Models of biological effects of radiation in the Geant4 Toolkit

Chauvie, Stéphane; Francis, Z.; Guatelli, Susanna; Incerti, S.; Mascialino, B.; Montarou, G.; Moretto, Ph.; Nieminen, P.; Pia, Maria Grazia

doi:10.1109/nssmic.2006.355972

Cited by 6 publications

(6 citation statements)

References 10 publications

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“…In this work, the radiation transport simulation code for cell irradiation is developed based on the microdosimetry example in Geant4 (ver. 10.4.p2) and used to calculate the energy deposition distribution information within the cell after irradiation. The energy deposition distribution information is used to determine the cell dose and subsequent DNA damage quantitation.…”

Section: Methodsmentioning

confidence: 99%

Modeling gold nanoparticle radiosensitization using a clustering algorithm to quantitate DNA double‐strand breaks with mixed‐physics Monte Carlo simulation

Liu

Zhao

et al. 2019

Medical Physics

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Purpose: The radiosensitization properties of gold nanoparticles (GNPs) are investigated using a simple Geant4 cell model considering a realistic cell geometry and a clustering algorithm to characterize the number of DNA double-strand breaks (DSBs). Materials and methods: A mixed-physics approach is taken for accurate modeling of low-energy photon interactions in the different regions of the model using Geant4-DNA physics within the cell, and Livermore physics within gold. Density-based spatial clustering of applications with noise (DBSCAN), a clustering algorithm, is used to directly quantitate DNA DSBs after irradiation. The simulation was run using different sizes of GNPs, different distances of GNPs from the cell nucleus, and several combinations of these two conditions. Results: Four types of radiation were simulated in the work: 80-keV monoenergetic photons, 100-keV monoenergetic photons, a 250-kVp photon spectrum, and a 6-MV flattening filter free (FFF) photon spectrum. A variable enhancement in DSB yield, nucleus dose, and cell dose was observed when there are GNPs in the cell cytoplasm, and increases with larger GNPs and proximity to the nucleus. The distance of the GNPs from the nucleus has a large impact on the DSB yield and nucleus dose, but little to no effect on the cell dose. The cell dose enhancement factor of 80 keV photons varies from 1.037-1.125 at 0.2 µm for 30-100 nm GNPs to 1.040-1.127 at 4 lm. The DSB enhancement factor varies from 1.050 to 1.174 at 0.2 µm to a marginal effect of <1.01 at 4 lm. For 100 keV, the dose enhancement factor is from 1.142-1.470 at 0.2 µm to 1.106-1.371 at 4 lm. The DSB enhancement factor varies from 1.249-1.813 at 0.2 µm to almost no effect at 4 lm. For 250 kVp, the dose enhancement factor is from 1.117-1.393 at 0.2 lm to 1.110-1.342 at 4 lm. The DSB enhancement factor varies from 1.183-1.600 at 0.2 lm to a marginal effect of~1.03 at 4 lm. A 6-MV FFF shows a dose enhancement factor of 1.061-1.103 at 0.2 lm and 1.053-1.107 at 4 lm. The DSB yield varies from 1.070-1.143 at 0.2 lm to a marginal effect at 4 lm. Conclusion: The stark difference in behavior for DSB yield when compared to cell dose highlights the importance of evaluating more complex radiobiological quantities rather than dose alone when evaluating the radiosensitization properties from metallic nanomaterials. The nucleus dose showed similar characteristics to the DSB yield demonstrating the ability of the method to predict DNA damage and its relationship with nuclear dose. The proposed method provides a way to explore the radiobiological mechanisms of radiation-induced DNA damages, and it aids to evaluate the physical radiosensitization properties of GNP-aided radiotherapy, which can be easily combined with radiochemical DSB quantitation in order to better understand the intricate DNA damage induction mechanisms that are involved in GNP-aided radiotherapy.

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Section: Methodsmentioning

confidence: 99%

Modeling gold nanoparticle radiosensitization using a clustering algorithm to quantitate DNA double‐strand breaks with mixed‐physics Monte Carlo simulation

Liu

Zhao

et al. 2019

Medical Physics

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“…As noted previously, the low energy physics models used in these simulations employ a condensed history approach with the cut-off for production of secondaries set to 250 eV, so the ionizations produced by very low energy electrons cannot be explicitly simulated. The very low energy models in Geant4-DNA (Chauvie et al 2006, Incerti et al 2010 track every interaction discretely. However, Geant4-DNA is currently only available for liquid water and so cannot be used to investigate the effect of chemical composition.…”

Section: Discussionmentioning

confidence: 99%

Radiation damage on sub-cellular scales: beyond DNA

et al. 2013

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This study investigates a model cell as a target for low-dose radiation using Monte Carlo simulations. Mono-energetic electrons and photons are used with initial energies between 10 and 50 keV, relevant to out-of-field radiotherapy scenarios where modern treatment modalities expose relatively large amounts of healthy tissue to low-dose radiation, and also to microbeam cell irradiation studies which show the importance of the cytoplasm as a radiation target. The relative proportions of number of ionizations and total energy deposit in the nucleus and cytoplasm are calculated. We show that for a macroscopic dose of no more than 1 Gy only a few hundred ionizations occur in the nucleus volume whereas the number of ionizations in the cytoplasm is over a magnitude larger. We find that the cell geometry can have an appreciable effect on the energy deposit in the cell and can cause a nonlinear increase in energy deposit with cytoplasm density. We also show that changing the nucleus volume has negligible effect on the total energy deposit but alters the relative proportion deposited in the nucleus and cytoplasm; the nucleus volume must increase to approximately the same volume as the cytoplasm before the energy deposit in the nucleus matches that in the cytoplasm. Additionally we find that energy deposited by electrons is generally insensitive to spatial variations in chemical composition, which can be attributed to negligible differences in electron stopping power for cytoplasm and nucleus materials. On the other hand, we find that chemical composition can affect energy deposited by photons due to non-negligible differences in attenuation coefficients. These results are of relevance in considering radiation effects in healthy cells, which tend to have smaller nuclei. Our results further show that the cytoplasm and organelles residing therein can be important targets for low-dose radiation damage in healthy cells and warrant investigation as much as the conventional focus of a high-dose radiation DNA target in tumour cells.

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“…Several track-structure Monte Carlo codes (nanodosimetric Monte Carlo code) have been developed to simulate the interaction of biological molecules and study the radiation damage, for example, PARTRAC (Friedland et al 2011), KURBUC (Matsuya et al 2021), Geant4-DNA (Chauvie et al 2006), NOREC (Semenenko et al 2003), and RITRACKS (Plante and Devroye 2017). The oxygen depletion in water radiolysis has been studied to analyze the oxygen depletion hypothesis using track structure Monte Carlo codes recently (Boscolo et al 2021, Alanazi et al 2021, Zhu et al 2021b.…”

Section: Introductionmentioning

confidence: 99%

CPU-GPU coupling independent reaction times method in NASIC and application in water radiolysis by FLASH irradiation

Hu¹,

Qiu²,

Wu³

et al. 2022

Biomed. Phys. Eng. Express

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The mechanism of the FLASH effect remains unclear and could be revealed by studying chemical reactions during irradiation. Monte Carlo simulation of the radiolytic species is an effective tool to analyze chemical reactions, but the simulation is limited by computing costs of the step-by-step simulation of radiolytic species, especially when considering beam with complex time structure. The complexity of the time structure of beams from accelerators in FLASH radiotherapy requires a high-performance Monte Carlo code. In this work, we develop a CPU-GPU coupling accelerating code with the independent reaction times (IRT) method to extend the chemical module of our nanodosimetry Monte Carlo code NASIC. Every chemical molecule in the microenvironment contains time information to consider the reactions from different tracks and simulate beams with complex time structures. Performance test shows that our code significantly improved the computing efficiency of the chemical module by four orders of magnitude. Then the code is used to study the oxygen depletion hypothesis in FLASH radiotherapy for different conditions by setting different parameters. The transient oxygen consumption rate values in the water are calculated when the pulses width ranges from 2 ps to 2 μs, the total dose ranges from 0.5 Gy to 100 Gy and the initial oxygen concentration ranges from 0.1% to 21%. The time evolution curves are simulated to study the effect of the time structure of an electron linear accelerator. Results show that the total dose in several microseconds is a better indicator reflecting the radiolytic oxygen consumption rate than the dose rate. The initial oxygen greatly affects the oxygen consumption rate because of the reaction competition. The diffusion of oxygen determined by the physiological parameters is the key factor affecting oxygen depletion during the radiation using electron linear accelerators. Our code provides an efficient tool for simulating water radiolysis in different conditions

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Models of biological effects of radiation in the Geant4 Toolkit

Cited by 6 publications

References 10 publications

Modeling gold nanoparticle radiosensitization using a clustering algorithm to quantitate DNA double‐strand breaks with mixed‐physics Monte Carlo simulation

Modeling gold nanoparticle radiosensitization using a clustering algorithm to quantitate DNA double‐strand breaks with mixed‐physics Monte Carlo simulation

Radiation damage on sub-cellular scales: beyond DNA

CPU-GPU coupling independent reaction times method in NASIC and application in water radiolysis by FLASH irradiation

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