Status and Extension of the Geant4-DNA Dielectric Models for Application to Electron Transport

The development of accurate physics models that enable track structure simulations of electrons in liquid water medium over a wide energy range, from the eV to the MeV scale, is a subject of continuous efforts due to its importance (among other things) in theoretical studies of radiation quality for application in radiotherapy and radiation protection. A few years ago, the Geant4-DNA very low-energy extension of the Geant4 Monte Carlo code had offered to users an improved set of physics models for discrete electron transport below 10 keV. In this work we present refinements to this model set and its extension to energies up to 1 MeV. Preliminary comparisons against the existing Geant4-DNA physics models with respect to total and differential ionization cross sections of electrons in liquid water are reported and discussed.

Review of the Geant4-DNA Simulation Toolkit for Radiobiological Applications at the Cellular and DNA Level

The Geant4-DNA low energy extension of the Geant4 Monte Carlo (MC) toolkit is a continuously evolving MC simulation code permitting mechanistic studies of cellular radiobiological effects. Geant4-DNA considers the physical, chemical, and biological stages of the action of ionizing radiation (in the form of x- and γ-ray photons, electrons and β±-rays, hadrons, α-particles, and a set of heavier ions) in living cells towards a variety of applications ranging from predicting radiotherapy outcomes to radiation protection both on earth and in space. In this work, we provide a brief, yet concise, overview of the progress that has been achieved so far concerning the different physical, physicochemical, chemical, and biological models implemented into Geant4-DNA, highlighting the latest developments. Specifically, the “dnadamage1” and “molecularDNA” applications which enable, for the first time within an open-source platform, quantitative predictions of early DNA damage in terms of single-strand-breaks (SSBs), double-strand-breaks (DSBs), and more complex clustered lesions for different DNA structures ranging from the nucleotide level to the entire genome. These developments are critically presented and discussed along with key benchmarking results. The Geant4-DNA toolkit, through its different set of models and functionalities, offers unique capabilities for elucidating the problem of radiation quality or the relative biological effectiveness (RBE) of different ionizing radiations which underlines nearly the whole spectrum of radiotherapeutic modalities, from external high-energy hadron beams to internal low-energy gamma and beta emitters that are used in brachytherapy sources and radiopharmaceuticals, respectively.

Quantitative modeling of carcinogenesis induced by single beams or mixtures of space radiations using targeted and non-targeted effects

Ionizing radiations encountered by astronauts on deep space missions produce biological damage by two main mechanisms: (1) Targeted effects (TE) due to direct traversals of cells by ionizing tracks. (2) Non-targeted effects (NTE) caused by release of signals from directly hit cells. The combination of these mechanisms generates non-linear dose response shapes, which need to be modeled quantitatively to predict health risks from space exploration. Here we used a TE + NTE model to analyze data on APC(1638N/+) mouse tumorigenesis induced by space-relevant doses of protons, 4He, 12C, 16O, 28Si or 56Fe ions, or γ rays. A customized weighted Negative Binomial distribution was used to describe the radiation type- and dose-dependent data variability. This approach allowed detailed quantification of dose–response shapes, NTE- and TE-related model parameters, and radiation quality metrics (relative biological effectiveness, RBE, and radiation effects ratio, RER, relative to γ rays) for each radiation type. Based on the modeled responses for each radiation type, we predicted the tumor yield for a Mars-mission-relevant mixture of these radiations, using the recently-developed incremental effect additivity (IEA) synergy theory. The proposed modeling approach can enhance current knowledge about quantification of space radiation quality effects, dose response shapes, and ultimately the health risks for astronauts.

Role of Mitochondria in IR Responses: Epigenetic, Metabolic, and Signaling Impacts

Until recently, radiation effects have been considered to be mainly due to nuclear DNA damage and their management by repair mechanisms. However, molecular biology studies reveal that the outcomes of exposures to ionizing radiation (IR) highly depend on activation and regulation through other molecular components of organelles that determine cell survival and proliferation capacities. As typical epigenetic-regulated organelles and central power stations of cells, mitochondria play an important pivotal role in those responses. They direct cellular metabolism, energy supply and homeostasis as well as radiation-induced signaling, cell death, and immunological responses. This review is focused on how energy, dose and quality of IR affect mitochondria-dependent epigenetic and functional control at the cellular and tissue level. Low-dose radiation effects on mitochondria appear to be associated with epigenetic and non-targeted effects involved in genomic instability and adaptive responses, whereas high-dose radiation effects (>1 Gy) concern therapeutic effects of radiation and long-term outcomes involving mitochondria-mediated innate and adaptive immune responses. Both effects depend on radiation quality. For example, the increased efficacy of high linear energy transfer particle radiotherapy, e.g., C-ion radiotherapy, relies on the reduction of anastasis, enhanced mitochondria-mediated apoptosis and immunogenic (antitumor) responses.

Quantitative Modeling of Carcinogenesis Induced By Single Beams Or Mixtures of Space Radiations Using Targeted And Non-Targeted Effects

Ionizing radiations encountered by astronauts on deep space missions produce biological damage by two main mechanisms: (1) Targeted effects (TE) due to direct traversals of cells by ionizing tracks. (2) Non-targeted effects (NTE) caused by release of signals from directly hit cells. The combination of these mechanisms generates non-linear dose response shapes, which need to be modeled quantitatively to predict health risks from space exploration. Here we used a TE+NTE model to analyze data on APC(1638N/+) mouse tumorigenesis induced by space-relevant doses of protons, 4He, 12C, 16O, 28Si or 56Fe ions, or γ rays. A customized weighted Negative Binomial distribution was used to describe the radiation type- and dose-dependent data variability. This approach allowed detailed quantification of dose-response shapes, NTE- and TE-related model parameters, and radiation quality metrics (relative biological effectiveness, RBE, and radiation effects ratio, RER, relative to γ rays) for each radiation type. Based on the modeled responses for each radiation type, we predicted the tumor yield for a Mars-mission-relevant mixture of these radiations, using the recently-developed incremental effect additivity (IEA) synergy theory. The proposed modeling approach can enhance current knowledge about quantification of space radiation quality effects, dose response shapes, and ultimately the health risks for astronauts.

A Practical Approach for Continuous In Situ Characterization of Radiation Quality Factors in Space

The space radiation environment is qualitatively different from Earth, and its radiation hazard is generally quantified relative to photons using quality factors that allow assessment of biologically-effective dose. Two approaches exist for estimating radiation quality factors in complex radiation environments: One is a fluence-based risk cross-section approach, which requires very detailed in silico characterization of the radiation field and biological cross sections, and thus cannot realistically be used for in situ monitoring. By contrast, the microdosimetric approach, using measured (or calculated) distributions of microdosimetric energy deposition together with empirical biological weighting functions, is conceptually and practically simpler. To demonstrate feasibility of the microdosimetric approach, we estimated a biological weighting function for one specific endpoint, heavy-ion-induced tumorigenesis in APC1638N/+ mice, which was unfolded from experimental results after a variety of heavy ion exposures together with corresponding calculated heavy-ion microdosimetric energy deposition spectra. Separate biological weighting functions were unfolded for targeted and non-targeted effects, and these differed substantially. We folded these biological weighting functions with microdosimetric energy deposition spectra for different space radiation environments, and conclude that the microdosimetric approach is indeed practical and, in conjunction with in-situ measurements of microdosimetric spectra, can allow continuous readout of biologically-effective dose during space flight.

Repeatability and Reproducibility of Microdosimetry With a Mini-TEPC

Experimental microdosimetry measures the energy deposited in a microscopic sensitive volume (SV) by single ionizing particles traversing the SV or passing by. The fundamental advantage of experimental microdosimetry over the computational approach is that the first allows to determine distributions of energy deposition when information on the energy and nature of the charged particles at the point of interest is incomplete or fragmentary. This is almost always the case in radiation protection applications, but discrepancies between the modelled and the actual scenarios should be considered also in radiation therapy. Models for physical reality are always imperfect and rely both on basic input data and on assumptions and simplifications that are necessarily implemented. Furthermore, unintended events due to human errors or machine/system failures can be minimized but cannot be completely avoided.Though in proton radiation therapy (PRT) a constant relative biological effectiveness (RBE) of 1.1 is assumed, there is evidence of an increasing RBE towards the end of the proton penetration depth. Treatment Planning Systems (TPS) that take into account a variable linear energy transfer (LET) or RBE are already available and could be implemented in PRT in the near future. However, while the calculated dose distributions produced by the TPS are routinely verified with ionization chambers as part of the quality assurance program of every radiotherapy center, there is no commercial detector currently available to perform routine verification of the radiation quality, calculated by the TPS through LET or RBE distributions. Verification of calculated LET is required to make sure that a complex robustly optimized plan will be delivered as planned. The scientific community is coming to conclusion that a new domain of Quality Assurance additionally to the physical dose verification is required, and microdosimetry can be the right approach to address that. A first important prerequisite is the repeatability and reproducibility of microdosimetric measurements. This work aims at studying experimentally the repeatability and reproducibility of microdosimetric measurements performed with a miniaturized Tissue Equivalent Proportional Counter (mini-TEPC) in a 62 MeV proton beam. Experiments were carried out within 1 year and without propane gas recharging and by different operators. RBE was also calculated by applying the Loncol’s weighting function r(y) to microdosimetric distributions. Demonstration of reproducibility of measured microdosimetric quantities y¯F, y¯D and RBE10 in 62 MeV proton beam makes this TEPC a possible metrological tool for LET verification in proton therapy. Future characterization will be performed in higher energy proton beams.