considerably affected by the Lorentz force. Our simulation study suggests that treatment planning for MRgRT can be made with consideration of only changed dose distribution.

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

Repair of DNA damage induced by ionizing radiation plays an important role in the cell response to ionizing radiation. Radiation-induced DNA damage also activates the p53 system, which determines the fate of cells. The kinetics of repair, which is affected by the cell itself and the complexity of DNA damage, influences the cell response and fate via affecting the p53 system. To mechanistically study the influences of the cell response to different LET radiations, we introduce a new repair module and a p53 system model with NASIC, a Monte Carlo track structure code. The factors determining the kinetics of the double-strand break (DSB) repair are modeled, including the chromosome environment and complexity of DSB. The kinetics of DSB repair is modeled considering the resection-dependent and resection-independent compartments. The p53 system is modeled by simulating the interactions among genes and proteins. With this model, the cell responses to low- and high-LET irradiation are simulated, respectively. It is found that the kinetics of DSB repair greatly affects the cell fate and later biological effects. A large number of DSBs and a slow repair process lead to severe biological consequences. High-LET radiation induces more complex DSBs, which can be repaired by slow processes, subsequently resulting in a longer cycle arrest and, furthermore, apoptosis and more secreting of TGFβ. The Monte Carlo track structure simulation with a more realistic repair module and the p53 system model developed in this study can expand the functions of the NASIC code in simulating mechanical radiobiological effects.

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

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

Mechanistic modelling of oxygen enhancement ratio of radiation via Monte Carlo simulation-based DNA damage calculation

Objective.Oxygen plays an important role in affecting the cellular radio-sensitivity to ionizing radiation. The objective of this study is to build a mechanistic model to compute oxygen enhancement ratio (OER) using a GPU-based Monte Carlo (MC) simulation package gMicroMC for microscopic radiation transport simulation and DNA damage calculation.Approach.We first simulated the water radiolysis process in the presence of DNA and oxygen for 1 ns and recorded the produced DNA damages. In this process, chemical reactions among oxygen, water radiolysis free radicals and DNA molecules were considered. We then applied a probabilistic approach to model the reactions between oxygen and indirect DNA damages for a maximal reaction time oft0. Finally, we defined two parametersP0andP1, representing probabilities for DNA damages without and with oxygen fixation effect not being restored in the repair process, to compute the final DNA double strand breaks (DSBs). As cell survival fraction is mainly determined by the number of DSBs, we assumed that the same numbers of DSBs resulted in the same cell survival rates, which enabled us to compute the OER as the ratio of doses producing the same number of DSBs without and with oxygen. We determined the three parameters (t0,P0andP1) by fitting the OERs obtained in our computation to a set of published experimental data under x-ray irradiation. We then validated the model by performing OER studies under proton irradiation and studied model sensitivity to parameter values.Main results.We obtained the model parameters ast0= 3.8 ms,P0= 0.08, andP1= 0.28 with a mean difference of 3.8% between the OERs computed by our model and that obtained from experimental measurements under x-ray irradiation. Applying the established model to proton irradiation, we obtained OERs as functions of oxygen concentration, LET, and dose values, which generally agreed with published experimental data. The parameter sensitivity analysis revealed that the absolute magnitude of the OER curve relied on the values ofP0andP1, while the curve was subject to a horizontal shift when adjustingt0.Significance.This study developed a mechanistic model that fully relies on microscopic MC simulations to compute OER.

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.