Modelling Dose Effects from Space Irradiations: Combination of High-LET and Low-LET Radiations with a Modified Microdosimetric Kinetic Model

Generalized methods for predicting biological response to mixed radiation types and calculating equieffective doses (EQDX)

BACKGROUND

Predicting biological responses to mixed radiation types is of considerable importance when combining radiation therapies that use multiple radiation types and delivery regimens. These may include the use of both low- and high-linear energy transfer (LET) radiations. A number of theoretical models have been developed to address this issue. However, model predictions do not consistently match published experimental data for mixed radiation exposures. Furthermore, the models are often computationally intensive. Accordingly, there is a need for efficient analytical models that can predict responses to mixtures of low- and high-LET radiations. Additionally, a general formalism to calculate equieffective dose (EQDX) for mixed radiations is needed.

PURPOSE

To develop a computationally efficient analytical model that can predict responses to complex mixtures of low- and high-LET radiations as a function of either absorbed dose or EQDX.

METHODS

The Zaider-Rossi model (ZRM) was modified by replacing the geometric mean of the quadratic coefficients in the interaction term with the arithmetic mean. This modified ZRM model (mZRM) was then further generalized to any number of radiation types and its validity was tested against published experimental observations. Comparisons between the predictions of the ZRM and mZRM, and other models, were made using two and three radiation types. In addition, a generalized formalism for calculating EQDX for mixed radiations was developed within the context of mZRM and validated with published experimental results.

RESULTS

The predictions of biological responses to mixed-LET radiations calculated with the mZRM are in better agreement with experimental observations than ZRM, especially when high- and low-LET radiations are mixed. In these situations, the ZRM overestimated the surviving fraction. Furthermore, the EQDX calculated with mZRM are in better agreement with experimental observations.

CONCLUSION

The mZRM is a computationally efficient model that can be used to predict biological response to mixed radiations that have low- and high-LET characteristics. Importantly, interaction terms are retained in the calculation of EQDX for mixed radiation exposures within the mZRM framework. The mZRM has application in a wide range of radiation therapies, including radiopharmaceutical therapy.

The complexity of DNA damage by radiation follows a Gamma distribution: insights from the Microdosimetric Gamma Model

Introduction

DNA damage is the main predictor of response to radiation therapy for cancer. Its Q8 quantification and characterization are paramount for treatment optimization, particularly in advanced modalities such as proton and alpha-targeted therapy.

Methods

We present a novel approach called the Microdosimetric Gamma Model (MGM) to address this important issue. The MGM uses the theory of microdosimetry, specifically the mean energy imparted to small sites, as a predictor of DNA damage properties. MGM provides the number of DNA damage sites and their complexity, which were determined using Monte Carlo simulations with the TOPAS-nBio toolkit for monoenergetic protons and alpha particles. Complexity was used together with a illustrative and simplistic repair model to depict the differences between high and low LET radiations.

Results

DNA damage complexity distributions were were found to follow a Gamma distribution for all monoenergetic particles studied. The MGM functions allowed to predict number of DNA damage sites and their complexity for particles not simulated with microdosimetric measurements (yF) in the range of those studied.

Discussion

Compared to current methods, MGM allows for the characterization of DNA damage induced by beams composed of multi-energy components distributed over any time configuration and spatial distribution. The output can be plugged into ad hoc repair models that can predict cell killing, protein recruitment at repair sites, chromosome aberrations, and other biological effects, as opposed to current models solely focusing on cell survival. These features are particularly important in targeted alpha-therapy, for which biological effects remain largely uncertain. The MGM provides a flexible framework to study the energy, time, and spatial aspects of ionizing radiation and offers an excellent tool for studying and optimizing the biological effects of these radiotherapy modalities.

Implementation of simplified stochastic microdosimetric kinetic models into PHITS for application to radiation treatment planning

PURPOSE

The stochastic microdosimetric kinetic (SMK) model is one of the most sophisticated and precise models used in the estimation of the relative biological effectiveness of carbon-ion radiotherapy (CRT) and boron neutron capture therapy (BNCT). However, because of its complicated and time-consuming calculation procedures, it is nearly impractical to directly incorporate this model into a radiation treatment-planning system.

MATERIALS AND METHODS

Through the introduction of Taylor expansion (TE) or fast Fourier transform (FFT), we developed two simplified SMK models and implemented them into the Particle and Heavy Ion Transport code System (PHITS). To verify the implementation, we calculated the photon isoeffective doses in a cylindrical phantom placed in the radiation fields of passive CRT and accelerator-based BNCT.

RESULTS AND DISCUSSION

Our calculation suggested that both TE-based and FFT-based SMK models can reproduce the data obtained from the original SMK model very well for absorbed doses approximately below 5 Gy, whereas the TE-based SMK model overestimates the original data at higher doses. In terms of computational efficiency, the TE-based SMK model is much faster than the FFT-based SMK model.

CONCLUSION

This study enables the instantaneous calculation of the photo isoeffective dose for CRT and BNCT, considering their cellular-scale dose heterogeneities. Treatment-planning systems that use the improved PHITS as a dose-calculation engine are under development.

Relative Biological Effectiveness of High LET Particles on the Reproductive System and Fetal Development

During a space mission, astronauts are inevitably exposed to space radiation, mainly composed of the particles having high values of linear energy transfer (LET), such as protons, helium nuclei, and other heavier ions. Those high-LET particles could induce severer health damages than low-LET particles such as photons and electrons. While it is known that the biological effectiveness of a specified type of radiation depends on the distribution of dose in time, type of the cell, and the biological endpoint in respect, there are still large uncertainties regarding the effects of high-LET particles on the reproductive system, gamete, embryo, and fetal development because of the limitation of relevant data from epidemiological and experimental studies. To safely achieve the planned deep space missions to the moon and Mars that would involve young astronauts having reproductive functions, it is crucial to know exactly the relevant radiological effects, such as infertility of the parent and various diseases of the child, and then to conduct proper countermeasures. Thus, in this review, the authors present currently available information regarding the relative biological effectiveness (RBE) of high-LET particles on the deterministic effects related to the reproductive system and embryonic/fetal development for further discussions about the safety of being pregnant after or during a long-term interplanetary mission.