Experimental validation in a neutron exposure frame of the MINAS TIRITH for cell damage simulation.

In the domains of medicine and space exploration, refining risk assessment models for protecting healthy tissue from ionizing radiation is crucial. Understanding radiation-induced effects requires biological experimentations at the cellular population level and the cellular scale modeling using Monte Carlo track structure codes. We present MINAS TIRITH, a tool using Geant4-DNA Monte Carlo-generated databases to study DNA damage distribution at the cell population scale. It introduces a DNA damage location module and proposes a method to convert double-strand breaks (DSB) into DNA Damage Response foci. We evaluate damage location precision and DSB-foci conversion parameters. MINAS TIRITH's accuracy is validated againstγ-H2AX foci distribution from cell population exposed to monoenergetic neutron beams (2.5 or 15.1 MeV) under different configurations, yielding mixed radiation fields. Strong agreement between simulation and experimental results was found demonstrating MINAS TIRITH's predictive precision in radiation-induced DNA damage topology. Additionally, modeling intercellular damage variability within a population subjected to a specific macroscopic dose identifies subpopulations, enhancing realistic fate models. This approach advances our understanding of radiation-induced effects on cellular systems for risk assessment improvement.

Geometrical Properties of the Nucleus and Chromosome Intermingling Are Possible Major Parameters of Chromosome Aberration Formation.

Ionizing radiation causes chromosome aberrations, which are possible biomarkers to assess space radiation cancer risks. Using the Monte Carlo codes Relativistic Ion Tracks (RITRACKS) and Radiation-Induced Tracks, Chromosome Aberrations, Repair and Damage (RITCARD), we investigated how geometrical properties of the cell nucleus, irradiated with ion beams of linear energy transfer (LET) ranging from 0.22 keV/µm to 195 keV/µm, influence the yield of simple and complex exchanges. We focused on the effect of (1) nuclear volume by considering spherical nuclei of varying radii; (2) nuclear shape by considering ellipsoidal nuclei of varying thicknesses; (3) beam orientation; and (4) chromosome intermingling by constraining or not constraining chromosomes in non-overlapping domains. In general, small nuclear volumes yield a higher number of complex exchanges, as compared to larger nuclear volumes, and a higher number of simple exchanges for LET < 40 keV/µm. Nuclear flattening reduces complex exchanges for high-LET beams when irradiated along the flattened axis. The beam orientation also affects yields for ellipsoidal nuclei. Reducing chromosome intermingling decreases both simple and complex exchanges. Our results suggest that the beam orientation, the geometry of the cell nucleus, and the organization of the chromosomes within are important parameters for the formation of aberrations that must be considered to model and translate in vitro results to in vivo risks.

Combined cell and nanoparticle models for TOPAS to study radiation dose enhancement in cell organelles.

Dose enhancement by gold nanoparticles (AuNP) increases the biological effectiveness of radiation damage in biomolecules and tissue. To apply them effectively during cancer therapy their influence on the locally delivered dose has to be determined. Hereby, the AuNP locations strongly influence the energy deposit in the nucleus, mitochondria, membrane and the cytosol of the targeted cells. To estimate these effects, particle scattering simulations are applied. In general, different approaches for modeling the AuNP and their distribution within the cell are possible. In this work, two newly developed continuous and discrete-geometric models for simulations of AuNP in cells are presented. These models are applicable to simulations of internal emitters and external radiation sources. Most of the current studies on AuNP focus on external beam therapy. In contrast, we apply the presented models in Monte-Carlo particle scattering simulations to characterize the energy deposit in cell organelles by radioactive 198AuNP. They emit beta and gamma rays and are therefore considered for applications with solid tumors. Differences in local dose enhancement between randomly distributed and nucleus targeted nanoparticles are compared. Hereby nucleus targeted nanoparticels showed a strong local dose enhancement in the radio sensitive nucleus. These results are the foundation for future experimental work which aims to obtain a mechanistic understanding of cell death induced by radioactive 198Au.

The effect of the nucleus random location on the cellular S-values - Based on Geant4-DNA.

INTRODUCTION: The nucleus is the most crucial target in cell micro-dosimetry. At cell division time, cells do not have concentric geometry synchronously. This issue will be more essential for the low-energy electron emitters. This study investigates the variety of mean absorbed dose (S-value) in the non-concentric cell-nucleus model and random nucleus location within the cell. METHODS: The S-values were calculated by Geant4-DNA for the cell and nucleus with different radius (with the RC/RN ratio = 1.2, 2, 3) and the cell geometry contains nuclei with varying positions inside the cell. Two important components, cytoplasm to the nucleus (N←Cy) and the cell surface to the nucleus (N←Cs) are considered in this work for mono energetic electrons (10-100 keV). To eliminate the effect of the nucleus position (during cell division) on the S-value, the nucleus location in each run was randomly selected inside the cell to represent the cell in a floating state. RESULTS: As the nucleus becomes closer to the cell membrane the differences are more noticeable especially for electrons with energy less than 20 keV as for RN/RC = 1.2, 2, and 3 about 18, 70, and 200%, respectively. CONCLUSION: Due to the variable position of the nucleus in cell division, using a random place defined in Geant4, the calculations are getting closer to the reality while there is not such possibility for analytical method used by MIRD.

An Analytical Microdosimetric Model for Radioimmunotherapeutic Alpha Emitters.

In this work, we present a methodology to analytically determine microdosimetric quantities in radioimmunotherapy and targeted radiotherapy with alpha particles. Monte Carlo simulations using the Geant4-DNA toolkit, which provides interaction models at the microscopic level, are performed for monoenergetic alpha particles traversing spherical sites with diameters of 1, 5 and 10 µm. An analytical function is fitted against the data in each case to model the energy imparted by monoenergetic particles to the site, as well as the variance of the distribution of energy imparted. Those models allow us to obtain the mean and dose-mean values of specific energy (z) and lineal energy (y) for polyenergetic arrangements of alpha particles. The energetic spectrum is estimated by considering the distance that each particle needs to travel to reach the sensitive target. We apply this methodology to a simple case in radioimmunotherapy: a spherical cell that has its membrane uniformly covered by 211At, an alpha emitter, with a spherical target representing the nucleus, placed at the center of the cell. We compare the results of our analytical method with calculations using Geant4-DNA of this specific setup for three nucleus sizes corresponding to our three functions. For nuclei with diameter of 1 µm and 5 µm, all mean and dose-mean quantities for y and z were in an agreement within 4% to Geant4-DNA calculations. This agreement improves to approximately 1% for dose-mean lineal energy and dose-mean specific energy. For the 10-µm-diameter case, discrepancies scale to approximately 9% for mean values and 3% for dose-mean values. Dose-mean values are within Geant4-DNA uncertainties in all cases. Our method provides accurate analytical calculations of dose-mean quantities that may be further employed to characterize radiobiological effectiveness of targeted radiotherapy. The spatial distributions of sources and targets are required to calculate microdosimetric-relevant quantities.

Comparison of MCNPX and MIRDcell in assessing self-dose and cross-dose delivered to cell nuclei and the development of a realistic geometric model.

Purpose: This study aims to provide a comparison between MCNPX and MIRDcell calculations for self-dose and cross-dose for three therapeutic isotopes used in internal radiotherapy (Lu-177, I-131 and Y-90) and to develop a multi-cellular geometric model to simulate an in vitro scenario.Materials and Methods: The self- and cross-dose to individual cell nuclei were assessed by Monte Carlo N-Particle eXtended (MCNPX). A close-packed cubic cell arrangement was assumed with the same amount of radioactivity per cell. Various cell sizes and subcellular distributions of radioactivity (nucleus, cytoplasm and cell membrane) were simulated. S values were obtained by MIRDcell for comparison. A Python 3.4 program was used to generate random cell coordinates in order to build a complex model that takes certain real conditions (cell size and cluster size) into account.Results: The relative differences of MCNPX versus MIRD S values (Sself) ranged from 2.88 to 10.10% for Lu-177; from 0 to 8.41% for I-131 and from 2.80 to 9.58% for Y-90. The relative differences of MCNPX versus MIRDcell cross-dose S values were 3.6%-15.7% for a sphere. The ratio of Scross max to Sself decreased for Lu-177 and I-131 with increasing cell size. The source localization within the cells had no significant impact on the cross-dosing. For single cells, the subcellular location of the source had an effect on Sself.Conclusions: MCNPX and MIRD cell-calculated S values showed good agreement. The model provided could be used to predict the biological effect caused by emitted radiation from therapeutic radionuclides at the cellular level.

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

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

Assessment of Nuclear and Mitochondrial DNA, Expression of Mitochondria-Related Genes in Different Brain Regions in Rats after Whole-Body X-ray Irradiation.

Studies of molecular changes occurred in various brain regions after whole-body irradiation showed a significant increase in terms of the importance in gaining insight into how to slow down or prevent the development of long-term side effects such as carcinogenesis, cognitive impairment and other pathologies. We have analyzed nDNA damage and repair, changes in mitochondrial DNA (mtDNA) copy number and in the level of mtDNA heteroplasmy, and also examined changes in the expression of genes involved in the regulation of mitochondrial biogenesis and dynamics in three areas of the rat brain (hippocampus, cortex and cerebellum) after whole-body X-ray irradiation. Long amplicon quantitative polymerase chain reaction (LA-QPCR) was used to detect nDNA and mtDNA damage. The level of mtDNA heteroplasmy was estimated using Surveyor nuclease technology. The mtDNA copy numbers and expression levels of a number of genes were determined by real-time PCR. The results showed that the repair of nDNA damage in the rat brain regions occurs slowly within 24 h; in the hippocampus, this process runs much slower. The number of mtDNA copies in three regions of the rat brain increases with a simultaneous increase in mtDNA heteroplasmy. However, in the hippocampus, the copy number of mutant mtDNAs increases significantly by the time point of 24 h after radiation exposure. Our analysis shows that in the brain regions of irradiated rats, there is a decrease in the expression of genes (ND2, CytB, ATP5O) involved in ATP synthesis, although by the same time point after irradiation, an increase in transcripts of genes regulating mitochondrial biogenesis is observed. On the other hand, analysis of genes that control the dynamics of mitochondria (Mfn1, Fis1) revealed that sharp decrease in gene expression level occurred, only in the hippocampus. Consequently, the structural and functional characteristics of the hippocampus of rats exposed to whole-body radiation can be different, most significantly from those of the other brain regions.

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

PURPOSE: Monte Carlo (MC) simulation of radiation interactions with water medium at physical, physicochemical, and chemical stages, as well as the computation of biologically relevant quantities such as DNA damages, are of critical importance for the understanding of microscopic basis of radiation effects. Due to the large problem size and many-body simulation problem in the chemical stage, existing CPU-based computational packages encounter the problem of low computational efficiency. This paper reports our development on a GPU-based microscopic Monte Carlo simulation tool gMicroMC using advanced GPU-acceleration techniques. METHODS: gMicroMC simulated electron transport in the physical stage using an interaction-by-interaction scheme to calculate the initial events generating radicals in water. After the physicochemical stage, initial positions of all radicals were determined. Simulation of radicals' diffusion and reactions in the chemical stage was achieved using a step-by-step model using GPU-accelerated parallelization together with a GPU-enabled box-sorting algorithm to reduce the computations of searching for interaction pairs and therefore improve efficiency. A multi-scale DNA model of the whole lymphocyte cell nucleus containing ~6.2 Gbp of DNA was built. RESULTS: Accuracy of physical stage simulation was demonstrated by computing stopping power and track length. The results agreed with published data and the data produced by GEANT4-DNA (version 10.3.3) simulations with 10 -20% difference in most cases. Difference of yield values of major radiolytic species from GEANT4-DNA results was within 10%. We computed DNA damages caused by monoenergetic 662 keV photons, approximately representing 137 Cs decay. Single-strand break (SSB) and double-strand break (DSB) yields were 196 ± 8 SSB/Gy/Gbp and 7.3 ± 0.7 DSB/Gy/Gbp, respectively, which agreed with the result of 188 SSB/Gy/Gbp and 8.4 DSB/Gy/Gbp computed by Hsiao et al. Compared to computation using a single CPU, gMicroMC achieved a speedup factor of ~540x using an NVidia TITAN Xp GPU card. CONCLUSIONS: The achieved accuracy and efficiency demonstrated that gMicroMC can facilitate research on microscopic radiation transport simulation and DNA damage calculation. gMicroMC is an open-source package available to the research community.

On the importance of modeling gold nanoparticles distribution in dose-enhanced radiotherapy.

Purpose: To investigate the effect of precise modeling for Monte Carlo simulations of gold nanoparticles (GNPs) dose-enhanced radiotherapy, two models characterized by their distribution of GNPs in a simulated macroscopic cubic tumor were introduced. The motivation was the widely documented tendency of GNPs to localize around the cell nucleus. Methods: The introduced models composed of 2.7×107 ellipsoid cells, each of them containing a centrally located nucleus as the target for dose evaluation. In the first model, the spheres of GNP are homogeneously distributed in the whole tumor volume, and in the latter, GNPs are localized in the cytoplasms surrounded the nuclei. Results: The results achieved through applying Monte Carlo radiation transports using the Mont Carlo N-Particle eXtended code (MCNPX) show an underestimation of nuclear dose enhancement caused by homogeneous model compared with that of heterogeneous distribution. By investigating various quantities, it was found that subcellular location of GNPs strongly governs the sensitivity of dose enhancement to the number and concentration of GNPs targeted in the tumor. Other obvious differences are revealed by studying the dose enhancement curves in depth of the tumor. While the heterogeneous model predicts an approximately constant dose enhancement in depth for primary photon energies of 50 keV and more, the homogeneous model estimates an energy-dependent increase of about 11 to 30%. Conclusion: It can be concluded that defining a model in accordance with the experimental observations can effectively account for accurate prediction of macroscopic dose enhancement in the target of interest.

Medium-thickness-dependent proton dosimetry for radiobiological experiments.

A calibration method was proposed in the present work to determine the medium-thickness-dependent proton doses absorbed in cellular components (i.e., cellular cytoplasm and nucleus) in radiobiological experiments. Consideration of the dependency on medium thickness was crucial as the linear energy transfer (LET) of protons could rise to a sharp peak (known as the Bragg peak) towards the end of their ranges. Relationships between the calibration coefficient R vs medium-layer thickness were obtained for incident proton energies of 10, 15, 20, 25, 30 and 35 MeV, and for various medium thicknesses up to 5000 µm, where R was defined as the ratio DA/DE, DA was the absorbed proton dose in cellular components, and DE was the absorbed proton dose in a separate radiation detector. In the present work, DA and DE were determined using the MCNPX (Monte Carlo N-Particle eXtended) code version 2.4.0. For lower incident proton energies (i.e., 10, 15 and 20 MeV), formation of Bragg-peak-like features were noticed in their R-vs-medium-layer-thickness relationships, and large R values of >7 and >6 were obtained for cytoplasm and nucleus of cells, respectively, which highlighted the importance of careful consideration of the medium thickness in radiobiological experiments.

Development of a dosimetric model for in vitro labelled cells with ß + emitters in PET tracking studies.

Positron emission tomography (PET) offers an effective method for tracking ß + emitters-labeled cells in vivo. However, in vitro high labelling activities used may cause cell damage or death. Our understanding of the impact of such procedure remains limited by the fact that the biological effects are usually linked to the activity per cell rather than the absorbed dose. To assess the dose delivered to the cells during the radiolabelling, a multi-cellular dosimetry computational tool was developed, allowing the study of two key parameters: the cell density and the labelling efficiency. Through a hybrid method based on Monte Carlo simulations (MCNP6 code) and an analytical approach implemented in Python, the mean absorbed dose received by a target cell was calculated for distributions with a very large number of cells-up to hundreds of millions. An advanced investigation of in vitro cell labelling with ß-emitting radionuclides was carried out via (i) a systematic study of the effects of the labelling parameters on the cell absorbed dose for 18F, 64Cu and 68Ga, and (ii) a quantitative comparison between cellular and conventional dosimetry. The results provided a thorough analysis of how the dose (self, cross and extracellular medium dose contributions) varies with the initial labelling parameters selected and highlighted the conditions where the cellular dosimetry is required over the conventional dosimetry. The dosimetric model was finally applied to real conditions of 18F-FDG labelling on the basis of eight reported studies. The results showed that similar activity per cell can lead to significantly different absorbed dose and pointed out differences between cellular and conventional dosimetry up to a factor of 5.

A cell-by-cell Monte Carlo simulation for assessing radiation-induced DNA double strand breaks.

This paper presents a cell-by-cell Monte Carlo simulation study that combines charged particle track structure data with an interphase cell nucleus model to quantify DNA double strand breaks (DSBs), spatial distribution of DSBs in a cell nucleus, and resulting potentially lethal or mutagenic events (PLMEs) between DSBs in close proximity. Cell nucleus is simulated according to the chromosome territory-interchromatin compartment (CT-IC) model in that chromatin content is unevenly distributed in chromatin domains (CDs) and IC with a chromatin compaction ratio of 22:1. A particle track structure coordinate (PTSC) library was first generated for each particle type, energy, and dose based on a large number of particle track data obtained by running the Monte Carlo track structure code Geant4-DNA. To assess the DNA DSBs of a cell for a specific particle type, energy, and dose, the corresponding PTSC was selected and "map overlaid" onto 960 unique cell nucleus data sets containing chromatin fiber (CF) locations. Clustering algorithm DBSCAN was next used to identify the clustered energy deposition events occurring inside the CF. These events were then converted to DNA DSBs using a probabilistic approach. The locations of the DSBs thus obtained were, in turn, used to calculate PLMEs within the cell nucleus that can result from DSB proximity and complexity. The results obtained from this simulation study are correctly correlated to the experimental data of DSB yield and the RBE-LET relationships for various types of charged particles and of various energies. The results show agreement with other published radiobiological models.

Evaluation of early radiation DNA damage in a fractal cell nucleus model using Geant4-DNA.

The advancement of multidisciplinary research fields dealing with ionising radiation induced biological damage - radiobiology, radiation physics, radiation protection and, in particular, medical physics - requires a clear mechanistic understanding of how cellular damage is induced by ionising radiation. Monte Carlo (MC) simulations provide a promising approach for the mechanistic simulation of radiation transport and radiation chemistry, towards the in silico simulation of early biological damage. We have recently developed a fully integrated MC simulation that calculates early single strand breaks (SSBs) and double strand breaks (DSBs) in a fractal chromatin based human cell nucleus model. The results of this simulation are almost equivalent to past MC simulations when considering direct/indirect strand break fraction, DSB yields and fragment distribution. The simulation results agree with experimental data on DSB yields within 13.6% on average and fragment distributions agree within an average of 34.8%.

From Energy Deposition of Ionizing Radiation to Cell Damage Signaling: Benchmarking Simulations by Measured Yields of Initial DNA Damage after Ion Microbeam Irradiation.

Advances in accelerator technology, which have enabled conforming radiotherapy with charged hadronic species, have brought benefits as well as potential new risks to patients. To better understand the effects of ionizing radiation on tumor and surrounding tissue, it is important to investigate and quantify the relationship between energy deposition at the nanometric scale and the initial biological events. Monte Carlo track structure simulation codes provide a powerful tool for investigating this relationship; however, their success and reliability are dependent on their improvement and development accordingly to the dedicated biological data to which they are challenged. For this aim, a microbeam facility that allows for fluence control, down to one ion per cell nucleus, was used to evaluate relative frequencies of DNA damage after interaction between the incoming ion and DNA according to radiation quality. Primary human cells were exposed to alpha particles of three different energies with respective linear energy transfers (LETs) of approximately 36, 85 or 170 keV·µm-1 at the cells' center position, or to protons (19 keV·µm-1). Statistical evaluation of nuclear foci formation (53BP1/γ-H2AX), observed using immunofluorescence and related to a particle traversal, was undertaken in a large population of cell nuclei. The biological results were adjusted to consider the factors that drive the experimental uncertainties, then challenged with results using Geant4-DNA code modeling of the ionizing particle interactions on a virtual phantom of the cell nucleus with the same mean geometry and DNA density as the cells used in our experiments. Both results showed an increase of relative frequencies of foci (or simulated DNA damage) in cell nuclei as a function of increasing LET of the traversing particles, reaching a quasi-plateau when the LET exceeded 80-90 keV·µm-1. For the LET of an alpha particle ranging from 80-90 to 170 keV·µm-1, 10-30% of the particle hits did not lead to DNA damage inducing 53BP1 or γ-H2AX foci formation.

Assessment of the radiation absorbed dose produced by 177Lu-iPSMA, 225Ac-iPSMA and 223RaCl2 to prostate cancer cell nuclei in a bone microenvironment model.

This research aimed to assess the radiation absorbed dose produced by 177Lu-iPSMA (177Lu-prostate specific membrane antigen inhibitor), 225Ac-iPSMA and 223RaCl2 to prostate cancer cell nuclei in a simplified model of bone by using an experimental in-vitro prostate cancer LNCaP cell biokinetic study and Monte Carlo simulation with the MCNPX code. Results showed that 225Ac-iPSMA releases a nine hundred-fold radiation dose greater than 177Lu-iPSMA and 14 times more than 223RaCl2 per unit of activity retained in bone. 225Ac-iPSMA could be the best option for treatment of bone metastases in prostate cancer.

Influence of chromatin compaction on simulated early radiation-induced DNA damage using Geant4-DNA.

PURPOSE: In this work, we present simulated double-strand breaks (DSBs) obtained for two human cell nucleus geometries. The first cell nucleus represents fibroblasts, filled with DNA molecules in different compaction forms: heterochromatin or euchromatin only. The second one represents an endothelial cell nucleus, either filled with heterochromatin only or with a uniform distribution of 48% of heterochromatin and 52% of euchromatin, obtained from measurements carried out at IRSN. Protons and alpha particles of different energies were used as projectiles. Each cell nucleus model includes a multi-scale description of the DNA target from the molecular level to the whole human genome representation. METHODS: The cell nucleus models were generated using an extended version of the DnaFabric software in which a new model of euchromatin was implemented in addition to the existing model of heterochromatin. Thus, each nucleus model contains the complete human genome (a total of 6 Gbp) in the G0/G1 phase of the cycle, filled with a continuous chromatin fiber per chromosome that can take into account the heterochromatin and the euchromatin compaction. These geometries were then exported to a simulation chain using the Monte Carlo toolkit Geant4-DNA to perform computations of the physical, physicochemical, and chemical stages, in order to evaluate the influence of chromatin compaction on DSB induction and the contribution of direct and indirect damage, as well as DSB complexity. RESULTS: More direct damage and less indirect damage were observed in the heterochromatin than in the euchromatin. Nevertheless, no difference in terms of DSB complexity was observed between those formed in the heterochromatin or the euchromatin models. Yields of DSB/Gy/Gbp show an increase when both heterochromatin and euchromatin models are taken into account, compared to when only heterochromatin is considered. CONCLUSIONS: The results presented indicate that the chromatin compaction decreases DNA damage generated by ionizing radiation and thus, DNA compaction should be considered for the simulation of DNA repair and other cellular outcomes.

AN ALGORITHM TO DETERMINE THE NANODOSIMETRIC IMPACT OF GOLD NANOPARTICLES ON CELL MODELS.

High-Z nanomaterials, e.g. gold nanoparticles (GNPs), are being investigated worldwide for potential application in radiation imaging and therapy. Photon irradiation of cells containing GNP was shown to produce enhanced DNA damage which is believed to be related to the increased secondary electron (SE) yield and ionization density. In this work, an algorithm was developed for simulating the physical radiation damage inside the nucleus of a spherical cell model for the case of uniformly distributed GNPs within the cytoplasm. Previously calculated energy spectra of SE emerging from a single NP irradiated with different photon sources are used as input to obtain the SE energy spectrum at the surface of the cell nucleus. In a second step, the SE transport inside the cell nucleus is simulated with a track structure Monte Carlo code to obtain the spatial distribution of ionizations. The preliminary results presented here show that the developed algorithm allows for a fast calculation of the SE spectra at the cell nucleus surface, thus enabling a more realistic assessment of the ionization density inside the cell nucleus than that obtained by the simulation of a single GNP. Furthermore, the algorithm can be easily adapted to investigate both the effect of GNP clustering and the impact of GNP-GNP interactions on SE spectra.

Investigating energy deposition within cell populations using Monte Carlo simulations.

In this work, we develop multicellular models of healthy and cancerous human soft tissues, which are used to investigate energy deposition in subcellular targets, quantify the microdosimetric spread in a population of cells, and determine how these results depend on model details. Monte Carlo (MC) tissue models combining varying levels of detail on different length scales are developed: microscopically-detailed regions of interest (>1500 explicitly-modelled cells) are embedded in bulk tissue phantoms irradiated by photons (20 keV-1.25 MeV). Specific energy (z; energy imparted per unit mass) is scored in nuclei and cytoplasm compartments using the EGSnrc user-code egs_chamber; specific energy mean, [Formula: see text], standard deviation, [Formula: see text], and distribution, [Formula: see text], are calculated for a variety of macroscopic doses, D. MC-calculated [Formula: see text] are compared with normal distributions having the same mean and standard deviation. For ∼mGy doses, there is considerable variation in energy deposition (microdosimetric spread) throughout a cell population: e.g. for 30 keV photons irradiating melanoma with 7.5 µm cell radius and 3 µm nuclear radius, [Formula: see text] for nuclear targets is [Formula: see text], and the fraction of nuclei receiving no energy deposition, f z=0, is 0.31 for a dose of 10 mGy. If cobalt-60 photons are considered instead, then [Formula: see text] decreases to [Formula: see text], and f z=0 decreases to 0.036. These results correspond to randomly arranged cells with cell/nucleus sizes randomly sampled from a normal distribution with a standard deviation of 1 µm. If cells are arranged in a hexagonal lattice and cell/nucleus sizes are uniform throughout the population, then [Formula: see text] decreases to [Formula: see text] and [Formula: see text] for 30 keV and cobalt-60, respectively; f z=0 decreases to 0.25 and 0.000 94 for 30 keV and cobalt-60, respectively. Thus, specific energy distributions are sensitive to cell/nucleus sizes and their distributions: variations in specific energy deposited over a cell population are underestimated if targets are assumed to be uniform in size compared with more realistic variation in target size. Bulk tissue dose differs from [Formula: see text] for nuclei (cytoplasms) by up to [Formula: see text] ([Formula: see text]) across all cell/nucleus sizes, bulk tissues, and incident photon energies, considering a 50 mGy dose level. Overall, results demonstrate the importance of microdosimetric considerations at low doses, and indicate the sensitivity of energy deposition within subcellular targets to incident photon energy, dose level, elemental compositions, and microscopic tissue model.

Estimation of the radiation-induced DNA double-strand breaks number by considering cell cycle and absorbed dose per cell nucleus.

DNA double-strand breaks (DSBs) are thought to be the main cause of cell death after irradiation. In this study, we estimated the probability distribution of the number of DSBs per cell nucleus by considering the DNA amount in a cell nucleus (which depends on the cell cycle) and the statistical variation in the energy imparted to the cell nucleus by X-ray irradiation. The probability estimation of DSB induction was made following these procedures: (i) making use of the Chinese Hamster Ovary (CHO)-K1 cell line as the target example, the amounts of DNA per nucleus in the logarithmic and the plateau phases of the growth curve were measured by flow cytometry with propidium iodide (PI) dyeing; (ii) the probability distribution of the DSB number per cell nucleus for each phase after irradiation with 1.0 Gy of 200 kVp X-rays was measured by means of γ-H2AX immunofluorescent staining; (iii) the distribution of the cell-specific energy deposition via secondary electrons produced by the incident X-rays was calculated by WLTrack (in-house Monte Carlo code); (iv) according to a mathematical model for estimating the DSB number per nucleus, we deduced the induction probability density of DSBs based on the measured DNA amount (depending on the cell cycle) and the calculated dose per nucleus. The model exhibited DSB induction probabilities in good agreement with the experimental results for the two phases, suggesting that the DNA amount (depending on the cell cycle) and the statistical variation in the local energy deposition are essential for estimating the DSB induction probability after X-ray exposure.