Review of Geant4-DNA applications for micro and nanoscale simulations

Incerti, S.; Douglass, Michael; Penfold, Scott; Guatelli, Susanna; Bezak, Eva

doi:10.1016/j.ejmp.2016.09.007

Cited by 112 publications

(88 citation statements)

References 111 publications

(175 reference statements)

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“…Future developments of Geant4-DNA to include physics models for metals would further improve the results of this study in close proximity to GNP. 47, 48 …”

Section: Discussionmentioning

confidence: 99%

Dependence of gold nanoparticle radiosensitization on cell geometry

Sung

McNamara

et al. 2017

Nanoscale

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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.

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“…Future developments of Geant4-DNA to include physics models for metals would further improve the results of this study in close proximity to GNP. 47, 48 …”

Section: Discussionmentioning

confidence: 99%

Dependence of gold nanoparticle radiosensitization on cell geometry

Sung

McNamara

et al. 2017

Nanoscale

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“…Modeling the biophysical processes associated with radiation‐induced cellular damage, eventually leading to cell death, is a complex challenge which requires a detailed description of the physical, chemical, and biological interactions of ionizing radiation with organic media . In particular, for more than 20 yr, track structure codes have been developed in order to accurately simulate physical interactions at the DNA and cellular scale, underlining the necessity to carefully simulate energy deposition for the prediction of critical biological lesions.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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PurposeTrack structure simulation codes can accurately reproduce the stochastic nature of particle–matter interactions in order to evaluate quantitatively radiation damage in biological cells such as DNA strand breaks and base damage. Such simulations handle large numbers of secondary charged particles and molecular species created in the irradiated medium. Every particle and molecular species are tracked step‐by‐step using a Monte Carlo method to calculate energy loss patterns and spatial distributions of molecular species inside a cell nucleus with high spatial accuracy. The Geant4‐DNA extension of the Geant4 general‐purpose Monte Carlo simulation toolkit allows for such track structure simulations and can be run on CPUs. However, long execution times have been observed for the simulation of DNA damage in cells. We present in this work an improvement of the computing performance of such simulations using ultraparallel processing on a graphical processing unit (GPU).MethodsA new Monte Carlo simulator named MPEXS‐DNA, allowing high computing performance by using a GPU, has been developed for track structure and radiolysis simulations at the subcellular scale. MPEXS‐DNA physics and chemical processes are based on Geant4‐DNA processes available in Geant4 version 10.02 p03. We have reimplemented the Geant4‐DNA process codes of the physics stage (electromagnetic processes of charged particles) and the chemical stage (diffusion and chemical reactions for molecular species) for microdosimetry simulation by using the CUDA language. MPEXS‐DNA can calculate a distribution of energy loss in the irradiated medium caused by charged particles and also simulate production, diffusion, and chemical interactions of molecular species from water radiolysis to quantitatively assess initial damage to DNA. The validation of MPEXS‐DNA physics and chemical simulations was performed by comparing various types of distributions, namely the radial dose distributions for the physics stage, and the G‐value profiles for each chemical product and their linear energy transfer dependency for the chemical stage, to existing experimental data and simulation results obtained by other simulation codes, including PARTRAC.ResultsFor physics validation, radial dose distributions calculated by MPEXS‐DNA are consistent with experimental data and numerical simulations. For chemistry validation, MPEXS‐DNA can also reproduce G‐value profiles for each molecular species with the same tendency as existing experimental data. MPEXS‐DNA also agrees with simulations by PARTRAC reasonably well. However, we have confirmed that there are slight discrepancies in G‐value profiles calculated by MPEXS‐DNA for molecular species such as H2 and H2O2 when compared to experimental data and PARTRAC simulations. The differences in G‐value profiles between MPEXS‐DNA and PARTRAC are caused by the different chemical reactions considered. MPEXS‐DNA can drastically boost the computing performance of track structure and radiolysis simulations. By using NVIDIA's GPU devices adopting the...

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“…The available geometries range from the micro-scale (cells, organelles) to the nano-scale (DNA molecule). Users also have the choice of performing condensed history simulations within micrometer geometries using the Geant4 physical models (e.g., dose to a cell) or advanced track structure simulations using the physical models in Geant4-DNA (e.g., strand break damage to a DNA segment) [9]. …”

Section: Introductionmentioning

confidence: 99%

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

et al. 2017

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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 (~ 2 eV) 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 17.5 eV 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.

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Review of Geant4-DNA applications for micro and nanoscale simulations

Cited by 112 publications

References 111 publications

Dependence of gold nanoparticle radiosensitization on cell geometry

Dependence of gold nanoparticle radiosensitization on cell geometry

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

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

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