Validation and investigation of reactive species yields of Geant4-DNA chemistry models

TOPAS-nBio-Reg: a regression testing system for track structure simulations in TOPAS-nBio

Objective.To develop a regression testing system for TOPAS-nBio: a wrapper of Geant4-DNA, and the radiobiological extension of TOPAS-a Monte Carlo code for the simulation of radiation transport. This regression testing system will be made publicly available on the TOPAS-nBio GitHub page.Approach.A set of seven regression tests were chosen to evaluate the suite of capabilities of TOPAS-nBio from both a physical and chemical point of view. Three different versions of the code were compared: TOPAS-nBio-v2.0 (the previous version), TOPAS-nBio-v3.0 (the current public release), and TOPAS-nBio-v4.0 (the current developer version, planned for future release). The main aspects compared for each test were the differences in execution times, variations from other versions of TOPAS-nBio, and agreement with measurements/in silico data.Main results.Execution times of nBio-v3.0 for all physics tests were faster than those of nBio-v2.0 due to the use of a new Geant4 version. Mean point-to-point differences between TOPAS-nBio versions across all tests fell largely within 5%. The exceptions were the radiolytic yields (Gvalues) ofH2andH2O2, which differed moderately (16% and 10% respectively) when going from nBio-v3.0 to nBio-v4.0. In all cases a good agreement with other experimental/simulated data was obtained.Significance.From a developer point of view, this regression testing system is essential as it allows a more rigorous reporting of the consequences of new version releases on quantities such as the LET orGvalues of chemical species. Furthermore, it enables us to test 'pushes' made to the codebase by collaborators and contributors. From an end-user point of view, users of the software are now able to easily evaluate how changes in the source code, made for their specific application, would affect the results of known quantities.

Intermediate LET-like effect in distal part of proton Bragg peak revealed by track-ends imaging during super-Fricke radiolysis

Upstream of the efficiency of proton or carbon ion beams in cancer therapy, and to optimize hadrontherapy results, we analysed the chemistry of Fricke solutions in track-end of 64-MeV protons and 1.14-GeV carbon ions. An original optical setup is designed to determine the primary track-segment yields along the last millimetres of the ion track with a sub-millimetre resolution. The Fe3+-yield falls in the Bragg peak to (4.9 ± 0.4) × 10-7 mol/J and 1.9 × 10-7 mol/J, under protons and carbon ions respectively. Beyond the Bragg peak, a yield recovery is observed over 1 mm for proton beams. It is attributed to the intermediate-LET of protons in this region where their energy decreases and energy distribution becomes broader, in relation with the longitudinal straggling of the beam. Consequently to this LET decrease in the distal part of the Bragg peak, Fe3+-yield increases. For the first time, this signature is highlighted at the chemical level under proton irradiation. Nevertheless, this phenomenon is not identified for carbon ion beams since their straggling is lower. It would need a greater spatial resolution to be observed.

A new approach for simulating inhomogeneous chemical kinetics

In this paper, inhomogeneous chemical kinetics are simulated by describing the concentrations of interacting chemical species by a linear expansion of basis functions in such a manner that the coupled reaction and diffusion processes are propagated through time efficiently by tailor-made numerical methods. The approach is illustrated through modelling [Formula: see text]- and [Formula: see text]-radiolysis in thin layers of water and at their solid interfaces from the start of the chemical phase until equilibrium was established. The method's efficiency is such that hundreds of such systems can be modelled in a few hours using a single core of a typical laptop, allowing the investigation of the effects of the underlying parameter space. Illustrative calculations showing the effects of changing dose-rate and water-layer thickness are presented. Other simulations are presented which show the approach's capability to solve problems with spherical symmetry (an approximation to an isolated radiolytic spur), where the hollowing out of an initial Gaussian distribution is observed, in line with previous calculations. These illustrative simulations show the generality and the computational efficiency of this approach to solving reaction-diffusion problems. Furthermore, these example simulations illustrate the method's suitability for simulating solid-fluid interfaces, which have received a lot of experimental attention in contrast to the lack of computational studies.

Monte-Carlo techniques for radiotherapy applications I: introduction and overview of the different Monte-Carlo codes

Introduction:

The dose calculation plays a crucial role in many aspects of contemporary clinical radiotherapy treatment planning process. It therefore goes without saying that the accuracy of the dose calculation is of very high importance. The gold standard for absorbed dose calculation is the Monte-Carlo algorithm.

Methods:

This first of two papers gives an overview of the main openly available and supported codes that have been widely used for radiotherapy simulations.

Results:

The paper aims to provide an overview of Monte-Carlo in the field of radiotherapy and point the reader in the right direction of work that could help them get started or develop their existing understanding and use of Monte-Carlo algorithms in their practice.

Conclusions:

It also serves as a useful companion to a curated collection of papers on Monte-Carlo that have been published in this journal.

Monte-Carlo techniques for radiotherapy applications II: equipment and source modelling, dose calculations and radiobiology

Introduction:

This is the second of two papers giving an overview of the use of Monte-Carlo techniques for radiotherapy applications.

Methods:

The first paper gave an introduction and introduced some of the codes that are available to the user wishing to model the different aspects of radiotherapy treatment. It also aims to serve as a useful companion to a curated collection of papers on Monte-Carlo that have been published in this journal.

Results and Conclusions:

This paper focuses on the application of Monte-Carlo to specific problems in radiotherapy. These include radiotherapy and imaging beam production, brachytherapy, phantom and patient dosimetry, detector modelling and track structure calculations for micro-dosimetry, nano-dosimetry and radiobiology.

Radiation exposure of microorganisms living in radioactive mineral springs

The TIRAMISU collaboration gathers expertise from biologists, physicists, radiochemists and geologists within the Zone-Atelier Territoires Uranifères (ZATU) in France to analyze the radiation exposure of microorganisms living in naturally radioactive mineral springs. These springs are small waterbodies that are extremely stable over geological time scales and display different physicochemical and radiological parameters compared to their surroundings. Water and sediment samples collected in 27 mineral springs of the volcanic Auvergne region (Massif Central, France) have been studied for their microbial biodiversity and their radionuclide content. Among the microorganisms present, microalgae (diatoms), widely used as environmental indicators of water quality, have shown to display an exceptional abundance of teratogenic forms in the most radioactive springs studied (radon activity up to 3700 Bq/L). The current work presents a first assessment of the dose received by the diatoms inhabiting these ecosystems. According to ERICA tool, microorganisms living in most of the sampled mineral springs were exposed to dose rates above 10 μGy/h due to the large concentration of radium in the sediments (up to 50 Bq/g). Radiological analyses of water and sediments were used as inputs to Monte Carlo simulations at micro-(GATE) and nano- (Geant4-DNA) scale in order to assess the direct and indirect damages on the diatom DNA.

Monte Carlo simulations of nanodosimetry and radiolytic species production for monoenergetic proton and electron beams: Benchmarking of GEANT4-DNA and LPCHEM codes

PURPOSE

In hadrontherapy, biophysical models can be used to predict the biological effect received by cancerous tissues and organs at risk. The input data of these models generally consist of information on nano/micro dosimetric quantities and, concerning some models, reactive species produced in water radiolysis. In order to fully account for the radiation stochastic effects, these input data have to be provided by Monte Carlo track structure (MCTS) codes allowing to estimate physical, physico-chemical, and chemical effects of radiation at the molecular scale. The objective of this study is to benchmark two MCTS codes, Geant4-DNA and LPCHEM, that are useful codes for estimating the biological effects of ions during radiation therapy treatments.

MATERIAL AND METHODS

In this study we considered the simulation of specific energy spectra for monoenergetic proton beams (10 MeV) as well as radiolysis species production for both electron (1 MeV) and proton (10 MeV) beams with Geant4-DNA and LPCHEM codes. Options 2, 4, and 6 of the Geant4-DNA physics lists have been benchmarked against LPCHEM. We compared probability distributions of energy transfer points in cylindrical nanometric targets (10 nm) positioned in a liquid water box. Then, radiochemical species (· OH, e aq - ${\rm{e}}_{{\rm{aq}}}^ - $ , H 3 O + , H 2 O 2 ${{\rm{H}}_3}{{\rm{O}}^ + },{\rm{\;}}{{\rm{H}}_2}{{\rm{O}}_2}$ , H₂ , and O H - ) ${\rm{O}}{{\rm{H}}^ - }){\rm{\;}}$ yields simulated between 10^-12 and 10^-6 s after irradiation are compared.

RESULTS

Overall, the specific energy spectra and the chemical yields obtained by the two codes are in good agreement considering the uncertainties on experimental data used to calibrate the parameters of the MCTS codes. For 10 MeV proton beams, ionization and excitation processes are the major contributors to the specific energy deposition (larger than 90%) while attachment, solvation, and vibration processes are minor contributors. LPCHEM simulates tracks with slightly more concentrated energy depositions than Geant4-DNA which translates into slightly faster recombination than Geant4-DNA. Relative deviations (C_EV ) with respect to the average of evolution rates of the radical yields between 10^-12 and 10^-6 s remain below 10%. When comparing execution times between the codes, we showed that LPCHEM is faster than Geant4-DNA by a factor of about four for 1000 primary particles in all simulation stages (physical, physico-chemical, and chemical). In multi-thread mode (four threads), Geant4-DNA computing times are reduced but remain slower than LPCHEM by ∼20% up to ∼50%.

CONCLUSIONS

For the first time, the entire physical, physico-chemical, and chemical models of two track structure Monte Carlo codes have been benchmarked along with an extensive analysis on the effects on the water radiolysis simulation. This study opens up new perspectives in using specific energy distributions and radiolytic species yields from monoenergetic ions in biophysical models integrated to Monte Carlo software.

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.

DNA damage modeled with Geant4-DNA: effects of plasmid DNA conformation and experimental conditions

The chemical stage of the Monte Carlo track-structure (MCTS) code Geant4-DNA was extended for its use in DNA strand break (SB) simulations and compared against published experimental data. Geant4-DNA simulations were performed using pUC19 plasmids (2686 base pairs) in a buffered solution of DMSO irradiated by⁶⁰Co or¹³⁷Csγ-rays. A comprehensive evaluation of SSB yields was performed considering DMSO, DNA concentration, dose and plasmid supercoiling. The latter was measured using the super helix density value used in a Brownian dynamics plasmid generation algorithm. The Geant4-DNA implementation of the independent reaction times method (IRT), developed to simulate the reaction kinetics of radiochemical species, allowed to score the fraction of supercoiled, relaxed and linearized plasmid fractions as a function of the absorbed dose. The percentage of the number of SB after •OH + DNA and H• + DNA reactions, referred as SSB efficiency, obtained using MCTS were 13.77% and 0.74% respectively. This is in reasonable agreement with published values of 12% and 0.8%. The SSB yields as a function of DMSO concentration, DNA concentration and super helix density recreated the expected published experimental behaviors within 5%, one standard deviation. The dose response of SSB and DSB yields agreed with published measurements within 5%, one standard deviation. We demonstrated that the developed extension of IRT in Geant4-DNA, facilitated the reproduction of experimental conditions. Furthermore, its calculations were strongly in agreement with experimental data. These two facts will facilitate the use of this extension in future radiobiological applications, aiding the study of DNA damage mechanisms with a high level of detail.

Applications of nanodosimetry in particle therapy planning and beyond

This topical review summarizes underlying concepts of nanodosimetry. It describes the development and current status of nanodosimetric detector technology. It also gives an overview of Monte Carlo track structure simulations that can provide nanodosimetric parameters for treatment planning of proton and ion therapy. Classical and modern radiobiological assays that can be used to demonstrate the relationship between the frequency and complexity of DNA lesion clusters and nanodosimetric parameters are reviewed. At the end of the review, existing approaches of treatment planning based on relative biological effectiveness (RBE) models or dose-averaged linear energy transfer are contrasted with an RBE-independent approach based on nandosimetric parameters. Beyond treatment planning, nanodosimetry is also expected to have applications and give new insights into radiation protection dosimetry.

The reactive oxygen species as pathogenic factors of fragmented microplastics to macrophages

The presence of microplastics in the various food web raised concerns on human health, but little is known about the target cells and mechanism of toxicity of microplastics. In this study, we evaluated the toxicity of microplastics using relevant cell lines to the oral route of exposure. Approximately 100 μm-sized fragment-type polypropylene (PP) and polystyrene (PS) particles were prepared by sieving after pulverization and further applied the accelerated weathering using ultraviolet and heat. Thus, the panel of microplastics includes fresh PP (f-PP), fresh PS (f-PS), weathered PP (w-PP), and weathered PS (w-PS). The spherical PS with a similar size was used as a reference particle. Treatment of all types of PP and PS did not show any toxic effects to the Caco-2 cells and HepG2 cells. However, the treatment of microplastics to THP-1 macrophages showed significant toxicity in the order of f-PS > f-PP > w-PS > w-PP. The weathering process significantly reduced the reactive oxygen species (ROS) generation potential of both microplastics because the weathered microplastics have an increased affinity to bind serum protein which acts as a ROS scavenger. The intrinsic ROS generation potential of microplastics showed a good correlation with the toxicity endpoints including cytotoxicity and pro-inflammatory cytokines in THP-1 macrophages. In conclusion, the results of this study suggest that the target cell type of microplastics via oral administration can be macrophages and the pathogenic factor to THP-1 macrophages is the intrinsic ROS generation potential of microplastics. Nevertheless, the toxic effect of microplastics tested in this study was much less than that of nano-sized particles.

A review of simulation codes and approaches for radiation chemistry

Historically, the field of radiation chemistry began shortly after the discovery of radioactivity, and its development has been closely related to discoveries in other related fields such as radiation and nuclear physics. Radiolysis of water and radiation chemistry have been very important in elucidating how radiation affects living matter and how it induces DNA damage. Nowadays, we recognize the importance of chemistry to understanding the effects of radiation on cells; however, it took several decades to obtain this insight, and much is still unknown. The radiolysis of water and aqueous solutions have been the subject of much experimental and theoretical research for many decades. One important concept closely related to radiation chemistry is radiation track structure. Track structure results from early physical and physicochemical events that lead to a highly non-homogenous distribution of radiolytic species. Because ionizing radiation creates unstable species that are distributed non-homogenously, the use of conventional reaction kinetics methods does not describe this chemistry well. In recent years, several methods have been developed for simulating radiation chemistry. In this review, we give a brief history of the field and the development of the simulation codes. We review the current methods used to simulate radiolysis of water and radiation chemistry, and we describe several radiation chemistry codes and their applications.

Quantitative estimation of track segment yields of water radiolysis species under heavy ions around Bragg peak energies using Geant4-DNA

We evaluate the track segment yield G' of typical water radiolysis products (e_aq^-, ^·OH and H₂O₂) under heavy ions (He, C and Fe ions) using a Monte Carlo simulation code in the Geant4-DNA. Furthermore, we reproduce experimental results of ^·OH of He and C ions around the Bragg peak energies (< 6 MeV/u). In the relatively high energy region (e.g., > 10 MeV/u), the simulation results using Geant4-DNA have agreed with experimental results. However, the G-values of water radiolysis species have not been properly evaluated around the Bragg peak energies, at which high ionizing density can be expected. Around the Bragg peak energy, dense continuous secondary products are generated, so that it is necessary to simulate the radical-radical reaction more accurately. To do so, we added the role of secondary products formed by irradiation. Consequently, our simulation results are in good agreement with experimental results and previous simulations not only in the high-energy region but also around the Bragg peak. Several future issues are also discussed regarding the roles of fragmentation and multi-ionization to realize more realistic simulations.

Scaling parameter of the lethal effect of mammalian cells based on radiation-induced OH radicals: effectiveness of direct action in radiation therapy

We have been studying the effectiveness of direct action, which induces clustered DNA damage leading to cell killing, relative to indirect action. Here a new criterion Direct Ation-Based Biological Effectiveness (DABBLE) is proposed to understand the contribution of direct action for cell killing induced by C ions. DABBLE is defined as the ratio of direct action to indirect action. To derive this ratio, we describe survival curves of mammalian cells as a function of the number of OH radicals produced 1 ps and 100 ns after irradiation, instead of the absorbed dose. By comparing values on the vertical axis of the survival curves at a certain number of OH radicals produced, we successfully discriminate the contribution of direct action induced by C ions from that of indirect action. DABBLE increases monotonically with increasing linear energy transfer (LET) up to 140 keV/μm and then drops, when the survival curves are described by the number of OH radicals 1 ps after irradiation. The trend of DABBLE is in agreement with that of relative biological effectiveness (RBE) of indirect action. In comparison, the value of DABBLE increases monotonically with LET, when the survival curves are described by the number of OH radicals 100 ns after irradiation. This finding implies that the effectiveness of C ion therapy for cancer depends on the contribution of direct action and we can follow the contribution of direct action over time in the chemical phase.

Independent reaction times method in Geant4-DNA: Implementation and performance

PURPOSE

The simulation of individual particle tracks and the chemical stage following water radiolysis in biological tissue is an effective means of improving our knowledge of the physico-chemical contribution to the biological effect of ionizing radiation. However, the step-by-step simulation of the reaction kinetics of radiolytic species is the most time-consuming task in Monte Carlo track-structure simulations, with long simulation times that are an impediment to research. In this work, we present the implementation of the independent reaction times (IRT) method in Geant4-DNA Monte Carlo toolkit to improve the computational efficiency of calculating G-values, defined as the number of chemical species created or lost per 100 eV of deposited energy.

METHODS

The computational efficiency of IRT, as implemented, is compared to that from available Geant4-DNA step-by-step simulations for electrons, protons and alpha particles covering a wide range of linear energy transfer (LET). The accuracy of both methods is verified using published measured data from fast electron irradiations for ^• OH and e aq - for time-dependent G-values. For IRT, simulations in the presence of scavengers irradiated by cobalt-60 γ-ray and 2 MeV protons are compared with measured data for different scavenging capacities. In addition, a qualitative assessment comparing measured LET-dependent G-values with Geant4-DNA calculations in pure liquid water is presented.

RESULTS

The IRT improved the computational efficiency by three orders of magnitude relative to the step-by-step method while differences in G-values by 3.9% at 1 μs were found. At 7 ps, ^• OH and e aq - yields calculated with IRT differed from recent published measured data by 5% ± 4% and 2% ± 4%, respectively. At 1 μs, differences were 9% ± 5% and 6% ± 7% for ^• OH and e aq - , respectively. Uncertainties are one standard deviation. Finally, G-values at different scavenging capacities and LET-dependent G-values reproduced the behavior of measurements for all radiation qualities.

CONCLUSION

The comprehensive validation of the Geant4-DNA capabilities to accurately simulate the chemistry following water radiolysis is an ongoing work. The implementation presented in this work is a necessary step to facilitate performing such a task.

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

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

Mechanisms of nanoparticle radiosensitization

Metal-based nanoparticles applied to potentiating the effects of radiotherapy have drawn significant attention from the research community and are now available clinically. By improving our mechanistic understanding, nanoparticles are likely to evolve to provide very significant improvements in radiotherapy outcomes with only incremental increase in cost. This review critically assesses the inconsistent observations surrounding physical, physicochemical, chemical and biological mechanisms of radiosensitization. In doing so, a number of needs are identified for continuing research and are highlighted. The large degree of variability from one nanoparticle to another emphasizes that it is a mistake to generalize nanoparticle radiosensitizer mechanisms. Nanoparticle formulations should be considered in an analogous way as pharmacological agents and as a broad class of therapeutic agents, needing to be considered with a high degree of individuality with respect to their interactions and ultimate impact on radiobiological response. In the same way that no universal anti-cancer drug exists, it is unlikely that a single nanoparticle formulation will lead to the best therapeutic outcomes for all cancers. The high degree of complexity and variability in mechanistic action provides notable opportunities for nanoparticle formulations to be optimized for specific indications. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Nanotechnology Approaches to Biology > Nanoscale Systems in Biology.

Modelling Spatial Scales of Dose Deposition and Radiolysis Products from Gold Nanoparticle Sensitisation of Proton Therapy in A Cell: From Intracellular Structures to Adjacent Cells

Gold nanoparticle (GNP) enhanced proton therapy is a promising treatment concept offering increased therapeutic effect. It has been demonstrated in experiments which provided indications that reactive species play a major role. Simulations of the radiolysis yield from GNPs within a cell model were performed using the Geant4 toolkit. The effect of GNP cluster size, distribution and number, cell and nuclear membrane absorption and intercellular yields were evaluated. It was found that clusters distributed near the nucleus increased the nucleus yield by 91% while reducing the cytoplasm yield by 7% relative to a disperse distribution. Smaller cluster sizes increased the yield, 200 nm clusters had nucleus and cytoplasm yields 117% and 35% greater than 500 nm clusters. Nuclear membrane absorption reduced the cytoplasm and nucleus yields by 8% and 35% respectively to a permeable membrane. Intercellular enhancement was negligible. Smaller GNP clusters delivered near sub-cellular targets maximise radiosensitisation. Nuclear membrane absorption reduces the nucleus yield, but can damage the membrane providing another potential pathway for biological effect. The minimal effect on adjacent cells demonstrates that GNPs provide a targeted enhancement for proton therapy, only effecting cells with GNPs internalised. The provided quantitative data will aid further experiments and clinical trials.

Chemical Mechanisms of Nanoparticle Radiosensitization and Radioprotection: A Review of Structure-Function Relationships Influencing Reactive Oxygen Species

Metal nanoparticles are of increasing interest with respect to radiosensitization. The physical mechanisms of dose enhancement from X-rays interacting with nanoparticles has been well described theoretically, however have been insufficient in adequately explaining radiobiological response. Further confounding experimental observations is examples of radioprotection. Consequently, other mechanisms have gained increasing attention, especially via enhanced production of reactive oxygen species (ROS) leading to chemical-based mechanisms. Despite the large number of variables differing between published studies, a consensus identifies ROS-related mechanisms as being of significant importance. Understanding the structure-function relationship in enhancing ROS generation will guide optimization of metal nanoparticle radiosensitisers with respect to maximizing oxidative damage to cancer cells. This review highlights the physico-chemical mechanisms involved in enhancing ROS, commonly used assays and experimental considerations, variables involved in enhancing ROS generation and damage to cells and identifies current gaps in the literature that deserve attention. ROS generation and the radiobiological effects are shown to be highly complex with respect to nanoparticle physico-chemical properties and their fate within cells. There are a number of potential biological targets impacted by enhancing, or scavenging, ROS which add significant complexity to directly linking specific nanoparticle properties to a macroscale radiobiological result.

Gold Nanoparticle Enhanced Proton Therapy: Monte Carlo Modeling of Reactive Species' Distributions Around a Gold Nanoparticle and the Effects of Nanoparticle Proximity and Clustering

Gold nanoparticles (GNPs) are promising radiosensitizers with the potential to enhance radiotherapy. Experiments have shown GNP enhancement of proton therapy and indicated that chemical damage by reactive species plays a major role. Simulations of the distribution and yield of reactive species from 10 ps to 1 µs produced by a single GNP, two GNPs in proximity and a GNP cluster irradiated with a proton beam were performed using the Geant4 Monte Carlo toolkit. It was found that the reactive species distribution at 1 µs extended a few hundred nm from a GNP and that the largest enhancement occurred over 50 nm from the nanoparticle. Additionally, the yield for two GNPs in proximity and a GNP cluster was reduced by up to 17% and 60% respectively from increased absorption. The extended range of action from the diffusion of the reactive species may enable simulations to model GNP enhanced proton therapy. The high levels of absorption for a large GNP cluster suggest that smaller clusters and diffuse GNP distributions maximize the total radiolysis yield within a cell. However, this must be balanced against the high local yields near a cluster particularly if the cluster is located adjacent to a biological target.