Microdosimetry of electrons in liquid water using the low-energy models of Geant4

Kyriakou, Ioanna; Emfietzoglou, Dimitris; Ivanchenko, V. N.; Bordage, Marie‐Claude; Guatelli, Susanna; Lazarakis, Peter; Tran, H.N.; Incerti, S.

doi:10.1063/1.4992076

Cited by 82 publications

(78 citation statements)

References 68 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Regarding the configuration where the cytoplasm is the source, differences are larger especially for the lowest incident energies: “option 4” differs from “option 2” by less than 5% down to 3 keV and “option 6” differs from “option 2” by less than 10% down to about 4 keV. This overall agreement between Geant4‐DNA constructors has been previously observed when studying the distribution of energy deposition in small spheres of liquid water larger than a few hundreds of nanometers in diameter . S‐values for these two configurations have been calculated by the MIRD Committee and are also shown in Fig.…”

Section: Resultssupporting

confidence: 66%

“…Since Geant4 version 10.2 released in 2016, “option 4” offers alternative discrete physics models to “option 2” (default) for electron transport in liquid water in the 10 eV–10 keV energy range. “Option 4” (developed at the University of Ioannina) provides updated cross sections for electron‐impact excitation and ionization in liquid water, and an alternative elastic scattering model . Similar to “option 2”, inelastic cross sections are calculated from Eq.…”

Section: Geant4‐dna Physics Constructorsmentioning

confidence: 99%

“…It was mainly developed to explain to users how to simulate microdosimetry spectra of lineal energy (usually denoted as “y”) and specific energy (usually denoted as “z”), thus the example name “microyz” and their related quantities (frequency‐mean and dose‐mean averages) in small spheres of liquid water. This example applies a weighting procedure avoiding bias of energy scoring in regions of the full cascade of particles with large number of energy depositions, and is described more fully in other work . Users have the possibility to apply a tracking cut.…”

Section: Geant4‐dna Examples For Ts Simulations In Liquid Watermentioning

confidence: 99%

See 2 more Smart Citations

Geant4‐DNA example applications for track structure simulations in liquid water: A report from the Geant4‐DNA Project

et al. 2018

Self Cite

View full text Add to dashboard Cite

This Special Report presents a description of Geant4-DNA user applications dedicated to the simulation of track structures (TS) in liquid water and associated physical quantities (e.g., range, stopping power, mean free path…). These example applications are included in the Geant4 Monte Carlo toolkit and are available in open access. Each application is described and comparisons to recent international recommendations are shown (e.g., ICRU, MIRD), when available. The influence of physics models available in Geant4-DNA for the simulation of electron interactions in liquid water is discussed. Thanks to these applications, the authors show that the most recent sets of physics models available in Geant4-DNA (the so-called "option4" and "option 6" sets) enable more accurate simulation of stopping powers, dose point kernels, and W-values in liquid water, than the default set of models ("option 2") initially provided in Geant4-DNA. They also serve as reference applications for Geant4-DNA users interested in TS simulations.

show abstract

Section: Resultssupporting

confidence: 66%

Section: Geant4‐dna Physics Constructorsmentioning

confidence: 99%

Section: Geant4‐dna Examples For Ts Simulations In Liquid Watermentioning

confidence: 99%

See 1 more Smart Citation

Geant4‐DNA example applications for track structure simulations in liquid water: A report from the Geant4‐DNA Project

et al. 2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…To assess where the charged particles deposit energy and cause damage in a DNA, it is necessary to simulate the track structures of each charged particle and associated secondary particles in a discrete (step‐by‐step) mode, followed by the calculation of the local energy loss distribution. The faster “condensed history” alternative approach, which groups several physical interactions (such as ionization and multiple Coulomb scattering), is not suitable for track structure simulations . In brief, the “condensed history” approach is largely adopted for general‐purpose Monte Carlo simulations of particle–matter interactions.…”

Section: Methodsmentioning

confidence: 99%

“…The faster "condensed history" alternative approach, which groups several physical interactions (such as ionization and multiple Coulomb scattering), is not suitable for track structure simulations. 16 In brief, the "condensed history" approach is largely adopted for generalpurpose Monte Carlo simulations of particle-matter interactions. It simplifies the simulation of physical interactions that occur along steps as the particle propagates through the medium, by calculating the amount of energy lost by the charged particle using stopping power information for the traversed material and step length.…”

Section: C1 the Physical Stagementioning

confidence: 99%

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

et al. 2019

View full text Add to dashboard Cite

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...

show abstract

Nanodosimetric quantities and RBE of a clinically relevant carbon‐ion beam

Dai

Liu

et al. 2019

Medical Physics

View full text Add to dashboard Cite

Purpose Although carbon‐ion therapy is becoming increasingly attractive to the treatment of tumors, details about the ionization pattern formed by therapeutic carbon‐ion beam in tissue have not been fully investigated. In this work, systematic calculations for the nanodosimetric quantities and relative biological effectiveness (RBE) of a clinically relevant carbon‐ion beam were studied for the first time. Methods The method combining both track structure and condensed history Monte Carlo (MC) simulations was adopted to calculate the nanodosimetric quantities. Fragments and energy spectra at different positions of the radiation field of a clinically relevant carbon‐ion pencil beam were generated by means of MC simulations in water. Nanodosimetric quantities such as mean ionization cluster size (M1), the first moment of conditional cluster size (M1C2), cumulative probability (F2), and conditional cumulative probability (F3C2) at these positions were then acquired based on the spectra and the pre‐calculated nanodosimetric database created by track structure MC simulations. What’s more, a novel approach to calculate RBE based on the said nanodosimetric quantities was introduced. The RBE calculations were then conducted for the carbon‐ion beam at different water‐equivalent depths. Results Lateral distributions at various water‐equivalent depths of both the nanodosimetric quantities and RBE values were obtained. The values of M1, M1C2, F2, and F3C2 were 1.49, 2.67, 0.30, and 0.38 at the plateau at the beam central axis and maximized at 2.79, 5.69, 0.47, and 0.68 at the depths around the Bragg peak, respectively. At a given depth, M1 and F2 decreased laterally with increasing the distance to the beam central axis while M1C2 and F3C2 remained nearly unchanged at first and then decreased except for M1C2 at the rising edge of the Bragg peak. The calculated RBE values were 1.07 at the plateau and 3.13 around the Bragg peak. Good agreement between the calculated RBE values and experimental data was obtained. Conclusions Different nanodosimetric quantities feature the track structure of therapeutic carbon‐ion beam in different manners. Detailed ionization patterns generated by carbon‐ion beam could be characterized by nanodosimetric quantities. Moreover the combined method adopted in this work to calculate nanodosimetric quantities is not only valid but also convenient. Nanodosimetric quantities are significantly helpful for the RBE calculations in carbon‐ion therapy.

show abstract

Microdosimetry of electrons in liquid water using the low-energy models of Geant4

Cited by 82 publications

References 68 publications

Geant4‐DNA example applications for track structure simulations in liquid water: A report from the Geant4‐DNA Project

Geant4‐DNA example applications for track structure simulations in liquid water: A report from the Geant4‐DNA Project

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

Nanodosimetric quantities and RBE of a clinically relevant carbon‐ion beam

Contact Info

Product

Resources

About