Track structure modeling in liquid water: A review of the Geant4-DNA very low energy extension of the Geant4 Monte Carlo simulation toolkit

Analysis of Relative Biological Effectiveness of Proton Beams and Iso-effective Dose Profiles Using Geant4

BACKGROUND

The assessment of RBE quantity in the treatment of cancer tumors with proton beams in treatment planning systems (TPS) is of high significance. Given the significance of the issue and the studies conducted in the literature, this quantity is fixed and is taken as equal to 1.1.

OBJECTIVE

The main objective of this study was to assess RBE quantity of proton beams and their variations in different depths of the tumor. This dependency makes RBE values used in TPS no longer be fixed as they depend on the depth of the tumor and therefore this dependency causes some changes in the physical dose profile.

MATERIALS AND METHODS

The energy spectrum of protons was measured at various depths of the tumor using proton beam simulations and well as the complete simulation of a cell to a pair of DNA bases through Monte Carlo GEANT4. The resulting energy spectrum was used to estimate the number of double-strand breaks generated in cells. Finally, RBE values were calculated in terms of the penetration depth in the tumor.

RESULTS AND CONCLUSION

The simulation results show that the RBE value not fixed terms of the depth of the tumor and it differs from the clinical value of 1.1 at the end of the dose profile and this will lead to a non-uniform absorbed dose profile. Therefore, to create a uniform impact dose area, deep-finishing systems need to be designed by taking into account deep RBE values.

Measurements and simulations of microscopic damage to DNA in water by 30 keV electrons: A general approach applicable to other radiation sources and biological targets

The determination of the microscopic dose-damage relationship for DNA in an aqueous environment is of a fundamental interest for dosimetry and applications in radiation therapy and protection. We combine geant4 particle-scattering simulations in water with calculations concerning the movement of biomolecules to obtain the energy deposit in the biologically relevant nanoscopic volume. We juxtaposition these results to the experimentally determined damage to obtain the dose-damage relationship at a molecular level. This approach is tested for an experimentally challenging system concerning the direct irradiation of plasmid DNA (pUC19) in water with electrons as primary particles. Here a microscopic target model for the plasmid DNA based on the relation of lineal energy and radiation quality is used to calculate the effective target volume. It was found that on average fewer than two ionizations within a 7.5-nm radius around the sugar-phosphate backbone are sufficient to cause a single strand break, with a corresponding median lethal energy deposit being E_{1/2}=6±4 eV. The presented method is applicable for ionizing radiation (e.g., γ rays, x rays, and electrons) and a variety of targets, such as DNA, proteins, or cells.

Radial dose distributions from carbon ions of therapeutic energies calculated with Geant4-DNA

We report on radial dose distributions [Formula: see text] for carbon ions calculated with Geant4-DNA code. These distributions characterize ion tracks on a nanoscale and are important for understanding the biological effects of ion beams. We present data for carbon ion beams in the energy range from 20 to 400 MeV u^-1. To approximate the Monte Carlo results, we developed a simple formula that combines the well-known inverse square distance dependence with a factor correcting [Formula: see text] for small [Formula: see text]. The proposed formula can be used to calculate [Formula: see text] for any energy within the above range and for distances [Formula: see text] from 1 nm to 2 μm with a maximum error not exceeding 14%. This range of distances corresponds to a dose range of over seven orders of magnitude. Differences between our results and those of previously published analytical models are discussed.

Dependence of gold nanoparticle radiosensitization on cell geometry

The radiosensitization effect of gold nanoparticles (GNPs) has been demonstrated both in vitro and in vivo in radiation therapy. The purpose of this study was to systematically assess the biological effectiveness of GNPs distributed in the extracellular media for realistic cell geometries. TOPAS-nBio simulations were used to determine the nanometre-scale radial dose distributions around the GNPs, which were subsequently used to predict the radiation dose response of cells surrounded by GNPs. MDA-MB-231 human breast cancer cells and F-98 rat glioma cells were used as models to assess different cell geometries by changing (1) the cell shape, (2) the nucleus location within the cell, (3) the size of GNPs, and (4) the photon energy. The results show that the sensitivity enhancement ratio (SER) was increased up to a factor of 1.2 when the location of the nucleus is close to the cell membrane for elliptical-shaped cells. Heat-maps of damage-likelihoods show that most of the lethal events occur in the regions of the nuclei closest to the membrane, potentially causing highly clustered damage patterns. The effect of the GNP size on radiosensitization was limited when the GNPs were located outside the cell. The improved modelling of the cell geometry was shown to be crucial because the dose enhancement caused by GNPs falls off rapidly with distance from the GNPs. We conclude that radiosensitization can be achieved for kV photons even without cellular uptake of GNPs when the nucleus is shifted towards the cell membrane. Furthermore, damage was found to concentrate in a small region of the nucleus in close proximity to the extracellular, GNP-laden region.

Accelerated Monte Carlo simulation on the chemical stage in water radiolysis using GPU

The accurate simulation of water radiolysis is an important step to understand the mechanisms of radiobiology and quantitatively test some hypotheses regarding radiobiological effects. However, the simulation of water radiolysis is highly time consuming, taking hours or even days to be completed by a conventional CPU processor. This time limitation hinders cell-level simulations for a number of research studies. We recently initiated efforts to develop gMicroMC, a GPU-based fast microscopic MC simulation package for water radiolysis. The first step of this project focused on accelerating the simulation of the chemical stage, the most time consuming stage in the entire water radiolysis process. A GPU-friendly parallelization strategy was designed to address the highly correlated many-body simulation problem caused by the mutual competitive chemical reactions between the radiolytic molecules. Two cases were tested, using a 750 keV electron and a 5 MeV proton incident in pure water, respectively. The time-dependent yields of all the radiolytic species during the chemical stage were used to evaluate the accuracy of the simulation. The relative differences between our simulation and the Geant4-DNA simulation were on average 5.3% and 4.4% for the two cases. Our package, executed on an Nvidia Titan black GPU card, successfully completed the chemical stage simulation of the two cases within 599.2 s and 489.0 s. As compared with Geant4-DNA that was executed on an Intel i7-5500U CPU processor and needed 28.6 h and 26.8 h for the two cases using a single CPU core, our package achieved a speed-up factor of 171.1-197.2.

A local effect model-based interpolation framework for experimental nanoparticle radiosensitisation data

A local effect model (LEM)-based framework capable of interpolating nanoparticle-enhanced photon-irradiated clonogenic cell survival fraction measurements as a function of nanoparticle concentration was developed and experimentally benchmarked for gold nanoparticle (AuNP)-doped bovine aortic endothelial cells (BAECs) under superficial kilovoltage X-ray irradiation. For three different superficial kilovoltage X-ray spectra, the BAEC survival fraction response was predicted for two different AuNP concentrations and compared to experimental data. The ability of the developed framework to predict the cell survival fraction trends is analysed and discussed. This developed framework is intended to fill in the existing gaps of individual cell line response as a function of NP concentration under photon irradiation and assist the scientific community in planning future pre-clinical trials of high Z nanoparticle-enhanced photon radiotherapy.

Validation of the radiobiology toolkit TOPAS-nBio in simple DNA geometries

Computational simulations offer a powerful tool for quantitatively investigating radiation interactions with biological tissue and can help bridge the gap between physics, chemistry and biology. The TOPAS collaboration is tackling this challenge by extending the current Monte Carlo tool to allow for sub-cellular in silico simulations in a new extension, TOPAS-nBio. TOPAS wraps and extends the Geant4 Monte Carlo simulation toolkit and the new extension allows the modeling of particles down to vibrational energies (∼2eV) within realistic biological geometries. Here we present a validation of biological geometries available in TOPAS-nBio, by comparing our results to two previously published studies. We compare the prediction of strand breaks in a simple linear DNA strand from TOPAS-nBio to a published Monte Carlo track structure simulation study. While TOPAS-nBio confirms the trend in strand break generation, it predicts a higher frequency of events below an energy of 17.5eV compared to the alternative Monte Carlo track structure study. This is due to differences in the physics models used by each code. We also compare the experimental measurement of strand breaks from incident protons in DNA plasmids to TOPAS-nBio simulations. Our results show good agreement of single and double strand breaks predicting a similar increase in the strand break yield with increasing LET.

Simulating the Impact of the Natural Radiation Background on Bacterial Systems: Implications for Very Low Radiation Biological Experiments

At very low radiation dose rates, the effects of energy depositions in cells by ionizing radiation is best understood stochastically, as ionizing particles deposit energy along tracks separated by distances often much larger than the size of cells. We present a thorough analysis of the stochastic impact of the natural radiative background on cells, focusing our attention on E. coli grown as part of a long term evolution experiment in both underground and surface laboratories. The chance per day that a particle track interacts with a cell in the surface laboratory was found to be 6 × 10-5 day-1, 100 times less than the expected daily mutation rate for E. coli under our experimental conditions. In order for the chance cells are hit to approach the mutation rate, a gamma background dose rate of 20 μGy hr-1 is predicted to be required.

Radiation damage to neuronal cells: Simulating the energy deposition and water radiolysis in a small neural network

Radiation damage to the central nervous system (CNS) has been an on-going challenge for the last decades primarily due to the issues of brain radiotherapy and radiation protection for astronauts during space travel. Although recent findings revealed a number of molecular mechanisms associated with radiation-induced impairments in behaviour and cognition, some uncertainties exist in the initial neuronal cell injury leading to the further development of CNS malfunction. The present study is focused on the investigation of early biological damage induced by ionizing radiations in a sample neural network by means of modelling physico-chemical processes occurring in the medium after exposure. For this purpose, the stochastic simulation of incident particle tracks and water radiation chemistry was performed in realistic neuron phantoms constructed using experimental data on cell morphology. The applied simulation technique is based on using Monte-Carlo processes of the Geant4-DNA toolkit. The calculations were made for proton, ¹²C, and ⁵⁶Fe particles of different energy within a relatively wide range of linear energy transfer values from a few to hundreds of keV/μm. The results indicate that the neuron morphology is an important factor determining the accumulation of microscopic radiation dose and water radiolysis products in neurons. The estimation of the radiolytic yields in neuronal cells suggests that the observed enhancement in the levels of reactive oxygen species may potentially lead to oxidative damage to neuronal components disrupting the normal communication between cells of the neural network.

Simulations and measurements in scanning electron microscopes at low electron energy

The advent of new imaging technologies in Scanning Electron Microscopy (SEM) using low energy (0-2 keV) electrons has brought about new ways to study materials at the nanoscale. It also brings new challenges in terms of understanding electron transport at these energies. In addition, reduction in energy has brought new contrast mechanisms producing images that are sometimes difficult to interpret. This is increasing the push for simulation tools, in particular for low impact energies of electrons. The use of Monte Carlo calculations to simulate the transport of electrons in materials has been undertaken by many authors for several decades. However, inaccuracies associated with the Monte Carlo technique start to grow as the energy is reduced. This is not simply associated with inaccuracies in the knowledge of the scattering cross-sections, but is fundamental to the Monte Carlo technique itself. This is because effects due to the wave nature of the electron and the energy band structure of the target above the vacuum energy level become important and these are properties which are difficult to handle using the Monte Carlo method. In this review we briefly describe the new techniques of scanning low energy electron microscopy and then outline the problems and challenges of trying to understand and quantify the signals that are obtained. The effects of charging and spin polarised measurement are also briefly explored. SCANNING 38:802-818, 2016. © 2016 Wiley Periodicals, Inc.

Implementation of new physics models for low energy electrons in liquid water in Geant4-DNA

A new alternative set of elastic and inelastic cross sections has been added to the very low energy extension of the Geant4 Monte Carlo simulation toolkit, Geant4-DNA, for the simulation of electron interactions in liquid water. These cross sections have been obtained from the CPA100 Monte Carlo track structure code, which has been a reference in the microdosimetry community for many years. They are compared to the default Geant4-DNA cross sections and show better agreement with published data. In order to verify the correct implementation of the CPA100 cross section models in Geant4-DNA, simulations of the number of interactions and ranges were performed using Geant4-DNA with this new set of models, and the results were compared with corresponding results from the original CPA100 code. Good agreement is observed between the implementations, with relative differences lower than 1% regardless of the incident electron energy. Useful quantities related to the deposited energy at the scale of the cell or the organ of interest for internal dosimetry, like dose point kernels, are also calculated using these new physics models. They are compared with results obtained using the well-known Penelope Monte Carlo code.

Evaluation of the microscopic dose enhancement for nanoparticle-enhanced Auger therapy

The aim of this study is to investigate the dosimetric characteristics of nanoparticle-enhanced Auger therapy. Monte Carlo (MC) simulations were performed to assess electron energy spectra and dose enhancement distributions around a nanoparticle. In the simulations, two types of nanoparticle structures were considered: nanoshell and nanosphere, both of which were assumed to be made of one of five elements (Fe, Ag, Gd, Au, and Pt) in various sizes (2-100 nm). Auger-electron emitting radionuclides (I-125, In-111, and Tc-99m) were simulated within a nanoshell or on the surface of a nanosphere. For the most promising combination of Au and I-125, the maximum dose enhancement was up to 1.3 and 3.6 for the nanoshell and the nanosphere, respectively. The dose enhancement regions were restricted within 20-100 nm and 0-30 nm distances from the surface of Au nanoshell and nanosphere, respectively. The dose enhancement distributions varied with sizes of nanoparticles, nano-elements, and radionuclides and thus should be carefully taken into account for biological modeling. If the nanoparticles are accumulated in close proximity to the biological target, this new type of treatment can deliver an enhanced microscopic dose to the target (e.g. DNA). Therefore, we conclude that Auger therapy combined with nanoparticles could have the potential to provide a better therapeutic effect than conventional Auger therapy alone.

Review of Geant4-DNA applications for micro and nanoscale simulations

Emerging radiotherapy treatments including targeted particle therapy, hadron therapy or radiosensitisation of cells by high-Z nanoparticles demand the theoretical determination of radiation track structure at the nanoscale. This is essential in order to evaluate radiation damage at the cellular and DNA level. Since 2007, Geant4 offers physics models to describe particle interactions in liquid water at the nanometre level through the Geant4-DNA Package. This package currently provides a complete set of models describing the event-by-event electromagnetic interactions of particles with liquid water, as well as developments for the modelling of water radiolysis. Since its release, Geant4-DNA has been adopted as an investigational tool in kV and MV external beam radiotherapy, hadron therapies using protons and heavy ions, targeted therapies and radiobiology studies. It has been benchmarked with respect to other track structure Monte Carlo codes and, where available, against reference experimental measurements. While Geant4-DNA physics models and radiolysis modelling functionalities have already been described in detail in the literature, this review paper summarises and discusses a selection of representative papers with the aim of providing an overview of a) geometrical descriptions of biological targets down to the DNA size, and b) the full spectrum of current micro- and nano-scale applications of Geant4-DNA.