Influence of track structure and condensed history physics models of Geant4 to nanoscale electron transport in liquid water

High-complexity of DNA double-strand breaks is key for alternative end-joining choice

The repair of DNA double-strand breaks (DSBs) through alternative non-homologous end-joining (alt-NHEJ) pathway significantly contributes to genetic instability. However, the mechanism governing alt-NHEJ pathway choice, particularly its association with DSB complexity, remains elusive due to the absence of a suitable reporter system. In this study, we established a unique Escherichia coli reporter system for detecting complex DSB-initiated alternative end-joining (A-EJ), an alt-NHEJ-like pathway. By utilizing various types of ionizing radiation to generate DSBs with varying degrees of complexity, we discovered that high complexity of DSBs might be a determinant for A-EJ choice. To facilitate efficient repair of high-complexity DSBs, A-EJ employs distinct molecular patterns such as longer micro-homologous junctions and non-templated nucleotide addition. Furthermore, the A-EJ choice is modulated by the degree of homology near DSB loci, competing with homologous recombination machinery. These findings further enhance the understanding of A-EJ/alt-NHEJ pathway choice.

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

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

Physics and small-scale dosimetry of α $\alpha$ -emitters for targeted radionuclide therapy: The case of 211 At $^{211}{\rm At}$

BACKGROUND

Monte Carlo simulations have been considered for a long time the gold standard for dose calculations in conventional radiotherapy and are currently being applied for the same purpose in innovative radiotherapy techniques such as targeted radionuclide therapy (TRT).

PURPOSE

We present in this work a benchmarking study of the latest version of the Transport d'Ions Lourds Dans l'Aqua & Vivo (TILDA-V ) Monte Carlo track structure code, highlighting its capabilities for describing the full slowing down of α $\alpha$ -particles in water and the energy deposited in cells by α $\alpha$ -emitters in the context of TRT.

METHODS

We performed radiation transport simulations of α $\alpha$ -particles (10 keVu - 1 ${\rm u}^{-1}$ -100 MeVu - 1 ${\rm u}^{-1}$ ) in water with TILDA-V and the Particle and Heavy Ion Transport code System (PHITS) version 3.33. We compared the predictions of each code in terms of track parameters (stopping power, range and radial dose profiles) and cellular S-values of the promising radionuclide astatine-211 (211 At $^{211}{\rm At}$ ). Additional comparisons were made with available data in the literature.

RESULTS

The stopping power, range and radial dose profiles of α $\alpha$ -particles computed with TILDA-V were in excellent agreement with other calculations and available data. Overall, minor differences with PHITS were ascribed to phase effects, that is, related to the use of interaction cross sections computed for water vapor or liquid water. However, important discrepancies were observed in the radial dose profiles of monoenergetic α $\alpha$ -particles, for which PHITS results showed a large underestimation of the absorbed dose compared to other codes and experimental data. The cellular S-values of211 At $^{211}{\rm At}$ computed with TILDA-V  agreed within 4% with the values predicted by PHITS and MIRDcell.

CONCLUSIONS

The validation of the TILDA-V code presented in this work opens the possibility to use it as an accurate simulation tool for investigating the interaction of α $\alpha$ -particles in biological media down to the nanometer scale in the context of medical research. The code may help nuclear medicine physicians in their choice of α $\alpha$ -emitters for TRT. Further research will focus on the application of TILDA-V for quantifying radioinduced damage on the deoxyribonucleic acid (DNA) molecule.

Nanoscale gold nanoparticle (GNP)-laden tumor cell model and its use for estimation of intracellular dose from GNP-induced secondary electrons

BACKGROUND

Gold nanoparticles (GNPs) accumulated within tumor cells have been shown to sensitize tumors to radiotherapy. From a physics point of view, the observed GNP-mediated radiosensitization is due to various downstream effects of the secondary electron (SE) production from internalized GNPs such as GNP-mediated dose enhancement. Over the years, numerous computational investigations on GNP-mediated dose enhancement/radiosensitization have been conducted. However, such investigations have relied mostly on simple cellular geometry models and/or artificial GNP distributions. Thus, it is at least desirable, if not necessary, to conduct further investigations using cellular geometry models that properly reflect realistic cell morphology as well as internalized GNP distributions at the nanoscale.

PURPOSE

The primary aim of this study was to develop a nanometer-resolution geometry model of a GNP-laden tumor cell for computational investigations of GNP-mediated dose enhancement/radiosensitization. The secondary aim was to demonstrate the utility of this model by quantifying GNP-induced SE tracks/dose distribution at sub-cellular levels for further validation of a nanoscopic dose point kernel (nDPK) method against full-fledged Geant4 Monte Carlo (MC) simulation.

METHODS

A transmission electron microscopy (TEM) image of a single cell showing cytoplasm, cellular nucleus, and internalized GNPs in the cellular endosome was segmented into sub-cellular levels based on pixel value thresholding. A corresponding material density was allocated to each pixel, and, by adding a thickness, each pixel was transformed to a geometric voxel and imported as a Geant4-acceptable input geometry file. In Geant4-Penelope MC simulation, a clinical 6 MV photon beam was applied, vertically or horizontally to the cell surface, and energy deposition to the cellular nucleus and cytoplasm, due to SEs emitted by internalized GNPs, was scored. Next, nDPK calculations were performed by generating virtual electron tracks from each GNP voxel to all nucleus and cytoplasm voxels. Subsequently, another set of Geant4 simulation was performed with both Penelope and DNA physics models under the geometry closely mimicking in vitro cell irradiation with a clinical 6 MV photon beam, allowing for derivation of nDPK specific to this geometry and further comparison between Gean4 simulation and nDPK method.

RESULTS

The Geant4-calculated SE tracks and associated energy depositions showed significant dependence on photon incidence angle. For perpendicular incidence, nDPK results showed good agreement (average percentage pixel-to-pixel difference of 0.4% for cytoplasm and 0.5% for nucleus) with Geant4 results, while, for parallel incidence, the agreement became worse (-1.7%-0.7% for cytoplasm and -5.5%-0.8% for nucleus). Under the 6 MV cell irradiation geometry, nDPK results showed reasonable agreement (pixel-to-pixel Pearson's product moment correlation coefficient of 0.91 for cytoplasm and 0.98 for nucleus) with Geant4 results.

CONCLUSIONS

The currently developed TEM-based model of a GNP-laden cell offers unprecedented details of realistic intracellular GNP distributions for nanoscopic computational investigations of GNP-mediated dose enhancement/radiosensitization. A benchmarking study performed with this model showed reasonable agreement between Geant4- and nDPK-calculated intracellular dose deposition by SEs emitted from internalized GNPs, especially under perpendicular incidence - a popular cell irradiation geometry and when the Geant4-Penelope physics model was used.

Clonogenic assay and computational modeling using real cell images to study physical enhancement and cellular sensitization induced by metal nanoparticles under MV and kV X-ray irradiation

This study was initiated due to the physically unexplainable tumor controls resulting from metal nanoparticle (MNP) experiments even under MV X-ray irradiation. A more accurate explanation of the mechanism of radiosensitization induced by MNP is warranted, considering both its physical dose enhancement and biological sensitization, as related research is lacking. Thus, we aimed to examine the intricate dynamics involved in MNP-induced radiosensitization. We conducted specifically designed clonogenic assays for the A549 lung cancer cell line with MNP irradiated by 6 MV and 300 kVp X-rays. Two types of MNP were employed: one based on iron oxide, promoting ferroptosis, and the other on gold nanoparticles known for inducing a significant dose enhancement, particularly at low-energy X-rays. We introduced the lethality enhancement factor (LEF) as the fraction in the cell killing attributed to biological sensitization. Subsequently, Monte Carlo simulations were conducted to evaluate the radial dose profiles for each MNP, corresponding to the physical enhancement. Finally, the local effect model was applied to the clonogenic assay results on real cell images. The LEF and the dose enhancement in the cytoplasm were incorporated to increase the accuracy in the average lethal events and, consequently, in the survival fraction. The results reveal an increased cell killing for both of the MNP under MV and kV X-ray irradiation. In both types of MNP, the LEF reveals a biological sensitization evident. The sensitizer enhancement ratio, derived from the calculations, exhibited only 3% and 1% relative differences compared to the conventional linear-quadratic model for gold and ferroptosis inducer nanoparticles, respectively. These findings indicate that MNPs sensitize cells via radiation through mechanisms akin to ferroptosis inducers, not exclusively relying on a physical dose enhancement. Their own contributions to survival fractions were successfully integrated into computational modeling.

Utility of realistic microscopy-based cell models in simulation studies of nanoparticle-enhanced photon radiotherapy

To enhance the effect of radiation on the tumor without increasing the dose to the patient, the combination of high-Z nanoparticles with radiotherapy has been proposed. In this work, we investigate the effects of the physical parameters of nanoparticles (NPs) on the Dose Enhancement Factor (DEF), and on the Sensitive Enhancement Ratio (SER) by applying a version of the Linear Quadratic Model. A method for constructing voxelized realistic cell geometries in Monte Carlo simulations from confocal microscopy images was developed and applied to Gliobastoma Multiforme cell lines (U87 and U373). The comparison of simulations with realistic geometry and spherical geometry shows that there is significant impact on the survival curves obtained for the same irradiation conditions. Using this model, the DEF and the SER are determined as a function of the concentration, size and distribution of gold nanoparticles within the cell. For small NPs,dAuNP= 10 nm, no clear trend in the DEF and SER was observed when the number of NPs within the cell increases. Experimentally, the variable number of NPs measured inside the U373 cells (ranging between 1.48 × 105and 1.19 × 106) also did not influence much the observed cell survival upon irradiation of the cells with a Co-60 source. The same lack of trend is obtained when the Au content in the cell is kept constant, 0.897 mg/g, but the size of the NPs is changed. However, if the number of NPs is kept constant (7.91 × 105) and the size changes, there is a critical diameter above which the dose effect increases significantly. Using the realistic geometries, it was verified that the key parameter for the DEF and the SER enhancement is the volume fraction of Au in the cell, with NP size being a more important parameter than the number of NPs.

Microdosimetric Analysis for Boron Neutron Capture Therapy via Monte Carlo Track Structure Simulation with Modified Lithium Cross-sections

Boron neutron capture therapy (BNCT) is a cellular-level hadron therapy achieving therapeutic effects via the synergistic action of multiple particles, including Lithium, alpha, proton, and photon. However, evaluating the relative biological effectiveness (RBE) in BNCT remains challenging. In this research, we performed a microdosimetric calculation for BNCT using the Monte Carlo track structure (MCTS) simulation toolkit, TOPAS-nBio. This paper reports the first attempt to derive the ionization cross-sections of low-energy (>0.025 MeV/u) Lithium for MCTS simulation based on the effective charge cross-section scalation method and phenomenological double-parameter modification. The fitting parameters λ 1 = 1.101 , λ 2 = 3.486 were determined to reproduce the range and stopping power data from the ICRU report 73. Besides, the lineal energy spectra of charged particles in BNCT were calculated, and the influence of sensitive volume (SV) size was discussed. Condensed history simulation obtained similar results with MCTS when using Micron-SV while overestimating the lineal energy when using Nano-SV. Furthermore, we found that the microscopic boron distribution can significantly affect the lineal energy for Lithium, while the effect for alpha is minimal. Similar results to the published data by PHITS simulation were observed for the compound particles and monoenergetic protons when using micron-SV. Spectra with nano-SV reflected that the different track densities and absorbed doses in the nucleus together result in the dramatic difference in the macroscopic biological response of BPA and BSH. This work and the developed methodology could impact the research fields in BNCT where understanding radiation effects is crucial, such as the treatment planning system, source evaluation, and new boron drug development.

Sub-keV corrections to binary encounter cross section models for electron ionization of liquid water with application to the Geant4-DNA Monte Carlo code

INTRODUCTION

The electron ionization cross section of water is one of the most important input in Monte Carlo studies of cellular radiobiological effects. Analytical cross section models of the binary-encounter type have the potential of reducing simulation time and facilitate application to a variety of biological materials (other than water). The Binary-Encounter-Bethe (BEB) and Binary-Encounter-Dipole (BED) models of NIST are perhaps the most popular of such models giving reliable results for atoms and molecules in the gas-phase over a wide energy range. However, the use of such models to sub-keV electron energies in liquid water raises concerns due to the neglect of condensed phase effects that leads to a significant overestimation when compared to medium-specific dielectric models.

PURPOSE

To modify the BEB and BED models towards better agreement with the recommended low-energy dielectric model of Geant4-DNA (Option 4). To implement the new modifications to the existing BEB model of the Option 6 physics constructor of Geant4-DNA and re-evaluate fundamental transport quantities for sub-keV electrons.

METHODS

In analogy to a Yukawa potential a simple, yet physically-motivated, modification of the Burgess correction term is proposed to account for the reduction of the Coulomb interaction due to the polarizability of the target. The magnitude of the correction is guided by the dielectric-based ionization cross section implemented in Option 4.

RESULTS

Differential, total and stopping ionization cross sections for low-energy electrons in liquid water are presented. When combined with the Vriens correction (which is not included in Option 6), the proposed modification to the BEB and BED models brings the ionization and stopping cross sections in much better agreement against those used in the Option 4 dielectric model of Geant4-DNA, with up to 30% and 10% deviation, respectively. Implementation of the new correction to the Option 6 constructor of Geant4-DNA and re-evaluation of fundamental transport quantities, such as electron penetration ranges and dose-point-kernels, reduced the discrepancies from Option 4 at sub-keV energies from 20 to 100% (or more) to well below 10% in most cases.

CONCLUSIONS

A simple modification to the BEB and BED analytic models was found to improve their performance for sub-keV electrons in liquid water medium. Implementation of the new modification to the Option 6 constructor of Geant4-DNA significantly improved the agreement with the recommended low-energy Option 4 constructor for a variety of fundamental quantities related to electron transport.

Research on the proximity functions of microdosimetry of low energy electrons in liquid water based on different Monte Carlo codes

PURPOSE

The proximity function is an important index in microdosimetry for describing the spatial distribution of energy, which is closely related to the biological effects of organs or tissues in the target area. In this work, the impact of parameters, such as physic models, cut-off energy, and initial energy, on the proximity function are quantitated and compared.

METHODS

According to the track structure (TS) and condensed history (CH) low-energy electromagnetic models, this paper chooses a variety of Monte Carlo (Monte Carlo, MC) codes (Geant4-DNA, PHITS, and Penelope) to simulate the track structure of low-energy electrons in liquid water and evaluates the influence of the electron initial energy, cut-off energy, energy spectrum, and physical model factors on the differential proximity function.

RESULTS

The results show that the initial energy of electrons in the low-energy part (especially less than 1 keV) has a greater impact on the differential proximity function, and the choice of cut-off energy has a greater impact on the differential proximity function corresponding to small radius sites (generally less than 10 nm). The difference in the electronic energy spectrum has little effect on the result, and the proximity functions of different physics models show better consistency under large radius sites.

CONCLUSIONS

This work comprehensively compares the differential proximity functions under different codes by setting a variety of simulation conditions and has basic guiding significance for helping users simulate and analyze the deposition characteristics of microscale electrons according to the selection of an appropriate methodology and cut-off energy.

THE APPLICATION OF NEURAL NETWORK TECHNOLOGY BASED ON MEA-BP ALGORITHM IN THE PREDICTION OF MICRODOSIMETRIC QUALITIES

The most abundant products of the interaction between radiation and matter are low-energy electrons, and the collisions between these electrons and biomolecules are the main initial source of radiation-based biological damage. To facilitate the rapid and accurate quantification of low-energy electrons (0.1-10 keV) in liquid water at different site diameters (1-2000 nm), this study obtained ${\overline{y}}_{\mathrm{F}}$ and ${\overline{y}}_{\mathrm{D}}$data for low-energy electrons under these conditions. This paper proposes a back-propagation (BP) neural network optimized by the mind evolutionary algorithm (MEA) to construct a prediction model and evaluate the corresponding prediction effect. The results show that the ${\overline{y}}_{\mathrm{F}}$ and ${\overline{y}}_{\mathrm{D}}$ values predicted by the MEA-BP neural network algorithm reach a training precision on the order of ${10}^{-8}$. The relative error range between the prediction results of the validated model and the Monte Carlo calculation results is 0.03-5.98% (the error range for single-energy electrons is 0.1-5.98%, and that for spectral distribution electrons is 0.03-4.4%).

Modified Geometry of 106Ru Asymmetric Eye Plaques to Improve Dosimetric Calculations in Ophthalmic Brachytherapy

Ru/Rh asymmetric plaques for ophthalmic brachytherapy have special geometric designs with a cutout intended to prevent irradiation of critical ocular structures proximal to the tumor. In this work, we present new geometric models for PENELOPE+PenEasy Monte Carlo simulations of these applicators, differing from the vendor-reported geometry, that better match their real geometry to assess their dosimetric impact. Simulation results were benchmarked to experimental dosimetric data from radiochromic film measurements, data provided by the manufacturer in the calibration certificates, and other experimental results published in the literature, obtaining, in all cases, better agreement with the modified geometries. The clinical impact of the new geometric models was evaluated by simulating real clinical cases using patient-specific eye models. The cases calculated using the modified geometries presented higher doses to the critical structures proximal to the cutout region. The modified geometric models presented in this work provide a more accurate representation of the asymmetric plaques, greatly improving the agreement between Monte Carlo calculations and experimental measurements. Lack of consideration of accurate geometric models has been shown to be translated into notable increases in dose to organs at risk in clinical cases.

Quantification of Nanoscale Dose Enhancement in Gold Nanoparticle-Aided External Photon Beam Radiotherapy

The recent progress in Nanotechnology has introduced Gold Nanoparticles (AuNPs) as promising radiosensitizing agents in radiation oncology. This work aims to estimate dose enhancement due to the presence of AuNPs inside an irradiated water region through Monte Carlo calculations. The GATE platform was used to simulate 6 MV photon histories generated from a TrueBeam^® linear accelerator with and without a Flattening Filter (FF) and model AuNPs clusters. The AuNPs size, concentration and distribution pattern were examined. To investigate different clinical irradiation conditions, the effect of field size, presence of FF and placement of AuNPs in water were evaluated. The range of Dose Enhancement Factors (DEF = Dose_Au/Dose_Water) calculated in this study is 0.99 ± 0.01-1.26 ± 0.02 depending on photon beam quality, distance from AuNPs surface, AuNPs size and concentration and pattern of distribution. The highest DEF is reported for irradiation using un-flattened photon beams and at close distances from AuNPs. The obtained findings suggest that dose deposition could be increased in regions that represent whole cells or subcellular targets (mitochondria, cell nucleus, etc.). Nevertheless, further and consistent research is needed in order to make a step toward AuNP-aided radiotherapy in clinical practice.

Comparing Geant4 physics models for proton-induced dose deposition and radiolysis enhancement from a gold nanoparticle

Gold nanoparticles (GNPs) are materials that make the tumor cells more radiosensitive when irradiated with ionizing radiation. The present study aimed to evaluate the impact of different physical interaction models on the dose calculations and radiochemical results around the GNP. By applying the Geant4 Monte Carlo (MC) toolkit, a single 50-nm GNP was simulated, which was immersed in a water phantom and irradiated with 5, 50, and 150 MeV proton beams. The present work assessed various parameters including the secondary electron spectra, secondary photon spectra, radial dose distribution (RDD), dose enhancement factor (DEF), and radiochemical yields around the GNP. The results with an acceptable statistical uncertainty of less than 1% indicated that low-energy electrons deriving from the ionization process formed a significant part of the total number of secondary particles generated in the presence of GNP; the Penelope model produced a larger number of these electrons by a factor of about 30%. Discrepancies of the secondary electron spectrum between Livermore and Penelope were more obvious at energies of less than 1 keV and reached the factor of about 30% at energies between 250 eV and 1 keV. The RDDs for Livermore and Penelope models were very similar with small variations within the first 6 nm from NP surface by a factor of 10%. In addition, neither the G-value nor the REF was affected by the choice of physical interaction models with the same energy cut-off. This work illustrated the similarity of the Livermore and Penelope models (within 15%) available in Geant4 for future simulation studies of GNP enhanced proton therapy with physical, physicochemical, and chemical mechanisms.

Review of the Geant4-DNA Simulation Toolkit for Radiobiological Applications at the Cellular and DNA Level

Simple Summary

A brief description of the methodologies to simulate ionizing radiation transport in biologically relevant matter is presented. Emphasis is given to the physical, chemical, and biological models of Geant4-DNA that enable mechanistic radiobiological modeling at the cellular and DNA level, important to improve the efficacy of existing and novel radiotherapeutic modalities for the treatment of cancer.

Abstract

The Geant4-DNA low energy extension of the Geant4 Monte Carlo (MC) toolkit is a continuously evolving MC simulation code permitting mechanistic studies of cellular radiobiological effects. Geant4-DNA considers the physical, chemical, and biological stages of the action of ionizing radiation (in the form of x- and γ-ray photons, electrons and β^±-rays, hadrons, α-particles, and a set of heavier ions) in living cells towards a variety of applications ranging from predicting radiotherapy outcomes to radiation protection both on earth and in space. In this work, we provide a brief, yet concise, overview of the progress that has been achieved so far concerning the different physical, physicochemical, chemical, and biological models implemented into Geant4-DNA, highlighting the latest developments. Specifically, the “dnadamage1” and “molecularDNA” applications which enable, for the first time within an open-source platform, quantitative predictions of early DNA damage in terms of single-strand-breaks (SSBs), double-strand-breaks (DSBs), and more complex clustered lesions for different DNA structures ranging from the nucleotide level to the entire genome. These developments are critically presented and discussed along with key benchmarking results. The Geant4-DNA toolkit, through its different set of models and functionalities, offers unique capabilities for elucidating the problem of radiation quality or the relative biological effectiveness (RBE) of different ionizing radiations which underlines nearly the whole spectrum of radiotherapeutic modalities, from external high-energy hadron beams to internal low-energy gamma and beta emitters that are used in brachytherapy sources and radiopharmaceuticals, respectively.

Quantification of gold nanoparticle photon radiosensitization from direct and indirect effects using a complete human genome single cell model based on Geant4

PURPOSE

To investigate the radiosensitization properties of gold nanoparticles (GNPs) and better understand the intricate deoxyribonucleic acid (DNA) damage induction mechanisms involved in GNP-aided radiotherapy, a single cell model with complete human genome based on the Geant4 Monte Carlo toolkit was applied.

MATERIALS AND METHODS

A Geant4-DNA model was implemented to simulate direct and indirect DNA damage generated in the physical and chemical stages. In the physical stage, a mixed-physics approach was taken by using Geant4-DNA in water and Livermore in gold. Water radiolysis was created posteriorly in the physicochemical and chemical stages to simulate indirect damage from reactions between DNA molecules and OH• radicals. A mono-energetic photon beam (100 keV) and two clinical photon sources (250-kVp, 6-MV flattening-filter free) were simulated for modeling the irradiation of a single cell with or without GNPs. In order to study the effects of GNP size on radiosensitization, 15, 30, and 100 nm GNPs were simulated. The effects of intracellular distribution were simulated using 90-nm GNPs with different characteristics of distribution within the cell. The time dependence of DNA damage enhancement was also studied with chemistry stage simulation end-time no larger than 10 ns.

RESULTS

Double strand break (DSB) enhancement due to direct and indirect action was quantified under different scenarios. Under realistic cellular uptake condition, the 100-nm GNPs had the most significant increase in DSBs: 40.9% and 28.5% for 100 keV and 250-kVp photon irradiation, respectively. The intracellular localization showed differing levels of radiosensitization with a maximum of 64%, 27%, and 6% DSB enhancements for 100 keV, 250-kVp, and 6-MV respectively, when 90-nm GNPs congregate around the nucleus.

CONCLUSION

The results indicate that photon energy, GNP size, and intracellular distribution play an important role in the enhancement of DSB from direct and indirect damage under scenarios close to cell experiments. The radiosensitization effects due to indirect damage are significant and should be considered carefully.

Intercomparison of Geant4 low energy electromagnetic models in 90Y dosimetry

This work shows the comparison between Geant4 low energy electromagnetic physics lists G4EmLi-vermorePhysics, G4EmPenelopePhysics, G4EmLowEPPhysics, and G4EmDNAPhysics_option2 when simulating the energy deposition of low mono-energetic electrons and β^- emitted from ⁹⁰Y isotope. The simulation time and influence of production cut were considered. In the sense of balance between the accuracy and computer resource, G4EmPenelopePhysics can be proposed as the best physics model for our future Treatment Planning System (TPS) for treating liver cancer using ⁹⁰Y microsphere radioembolization therapy.

Computational modeling for the evaluation of suppressed scintillation yields in plastic scintillators using Geant4

The yield of scintillation photons emitted from scintillators is considered to be proportional to the LET (linear energy transfer) which is energy distribution per unit length, in the low-LET domain, but not proportional in the high LET domain due to the suppression yield from the so-called quenching effect. Ogawa et al. proposed a computational method to estimate scintillation yield using Monte Carlo simulations considering the principle of the FRET (fluorescence resonance energy transfer) process, which is a phenomenon of energy transfer between fluorescent molecules. In their study, the track structure simulations could reproduce measured yields of scintillation. However, Ogawa et al.'s model was not suitable for estimating the scintillation yields when the particle energy was low when using condensed history simulations. Therefore, we propose a new method for estimating scintillation yields more accurately using Geant4 to improve the model calculations based on condensed history simulations. We simulated the local energy deposition pattern in a NE102A plastic scintillator to calculate the number of excitors in the microscopic volume for various nuclides (helium to argon ions). The suppressed scintillation yields were estimated using the model calculations of sequential FRET processes while considering the inactivation of the excitors selected as donors of the FRET process. The model calculations successfully reproduced the experimental scintillation yields within 10% error for the lighter ions up to neon. However, when the analysis was repeated for silicon and argon, the maximum error in the scintillation yields increased up to 27%. The proposed computational model for the evaluation of the suppressed scintillation yields emitted from NE102A scintillator irradiated with heavy ions using sequential FRET calculations with condensed history method returned simulated scintillation yields.

Patient-specific microdosimetry: a proof of concept

Microscopic energy deposition distributions from ionizing radiation are used to predict the biological effects of an irradiation and vary depending on biological target size. Ionizing radiation is thought to kill cells or inhibit cell cycling mainly by damaging DNA in the cell nucleus. The size of cells and nuclei depends on tissue type, cell cycle, and malignancy, all of which vary between patients. The aim of this study was to develop methods to perform patient-specific microdosimetry, that being, determining microdosimetric quantities in volumes that correspond to the sizes of cells and nuclei observed in a patient's tissue. A histopathological sample extracted from a stage I lung adenocarcinoma patient was analyzed. A pouring simulation was used to generate a three-dimensional tissue model from cell and nucleus size information determined from the histopathological sample. Microdosimetric distributions including f(y) and d(y) were determined for Co-60,Ir-192,Yb-169 and I-125 in a patient-specific model containing a distribution of cell and nucleus sizes. Fixed radius models and a summation method (where f(y) from many fixed radii models are summed) were compared to the full patient-specific model to evaluate their suitability for fast determination of patient-specific microdosimetric parameters. Fixed radius models do not provide a close approximation of the full patient-specific model y ̅_f or y ̅_d for the lower energy sources investigated, Yb-169 and I-125. The higher energy sources investigated, Co-60 and Ir-192 are less sensitive to target size variation than Yb-169 and I-125. A summation method yields the most accurate approximation of the full model d(y) for all radioisotopes investigated. A summation method allows for the computation of patient-specific microdosimetric distributions with the computing power of a personal computer. With appropriate biological inputs the microdosimetric distributions computed using these methods can yield a patient-specific relative biological effectiveness as part of a multiscale treatment planning approach.

Monte Carlo-based calculation of nano-scale dose enhancement factor and relative biological effectiveness in using different nanoparticles as a radiosensitizer

INTRODUCTION

Nowadays, some nanoparticles (NPs) are known and used as radiosensitizers in radiotherapy and radiobiology, due to their desired biological, physical, and chemical effects on cells. This study aimed to evaluate and compare the dose enhancement factor (DEF) and the biological effectiveness of some common NPs through EGSnrc and MCDS Monte Carlo (MC) simulation codes.

MATERIALS AND METHODS

To evaluate considered NPs' DEF, a single NP with 50 nm diameter was simulated at the center of concentric spheres. NP irradiations were done with 30, 60, and 100 keV photon energies. The secondary electron spectra were scored at the surface of considered NPs, and the dose values were scored at surrounding water-filled spherical shells which were distributed up to 4000 nm from the NP surface. The electron spectra were used in the MCDS code to obtain different initial DNA damages for the calculation of enhanced relative biological effectiveness (eRBE).

RESULTS

By decreasing the photon energy, an increment of DEF was seen for all studied NPs. The maximum DEF at 30, 60, and 100 keV photon energies were respectively related to silver (Ag), gadolinium (Gd), and bismuth (Bi) NPs. The maximum double-strand break (DSB) related (eRBEDSB) values for the 30 keV photon belonged to Ag, while BiNPs showed the maximum values at other photon energies. The minimum eRBEDSB values were also related to iron (Fe) NPs at the entire range of studied photon energies.

CONCLUSIONS

The compared nanoscale physical and biological results of our study can be helpful in the selection of optimum NP as a radiosensitizer in future radiobiological studies. Bi, gold (Au), Ag, and platinum (Pt) NPs had great potential, respectively, as radiosensitizers relative to the other studied NPs.

Multi-scaled Monte Carlo calculation for radon-induced cellular damage in the bronchial airway epithelium

Radon is a leading cause of lung cancer in indoor public and mining workers. Inhaled radon progeny releases alpha particles, which can damage cells in the airway epithelium. The extent and complexity of cellular damage vary depending on the alpha particle's kinetic energy and cell characteristics. We developed a framework to quantitate the cellular damage on the nanometer and micrometer scales at different intensities of exposure to radon progenies Po-218 and Po-214. Energy depositions along the tracks of alpha particles that were slowing down were simulated on a nanometer scale using the Monte Carlo code Geant4-DNA. The nano-scaled track histories in a 5 μm radius and 1 μm-thick cylindrical volume were integrated into the tracking scheme of alpha trajectories in a micron-scale bronchial epithelium segment in the user-written SNU-CDS program. Damage distribution in cellular DNA was estimated for six cell types in the epithelium. Deep-sited cell nuclei in the epithelium would have less chance of being hit, but DNA damage from a single hit would be more serious, because low-energy alpha particles of high LET would hit the nuclei. The greater damage in deep-sited nuclei was due to the 7.69 MeV alpha particles emitted from Po-214. From daily work under 1 WL of radon concentration, basal cells would respond with the highest portion of complex DSBs among the suspected progenitor cells in the most exposed regions of the lung epithelium.

IDDRRA: A novel platform, based on Geant4-DNA to quantify DNA damage by ionizing radiation

PURPOSE

This study proposes a novel computational platform that we refer to as IDDRRA (DNA Damage Response to Ionizing RAdiation), which uses Monte Carlo (MC) simulations to score radiation induced DNA damage. MC simulations provide results of high accuracy on the interaction of radiation with matter while scoring the energy deposition based on state-of-the-art physics and chemistry models and probabilistic methods.

METHODS

The IDDRRA software is based on the Geant4-DNA toolkit together with new tools that were developed for the purpose of this study, including a new algorithm that was developed in Python for the design of the DNA molecules. New classes were developed in C++ to integrate the GUI and produce the simulation's output in text format. An algorithm was also developed to analyze the simulation's output in terms of energy deposition, Single Strand Breaks (SSB), Double Strand Breaks (DSB) and Cluster Damage Sites (CDS). Finally, a new tool was developed to implement probabilistic SSB and DSB repair models using MC techniques.

RESULTS

This article provides the first benchmarks that the user of the IDDRRA tool can use to validate the functionality of the software as well as to provide a starting point to produce different types of DNA simulations. These benchmarks incorporate different kind of particles (e-, e+, protons, electron spectrum) and DNA molecules.

CONCLUSION

We have developed the IDDRRA tool and demonstrated its use to study various aspects of the modeling and simulation of a DNA irradiation experiment. The tool is expandable and can be expanded by other users with new benchmarks and applications based on the user's needs and experience. New functionality will be added over time, including the quantification of the indirect damage.

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.

Report on G4-Med, a Geant4 benchmarking system for medical physics applications developed by the Geant4 Medical Simulation Benchmarking Group

BACKGROUND

Geant4 is a Monte Carlo code extensively used in medical physics for a wide range of applications, such as dosimetry, micro- and nanodosimetry, imaging, radiation protection, and nuclear medicine. Geant4 is continuously evolving, so it is crucial to have a system that benchmarks this Monte Carlo code for medical physics against reference data and to perform regression testing.

AIMS

To respond to these needs, we developed G4-Med, a benchmarking and regression testing system of Geant4 for medical physics.

MATERIALS AND METHODS

G4-Med currently includes 18 tests. They range from the benchmarking of fundamental physics quantities to the testing of Monte Carlo simulation setups typical of medical physics applications. Both electromagnetic and hadronic physics processes and models within the prebuilt Geant4 physics lists are tested. The tests included in G4-Med are executed on the CERN computing infrastructure via the use of the geant-val web application, developed at CERN for Geant4 testing. The physical observables can be compared to reference data for benchmarking and to results of previous Geant4 versions for regression testing purposes.

RESULTS

This paper describes the tests included in G4-Med and shows the results derived from the benchmarking of Geant4 10.5 against reference data.

DISCUSSION

Our results indicate that the Geant4 electromagnetic physics constructor G4EmStandardPhysics_option4 gives a good agreement with the reference data for all the tests. The QGSP_BIC_HP physics list provided an overall adequate description of the physics involved in hadron therapy, including proton and carbon ion therapy. New tests should be included in the next stage of the project to extend the benchmarking to other physical quantities and application scenarios of interest for medical physics.

CONCLUSION

The results presented and discussed in this paper will aid users in tailoring physics lists to their particular application.

Cellular S-value evaluation based on real human cell models using the GATE MC package

Exploring the spatial distribution of the energy loss of ionising radiation at the subcellular level is indispensable for evaluating the radiobiological effects of targeted radionuclide therapy accurately. Believing that S-values are important for obtaining the target dose, the Committee on Medical Internal Radiation Dose (MIRD) proposed a method to obtain the cellular dosimetric parameter. However, most available data on cellular S-values were calculated based on simple geometric models, such as ellipsoids or spheres, which do not accurately reflect biological reality. To investigate the influence of the cellular model on S-values, calculations were performed for two kinds of polygon-surface phantom models of realistic, individual human cells, the lung epithelial cell model (the B2B Phantom model) and the hepatocyte model (the Liver Phantom model), using the Monte Carlo (MC) software package GATE. To analyse the influence of cell geometry on the final S-value, the differences in the S-values between the realistic cell models and simple geometric sphere and ellipsoid models with similar volumes were calculated and compared for six different combinations of source and target regions. The irradiation conditions were 0.01-1.10 MeV monoenergetic electron sources and the Auger electronic therapy nuclides Ga-67, Tc-99m, In-111, I-125 and Tl-201, which are commonly used in nuclear medicine. The S-values calculated in this study are different from the results of the simple geometry models proposed by previous researchers. Two more precise polygon-surface phantom models of realistic, individual human cells were used, which provided more accurate information about the cell dose and will be very useful for the diagnostic application of radiotherapy in the future.

Advances in modelling gold nanoparticle radiosensitization using new Geant4-DNA physics models

Gold nanoparticles have demonstrated significant radiosensitization of cancer treatment with x-ray radiotherapy. To understand the mechanisms at the basis of nanoparticle radiosensitization, Monte Carlo simulations are used to investigate the dose enhancement, given a certain nanoparticle concentration and distribution in the biological medium. Earlier studies have ordinarily used condensed history physics models to predict nanoscale dose enhancement with nanoparticles. This study uses Geant4-DNA complemented with novel track structure physics models to accurately describe electron interactions in gold and to calculate the dose surrounding gold nanoparticle structures at nanoscale level. The computed dose in silico due to a clinical kilovoltage beam and the presence of gold nanoparticles was related to in vitro brain cancer cell survival using the local effect model. The comparison of the simulation results with radiobiological experimental measurements shows that Geant4-DNA and local effect model can be used to predict cell survival in silico in the case of x-ray kilovoltage beams.

Geant4 electromagnetic physics progress

The Geant4 electromagnetic (EM) physics sub-packages are a component of LHC experiment simulations. During long shutdown 2 for LHC, these packages are under intensive development and we report progress of EM physics in Geant4 versions 10.5 and 10.6, which includes faster computation, more accurate EM models, and extensions to the validation suite. New approaches are developed to simulate radiation damage for silicon vertex detectors and for configuration of multiple scattering per detector region. Improvements in user interfaces developed for low-energy and the Geant4-DNA project are used also for LHC simulation optimisation.

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 R_C/R_N 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 R_N/R_C = 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.

Monte Carlo track-structure for the radionuclide Copper-64: characterization of S-values, nanodosimetry and quantification of direct damage to DNA

TOPAS-nBio was used to simulate, collision-to-collision, the complete trajectories of electrons in water generated during the explicit simulation of ⁶⁴Cu decay. S-values and direct damage to the DNA were calculated representing the cell (C) and the cell nucleus (N) with concentric spheres of 5 μm and 4 μm in radius, respectively. The considered 'target'←'source' configurations, including the cell surface (Cs) and cytoplasm (Cy), were: C←C, C←Cs, N←N, N←Cy and N←Cs. Ionization cluster size distributions were also calculated in a cylinder immersed in water corresponding to a DNA segment of 10 base-pairs in length (diameter 2.3 nm, length 3.4 nm), modeling a radioactive point source moving from the central axis to the edge of the cylinder. For that, the first moment (M₁) and cumulative probability of having a cluster size of 2 or more ionizations in the cylindrical volume (F₂) were obtained. Finally, the direct damage to the DNA was estimated by quantifying double-strand breaks (DSBs) using the clustering algorithm DBSCAN. The S-values obtained with TOPAS-nBio for ⁶⁴Cu were 7.879 × 10^-4 ± 5 × 10^-7, 4.351 × 10^-4 ± 6 × 10^-7, 1.442 × 10^-3 ± 1 × 10^-6, 2.596 × 10^-4 ± 8 × 10^-7, 1.127 × 10^-4 ± 4 × 10^-7 Gy Bq-s^-1 for the configurations C←C, C←Cs, N←N, N←Cy and N←Cs, respectively. The difference of these values, compared with previously reported S-values for ⁶⁴Cu with the code MNCP and software MIRDCell, ranged from -4% to -25% for the configurations N←N and N←Cs, respectively. On the other hand, F₂ was maximum with the source at the center of the cylinder 0.373 ± 0.001, and monotonically decreased until reaching a value of 0.058 ± 0.001 at 2.3 nm. The same behavior was observed for M₁ with values ranging from 2.188 ± 0.004 to 0.242 ± 0.002. Finally, the DBSCAN algorithm showed that the mean number of DNA DSBs per decay were 0.187 ± 0.001, 0.0317 ± 0.0005, and 0.0125 ± 0.0002 DSB-(Bq-s)^-1 for the configurations N←N, N←Cs, and N←Cy, respectively. In conclusion, the results of the S-values show that the absorbed dose strongly depends on the distribution of the radionuclide in the cell, the dose being higher when ⁶⁴Cu is internalized in the cell nucleus, which is reinforced by the nanodosimetric study by the presence of DNA DSBs attributable to the Auger electrons emitted during the decay of ⁶⁴Cu.

A microdosimetric analysis of the interactions of mono-energetic neutrons with human tissue

Nuclear reactions induced during high-energy radiotherapy produce secondary neutrons that, due to their carcinogenic potential, constitute an important risk for the development of iatrogenic cancer. Experimental and epidemiological findings indicate a marked energy dependence of neutron relative biological effectiveness (RBE) for carcinogenesis, but little is reported on its physical basis. While the exact mechanism of radiation carcinogenesis is yet to be fully elucidated, numerical microdosimetry can be used to predict the biological consequences of a given irradiation based on its microscopic pattern of energy depositions. Building on recent studies, this work investigated the physics underlying neutron RBE by using the microdosimetric quantity dose-mean lineal energy (y‾_D) as a proxy. A simulation pipeline was constructed to explicitly calculate the y‾_D of radiation fields that consisted of (i) the open source Monte Carlo toolkit Geant4, (ii) its radiobiological extension Geant4-DNA, and (iii) a weighted track-sampling algorithm. This approach was used to study mono-energetic neutrons with initial kinetic energies between 1 eV and 10 MeV at multiple depths in a tissue-equivalent phantom. Spherical sampling volumes with diameters between 2 nm and 1 μm were considered. To obtain a measure of RBE, the neutron y‾_D values were divided by those of 250 keV X-rays that were calculated in the same way. Qualitative agreement was found with published radiation protection factors and simulation data, allowing for the dependencies of neutron RBE on depth and energy to be discussed in the context of the neutron interaction cross sections and secondary particle distributions in human tissue.

Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations

Ionizing radiation is a common tool in medical procedures. Monte Carlo (MC) techniques are widely used when dosimetry is the matter of investigation. The scientific community has invested, over the last 20 years, a lot of effort into improving the knowledge of radiation biology. The present article aims to summarize the understanding of the field of DNA damage response (DDR) to ionizing radiation by providing an overview on MC simulation studies that try to explain several aspects of radiation biology. The need for accurate techniques for the quantification of DNA damage is crucial, as it becomes a clinical need to evaluate the outcome of various applications including both low- and high-energy radiation medical procedures. Understanding DNA repair processes would improve radiation therapy procedures. Monte Carlo simulations are a promising tool in radiobiology studies, as there are clear prospects for more advanced tools that could be used in multidisciplinary studies, in the fields of physics, medicine, biology and chemistry. Still, lot of effort is needed to evolve MC simulation tools and apply them in multiscale studies starting from small DNA segments and reaching a population of cells.

Microdosimetric calculations of the direct DNA damage induced by low energy electrons using the Geant4-DNA Monte Carlo code

To calculate the yield of direct DNA damage induced by low energy electrons using Monte Carlo generated microdosimetric spectra at the nanometer scale and examine the influence of various simulation inputs. The potential of classical microdosimetry to offer a viable and simpler alternative to more elaborate mechanistic approaches for practical applications is discussed. Track-structure simulations with the Geant4-DNA low-energy extension of the Geant4 Monte Carlo toolkit were used for calculating lineal energy spectra in spherical volumes with dimensions relevant to double-strand-break (DSB) induction. The microdosimetric spectra were then used to calculate the yield of simple and clustered DSB based on literature values of the threshold energy of DNA damage. The influence of the different implementations of the dielectric function of liquid water available in Geant4-DNA (Option 2 and Option 4 constructors), as well as the effect of particle tracking cutoff energy and target size are examined. Frequency- and dose-mean lineal energies in liquid-water spheres of 2, 2.3, 2.6, and 3.4 nm diameter, as well as, number of simple and clustered DSB/Gy/cell are presented for electrons over the 100 eV to 100 keV energy range. Results are presented for both the 'default' (Option 2) and 'Ioannina' (Option 4) physics models of Geant4-DNA applying several commonly used tracking cutoff energies (10, 20, 50, 100 eV). Overall, the choice of the physics model and target diameter has a moderate effect (up to ~10%-30%) on the DSB yield whereas the effect of the tracking cutoff energy may be significant (>100%). Importantly, the yield of both simple and clustered DSB was found to vary significantly (by a factor of 2 or more) with electron energy over the examined range. The yields of electron-induced simple and clustered DSB exhibit a strong energy dependence over the 100 eV-100 keV range with implications to radiation quality issues. It is shown that a classical microdosimetry approach for the calculation of DNA damage based on lineal energy spectra in nanometer-size targets predicts comparable results to computationally intensive mechanistic approaches which use detailed atomistic DNA geometries, thus, offering a relatively simple and robust alternative for some practical applications.

The influence of Geant4-DNA toolkit parameters on electron microdosimetric track structure

The influence of different physical process factors on tracks of low-energy electrons in liquid water was analyzed and evaluated based on the Geant4-DNA toolkit of Geant4 version 10.4, and it provides theoretical support for obtaining the basic parameters of microdosimetry concerned with radiotherapy and radiation protection. According to the characteristics of different models, five physics constructors of Geant4-DNA toolkit were selected to simulate monoenergetic electrons in microscopic scale. Details of track structure of different Geant4-DNA physics constructors were compared, including total number of interaction processes, number and energy percentage of excitation and ionization; analyzing the impacts of mean lineal energy of several factors, including Geant4-DNA physics constructors, initial energy, radius of scoring spheres, interaction processes and cut-off energy. Firstly, 'G4EmDNAPhysics' (hereinafter referred to as 'dna') is well consistent with 'G4EmDNAPhysics_option 2' (hereinafter referred to as 'option 2'), and 'G4EmDNAPhysics_option 4' (hereinafter referred to as 'option 4') is well consistent with 'G4EmDNAPhysics_option 5' (hereinafter referred to as 'option 5'); secondly, there are differences for the information of track structure and mean lineal energy between 'option 2' 'option 4' and 'G4EmDNAPhysics_option 6' (hereinafter referred to as 'option 6'); thirdly, the influence of the model on the mean lineal energy decreases with the increase of the radius of the scoring spheres, whereas mean lineal energy increases as the tracking cut increases. Several alternative discrete physics constructors of Geant4-DNA are comprehensively discussed overlaying multiple perspectives under different conditions in this work.

Intercomparison of dose enhancement ratio and secondary electron spectra for gold nanoparticles irradiated by X-rays calculated using multiple Monte Carlo simulation codes

PURPOSE

Targeted radiation therapy has seen an increased interest in the past decade. In vitro and in vivo experiments showed enhanced radiation doses due to gold nanoparticles (GNPs) to tumors in mice and demonstrated a high potential for clinical application. However, finding a functionalized molecular formulation for actively targeting GNPs in tumor cells is challenging. Furthermore, the enhanced energy deposition by secondary electrons around GNPs, particularly by short-ranged Auger electrons is difficult to measure. Computational models, such as Monte Carlo (MC) radiation transport codes, have been used to estimate the physical quantities and effects of GNPs. However, as these codes differ from one to another, the reliability of physical and dosimetric quantities needs to be established at cellular and molecular levels, so that the subsequent biological effects can be assessed quantitatively.

METHODS

In this work, irradiation of single GNPs of 50 nm and 100 nm diameter by X-ray spectra generated by 50 and 100 peak kilovoltages was simulated for a defined geometry setup, by applying multiple MC codes in the EURADOS framework.

RESULTS

The mean dose enhancement ratio of the first 10 nm-thick water shell around a 100 nm GNP ranges from 400 for 100 kVp X-rays to 600 for 50 kVp X-rays with large uncertainty factors up to 2.3.

CONCLUSIONS

It is concluded that the absolute dose enhancement effects have large uncertainties and need an inter-code intercomparison for a high quality assurance; relative properties may be a better measure until more experimental data is available to constrain the models.

Ionizing Radiation and Complex DNA Damage: From Prediction to Detection Challenges and Biological Significance

Biological responses to ionizing radiation (IR) have been studied for many years, generally showing the dependence of these responses on the quality of radiation, i.e., the radiation particle type and energy, types of DNA damage, dose and dose rate, type of cells, etc. There is accumulating evidence on the pivotal role of complex (clustered) DNA damage towards the determination of the final biological or even clinical outcome after exposure to IR. In this review, we provide literature evidence about the significant role of damage clustering and advancements that have been made through the years in its detection and prediction using Monte Carlo (MC) simulations. We conclude that in the future, emphasis should be given to a better understanding of the mechanistic links between the induction of complex DNA damage, its processing, and systemic effects at the organism level, like genomic instability and immune responses.

Radio-enhancement effects by radiolabeled nanoparticles

In cancer radiation therapy, dose enhancement by nanoparticles has to date been investigated only for external beam radiotherapy (EBRT). Here, we report on an in silico study of nanoparticle-enhanced radiation damage in the context of internal radionuclide therapy. We demonstrate the proof-of-principle that clinically relevant radiotherapeutic isotopes (i.e. 213Bi, 223Ra, 90Y, 177Lu, 67Cu, 64Cu and 89Zr) labeled to clinically relevant superparamagnetic iron oxide nanoparticles results in enhanced radiation damage effects localized to sub-micron scales. We find that radiation dose can be enhanced by up to 20%, vastly outperforming nanoparticle dose enhancement in conventional EBRT. Our results demonstrate that in addition to the favorable spectral characteristics of the isotopes and their proximity to the nanoparticles, clustering of the nanoparticles results in a nonlinear collective effect that amplifies nanoscale radiation damage effects by electron-mediated inter-nanoparticle interactions. In this way, optimal radio-enhancement is achieved when the inter-nanoparticle distance is less than the mean range of the secondary electrons. For the radioisotopes studied here, this corresponds to inter-nanoparticle distances <50 nm, with the strongest effects within 20 nm. The results of this study suggest that radiolabeled nanoparticles offer a novel and potentially highly effective platform for developing next-generation theranostic strategies for cancer medicine.