Verification of KURBUC-based ion track structure mode for proton and carbon ions in the PHITS code

A step-by-step simulation code for estimating yields of water radiolysis species based on electron track-structure mode in the PHITS code

Objective. Time-dependent yields of chemical products resulting from water radiolysis play a great role in evaluating DNA damage response after exposure to ionizing radiation. Particle and Heavy Ion Transport code System (PHITS) is a general-purpose Monte Carlo simulation code for radiation transport, which simulates atomic interactions originating from discrete energy levels of ionizations and electronic excitations as well as molecular excitations as physical stages. However, no chemical code for simulating water radiolysis products exists in the PHITS package.Approach.Here, we developed a chemical simulation code dedicated to the PHITS code, hereafter calledPHITS-Chemcode, which enables the calculation of theGvalues of water radiolysis species (•OH, eaq-, H2, H2O2etc) by electron beams.Main results.The estimatedGvalues during 1 μs are in agreement with the experimental ones and other simulations. ThisPHITS-Chemcode also simulates the radiolysis in the presence of OH radical scavengers, such as tris(hydroxymethyl)aminomethane and dimethyl sulfoxide. Thank to this feature, the contributions of direct and indirect effects on DNA damage induction under various scavenging capacities can be analyzed.Significance.This chemical code coupled with PHITS could contribute to elucidating the mechanism of radiation effects by connecting physical, physicochemical, and chemical processes.

Computational model of radiation oxygen effect with Monte Carlo simulation: effects of antioxidants and peroxyl radicals

PURPOSE

Oxygen plays a crucial role in radiation biology. Antioxidants and peroxyl radicals affect the oxygen effect greatly. This study aims to establish a computational model of the oxygen effect and explore the effect attributed to antioxidants and peroxyl radicals.

MATERIALS AND METHODS

Oxygen-related reactions are added to our track-structure Monte Carlo code NASIC, including oxygen fixation, chemical repair by antioxidants and damage migration from base-derived peroxyl radicals. Then the code is used to simulate the DNA damage under various oxygen, antioxidant and damage migration rate conditions. The oxygen enhancement ratio(OER) is calculated quantifying by the number of double-strand breaks for each condition. The roles of antioxidants and peroxyl radicals are examined by manipulating the relevant parameters.

RESULTS AND CONCLUSIONS

Our results indicate that antioxidants are capable of rapidly restoring DNA radicals through chemical reactions, which compete with natural and oxygen fixation processes. Additionally, antioxidants can react with peroxyl radicals derived from bases, thereby preventing the damage from migrating to DNA strands. By quantitatively accounting for the impact of peroxyl radicals and antioxidants on the OER curves, our study establishes a more precise and comprehensive model of the radiation oxygen effect.

Microdosimetric assessment about proton spread-out Bragg peak at different depths based on the normal human mesh-type cell population model

Objective.In clinical proton therapy, the spread-out Bragg peak (SOBP) is commonly used to fit the target shape. Dose depositions at microscopic sites vary, even with a consistent absorbed dose (D) in SOBP. In the present study, monolayer mesh-type cell population models were developed for microdosimetric assessment at different SOBP depths.Approach.Normal human bronchial epithelial (BEAS-2B) and hepatocytes (L-O2) mesh-type cell models were constructed based on fluorescence tomography images of normal human cells. Particle transport simulation in cell populations was performed coupled with Monte Carlo software PHITS. The relationship between microdosimetry and macrodosimetry of SOBP at different depths was described by analyzing the microdosimetric indicators such as specific energyz,specific energy distributionfz,D,and relative standard deviationσz/z¯within cells. Additionally, the microdosimetric distributions characteristics and their contributing factors were also discussed.Main results.The microscopic dose distribution is strongly influenced by cellular size, shape, and material. The mean specific energyz¯of nucleus and cytoplasm in the cell population is greater than the overall absorbed dose of the cell population model (Dp), with a maximumz¯/Dpof 1.1. The cellular dose distribution is different between the BEAS-2B mesh-type model and its concentric ellipsoid geometry-type model, which difference inz¯is about 10.3% for the nucleus and about 7.5% for the cytoplasm with the SOBP depth of 15 cm. WhenD= 2 Gy, the maximumzof L-O2 nucleus reaches 2.8 Gy andσz/z¯is 5.1% at the mid-depth SOBP (16-18 cm); while the maximumzof the BEAS-2B nucleus reaches 2.2 Gy with only 2.7% ofσz/z¯.Significance.The significant variation of microdosimetric distributions of SOBP different depths indicates the necessity to use mesh-type cell population models, which have the potential to be compared with biological results and build the bio-physical model.

Space radiation quality factor for Galactic Cosmic Rays and typical space mission scenarios using a microdosimetric approach

Space radiation exposure from omnipresent Galactic Cosmic Rays (GCRs) in interplanetary space poses a serious carcinogenic risk to astronauts due to the-limited or absent-protective effect of the Earth's magnetosphere and, in particular, the terrestrial atmosphere. The radiation risk is directly influenced by the quality of the radiation, i.e., its pattern of energy deposition at the micron/DNA scale. For stochastic biological effects, radiation quality is described by the quality factor, [Formula: see text], which can be defined as a function of Linear Energy Transfer (LET) or the microdosimetric lineal energy ([Formula: see text]). In the present work, the average [Formula: see text] of GCR for different mission scenarios was calculated using a modified version of the microdosimetric Theory of Dual Radiation Action (TDRA). NASA's OLTARIS platform was utilized to generate the radiation environment behind different aluminum shielding (0-30 g/cm²) for a typical mission scenario in low-earth orbit (LEO) and in deep space. The microdosimetric lineal energy spectra of ions ([Formula: see text]) in 1 μm liquid water spheres were calculated by a generalized analytical model which considers energy-loss fluctuations and δ-ray transport inside the irradiated medium. The present TDRA-based [Formula: see text]-values for the LEO and deep space missions were found to differ by up to 10% and 14% from the corresponding ICRP-based [Formula: see text]-values and up to 3% and 6% from NASA's [Formula: see text]-model. In addition, they were found to be in good agreement with the [Formula: see text]-values measured in the International Space Station (ISS) and by the Mars Science Laboratory (MSL) Radiation Assessment Detector (RAD) which represent, respectively, a LEO and deep space orbit.

Application of a simple DNA damage model developed for electrons to proton irradiation

Proton beam therapy allows irradiating tumor volumes with reduced side effects on normal tissues with respect to conventional x-ray radiotherapy. Biological effects such as cell killing after proton beam irradiations depend on the proton kinetic energy, which is intrinsically related to early DNA damage induction. As such, DNA damage estimation based on Monte Carlo simulations is a research topic of worldwide interest. Such simulation is a mean of investigating the mechanisms of DNA strand break formations. However, past modellings considering chemical processes and DNA structures require long calculation times. Particle and heavy ion transport system (PHITS) is one of the general-purpose Monte Carlo codes that can simulate track structure of protons, meanwhile cannot handle radical dynamics simulation in liquid water. It also includes a simple model enabling the efficient estimation of DNA damage yields only from the spatial distribution of ionizations and excitations without DNA geometry, which was originally developed for electron track-structure simulations. In this study, we investigated the potential application of the model to protons without any modification. The yields of single-strand breaks, double-strand breaks (DSBs) and the complex DSBs were assessed as functions of the proton kinetic energy. The PHITS-based estimation showed that the DSB yields increased as the linear energy transfer (LET) increased, and reproduced the experimental and simulated yields of various DNA damage types induced by protons with LET up to about 30 keV μm−1. These results suggest that the current DNA damage model implemented in PHITS is sufficient for estimating DNA lesion yields induced after protons irradiation except at very low energies (below 1 MeV). This model contributes to evaluating early biological impacts in radiation therapy.

Impact of the Lorentz force on electron track structure and early DNA damage yields in magnetic resonance-guided radiotherapy

Magnetic resonance-guided radiotherapy (MRgRT) has been developed and installed in recent decades for external radiotherapy in several clinical facilities. Lorentz forces modulate dose distribution by charged particles in MRgRT; however, the impact of Lorentz forces on low-energy electron track structure and early DNA damage induction remain unclear. In this study, we estimated features of electron track structure and biological effects in a static magnetic field (SMF) using a general-purpose Monte Carlo code, particle and heavy ion transport code system (PHITS) that enables us to simulate low-energy electrons down to 1 meV by track-structure mode. The macroscopic dose distributions by electrons above approximately 300 keV initial energy in liquid water are changed by both perpendicular and parallel SMFs against the incident direction, indicating that the Lorentz force plays an important role in calculating dose within tumours. Meanwhile, DNA damage estimation based on the spatial patterns of atomic interactions indicates that the initial yield of DNA double-strand breaks (DSBs) is independent of the SMF intensity. The DSB induction is predominantly attributed to the secondary electrons below a few tens of eV, of which energy deposition patterns are not considerably affected by the Lorentz force. Our simulation study suggests that treatment planning for MRgRT can be made with consideration of only changed dose distribution.

Research on the proximity functions of microdosimetry of low energy electrons in liquid water based on different Monte Carlo codes

PURPOSE

The proximity function is an important index in microdosimetry for describing the spatial distribution of energy, which is closely related to the biological effects of organs or tissues in the target area. In this work, the impact of parameters, such as physic models, cut-off energy, and initial energy, on the proximity function are quantitated and compared.

METHODS

According to the track structure (TS) and condensed history (CH) low-energy electromagnetic models, this paper chooses a variety of Monte Carlo (Monte Carlo, MC) codes (Geant4-DNA, PHITS, and Penelope) to simulate the track structure of low-energy electrons in liquid water and evaluates the influence of the electron initial energy, cut-off energy, energy spectrum, and physical model factors on the differential proximity function.

RESULTS

The results show that the initial energy of electrons in the low-energy part (especially less than 1 keV) has a greater impact on the differential proximity function, and the choice of cut-off energy has a greater impact on the differential proximity function corresponding to small radius sites (generally less than 10 nm). The difference in the electronic energy spectrum has little effect on the result, and the proximity functions of different physics models show better consistency under large radius sites.

CONCLUSIONS

This work comprehensively compares the differential proximity functions under different codes by setting a variety of simulation conditions and has basic guiding significance for helping users simulate and analyze the deposition characteristics of microscale electrons according to the selection of an appropriate methodology and cut-off energy.

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

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

Development and validation of proton track-structure model applicable to arbitrary materials

A novel transport algorithm performing proton track-structure calculations in arbitrary materials was developed. Unlike conventional algorithms, which are based on the dielectric function of the target material, our algorithm uses a total stopping power formula and single-differential cross sections of secondary electron production. The former was used to simulate energy dissipation of incident protons and the latter was used to consider secondary electron production. In this algorithm, the incident proton was transmitted freely in matter until the proton produced a secondary electron. The corresponding ionising energy loss was calculated as the sum of the ionisation energy and the kinetic energy of the secondary electron whereas the non-ionising energy loss was obtained by subtracting the ionising energy loss from the total stopping power. The most remarkable attribute of this model is its applicability to arbitrary materials, i.e. the model utilises the total stopping power and the single-differential cross sections for secondary electron production rather than the material-specific dielectric functions. Benchmarking of the stopping range, radial dose distribution, secondary electron energy spectra in liquid water, and lineal energy in tissue-equivalent gas, against the experimental data taken from literature agreed well. This indicated the accuracy of the present model even for materials other than liquid water. Regarding microscopic energy deposition, this model will be a robust tool for analysing the irradiation effects of cells, semiconductors and detectors.

Track-structure modes in particle and heavy ion transport code system (PHITS): application to radiobiological research

PURPOSE

In radiation physics, Monte Carlo radiation transport simulations are powerful tools to evaluate the cellular responses after irradiation. When investigating such radiation-induced biological effects, it is essential to perform track structure simulations by explicitly considering each atomic interaction in liquid water at the sub-cellular and DNA scales. The Particle and Heavy-Ion Transport code System (PHITS) is a Monte Carlo code which enables to calculate track structure at DNA scale by employing the track-structure modes for electrons, protons and carbon ions. In this paper, we review the recent development status and future prospects of the track-structure modes in the PHITS code.

CONCLUSIONS

To date, the physical features of these modes have been verified using the available experimental data and Monte Carlo simulation results reported in literature. These track-structure modes can be used for calculating microdosimetric distributions to estimate cell survival and for estimating initial DNA damage yields. The use of PHITS track-structure mode is expected not only to clarify the underlying mechanisms of radiation effects but also to predict curative effects in radiation therapy. The results of PHITS simulations coupled with biophysical models will contribute to the radiobiological studies by precisely predicting radiation-induced biological effects based on the Monte Carlo approach.

Applications of nanodosimetry in particle therapy planning and beyond

This topical review summarizes underlying concepts of nanodosimetry. It describes the development and current status of nanodosimetric detector technology. It also gives an overview of Monte Carlo track structure simulations that can provide nanodosimetric parameters for treatment planning of proton and ion therapy. Classical and modern radiobiological assays that can be used to demonstrate the relationship between the frequency and complexity of DNA lesion clusters and nanodosimetric parameters are reviewed. At the end of the review, existing approaches of treatment planning based on relative biological effectiveness (RBE) models or dose-averaged linear energy transfer are contrasted with an RBE-independent approach based on nandosimetric parameters. Beyond treatment planning, nanodosimetry is also expected to have applications and give new insights into radiation protection dosimetry.

What can space radiation protection learn from radiation oncology?

Protection from cosmic radiation of crews of long-term space missions is now becoming an urgent requirement to allow a safe colonization of the moon and Mars. Epidemiology provides little help to quantify the risk, because the astronaut group is small and as yet mostly involved in low-Earth orbit mission, whilst the usual cohorts used for radiation protection on Earth (e.g. atomic bomb survivors) were exposed to a radiation quality substantially different from the energetic charged particle field found in space. However, there are over 260,000 patients treated with accelerated protons or heavier ions for different types of cancer, and this cohort may be useful for quantifying the effects of space-like radiation in humans. Space radiation protection and particle therapy research also share the same tools and devices, such as accelerators and detectors, as well as several research topics, from nuclear fragmentation cross sections to the radiobiology of densely ionizing radiation. The transfer of the information from the cancer radiotherapy field to space is manifestly complicated, yet the two field should strengthen their relationship and exchange methods and data.

Medical application of particle and heavy ion transport code system PHITS

The Particle and Heavy Ion Transport code System (PHITS) is a general-purpose Monte Carlo simulation code that has been applied in various areas of medical physics. These include application in different types of radiotherapy, shielding calculations, application to radiation biology, and research and development of medical tools. In this article, the useful features of PHITS are explained by referring to actual examples of various medical applications.