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.

Computational modeling and a Geant4-DNA study of the rejoining of direct and indirect DNA damage induced by low energy electrons and carbon ions.

PURPOSE: DNA double-strand breaks (DSBs) created by ionizing radiations are considered as the most detrimental lesion, which could result in the cell death or sterilization. As the empirical evidence gathered from the cellular and molecular radiation biology has demonstrated significant correlations between the initial and lasting levels of DSBs, gaining knowledge into the DSB repair mechanisms proves vital. Much effort has been invested into understanding the mechanisms triggering the repair and processes engaged after irradiation of cells. Given a mechanistic model, we performed - to our knowledge - the first Monte Carlo study of the expected repair kinetics of carbon ions and electrons using on the one hand Geant4-DNA simulations of electrons for benchmarking purposes and on the other hand quantifying the influence of direct and indirect damage. Our objective was to calculate the DSB repair rates using a repair mechanism for G1 and early S phases of the cell cycle in conjunction with simulations of the DNA damage. MATERIALS AND METHODS: Based on Geant4-DNA simulations of DSB damage caused by electrons and carbon ions - using a B-DNA model and a water sphere of 3 µm radius resembling the mean size of human cells - we derived the kinetics of various biochemical repair processes. RESULTS: The overall repair times of carbon ions increased with the DSB complexity. Comparison of the DSB complexity (DSBc) and repair times as a function of carbon-ion energy suggested that the repair time of no specific fraction of DSBs could solely be explained as a function of DSB complexity. CONCLUSION: Analysis of the carbon-ion repair kinetics indicated that, given a fraction of DSBs, decreasing the energy would result in an increase of the repair time. The disagreements of the calculated and experimental repair kinetics for electrons could, among others, be due to larger damage complexity predicted by simulations or created actually by electrons of comparable energies to x-rays. They are also due to the employed repair mechanisms, which introduce no inherent dependence on the radiation type but make direct use of the simulated DSBs.

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.

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

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

Fully integrated Monte Carlo simulation for evaluating radiation induced DNA damage and subsequent repair using Geant4-DNA.

Ionising radiation induced DNA damage and subsequent biological responses to it depend on the radiation's track-structure and its energy loss distribution pattern. To investigate the underlying biological mechanisms involved in such complex system, there is need of predicting biological response by integrated Monte Carlo (MC) simulations across physics, chemistry and biology. Hence, in this work, we have developed an application using the open source Geant4-DNA toolkit to propose a realistic "fully integrated" MC simulation to calculate both early DNA damage and subsequent biological responses with time. We had previously developed an application allowing simulations of radiation induced early DNA damage on a naked cell nucleus model. In the new version presented in this work, we have developed three additional important features: (1) modeling of a realistic cell geometry, (2) inclusion of a biological repair model, (3) refinement of DNA damage parameters for direct damage and indirect damage scoring. The simulation results are validated with experimental data in terms of Single Strand Break (SSB) yields for plasmid and Double Strand Break (DSB) yields for plasmid/human cell. In addition, the yields of indirect DSBs are compatible with the experimental scavengeable damage fraction. The simulation application also demonstrates agreement with experimental data of [Formula: see text]-H2AX yields for gamma ray irradiation. Using this application, it is now possible to predict biological response along time through track-structure MC simulations.

Simulation of Proton-Induced DNA Damage Patterns Using an Improved Clustering Algorithm.

Simulations of deoxyribonucleic acid (DNA) molecular damage use the traversal algorithm that has the disadvantages of being time-consuming, slowly converging, and requiring high-performance computer clusters. This work presents an improved version of the algorithm, "density-based spatial clustering of applications with noise" (DBSCAN), using a KD-tree approach to find neighbors of each point for calculating clustered DNA damage. The resulting algorithm considers the spatial distributions for sites of energy deposition and hydroxyl radical attack, yielding the statistical probability of (single and double) DNA strand breaks. This work achieves high accuracy and high speed at calculating clustered DNA damage that has been induced by proton treatment at the molecular level while running on an i7 quad-core CPU. The simulations focus on the indirect effect generated by hydroxyl radical attack on DNA. The obtained results are consistent with those of other published experiments and simulations. Due to the array of chemical processes triggered by proton treatment, it is possible to predict the effects that different track structures of various energy protons produce on eliciting direct and indirect damage of DNA.

Harnessing radiation to improve immunotherapy: better with particles?

The combination of radiotherapy and immunotherapy is one of the most promising strategies for cancer treatment. Recent clinical results support the pre-clinical experiments pointing to a benefit for the combined treatment in metastatic patients. Charged particle therapy (using protons or heavier ions) is considered one of the most advanced radiotherapy techniques, but its cost remains higher than conventional X-ray therapy. The most important question to be addressed to justify a more widespread use of particle therapy is whether they can be more effective than X-rays in combination with immunotherapy. Protons and heavy ions have physical advantages compared to X-rays that lead to a reduced damage to the immune cells, that are required for an effective immune response. Moreover, densely ionizing radiation may have biological advantages, due to different cell death pathways and release of cytokine mediators of inflammation. We will discuss results in esophageal cancer patients showing that charged particles can reduce the damage to blood lymphocytes compared to X-rays, and preliminary in vitro studies pointing to an increased release of immune-stimulating cytokines after heavy ion exposure. Pre-clinical and clinical studies are ongoing to test these hypotheses.

Modelling variable proton relative biological effectiveness for treatment planning.

Dose in proton radiotherapy is generally prescribed by scaling the physical proton dose by a constant value of 1.1. Relative biological effectiveness (RBE) is defined as the ratio of doses required by two radiation modalities to cause the same level of biological effect. The adoption of an RBE of 1.1. assumes that the biological efficacy of protons is similar to photons, allowing decades of clinical dose prescriptions from photon treatments and protocols to be utilized in proton therapy. There is, however, emerging experimental evidence that indicates that proton RBE varies based on technical, tissue and patient factors. The notion that a single scaling factor may be used to equate the effects of photons and protons across all biological endpoints and doses is too simplistic and raises concern for treatment planning decisions. Here, we review the models that have been developed to better predict RBE variations in tissue based on experimental data as well as using a mechanistic approach.

Effects of indirect actions and oxygen on relative biological effectiveness: estimate of DSB inductions and conversions induced by therapeutic proton beams.

Purpose: This study evaluated the DNA double strand breaks (DSBs) induced by indirect actions and its misrepairs to estimate the relative biological effectiveness (RBE) of proton beams.Materials and methods: From experimental data, DSB induction was evaluated in cells irradiated by 62 MeV proton beams in the presence of dimethylsulphoxide (DMSO) and under hypoxic conditions. The DNA damage yields for calculating the RBE were estimated using Monte Carlo Damage Simulation (MCDS) software. The repair outcomes (correct repairs, mutations and DSB conversions) were estimated using Monte Carlo Excision Repair (MCER) simulations.Results: The values for RBE of 62 MeV protons (LET = 1.051 keV/µm) for DSB induction and enzymatic DSB under aerobic condition (21% O2) was 1.02 and 0.94, respectively, as comparing to 60Co γ-rays (LET = 2.4 keV/µm). DMSO mitigated the inference of indirect action and reduced DSB induction to a greater extent when damaged by protons rather than γ-rays, resulting in a decreased RBE of 0.86. DMSO also efficiently prevented enzymatic DSB yields triggered by proton irradiation and reduced the RBE to 0.83. However, hypoxia (2% O2) produced a similar level of DSB induction with respect to the protons and γ-rays, with a comparable RBE of 1.02.Conclusions: The RBE values of proton beams estimated from DSB induction and enzymatic DSB decreased by 16% and 12%, respectively, in the presence of DMSO. Our findings indicate that the overall effects of DSB induction and enzymatic DSB could intensify the tumor killing, while alleviate normal tissue damage when indirect actions are effectively interrupted.

BIOPHYSICAL SIMULATION TOOL PARTRAC: MODELLING PROTON BEAMS AT THERAPY-RELEVANT ENERGIES.

The biophysical simulation tool PARTRAC has been primarily developed to model radiation physics, chemistry and biology on nanometre to micrometre scales. However, the tool can be applied in simulating radiation effects in an event-by-event manner over macroscopic volumes as well. Benchmark simulations are reported showing that PARTRAC does reproduce the macroscopic Bragg peaks of proton beams, although the penetration depths are underestimated by a few per cent for high-energy beams. PARTRAC also quantifies the increase in DNA damage and its complexity along the beam penetration depth. Enhanced biological effectiveness is predicted in particular within distal Bragg peak parts of therapeutic proton beams.

RADIATION-INDUCED PLASMID DNA DAMAGE: EFFECT OF CONCENTRATION AND LENGTH.

Plasmid DNA is commonly used as a simpler substitute for a cell in studies of early effects of ionizing radiation because it allows to determine yields of primary DNA lesions. Experimental studies often employ plasmids of different lengths, in different concentrations in the aqueous solution. Influence of these parameters on the heavy-ion induced yields of primary DNA damage has been studied, using plasmids pUC19 (2686 bp), pBR322 (4361 bp) and pKLAC2 (9107 bp) in 10 and 50 ng/µl concentration. Results demonstrate the impact of plasmid length, while no significant difference was observed between the two concentrations. The uncertainty of the results is discussed.

Radio-Enhancing Properties of Bimetallic Au:Pt Nanoparticles: Experimental and Theoretical Evidence.

The use of nanoparticles, in combination with ionizing radiation, is considered a promising method to improve the performance of radiation therapies. In this work, we engineered mono- and bimetallic core-shell gold-platinum nanoparticles (NPs) grafted with poly (ethylene glycol) (PEG). Their radio-enhancing properties were investigated using plasmids as bio-nanomolecular probes and gamma radiation. We found that the presence of bimetallic Au:Pt-PEG NPs increased by 90% the induction of double-strand breaks, the signature of nanosize biodamage, and the most difficult cell lesion to repair. The radio-enhancement of Au:Pt-PEG NPs were found three times higher than that of Au-PEG NPs. This effect was scavenged by 80% in the presence of dimethyl sulfoxide, demonstrating the major role of hydroxyl radicals in the damage induction. Geant4-DNA Monte Carlo simulations were used to elucidate the physical processes involved in the radio-enhancement. We predicted enhancement factors of 40% and 45% for the induction of nanosize damage, respectively, for mono- and bimetallic nanoparticles, which is attributed to secondary electron impact processes. This work contributed to a better understanding of the interplay between energy deposition and the induction of nanosize biomolecular damage, being Monte Carlo simulations a simple method to guide the synthesis of new radio-enhancing agents.

[Study of clustered damage in DNA after proton irradiation based on density-based spatial clustering of applications with noise algorithm].

The deoxyribonucleic acid (DNA) molecule damage simulations with an atom level geometric model use the traversal algorithm that has the disadvantages of quite time-consuming, slow convergence and high-performance computer requirement. Therefore, this work presents a density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm based on the spatial distributions of energy depositions and hydroxyl radicals (·OH). The algorithm with probability and statistics can quickly get the DNA strand break yields and help to study the variation pattern of the clustered DNA damage. Firstly, we simulated the transportation of protons and secondary particles through the nucleus, as well as the ionization and excitation of water molecules by using Geant4-DNA that is the Monte Carlo simulation toolkit for radiobiology, and got the distributions of energy depositions and hydroxyl radicals. Then we used the damage probability functions to get the spatial distribution dataset of DNA damage points in a simplified geometric model. The DBSCAN clustering algorithm based on damage points density was used to determine the single-strand break (SSB) yield and double-strand break (DSB) yield. Finally, we analyzed the DNA strand break yield variation trend with particle linear energy transfer (LET) and summarized the variation pattern of damage clusters. The simulation results show that the new algorithm has a faster simulation speed than the traversal algorithm and a good precision result. The simulation results have consistency when compared to other experiments and simulations. This work achieves more precise information on clustered DNA damage induced by proton radiation at the molecular level with high speed, so that it provides an essential and powerful research method for the study of radiation biological damage mechanism.

Development of computational model for cell dose and DNA damage quantification of multicellular system.

Purpose: The aim of this study is to build a computational model to investigate the cell dose and cell DNA damage distribution of a multicellular tissue system under the irradiation.Materials and methods: In this work, we developed a computational model for quantifying cell dose and double strand break (DSB) number in a multicellular system by simulating the radiation transport in 2D and 3D cell culture. The model was based on an open-source radiation transport package, Geant4 with Geant4-DNA physics. First, the computational multicellular system was created using a developed program, CelllMaker. Second, the radiation transport simulation for cells was conducted using Geant4 package with the Geant4-DNA physics to obtain the cellular dose and cellular DSB yield.Results: Using the method described in this work, it is possible to obtain the cellular dose and DNA damage simultaneously. The developed model provides a solution for quantifying the cellular dose and cellular DNA damage which are not easily determined in a radiobiological experiment.Conclusions: With limited validation data for the model, this preliminary study provides a roadmap for building a comprehensive toolkit for simulating cellular dose and DNA damage of multicellular tissue systems.

Optimizing the response, precision, and cost of a DNA double-strand break dosimeter.

We developed a dosimeter that measures biological damage following delivery of therapeutic beams in the form of double-strand breaks (DSBs) to DNA. The dosimeter contains DNA strands that are labeled on one end with biotin and on the other with fluorescein and attached to magnetic microbeads. Following irradiation, a magnet is used to separate broken from unbroken DNA strands. Then, fluorescence is utilized to measure the relative amount of broken DNA and determine the probability for DSB. The long-term goal for this research is to evaluate whether this type of biologically based dosimeter holds any advantages over the conventional techniques. The purpose of this work was to optimize the dosimeter fabrication and usage to enable higher precision for the long-term research goal. More specifically, the goal was to optimize the DNA dosimeter using three metrics: the response, precision, and cost per dosimeter. Six aspects of the dosimeter fabrication and usage were varied and evaluated for their effect on the metrics: (1) the type of magnetic microbeads, (2) the microbead to DNA mass ratio at attachment, (3) the type of suspension buffer used during irradiation, (4) the concentration of the DNA dosimeter during irradiation, (5) the time waited between fabrication and irradiation of the dosimeter, and (6) the time waited between irradiation and read out of the response. In brief, the best results were achieved with the dosimeter when attaching 4.2 µg of DNA with 1 mg of MyOne T1 microbeads and by suspending the microbead-connected DNA strands with 200 µl of phosphate-buffered saline for irradiation. Also, better results were achieved when waiting a day after fabrication before irradiating the dosimeter and also waiting an hour after irradiation to measure the response. This manuscript is meant to serve as guide for others who would like to replicate this DNA dose measurement technique.

Monte Carlo single-cell dosimetry using Geant4-DNA: the effects of cell nucleus displacement and rotation on cellular S values.

Investigation of biological effects of low-dose ionizing radiation at the (sub-) cellular level, which is referred to as microdosimetry, remains a major challenge of today's radiobiology research. Monte Carlo simulation of radiation tracks can provide a detailed description of the physical processes involved in dimensions as small as the critical substructures of the cell. Hereby, in the present study, microdosimetric calculations of cellular S values for mono-energetic electrons and six Auger-emitting radionuclides were performed in single-cell models of liquid water using Geant4-DNA. The effects of displacement and rotation of the nucleus within the cell on the cellular S values were studied in spherical and ellipsoidal geometries. It was found that for the examined electron energies and radionuclides, in the case of nucleus cross-absorption where the radioactivity is either localized in the cytoplasm of the cell or distributed on the cell surface, rotation of the nucleus within the cell affects cellular S values less than displacement of the nucleus. Especially, the considerable differences observed in S(nucleus ← cell surface) values between an eccentric and a concentric cell-nucleus configuration in spherical and ellipsoidal geometries (up to 63% and up to 44%, respectively) suggests that the approximation of concentricity should be used with caution, at least for localized irradiation of the cell membrane by an Auger-emitter in targeted radionuclide cancer therapy. The obtained results, which are based on a more realistic modeling of the cell than was done before, provide more accurate information about nuclear dose. This can be useful for theranostic applications.

MPEXS-DNA, a new GPU-based Monte Carlo simulator for track structures and radiation chemistry at subcellular scale.

PURPOSE: Track structure simulation codes can accurately reproduce the stochastic nature of particle-matter interactions in order to evaluate quantitatively radiation damage in biological cells such as DNA strand breaks and base damage. Such simulations handle large numbers of secondary charged particles and molecular species created in the irradiated medium. Every particle and molecular species are tracked step-by-step using a Monte Carlo method to calculate energy loss patterns and spatial distributions of molecular species inside a cell nucleus with high spatial accuracy. The Geant4-DNA extension of the Geant4 general-purpose Monte Carlo simulation toolkit allows for such track structure simulations and can be run on CPUs. However, long execution times have been observed for the simulation of DNA damage in cells. We present in this work an improvement of the computing performance of such simulations using ultraparallel processing on a graphical processing unit (GPU). METHODS: A new Monte Carlo simulator named MPEXS-DNA, allowing high computing performance by using a GPU, has been developed for track structure and radiolysis simulations at the subcellular scale. MPEXS-DNA physics and chemical processes are based on Geant4-DNA processes available in Geant4 version 10.02 p03. We have reimplemented the Geant4-DNA process codes of the physics stage (electromagnetic processes of charged particles) and the chemical stage (diffusion and chemical reactions for molecular species) for microdosimetry simulation by using the CUDA language. MPEXS-DNA can calculate a distribution of energy loss in the irradiated medium caused by charged particles and also simulate production, diffusion, and chemical interactions of molecular species from water radiolysis to quantitatively assess initial damage to DNA. The validation of MPEXS-DNA physics and chemical simulations was performed by comparing various types of distributions, namely the radial dose distributions for the physics stage, and the G-value profiles for each chemical product and their linear energy transfer dependency for the chemical stage, to existing experimental data and simulation results obtained by other simulation codes, including PARTRAC. RESULTS: For physics validation, radial dose distributions calculated by MPEXS-DNA are consistent with experimental data and numerical simulations. For chemistry validation, MPEXS-DNA can also reproduce G-value profiles for each molecular species with the same tendency as existing experimental data. MPEXS-DNA also agrees with simulations by PARTRAC reasonably well. However, we have confirmed that there are slight discrepancies in G-value profiles calculated by MPEXS-DNA for molecular species such as H2 and H2 O2 when compared to experimental data and PARTRAC simulations. The differences in G-value profiles between MPEXS-DNA and PARTRAC are caused by the different chemical reactions considered. MPEXS-DNA can drastically boost the computing performance of track structure and radiolysis simulations. By using NVIDIA's GPU devices adopting the Volta architecture, MPEXS-DNA has achieved speedup factors up to 2900 against Geant4-DNA simulations with a single CPU core. CONCLUSION: The MPEXS-DNA Monte Carlo simulation achieves similar accuracy to Monte Carlo simulations performed using other codes such as Geant4-DNA and PARTRAC, and its predictions are consistent with experimental data. Notably, MPEXS-DNA allows calculations that are, at maximum, 2900 times faster than conventional simulations using a CPU.

Monte Carlo Simulation of the Oxygen Effect in DNA Damage Induction by Ionizing Radiation.

DNA damage induced by ionizing radiation exposure is enhanced in the presence of oxygen (the "oxygen effect"). Despite its practical importance in radiotherapy, the oxygen effect has largely been excluded from models that predict DNA damage from radiation tracks. A Monte Carlo-based algorithm was developed in MATLAB software to predict DNA damage from physical and chemical tracks through a cell nucleus simulated in Geant4-DNA, taking into account the effects of cellular oxygenation (pO2) on DNA radical chemistry processes. An initial spatial distribution of DNA base and sugar radicals was determined by spatially clustering direct events (that deposited at least 10.79 eV) and hydroxyl radical (•OH) interactions. The oxygen effect was modeled by increasing the efficiency with which sugar radicals from direct-type effects were converted to strand breaks from 0.6 to 1, the efficiency with which sugar radicals from the indirect effect were converted to strand breaks from 0.28 to 1 and the efficiency of base-to-sugar radical transfer from •OH-mediated base radicals from 0 to 0.03 with increasing pO2 from 0 to 760 mmHg. The DNA damage induction algorithm was applied to tracks from electrons, protons and alphas with LET values from 0.2 to 150 keV/µm under different pO2 conditions. The oxygen enhancement ratio for double-strand break induction was 3.0 for low-LET radiation up to approximately 15 keV/µm, after which it gradually decreased to a value of 1.3 at 150 keV/µm. These values were consistent with a range of experimental data published in the literature. The DNA damage yields were verified using experimental data in the literature and results from other theoretical models. The spatial clustering approach developed in this work has low memory requirements and may be suitable for particle tracking simulations with a large number of cells.

Proximity effects in chromosome aberration induction: Dependence on radiation quality, cell type and dose.

It is widely accepted that, in chromosome-aberration induction, the (mis-)rejoining probability of two chromosome fragments depends on their initial distance, r. However, several aspects of these "proximity effects" need to be clarified, also considering that they can vary with radiation quality, cell type and dose. A previous work performed by the BIANCA (BIophysical ANalysis of Cell death and chromosome Aberrations) biophysical model has suggested that, in human lymphocytes and fibroblasts exposed to low-LET radiation, an exponential function of the form exp(-r/r0), which is consistent with free-end (confined) diffusion, describes proximity effects better than a Gaussian function. Herein, the investigation was extended to intermediate- and high-LET. Since the r0 values (0.8 µm for lymphocytes and 0.7 µm for fibroblasts) were taken from the low-LET study, the results were obtained by adjusting only one model parameter, i.e. the yield of "Cluster Lesions" (CLs), where a CL was defined as a critical DNA damage producing two independent chromosome fragments. In lymphocytes, the exponential model allowed reproducing both dose-response curves for different aberrations (dicentrics, centric rings and excess acentrics), and values of F-ratio (dicentrics to centric rings) and G-ratio (interstitial deletions to centric rings). In fibroblasts, a good correspondence was found with the dose-response curves, whereas the G-ratio (and, to a lesser extent, the F-ratio) was underestimated. With increasing LET, F decreased and G increased in both cell types, supporting their role as "fingerprints" of high-LET exposure. A dose-dependence was also found at high LET, where F increased with dose and G decreased, possibly due to inter-track effects. We therefore conclude that, independent of radiation quality, in lymphocytes an exponential function can describe proximity effects at both inter- and intra-chromosomal level; on the contrary, in fibroblasts further studies (experimental and theoretical) are needed to explain the strong bias for intra-arm relative to inter-arm exchanges.

A MONTE CARLO TOOL FOR MULTI-TARGET NANODOSIMETRY.

A Monte Carlo simulation tool has been developed, based on the physical models of the Geant4-DNA extension of Geant4, to study the ionisation pattern of charged particles in a multi-target environment. The tool allows to code easily the geometry to build a simulation with multiple targets, since several parameters can be changed interactively and independently via macro commands. In this work a set of nanometric target spheres is embedded in a cylindrical water phantom 20 nm in height and 40 nm in diameter. The targets are randomly distributed in such a way that they do not overlap and are contained within a smaller cylindrical volume 20 nm in diameter and height. The water phantom is irradiated by ions which are shot parallel to the central axis and randomly distributed over the cross section of the inner cylinder. Two different types of simulations are performed. In one, the penumbra of secondary electrons is fully simulated, in the other the transport of secondary electrons is carried out only if they are produced inside one of the targets, and the electron track is terminated when it leaves the sphere of production. First results are presented and discussed.