Track Structure Simulations Research Articles

TOPAS-Tissue: A Framework for the Simulation of the Biological Response to Ionizing Radiation at the Multi-Cellular Level.

This work aims to develop and validate a framework for the multiscale simulation of the biological response to ionizing radiation in a population of cells forming a tissue. We present TOPAS-Tissue, a framework to allow coupling two Monte Carlo (MC) codes: TOPAS with the TOPAS-nBio extension, capable of handling the track-structure simulation and subsequent chemistry, and CompuCell3D, an agent-based model simulator for biological and environmental behavior of a population of cells. We verified the implementation by simulating the experimental conditions for a clonogenic survival assay of a 2-D PC-3 cell culture model (10 cells in 10,000 µm2) irradiated by MV X-rays at several absorbed dose values from 0-8 Gy. The simulation considered cell growth and division, irradiation, DSB induction, DNA repair, and cellular response. The survival was obtained by counting the number of colonies, defined as a surviving primary (or seeded) cell with progeny, at 2.7 simulated days after irradiation. DNA repair was simulated with an MC implementation of the two-lesion kinetic model and the cell response with a p53 protein-pulse model. The simulated survival curve followed the theoretical linear-quadratic response with dose. The fitted coefficients α = 0.280 ± 0.025/Gy and β = 0.042 ± 0.006/Gy2 agreed with published experimental data within two standard deviations. TOPAS-Tissue extends previous works by simulating in an end-to-end way the effects of radiation in a cell population, from irradiation and DNA damage leading to the cell fate. In conclusion, TOPAS-Tissue offers an extensible all-in-one simulation framework that successfully couples Compucell3D and TOPAS for multiscale simulation of the biological response to radiation.

Radial dependence of ionization clustering around a gold nanoparticle irradiated by X-rays under charged particle equilibrium

Objective.This work explores the enhancement of ionization clustering and its radial dependence around a gold nanoparticle (NP), indicative of the induction of DNA lesions, a potential trigger for cell-death.Approach.Monte Carlo track structure simulations were performed to determine (a) the spectral fluence of incident photons and electrons in water around a gold NP under charged particle equilibrium conditions and (b) the density of ionization clusters produced on average as well as conditional on the occurrence of at least one interaction in the NP using Associated Volume Clustering. Absorbed dose was determined for comparison with a recent benchmark intercomparison. Reported quantities are normalized to primary fluence, allowing to establish a connection to macroscopic dosimetric quantities.Main results.The modification of the electron spectral fluence by the gold NP is minor and mainly occurs at low energies. The net fluence of electrons emitted from the NP is dominated by electrons resulting from photon interactions. Similar to the known dose enhancement, increased ionization clustering is limited to a distance from the NP surface of up to200nm. The number of clusters per energy imparted is increased at distances of up to150nm, and accordingly the enhancement in clustering notably surpasses that of dose enhancement. Smaller NPs cause noticeable peaks in the conditional frequency of clusters between50nm-100nmfrom the NP surface.Significance.This work shows that low energy electrons emitted by NPs lead to an increase of ionization clustering in their vicinity exceeding that of energy imparted. While the electron component of the radiation field plays an important role in determining the background contribution to ionization clustering and energy imparted, the dosimetric effects of NPs are governed by the interplay of secondary electron production by photon interaction and their ability to leave the NP.

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.

Modelling and numerical simulation of high-speed railway slab track structure

In terms of maintenance and structural behavior, slab track proves to be an advantage over conventional ballasted track due to increasing train speed, axle load, and traffic density. Since the vibration, noise, and risk of derailment, all accelerate as train speed increases, an in-depth investigation of track dynamics becomes essential for identifying the fundamental cause of the problem. In this paper modelling and numerical simulation of high-speed railway slab track structure has been studied using finite element method. Using the multi-body simulation approach and the finite element method a model of the 3D slab track system is developed. The slab track model has rail, rail pad, and concrete slab, HBL, and subgrade layers. In order to determine the fundamental frequency and the mode shapes associated with it, a modal analysis is carried out. Dynamic response, or acceleration against frequency curves derived via harmonic response analysis, is the result of the numerical simulation. The dynamic reaction of the structure of a high-speed slab track is studied, and the effect of elastic materials on reducing vibration is investigated. The results suggest that a layer of elastic material, like a slab of mat, inserted between a layer of concrete slab and a layer of HBL is capable of lowering the amount of vibration response of the track.

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

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

Development of a model for evaluating the luminescence intensity of phosphors based on the PHITS track-structure simulation

Radiation-induced phosphors are frequently used as radiation detectors to measure dose distributions of swift ions. However, the luminescence intensity per dose of the phosphor at the Bragg peak regions decreases because of the quenching effects. To precisely measure the dose distribution for various radiation types using phosphor detectors, understanding the mechanism of quenching effects, induced by the electrons at the atomic scale, is crucial. In this study, we developed a new microdosimetric model for evaluating the luminescence intensity of phosphors based on the track-structure (TS) modes applicable to arbitrary materials implemented in the Particle and Heavy Ion Transport code System (PHITS). Herein, the two dominant factors for determining the luminescence intensity, such as (1) the energy required to generate an electron-hole pair and (2) their transfer efficiency to the luminescence center, are estimated from the TS mode in PHITS by calculating the number of stopped electrons and their spatial distributions. Using the developed model, we calculated the energy required to generate an electron-hole pair in various phosphors, which revealed a complex dependency on the bandgap energy, the composition, and the density of the material. Furthermore, we simulated the quenching effects of the BaFBr detector by calculating its transfer efficiencies for swift-ion irradiation and compared the simulation results with the corresponding experimental data. The comparison suggested that the density of luminescence centers is an essential parameter of the phosphors to reproduce the experimental quenching effects. The developed model is based on the first-principles calculation without any empirical correction; therefore, it is expected to contribute widely to developing phosphor detectors.

A Molecular Approach to Characterize the Effects of Fluence, Fluence Rate and LET on Radiation Damage

Effects of fluence, fluence rate and LET on radiation damage are not resolved using traditional methods of measuring energy deposited by ionization events. The deficiency led to the use of empirical RBE factors in the clinical applications of particle therapy. The use of ionization dosimetry is similarly challenged when applied to development of radiation treatment at ultrahigh (FLASH) dose rate. This study reports a molecular method using plasmid DNA as a more comprehensive model for radiation dosimetry than ionization measurements. Aqueous solutions of purified supercoiled plasmid DNA, pUC19 (2686 bp), were prepared at different scavenging conditions and injected into 5x5x1 mm3 wells as detector elements. Irradiated samples were analyzed using base excision repair enzymes (Nth and Fpg) and gel electrophoresis to measure yields for DNA single and double strand breaks (SSB and DSB), and clustered lesions. The low LET characteristics of conventional radiation treatment was modeled using orthovoltage 150 kVp x-rays to deliver 2-110 Gy at 90 and 0.5 Gy/s. Higher LET irradiations in the range of 2 - 14 keV/μm were facilitated by measurements in the pristine Bragg peak region using synchrotron-produced 142.2 MeV protons to deliver dose at 2 - 160 Gy at 600 and 1 Gy/s. The DNA wells were inserted into a solid water equivalent phantom for proton irradiation. Only 4 wells could be positioned in the short Bragg peak region in water (∼ 2 cm). To alleviate the uncertainties due to rapidly varying dose and LET distributions, we innovated the use of a 3% water density (i.e., Styrofoam) medium to extend the Bragg peak region from 2 cm to 20 cm, enabling the placement of 20 well containers. Quantity and quality of molecular damage in the plasmid DNA model varies with fluence, fluence rate and LET of radiation. At high fluence (> 30 Gy) of low-LET radiations, the yields of DNA SSB and non-DSB clustered lesions depend on the fluence rate. These yields decrease by two times between ultrahigh and conventional dose rate irradiation. At a given fluence and fluence rate, the yields for the formation of DNA DSB and non-DSB clustered lesions increase linearly with LET. The low-density phantom allows significant (∼ 10 folds) increase in the number of sampling points and more accurate sample positioning at specific LET compared to water-equivalent phantom. Monte-Carlo track structure simulation of yields for different DNA lesions is being developed to model the molecular damage. In parallel, approaches to improve the sensitivity of the measurements to dose are being investigated. Our results suggest that a molecular-based approach can be used to differentiate the effects of fluence, fluence rate, and LET on radiation damage. The approach demonstrates the potential to improve on the modeling of radiation effects in biological systems than using measured ionization energy. Correlation of the molecular changes to biological outcome for in vitro and in vivo systems are under investigation.

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

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

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

AimOver 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.MethodsThis 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.ResultsBased 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.ConclusionIn 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.

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.

Spatial-temporal tracking of molecular species in Geant4-DNA track structure simulations

Monte Carlo particle transport codes have been used to simulate the radiolysis of water and subsequent evolution of molecular species during the chemical stage. In Geant4, accounting of molecules is performed using a molecule counter which provides only a global molecule count. We developed a modular counter implementation that was used to perform spatial-temporal tracking of molecule counts. This custom counter was validated in homogeneous and simplistic split geometries for 1 MeV electrons and 50 MeV protons.Using a spherical cell with one nucleus and one hundred mitochondria as an example, the radiolytic yields in the cytoplasm, nucleus, and mitochondria were compared between targeted (electrons originating from within mitochondria) and unspecific (electrons originating from within cytoplasm) for (very) low energy electrons with kinetic energies of 100 eV to 1 keV.At short times radiolytic yields in source volumes were consistent with reference yields obtained in a large homogeneous volume. Past 1 ns diffusion out of the source volumes led to yield reductions. For volumes abutting the source volumes radiolytic yields at short times strongly depended on track end effects, most pronounced for 100 eV electrons. Similarly, diffusion out of the source volumes greatly increased yields in abutting volumes past 1 ns with magnitude decreasing and time of increase increasing with increasing electron energy. For higher energy electron beams (100 keV and 200 keV) radiolytic yields in all volumes were consistent with reference yields for large statistics.Thus, in cases where energy deposit sites are uniformly distributed in the volume of interest and energies of the charged particles are high to avoid track end effects reference yields may be used in place of resource intensive chemical stage simulations. Spatially heterogeneous energy deposits, as observed in targeted ɑ or β radiation therapy or with targeted nanoparticles, using a spatially sensitive molecule counter is suggested when estimating radiolytic yields outside of the source volumes or at distances that are within the diffusion range of the molecules of interest.

Improvement of the hybrid approach between Monte Carlo simulation and analytical function for calculating microdosimetric probability densities in macroscopic matter

Objective. Estimation of the probability density of the microdosimetric quantities in macroscopic matter is indispensable for applying the concept of microdosimetry to medical physics and radiological protection. The Particle and Heavy Ion Transport code System (PHITS) enables estimating the microdosimetric probability densities due to its unique hybrid modality between the Monte Carlo and analytical approaches called the microdosimetric function. It can convert the deposition energies calculated by the macroscopic Monte Carlo radiation transport simulation to microdosimetric probability densities in water using an analytical function based on the track-structure simulations. Approach. In this study, we improved this function using the latest track-structure simulation codes implemented in PHITS. The improved function is capable of calculating the probability densities of not only the conventional microdosimetric quantities such as lineal energy but also the number of ionization events occurring in a target site, the so-called ionization cluster size distribution, for arbitrary site diameters from 3 nm to 1 μm. Main results. The accuracy of the improved function was well verified by comparing the microdosimetric probability densities measured by tissue-equivalent proportional counters with the corresponding data calculated in this study. Test calculations for clonogenic cell survival using the improved function coupled with the modified microdosimetric kinetic model suggested a slight increase of its relative biological effectiveness compared with our previous estimations. As a new application of the improved function, we calculated the relative biological effectiveness of the single-strand break and double-strand break yields for proton irradiations using the updated PHITS coupled with the simplified DNA damage estimation model, and confirmed its equivalence in accuracy and its superiority in computational time compared to our previously proposed method based on the track-structure simulation. Significance. From these features, we concluded that the improved function could expand the application fields of PHITS by bridging the gap between microdosimetry and macrodosimetry.

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

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

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

Objective. The TOPAS-nBio Monte Carlo track structure simulation code, a wrapper of Geant4-DNA, was extended for its use in pulsed and longtime homogeneous chemistry simulations using the Gillespie algorithm. Approach. Three different tests were used to assess the reliability of the implementation and its ability to accurately reproduce published experimental results: (1) a simple model with a known analytical solution, (2) the temporal evolution of chemical yields during the homogeneous chemistry stage, and (3) radiolysis simulations conducted in pure water with dissolved oxygen at concentrations ranging from 10 μM to 1 mM with [H2O2] yields calculated for 100 MeV protons at conventional and FLASH dose rates of 0.286 Gy s−1 and 500 Gy s−1, respectively. Simulated chemical yield results were compared closely with data calculated using the Kinetiscope software which also employs the Gillespie algorithm. Main results. Validation results in the third test agreed with experimental data of similar dose rates and oxygen concentrations within one standard deviation, with a maximum of 1% difference for both conventional and FLASH dose rates. In conclusion, the new implementation of TOPAS-nBio for the homogeneous long time chemistry simulation was capable of recreating the chemical evolution of the reactive intermediates that follow water radiolysis. Significance. Thus, TOPAS-nBio provides a reliable all-in-one chemistry simulation of the physical, physico-chemical, non-homogeneous, and homogeneous chemistry and could be of use for the study of FLASH dose rate effects on radiation chemistry.

Extension of matRad with a modified microdosimetric kinetic model for carbon ion treatment planning: Comparison with Monte Carlo calculation.

Treatment planning is essential for in silico particle therapy studies. matRad is an open-source research treatment planning system (TPS) based on the local effect model, which is a type of relative biological effectiveness (RBE) model. This study aims to implement a microdosimetric kinetic model (MKM) in matRad and develop an automation algorithm for Monte Carlo (MC) dose recalculation using the TOPAS code. In addition, we provide the developed MKM extension as open-source tool for users. Carbon beam data were generated using TOPAS MC pencil beam irradiation. We parameterized the TOPAS MC beam data with a double-Gaussian fit and modeled the integral depth doses and lateral spot profiles in the range of 100-430 MeV/u. To implement the MKM, the specific energy data table for Z=1-6 and integrated depth-specific energy data were acquired based on the Kiefer-Chatterjee track structure and TOPAS MC simulation, respectively. Generic data were integrated into matRad, and treatment planning was performed based on these data. The optimized plan parameters were automatically converted into MC simulation input. Finally, the matRad TPS and TOPAS MC simulations were compared using the RBE-weighted dose calculation results. A comparison was made for three geometries: homogeneous water phantom, inhomogeneous phantom, and patient. The RBE-weighted dose (DRBE ) distribution agreed with TOPAS MC within 1.8% for all target sizes for the homogeneous phantom. For the inhomogeneous phantom, the relative difference in the range of 80% of the prescription dose in the distal fall-off region (R80) between the matRad TPS and TOPAS MC was 0.6% (1.1mm). DRBE between the TPS and the MC was within 4.0%. In the patient case, the difference in the dose-volume histogram parameters for the target volume between the TPS and the MC was less than 2.7%. The relative difference in R80 was 0.7% (1.2mm). The MKM was successfully implemented in matRad TPS, and the RBE-weighted dose was comparable to that of TOPAS MC. The MKM-implemented matRad was released as an open-source tool. Further investigations with MC simulations can be conducted using this tool, providing a good option for carbon ion research.

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

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

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

Boron neutron capture therapy (BNCT) is a cellular-level hadron therapy achieving therapeutic effects via the synergistic action of multiple particles, including Lithium, alpha, proton, and photon. However, evaluating the relative biological effectiveness (RBE) in BNCT remains challenging. In this research, we performed a microdosimetric calculation for BNCT using the Monte Carlo track structure (MCTS) simulation toolkit, TOPAS-nBio. This paper reports the first attempt to derive the ionization cross-sections of low-energy (>0.025 MeV/u) Lithium for MCTS simulation based on the effective charge cross-section scalation method and phenomenological double-parameter modification. The fitting parameters (λ1 = 1.101, λ2 = 3.486) were determined to reproduce the range and stopping power data from the ICRU report 73. Besides, the lineal energy spectra of charged particles in BNCT were calculated, and the influence of sensitive volume (SV) size was discussed. Condensed history simulation obtained similar results with MCTS when using Micron-SV while overestimating the lineal energy when using Nano-SV. Furthermore, we found that the microscopic boron distribution can significantly affect the lineal energy for Lithium, while the effect for alpha is minimal. Similar results to the published data by PHITS simulation were observed for the compound particles and monoenergetic protons when using micron-SV. Spectra with nano-SV reflected that the different track densities and absorbed doses in the nucleus together result in the dramatic difference in the macroscopic biological response of BPA and BSH. This work and the developed methodology could impact the research fields in BNCT where understanding radiation effects is crucial, such as the treatment planning system, source evaluation, and new boron drug development.

A study of indirect action’s impact on simulated neutron-induced DNA damage

Objective. The risk of radiobiological stochastic effects associated with neutrons is strongly energy dependent. Recent Monte Carlo studies simulating neutron-irradiated nuclear DNA have demonstrated that this energy dependence is correlated with the relative biological effectiveness (RBE) of neutrons to inflict DNA damage clusters that contain difficult-to-repair double-strand breaks. However, these previous investigations were either limited to modeling direct radiation action or considered the effects of both direct and indirect action together without distinguishing between the two. In this study, we aimed to quantify the influence of indirect action in neutron irradiation scenarios and acquire novel estimations of the energy-dependent neutron RBE for inducing DNA damage clusters due to both direct and indirect action. Approach. We explored the role of indirect action in neutron-induced DNA damage by integrating a validated indirect action model into our existing simulation pipeline. Using this pipeline, we performed track-structure simulations of monoenergetic neutron irradiations (1 eV to 10 MeV) in a nuclear DNA model and analyzed the resulting simple and clustered DNA lesions. We repeated the irradiation simulations for 250 keV x-rays that acted as our reference radiation. Main results. Including indirect action significantly increased the occurrence of DNA lesions. We found that indirect action tends to amplify the damage due to direct action by inducing DNA lesions in the vicinity of directly-induced lesions, resulting in additional and larger damage clusters. Our neutron RBE results are qualitatively similar to but lower in magnitude than the established radiation protection factors and the results of previous similar investigations, due to the greater relative impact of indirect action in photon-induced damage than in neutron-induced damage. Significance. Although our model for neutron-induced DNA damage has some important limitations, our findings suggest that the energy-dependent risk of neutron-induced stochastic effects may not be completely modeled alone by the relative potential of neutrons to inflict clustered lesions via direct and indirect action in DNA damage.

Track Structure of Light Ions: The Link to Radiobiology.

It is generally recognized that the biological response to irradiation by light ions is initiated by complex damages at the DNA level. In turn, the occurrence of complex DNA damages is related to spatial and temporal distribution of ionization and excitation events, i.e., the particle track structure. It is the aim of the present study to investigate the correlation between the distribution of ionizations at the nanometric scale and the probability to induce biological damage. By means of Monte Carlo track structure simulations, the mean ionization yield M1 and the cumulative probabilities F1, F2, and F3 of at least one, two and three ionizations, respectively, were calculated in spherical volumes of water-equivalent diameters equal to 1, 2, 5 and 10 nm. When plotted as a function of M1, the quantities F1, F2 and F3 are distributed along almost unique curves, largely independent of particle type and velocity. However, the shape of the curves depends on the size of the sensitive volume. When the site size is 1 nm, biological cross sections are strongly correlated to combined probabilities of F2 and F3 calculated in the spherical volume, and the proportionality factor is the saturation value of biological cross sections.

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

Complex DNA double-strand break (DSB), which is defined as a DSB coupled with additional strand breaks within 10 bp in this study, induced after ionizing radiation or X-rays, is recognized as fatal damage which can induce cell death with a certain probability. In general, a DSB site inside the nucleus of live cells can be experimentally detected using the γ-H2AX focus formation assay. DSB complexity is believed to be detected by analyzing the focus size using such an assay. However, the relationship between focus size and DSB complexity remains uncertain. In this study, using Monte Carlo (MC) track-structure simulation codes, i.e., an in-house WLTrack code and a Particle and Heavy Ion Transport code System (PHITS), we developed an analytical method for qualifying the DSB complexity induced by photon irradiation from the microscopic image of γ-H2AX foci. First, assuming that events (i.e., ionization and excitation) potentially induce DNA strand breaks, we scored the number of events in a water cube (5.03 × 5.03 × 5.03 nm3) along electron tracks. Second, we obtained the relationship between the number of events and the foci size experimentally measured by the γ-H2AX focus formation assay. Third, using this relationship, we evaluated the degree of DSB complexity induced after photon irradiation for various X-ray spectra using the foci size, and the experimental DSB complexity was compared to the results estimated by the well-verified DNA damage estimation model in the PHITS code. The number of events in a water cube was found to be proportional to foci size, suggesting that the number of events intrinsically related to DSB complexity at the DNA scale. The developed method was applicable to focus data measured for various X-ray spectral situations (i.e., diagnostic kV X-rays and therapeutic MV X-rays). This method would contribute to a precise understanding of the early biological impacts of photon irradiation by means of the γ-H2AX focus formation assay.