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

Okada, Shogo; Murakami, K.; Incerti, S.; Amako, K.; Sasaki, Takashi

doi:10.1002/mp.13370

Cited by 19 publications

(18 citation statements)

References 47 publications

(109 reference statements)

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“…It is based on the Geant4-DNA package and can also simulate chemical reactions and the diffusion process for molecular species, and the distribution of molecular species can also be determined. In this study [114], the authors confirmed that the simulation results, which were obtained using MPEXS-DNA, were consistent with existing experimental and simulation data. Compared with simulations that were performed in Geant4-DNA with a single CPU core, MPEXSDNA performed the same simulations thousands times faster, keeping the accuracy at the same level.…”

Section: Monte Carlo Techniques For Radiobiological Modellingsupporting

confidence: 89%

“…A recent addition on simulating radiation chemistry and track structures at the subcellular scale is the MPEXS-DNA, GPU-based Monte Carlo simulator [114]. MPEXS-DNA uses the speed of GPU processing for the physical, physicochemical, chemical and biological stages of the simulation process of IR interaction with biological matter.…”

Section: Monte Carlo Techniques For Radiobiological Modellingmentioning

confidence: 99%

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Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations

Chatzipapas

Papadimitroulas²,

Emfietzoglou

et al. 2020

Cancers

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Ionizing radiation is a common tool in medical procedures. Monte Carlo (MC) techniques are widely used when dosimetry is the matter of investigation. The scientific community has invested, over the last 20 years, a lot of effort into improving the knowledge of radiation biology. The present article aims to summarize the understanding of the field of DNA damage response (DDR) to ionizing radiation by providing an overview on MC simulation studies that try to explain several aspects of radiation biology. The need for accurate techniques for the quantification of DNA damage is crucial, as it becomes a clinical need to evaluate the outcome of various applications including both low- and high-energy radiation medical procedures. Understanding DNA repair processes would improve radiation therapy procedures. Monte Carlo simulations are a promising tool in radiobiology studies, as there are clear prospects for more advanced tools that could be used in multidisciplinary studies, in the fields of physics, medicine, biology and chemistry. Still, lot of effort is needed to evolve MC simulation tools and apply them in multiscale studies starting from small DNA segments and reaching a population of cells.

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Section: Monte Carlo Techniques For Radiobiological Modellingsupporting

confidence: 89%

Section: Monte Carlo Techniques For Radiobiological Modellingmentioning

confidence: 99%

Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations

Chatzipapas

Papadimitroulas²,

Emfietzoglou

et al. 2020

Cancers

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show abstract

“…Another interesting example is reported by Okada et al [248], where a new MC simulator named MPEXS-DNA is described, allowing high computing performance by using a GPU. The code has been developed for track structure and radiolysis simulations at the subcellular scale.…”

Section: Gpu-based MC For Radiobiological Calculationsmentioning

confidence: 99%

Challenges in Monte Carlo Simulations as Clinical and Research Tool in Particle Therapy: A Review

2020

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The use and interest in Monte Carlo (MC) techniques in the field of medical physics have been rapidly increasing in the past years. This is the case especially in particle therapy, where accurate simulations of different physics processes in complex patient geometries are crucial for a successful patient treatment and for many related research and development activities. Thanks to the detailed implementation of physics processes in any type of material, to the capability of tracking particles in 3D, and to the possibility of including the most important radiobiological effects, MC simulations have become an essential calculation tool not only for dose calculations but also for many other purposes, like the design and commissioning of novel clinical facilities, shielding and radiation protection, the commissioning of treatment planning systems, and prediction and interpretation of data for range monitoring strategies. MC simulations are starting to be more frequently used in clinical practice, especially in the form of specialized codes oriented to dose calculations that can be performed in short time. The use of general purpose MC codes is instead more devoted to research. Despite the increased use of MC simulations for patient treatments, the existing literature suggests that there are still a number of challenges to be faced in order to increase the accuracy of MC calculations for patient treatments. The goal of this review is to discuss some of these remaining challenges. Undoubtedly, it is a work for which a multidisciplinary approach is required. Here, we try to identify some of the aspects where the community involved in applied nuclear physics, radiation biophysics, and computing development can contribute to find solutions. We have selected four specific challenges: i) the development of models in MC to describe nuclear physics interactions, ii) modeling of radiobiological processes in MC simulations, iii) developments of MC-based treatment planning tools, and iv) developments of fast MC codes. For each of them, we describe the underlying problems, present selected examples of proposed solutions, and try to give recommendations for future research.

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“…A number of tools and computational platforms have been developed based on MC techniques by many researchers with varying degree of complexity. 2 Several MC packages have been proposed and/or studied for radiobiology calculations, such as MCDS 3 and DBSCAN, 4 which are based on MC simulations' results to calculate radiobiological parameters, and RADAMOL, 5 PAR-TRAC, 6 Geant4-DNA, 7,8 TRAX, 9,10 RITRACKS, [11][12][13] MPEXS-DNA, 14 TOPAS-nBio, 15,16 gMicroMC, 17,18 which are MC simulation codes. Recent studies, 7,8,[16][17][18][19][20] include specific DNA or cell models that can also simulate the early radiation-induced damage.…”

Section: Introductionmentioning

confidence: 99%

IDDRRA: A novel platform, based on Geant4‐DNA to quantify DNA damage by ionizing radiation

Chatzipapas

Papadimitroulas²,

Loudos³

et al. 2021

Medical Physics

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This study proposes a novel computational platform that we refer to as IDDRRA (DNA Damage Response to Ionizing RAdiation), which uses Monte Carlo (MC) simulations to score radiation induced DNA damage. MC simulations provide results of high accuracy on the interaction of radiation with matter while scoring the energy deposition based on state-of-the-art physics and chemistry models and probabilistic methods. Methods: The IDDRRA software is based on the Geant4-DNA toolkit together with new tools that were developed for the purpose of this study, including a new algorithm that was developed in Python for the design of the DNA molecules. New classes were developed in C++ to integrate the GUI and produce the simulation's output in text format. An algorithm was also developed to analyze the simulation's output in terms of energy deposition, Single Strand Breaks (SSB), Double Strand Breaks (DSB) and Cluster Damage Sites (CDS). Finally, a new tool was developed to implement probabilistic SSB and DSB repair models using MC techniques. Results: This article provides the first benchmarks that the user of the IDDRRA tool can use to validate the functionality of the software as well as to provide a starting point to produce different types of DNA simulations. These benchmarks incorporate different kind of particles (e-, e+, protons, electron spectrum) and DNA molecules. Conclusion:We have developed the IDDRRA tool and demonstrated its use to study various aspects of the modeling and simulation of a DNA irradiation experiment. The tool is expandable and can be expanded by other users with new benchmarks and applications based on the user's needs and experience. New functionality will be added over time, including the quantification of the indirect damage.

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

Cited by 19 publications

References 47 publications

Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations

Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations

Challenges in Monte Carlo Simulations as Clinical and Research Tool in Particle Therapy: A Review

IDDRRA: A novel platform, based on Geant4‐DNA to quantify DNA damage by ionizing radiation

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