Review of the Geant4-DNA Simulation Toolkit for Radiobiological Applications at the Cellular and DNA Level
Abstract
:Simple Summary
Abstract
1. Monte Carlo Radiation Track Simulations
Code | Particles | Energy Range | Target Materials | Chemical Stage | Reference |
---|---|---|---|---|---|
CPA100 | e− | Thermalization–256 keV | Water (l), DNA | Yes | Terrisol and Beaudré (1990) [17] |
DELTA | e− | ≥10 eV–10 keV | Water (v) | Yes | Zaider et al. (1983) [18] |
EPOTRAN | e−, e+ | ≥7.4 eV–10 keV | Water (l,v) | No | Champion et al. (2012) [19] |
ETRACK | e−, p, α | ≥10 eV–10 keV | Water (v) | Yes | Ito (1987) [20] |
ETS | e− | ≥10 eV–10 keV | Water (l,v) | Yes | Hill and Smith (1994) [21] |
Geant4-DNA | e−, p, H, α, ions | Thermalization–1MeV e−, 100 eV–100 MeV p, H, 1 keV–400 MeVα, 0.5MeV/u−106MeV/u ions | Water (l), DNA, Gold | Yes | Incerti et al. (2010, 2018), Bernal et al. (2015) [14,22,23,24] |
IONLYS/IONLYS-IRT | e−, p, ions | 0.2 eV–150 keV e−, p, 0.1 MeV-300 MeV ions | Water (l) | Yes | Cobut et al. (1998) [25] |
KAPLAN | e− | ≥1–10 keV | Water (l,v) | Yes | Kaplan (1990) [26] |
KITrack | e−, ions | ≥10 eV–100 keV | Water (l) | No | Wiklund et al. (2011) [27] |
KURBUC (KURBUC/LEAHIST/LEPHIST/CHEM-KURBUC) | e−, p, α, C | 10 eV–10 MeV (10keV, liq.) e−,1 keV–300 MeV p, 1keV/u-2MeV/u α, 1 keV/u–10 MeV/u carbon | Water (l,v) | Yes | Nikjoo et al. (2016) [10] |
LEEPS | e−, e+ | 0.1–100 keV | All materials | Yes | Fernández-Varea et al. (1996) [28] |
LEPTS | e−, e+, p | Thermalization–10 keV e−, Thermalization–10 MeV p | Water (v), CH4, C2H4, C4H8O, SF6, C4H4N2 | No | Sanz et al. (2012), Blanco et al. (2013) [29,30] |
Lion Track | e−, p, ions | >50 eV e−, 0.5 MeV/u–300 MeV/u p, ions | Water (l) | No | Bäckström et al. (2013) [31] |
MC4 | e−, ions | ≥10 eV e−, ≥0.3 MeV/u ions | Water (l,v) | No | Emfietzoglou et al. (2017) [32] |
MOCA8B | e− | 10 eV–100 keV | Water (v) | Yes | Paretzke (1970) [33] |
NASIC | e− | Thermalization–1 MeV e− | Water (l) | Yes | Li et al. (2015) [34] |
NOTRE DAME | e−, ions | ≥ 10 eV e−, ≥0.3 MeV/u ions | Water (l,v) | Yes | Pimblott et al. (1990) [35] |
OREC/NOREC | e− | 7.4 eV–1 MeV e− | Water (l) | No | Semenenko et al. (2003) [8] |
PARTRAC | e−, e+, p, H, α, ions | 1 eV–10 MeV e−, 1 keV–1 GeV p, H, α, 1 MeV/u–1 GeV/u ions | Water (l), DNA | Yes | Friedland et al. (2003) [36] |
PITS04 | e−, ions | ≥ 10 eV e−, ≥ 0,3 MeV/u ions | Water (l) | No | Wilson et al. (2004) [37] |
PITS99 | e−, ions | ≥ 10 eV e−, ≥ 0,3 MeV/u ions | Water (v) | Yes | Wilson and Nikjoo (1999) [38] |
PTra | e−, p, α | 1 eV–10 keV e−, 1–10 MeV α, 300 keV-10 MeV p | Water (l,v), DNA | No | Grosswendt and Pszona (2002) [39] |
RITRACKS/RETRACKS | e−, ions | 0.1 eV–100 MeV e−, 10−1MeV/u–104MeV/u ions | Water (l,v) | Yes | Plante and Cucinotta (2009) [40] |
SHERBROOKE | e−, ions | ≥ 10 eV e−, ≥ 0,3 MeV/u ions | Water (l,v) | Yes | Cobut et al. (2004) [41] |
STBRGEN | e−, ions | ≥ 10 eV e−, ≥ 0,3 MeV/u ions | Water (l,v) | Yes | Chatterjee and Holley (1993) [42] |
TILDA-V | e−, p, H, ions | ≥ 7,4 eV e−, 10 keV/u–100 MeV/u ions | Water (l,v), DNA | No | Champion et al. (2005) [43] |
TRAX | e−, p, ions | 1 eV–few MeV e−, 10 eV–few hundred MeV/u ions | Water (v) | Yes | Krämer and Kraft (1994) [44] |
RADAMOL (TRIOL/STOCHECO) | e−, ions | ≥7.4 eV–2 MeV e−, ≥0.3–200 MeV/u ions | Water (l) | Yes | Bigildeev and Michalik (1996) [45] |
TRION | e−, ions | ≥10 eV e−, ≥0.3 MeV/u ions | Water (l,v) | No | Lappa et al. (1993) [46] |
TRACEL/RADYIE/RADIFF | e−, ions | ≥10 eV e−, ≥0.3 MeV/u ions | Water (l,v) | Yes | Tomita et al. (1997) [47] |
2. The Geant4-DNA Extension
3. Physical Interactions in Geant4-DNA: Energy-Loss Models
4. The Physico-Chemical and Chemical Stages of Water Radiolysis
4.1. The Physico-Chemical Stage
4.2. The Chemical Stage
4.2.1. Step by Step Method
4.2.2. Independent Reaction Time
5. Towards the Modelling of Early DNA Damage
5.1. History
5.2. “FullSim” Complete Simulation Chain for DSBs Calculations
5.3. Review of “MolecularDNA”Application
6. Geant4-DNA Extended Examples
6.1. Physics Examples
- The “clustering” example calculates the energy deposition with a dedicated clustering algorithm to assess DNA strand breaks in a simple liquid water geometry [14];
- “dnaphysics” is a general example that enables track-structure simulation of charged particles in a liquid water geometry and allows for the automatic combination between Geant4-DNA physics models and condensed-history models at higher energies (i.e., above 1 MeV) and can be used for benchmarking simulations that are related to track-structure characteristics [23];
- “icsd”, that stands for ionization cluster size distribution, calculates the number of ionizations for each simulated track in a cylinder mimicking a piece of chromatin and uses DNA-like material’s cross sections that were obtained experimentally or by simulations [50];
- “mfp” stands for mean free path and allows the calculation of the aforementioned distance and related distance quantities for a charged particle in a sphere geometry of liquid water [23];
- “microdosimetry” simulates lineal and specific energy distributions and related quantities in liquid water spheres that are randomly placed along the particle track [59];
- “microprox” is another microdosimetric example that calculates proximity functions from energy depositions scored in liquid water spherical shells from randomly selected hits [60];
- “range” example performs a simulation of penetration distances in liquid water [70];
- “slowing” enables simulation of the slowing down spectra of electrons in a cube of liquid water [136];
- “splitting” uses variance reduction techniques to improve the efficiency of the calculation of ionization cluster size distributions. This is done in a nm sized cylinder as in the case of the icsd example and aims to separate secondaries that are generated within the cylinder to avoid the overlapping of tracks [137];
- “spower” allows for stopping power simulations of particles in liquid water with the use of specific physics modules that enable the use of a stationary mode for appropriate computation [23];
- “svalue” calculates the dose to a target volume per unit of cumulated activity in a source volume, called S-value [138,139]. The source and target volumes can be different cell compartments or an entire cell of a simple spherical geometry which can be modified to account for more complex cell geometries, as has been done in many studies i.e. [140,141];
- “wvalue” serves to simulate the mean energy that is expended to form an ion pair known as W-value. It also provides information on the total number of ionizations in a liquid water volume and its penetration details. It is a useful benchmark simulation for the inelastic models given that elastic interactions are indifferent in this simulation scheme [23,58].
6.2. Chemical Examples
- “chem1” aims to show how to activate or deactivate physicochemical and chemical stage after physical stage. Chemical reactions are printed and the step-by-step model is used by default.
- “chem2” provides a user-class “TimeStepAction” which allows users to change Minimum Time Steps. These parameters constrain the minimum time-step that is allowed for each reactant pair using the step-by-step model. The user-class also shows how to print reaction information such as reactants and products as well as their positions.
- “chem3” illustrates how to implement user actions in the chemistry module using the step-by-step model. Users can also visualize the trajectories of the chemical species in time and space using the graphical user interface.
- “chem4” provides scorer classes to compute radiochemical yields (“G”) versus time using the step-by-step model, including a dedicated ROOT graphical interface. The G-value is useful for benchmark simulations in comparing with other MC codes and experimental data [80].
- “chem5” computes radiochemical yields (“G”) versus time using alternative physics and chemical reaction lists using the step-by-step model [142].
6.3. The dnadamage1 Example
7. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Electronic State | Decay Channel | Fraction |
---|---|---|
All ionization states | H3O+ + •OH (through proton transfer) | 100% |
Excitation state A1B1: (4a1/3s) | •OH + H• H2O + ∆E | 65% 35% |
Excitation state B1A1: (4a1/3s) | HO++ •OH + e−aq •OH + •OH + H2 H2O + ∆E | 55% 15% 30% |
Excitation state: Rydberg, diffusion bands | HO++ •OH + e−aq H2O + ∆E | 50% 50% |
Electron attachment | OH− + •OH + H2 | 100 |
Electron-hole recombination | •OH + H• | 55% |
H2 + 2•OH | 15% | |
H2O + ∆E | 30% |
Reaction | ||
---|---|---|
G4EmDNAChemistry | G4EmDNAChemistry_ Option1 | |
0.5 | 0.636 | |
2.65 | 2.5 | |
2.95 | 2.95 | |
2.11 | 2.11 | |
1.41 | 1.10 | |
0.44 | 0.550 | |
1.44 | 1.55 | |
1.2 | 0.503 | |
14.3 | 11.3 |
Parameters | FullSim | MolecularDNA | |
---|---|---|---|
Physical parameters | Rdir (Å) | VDWR + hydration shells * | 3.5 |
Elower(eV) | 17.5 | 5.0 | |
Ehigher(eV) | 17.5 | 37.5 | |
Chemical parameters | POH | 0.4 | 0.405 |
Tchem (ns) | 2.5 | 5.0 | |
dkill (nm) | N/A | 9.0 |
Simulated DSBs and Experimental Foci at 1 Gy | 40 kVp X-rays | 220 kVp X-rays | 4 MV X-rays |
---|---|---|---|
Sim. mean number of DSBs per nucleus | 21.0 ± 0.3 | 21.0 ± 0.3 | 16.8 ± 0.3 |
Exp. mean number of γ-H2AX foci per nucleus | 18.59 ± 0.43 | 18.64 ± 2.33 | 16.46 ± 1.63 |
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Kyriakou, I.; Sakata, D.; Tran, H.N.; Perrot, Y.; Shin, W.-G.; Lampe, N.; Zein, S.; Bordage, M.C.; Guatelli, S.; Villagrasa, C.; et al. Review of the Geant4-DNA Simulation Toolkit for Radiobiological Applications at the Cellular and DNA Level. Cancers 2022, 14, 35. https://doi.org/10.3390/cancers14010035
Kyriakou I, Sakata D, Tran HN, Perrot Y, Shin W-G, Lampe N, Zein S, Bordage MC, Guatelli S, Villagrasa C, et al. Review of the Geant4-DNA Simulation Toolkit for Radiobiological Applications at the Cellular and DNA Level. Cancers. 2022; 14(1):35. https://doi.org/10.3390/cancers14010035
Chicago/Turabian StyleKyriakou, Ioanna, Dousatsu Sakata, Hoang Ngoc Tran, Yann Perrot, Wook-Geun Shin, Nathanael Lampe, Sara Zein, Marie Claude Bordage, Susanna Guatelli, Carmen Villagrasa, and et al. 2022. "Review of the Geant4-DNA Simulation Toolkit for Radiobiological Applications at the Cellular and DNA Level" Cancers 14, no. 1: 35. https://doi.org/10.3390/cancers14010035