Time-Dependent Density-Functional Theory for Determining the Electron-Capture Cross Section for Protons Impacting on Atoms and Molecules.

The use of the Time-Dependent Density-Functional Theory (TDDFT) has increased in the atomic collision field. Calculating the electron-capture cross section (ECCS) for protons is an important question in hadrontherapy and plasma physics, among other areas. In previous studies, it was shown that the approach based on the Local Density Approximation (LDA) fails in the 1-50 keV region, requiring the use of the Optimized Effective Potential (OEP) method. In this work, the ECCS values for 1-50 keV protons impacting on isolated hydrogen, carbon, nitrogen, oxygen, and nitrogenous atoms were determined using the TDDFT. It is shown that adding the Self Interaction Correction to the LDA (LDA-Sic) allows obtaining results close to those provided by the OEP and experiments, with the advantage that the LDA-Sic consumes less computational time. In addition, it was demonstrated that it is imperative to include the spin correction for the specific helium and oxygen cases, in order to get good results for the ECCS using the TDDFT. Theoretical results obtained in this work show excellent agreement with experimental values.

Prediction of DNA rejoining kinetics and cell survival after proton irradiation for V79 cells using Geant4-DNA.

PURPOSE: Track structure Monte Carlo (MC) codes have achieved successful outcomes in the quantitative investigation of radiation-induced initial DNA damage. The aim of the present study is to extend a Geant4-DNA radiobiological application by incorporating a feature allowing for the prediction of DNA rejoining kinetics and corresponding cell surviving fraction along time after irradiation, for a Chinese hamster V79 cell line, which is one of the most popular and widely investigated cell lines in radiobiology. METHODS: We implemented the Two-Lesion Kinetics (TLK) model, originally proposed by Stewart, which allows for simulations to calculate residual DNA damage and surviving fraction along time via the number of initial DNA damage and its complexity as inputs. RESULTS: By optimizing the model parameters of the TLK model in accordance to the experimental data on V79, we were able to predict both DNA rejoining kinetics at low linear energy transfers (LET) and cell surviving fraction. CONCLUSION: This is the first study to demonstrate the implementation of both the cell surviving fraction and the DNA rejoining kinetics with the estimated initial DNA damage, in a realistic cell geometrical model simulated by full track structure MC simulations at DNA level and for various LET. These simulation and model make the link between mechanistic physical/chemical damage processes and these two specific biological endpoints.

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

PURPOSE: We explored different technologies to minimize simulation time of the Monte-Carlo method for track generation following the Geant4-DNA processes for electrons in water. METHODS: A GPU software tool is developed for electron track simulations. A similar CPU version is also developed using the same collision models. CPU simulations were carried out on a single user desktop computer and on the computing grid France Grilles using 10 and 100 computing nodes. Computing time results for CPU, GPU, and grid simulations are compared with those using Geant4-DNA processes. RESULTS: The CPU simulations better performs when the number of electrons is less than 104 with 100 eV initial energy, this number decreases as the energy increases. The GPU simulations gives better results when the number of electrons is more than 104 with initial energy of 100 eV, this number decreases to 103 for electrons with 10KeV and increases back with higher energy. The use of the grid introduces an additional queuing time which slows down the overall simulation performance. Thus, the Grid gives better performance when the number of electrons is over 105 with initial energy of 10KeV, and this number decreases as the energy increases. CONCLUSIONS: The CPU is best suited for small numbers of primary incident electrons. The GPU is best suited when the number of primary incident particles occupies sufficient resources on GPU card in order to get an important computing power. The grid is best suited for simulations with high number of primary incident electrons with high initial energy.

Evaluation of the Reax Force-Field for Studying the Collision of an Energetic Proton with the DNA.

The early DNA damage induced by ionizing radiation depends on how ionizing particles transfer energy to this molecule and the surrounding medium, mostly water. In preliminary studies, we found that the energy transferred by a 4 keV proton to a cytosine-guanine base pair in a classical simulation collision using the ReaxFF potential is much smaller than that obtained by a quantum calculation using time-dependent density functional theory (TDDFT). We observed that there are two main reasons for that: no accurate force-field for this situation and problems while dealing with the proton charge during the collision. Here, we only focus on the interaction potential. We calibrated the van der Waals energy term of the ReaxFF potential using TDDFT calculations and a genetic algorithm, specifically for the interaction of a proton with the DNA constituent atoms (carbon, hydrogen, phosphorus, nitrogen, and oxygen). We obtained a significant improvement in the interaction potential and, consequently, in the scattering angle of the proton colliding with the target atoms in question. However, we conclude that despite the improvement for the force-field and scattering angle, the classical charge equilibration method should also be improved to properly describe the proton-DNA collision process.

A TD-DFT-Based Study on the Attack of the OH· Radical on a Guanine Nucleotide.

Heavy charged particles induce severe damage in DNA, which is a radiobiological advantage when treating radioresistant tumors. However, these particles can also induce cancer in humans exposed to them, such as astronauts in space missions. This damage can be directly induced by the radiation or indirectly by the attack of free radicals mainly produced by water radiolysis. We previously studied the impact of a proton on a DNA base pair, using the Time Dependent-Density Functional Theory (TD-DFT). In this work, we go a step further and study the attack of the OH· radical on the Guanine nucleotide to unveil how this molecule subsequently dissociates. The OH· attack on the H1', H2', H3', and H5' atoms in the guanine was investigated using the Ehrenfest dynamics within the TD-DFT framework. In all cases, the hydrogen abstraction succeeded, and the subsequent base pair dissociation was observed. The DNA dissociates in three major fragments: the phosphate group, the deoxyribose sugar, and the nitrogenous base, with slight differences, no matter which hydrogen atom was attacked. Hydrogen abstraction occurs at about 6 fs, and the nucleotide dissociation at about 100 fs, which agrees with our previous result for the direct proton impact on the DNA. These calculations may be a reference for adjusting reactive force fields so that more complex DNA structures can be studied using classical molecular dynamics, including both direct and indirect DNA damage.

Application of High-Z Gold Nanoparticles in Targeted Cancer Radiotherapy-Pharmacokinetic Modeling, Monte Carlo Simulation and Radiobiological Effect Modeling.

High-Z gold nanoparticles (AuNPs) conjugated to a targeting antibody can help to improve tumor control in radiotherapy while simultaneously minimizing radiotoxicity to adjacent healthy tissue. This paper summarizes the main findings of a joint research program which applied AuNP-conjugates in preclinical modeling of radiotherapy at the Klinikum rechts der Isar, Technical University of Munich and Helmholtz Zentrum München. A pharmacokinetic model of superparamagnetic iron oxide nanoparticles was developed in preparation for a model simulating the uptake and distribution of AuNPs in mice. Multi-scale Monte Carlo simulations were performed on a single AuNP and multiple AuNPs in tumor cells at cellular and molecular levels to determine enhancements in the radiation dose and generation of chemical radicals in close proximity to AuNPs. A biologically based mathematical model was developed to predict the biological response of AuNPs in radiation enhancement. Although simulations of a single AuNP demonstrated a clear dose enhancement, simulations relating to the generation of chemical radicals and the induction of DNA strand breaks induced by multiple AuNPs showed only a minor dose enhancement. The differences in the simulated enhancements at molecular and cellular levels indicate that further investigations are necessary to better understand the impact of the physical, chemical, and biological parameters in preclinical experimental settings prior to a translation of these AuNPs models into targeted cancer radiotherapy.

A Geant4-DNA Evaluation of Radiation-Induced DNA Damage on a Human Fibroblast.

Accurately modeling the radiobiological mechanisms responsible for the induction of DNA damage remains a major scientific challenge, particularly for understanding the effects of low doses of ionizing radiation on living beings, such as the induction of carcinogenesis. A computational approach based on the Monte Carlo technique to simulate track structures in a biological medium is currently the most reliable method for calculating the early effects induced by ionizing radiation on DNA, the primary cellular target of such effects. The Geant4-DNA Monte Carlo toolkit can simulate not only the physical, but also the physico-chemical and chemical stages of water radiolysis. These stages can be combined with simplified geometric models of biological targets, such as DNA, to assess direct and indirect early DNA damage. In this study, DNA damage induced in a human fibroblast cell was evaluated using Geant4-DNA as a function of incident particle type (gammas, protons, and alphas) and energy. The resulting double-strand break yields as a function of linear energy transfer closely reproduced recent experimental data. Other quantities, such as fragment length distribution, scavengeable damage fraction, and time evolution of damage within an analytical repair model also supported the plausibility of predicting DNA damage using Geant4-DNA.The complete simulation chain application "molecularDNA", an example for users of Geant4-DNA, will soon be distributed through Geant4.

Microdosimetric calculations for radionuclides emitting ß and α particles and Auger electrons.

This work focuses on the calculation of S-values and radial energy profiles for radionuclides emitting high (Y-90, Sr-89), medium (Re-186, Sm-153) and low-energy (Er-169, Lu-177) ß-particles, Auger electrons (In-111, Ga-67, I-123) and α-particles (At-211, Ac-225). Simulations were performed using the EGSnrc and GEANT4-DNA Monte Carlo (MC) codes for a spherical cell geometry. S-values were computed using decay spectra available in literature for Tc-99m and In-111. To investigate the effect on S-value when the same emission spectrum is used in two different MC codes. Internal modules of the MC codes were used to simulate the decay of other radionuclides mentioned above. Radial energy profiles for uniformly distributed radioactive sources in the cell nucleus and cytoplasm were calculated and results were compared with the literature. For S-values calculated using the same emission spectrum, the results showed good agreement with each other and with the literature. Whereas, the S-values calculated using the internal decay data of the MC codes, for instance, for Ga-67 and Y-90, showed discrepancies up to 40%. Radial energy profiles were also different from those reported in the literature. Our results show that well validated radiation emission spectra must be used for such calculations and internal decay spectra of MC codes should be used with caution. The normalized probability density functions must be used to sample points uniformly into spherical volumes and the methodology proposed here can be used to correctly determine radial energy profiles.

Determination of fast neutron RBE using a fully mechanistic computational model.

This work presents a model previously developed for estimating relative biological effectiveness (RBE) associated with high-LET particles. It is based on the combination of Monte Carlo simulations of particle interactions when traversing an atomic resolution DNA geometrical model. In addition, the model emulates the induction of lethal damage from the interaction of two sublethal lesions, taken as double-strand breaks. The Geant4-DNA package was used for simulations with liquid water as the transport medium. The RBE of neutron beams with energies ranging from 0.1 MeV up to 14 MeV was studied. The model succeeded in reproducing the general behavior of RBE as a function of neutron energy, including the RBE peak reported by experiments at approximately 0.4 MeV. Furthermore, the results of the model agree rather well with some experimental works. However, our results underestimate RBE for neutron energies above approximately 5 MeV due to the current limitations of Geant4-DNA for the tracking of heavy ions below 0.5 MeV/u.

Assessment of Radio-Induced Damage in Endothelial Cells Irradiated with 40 kVp, 220 kVp, and 4 MV X-rays by Means of Micro and Nanodosimetric Calculations.

The objective of this work was to study the differences in terms of early biological effects that might exist between different X-rays energies by using a mechanistic approach. To this end, radiobiological experiments exposing cell monolayers to three X-ray energies were performed in order to assess the yields of early DNA damage, in particular of double-strand breaks (DSBs). The simulation of these irradiations was set in order to understand the differences in the obtained experimental results. Hence, simulated results in terms of microdosimetric spectra and early DSB induction were analyzed and compared to the experimental data. Human umbilical vein endothelial cells (HUVECs) were irradiated with 40, 220 kVp, and 4 MV X-rays. The Geant4 Monte Carlo simulation toolkit and its extension Geant4-DNA were used for the simulations. Microdosimetric calculations aiming to determine possible differences in the variability of the energy absorbed by the irradiated cell population for those photon spectra were performed on 10,000 endothelial cell nuclei representing a cell monolayer. Nanodosimetric simulations were also carried out using a computation chain that allowed the simulation of physical, physico-chemical, and chemical stages on a single realistic endothelial cell nucleus model including both heterochromatin and euchromatin. DNA damage was scored in terms of yields of prompt DSBs per Gray (Gy) and per giga (109) base pair (Gbp) and DSB complexity was derived in order to be compared to experimental data expressed as numbers of histone variant H2AX (γ-H2AX) foci per cell. The calculated microdosimetric spread in the irradiated cell population was similar when comparing between 40 and 220 kVp X-rays and higher when comparing with 4 MV X-rays. Simulated yields of induced DSB/Gy/Gbp were found to be equivalent to those for 40 and 220 kVp but larger than those for 4 MV, resulting in a relative biological effectiveness (RBE) of 1.3. Additionally, DSB complexity was similar between the considered photon spectra. Simulated results were in good agreement with experimental data obtained by IRSN (Institut de radioprotection et de sûreté nucléaire) radiobiologists. Despite differences in photon energy, few differences were observed when comparing between 40 and 220 kVp X-rays in microdosimetric and nanodosimetric calculations. Nevertheless, variations were observed when comparing between 40/220 kVp and 4 MV X-rays. Thanks to the simulation results, these variations were able to be explained by the differences in the production of secondary electrons with energies below 10 keV.

Computational approach to determine the relative biological effectiveness of fast neutrons using the Geant4-DNA toolkit and a DNA atomic model from the Protein Data Bank.

This study proposes an innovative approach to estimate relative biological effectiveness (RBE) of fast neutrons using the Geant4 toolkit. The Geant4-DNA version cannot track heavy ions below 0.5 MeV/nucleon. In order to explore the impact of this issue, secondary particles are simulated instead of the primary low-energy neutrons. The Evaluated Nuclear Data File library is used to determine the cross sections for the elastic and inelastic interactions of neutrons with water and to find the contribution of each secondary particle spectrum. Two strategies are investigated in order to find the best possible approach and results. The first one takes into account only light particles, protons produced from elastic scattering, and α particles from inelastic scattering. Geantino particles are shot instead of heavy ions; hence all heavy ions are considered in the simulations, though their physical effects on DNA not. The second strategy takes into account all the heavy and light ions, although heavy ions cannot be tracked down to very low energies (E<0.5 MeV/nucleon). Our model is based on the combination of an atomic resolution DNA geometrical model and a Monte Carlo simulation toolkit for tracking particles. The atomic coordinates of the DNA double helix are extracted from the Protein Data Bank. Since secondary particle spectra are used instead of simulating the interaction of neutrons explicitly, this method reduces the computation times dramatically. Double-strand break induction is used as the end point for the estimation of the RBE of fast neutrons. ^{60}Co Î³ rays are used as the reference radiation quality. Both strategies succeed in reproducing the behavior of the RBE_{max} as a function of the incident neutron energy ranging from 0.1 to 14 MeV, including the position of its peak. A comparison of the behavior of the two strategies shows that for neutrons with energies less than 0.7 MeV, the effect of heavy ions would not be very significant, but above 0.7 MeV, heavy ions have an important role in neutron RBE.

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%.

Accounting for radiation-induced indirect damage on DNA with the Geant 4-DNA code.

The use of Monte Carlo (MC) simulations remains a powerful tool to study the biological effects induced by ionizing radiation on living beings. Several MC codes are commonly used in research fields such as nanodosimetry, radiotherapy, radiation protection, and space radiation. This work presents an enhancement of an existing model [1] for radiobiological purposes, to account for the indirect DNA damage induced by ionizing particles. The Geant4-DNA simulation toolkit was used to simulate the physical, pre-chemical, and chemical stages of early DNA damage induced by protons and α-particles. Liquid water was used as the medium for simulations. Two phase-space files were generated, one containing the energy deposition events and another with the position of chemical species produced by water radiolysis from 0.1 ps up to 1 ns. These files were used as input in the radiobiological code that contains the genetic material model with atomic resolution, consisting of several copies of 30 nm chromatin fibers. The B-DNA configuration was used. This work focused on the indirect damage produced by the hydroxyl radical (OH) attack on the sugar-phosphate group. The approach followed to account for the indirect DNA damage was the same as those used by other radiobiological codes [2,3]. The critical parameter considered here was the reaction radius, which was calculated from the Smoluchowski's diffusion equation. Single, double, and total strand break yields produced by direct, indirect, and mixed mechanisms are reported. The obtained results are consistent with experimental and calculation data sets published in the literature.

Targeted alpha therapy with 212Pb or 225Ac: Change in RBE from daughter migration.

Targeted α-therapy (TAT) could be delivered early to patients who are at a high-risk for developing brain metastases, targeting the areas of the vasculature where tumor cells are penetrating into the brain. We have utilized a Monte Carlo model representing brain vasculature to calculate physical dose and DNA damage from the α-emitters 225Ac and 212Pb. The micron-scale dose distributions from all radioactive decay products were modeled in Geant4, including the eV-scale interactions using the Geant4-DNA models. These interactions were then superimposed on an atomic-scale DNA model to estimate strand break yields. In addition to 225Ac having a higher dose per decay than 212Pb, it also has a double strand break yield per decay that is 4.7 ±â€¯0.5 times that of 212Pb. However, the efficacy of both nuclides depends on retaining the daughter nuclei at the target location in the brain vasculature. The relative biological effectiveness (RBE) of 225Ac and 212Pb are similar when the entire decay chains are included, with maxima of 2.7 ±â€¯0.6 and 2.5 ±â€¯0.5 (respectively), and RBE values of about 2 to a depth of 80 µm. If the initial daughter is lost, the RBE of 212Pb is completely reduced to 1 or lower and the RBE of 225Ac is approximately 2 only for the first 40 µm.

Dosimetric evaluation of radionuclides for VCAM-1-targeted radionuclide therapy of early brain metastases.

Brain metastases develop frequently in patients with breast cancer, and present a pressing therapeutic challenge. Expression of vascular cell adhesion molecule 1 (VCAM-1) is upregulated on brain endothelial cells during the early stages of metastasis and provides a target for the detection and treatment of early brain metastases. The aim of this study was to use a model of early brain metastasis to evaluate the efficacy of α-emitting radionuclides, 149Tb, 211At, 212Pb, 213Bi and 225Ac; ß-emitting radionuclides, 90Y, 161Tb and 177Lu; and Auger electron (AE)-emitters 67Ga, 89Zr, 111In and 124I, for targeted radionuclide therapy (TRT). METHODS: Histologic sections and two photon microscopy of mouse brain parenchyma were used to inform a cylindrical vessel geometry using the Geant4 general purpose Monte Carlo (MC) toolkit with the Geant4-DNA low energy physics models. Energy deposition was evaluated as a radial function and the resulting phase spaces were superimposed on a DNA model to estimate double-strand break (DSB) yields for representative ß- and α-emitters, 177Lu and 212Pb. Relative biological effectiveness (RBE) values were determined by only evaluating DNA damage due to physical interactions. RESULTS: 177Lu produced 2.69 ± 0.08 DSB per GbpGy, without significant variation from the lumen of the vessel to a radius of 100 µm. The DSB yield of 212Pb included two local maxima produced by the 6.1 MeV and 8.8 MeV α-emissions from decay products, 212Bi and 212Po, with yields of 7.64 ± 0.12 and 9.15 ± 0.24 per GbpGy, respectively. Given its higher DSB yield 212Pb may be more effective for short range targeting of early micrometastatic lesions than 177Lu. CONCLUSION: MC simulation of a model of early brain metastases provides invaluable insight into the potential efficacy of α-, ß- and AE-emitting radionuclides for TRT. 212Pb, which has the attributes of a theranostic radionuclide since it can be used for SPECT imaging, showed a favorable dose profile and RBE.

TDDFT-Based Study on the Proton-DNA Collision.

The interaction of heavy charged particles with DNA is of interest for hadrontherapy and the aerospace industry. Here, a time-dependent density functional theory study on the interaction of a 4 keV proton with an isolated DNA base pair (bp) was carried out. Ehrenfest dynamics was used to study the evolution of the system up to about 193 fs. It was observed that the dissociation of the target occurs between 80 and 100 fs. The effect of bp linking to the DNA double helix was emulated by fixing the four O3' atoms responsible for the attachment. The bp tends to dissociate into its main components, namely, the phosphate groups, sugars, and nitrogenous bases. A central impact with an energy transfer of 17.9 eV only produces a base damage while keeping the backbone intact. An impact on a phosphate group with an energy transfer of about 60 eV leads to a backbone break at that site together with a base damage, and the opposite backbone site integrity is kept. As the whole system is perturbed during this collision, no atom remains passive. These results suggest that base damage accompanies all backbone breaks as the hydrogen bonds that keep bases together are much weaker that those between the other components of the DNA.

On the consistency of Monte Carlo track structure DNA damage simulations.

PURPOSE: Monte Carlo track structures (MCTS) simulations have been recognized as useful tools for radiobiological modeling. However, the authors noticed several issues regarding the consistency of reported data. Therefore, in this work, they analyze the impact of various user defined parameters on simulated direct DNA damage yields. In addition, they draw attention to discrepancies in published literature in DNA strand break (SB) yields and selected methodologies. METHODS: The MCTS code Geant4-DNA was used to compare radial dose profiles in a nanometer-scale region of interest (ROI) for photon sources of varying sizes and energies. Then, electron tracks of 0.28 keV-220 keV were superimposed on a geometric DNA model composed of 2.7 × 10(6) nucleosomes, and SBs were simulated according to four definitions based on energy deposits or energy transfers in DNA strand targets compared to a threshold energy ETH. The SB frequencies and complexities in nucleosomes as a function of incident electron energies were obtained. SBs were classified into higher order clusters such as single and double strand breaks (SSBs and DSBs) based on inter-SB distances and on the number of affected strands. RESULTS: Comparisons of different nonuniform dose distributions lacking charged particle equilibrium may lead to erroneous conclusions regarding the effect of energy on relative biological effectiveness. The energy transfer-based SB definitions give similar SB yields as the one based on energy deposit when ETH ≈ 10.79 eV, but deviate significantly for higher ETH values. Between 30 and 40 nucleosomes/Gy show at least one SB in the ROI. The number of nucleosomes that present a complex damage pattern of more than 2 SBs and the degree of complexity of the damage in these nucleosomes diminish as the incident electron energy increases. DNA damage classification into SSB and DSB is highly dependent on the definitions of these higher order structures and their implementations. The authors' show that, for the four studied models, different yields are expected by up to 54% for SSBs and by up to 32% for DSBs, as a function of the incident electrons energy and of the models being compared. CONCLUSIONS: MCTS simulations allow to compare direct DNA damage types and complexities induced by ionizing radiation. However, simulation results depend to a large degree on user-defined parameters, definitions, and algorithms such as: DNA model, dose distribution, SB definition, and the DNA damage clustering algorithm. These interdependencies should be well controlled during the simulations and explicitly reported when comparing results to experiments or calculations.