FLASH radiotherapy delivers a high dose (≥10 Gy) at a high rate (≥40 Gy/s). In this way, particles are delivered in pulses as short as a few nanoseconds. At that rate, intertrack reactions between chemical species produced within the same pulse may affect the heterogeneous chemistry stage of water radiolysis. This stochastic process suits the capabilities of the Monte Carlo method, which can model intertrack effects to aid in radiobiology research, including the design and interpretation of experiments. In this work, the TOPAS-nBio Monte Carlo track-structure code was expanded to allow simulations of intertrack effects in the chemical stage of water radiolysis. Simulation of the behavior of radiolytic yields over a long period of time (up to 50 s) was verified by simulating radiolysis in a Fricke dosimeter irradiated by ⁶⁰Co γ rays. In addition, LET-dependent G values of protons delivered in single squared pulses of widths, 1 ns, 1 µs and 10 µs, were obtained and compared to simulations using no intertrack considerations. The Fricke simulation for the calculated G value of Fe³⁺ ion at 50 s was within 0.4% of the accepted value from ICRU Report 34. For LET-dependent G values at the end of the chemical stage, intertrack effects were significant at LET values below 2 keV/µm. Above 2 keV/µm the reaction kinetics remained limited locally within each track and thus, effects of intertrack reactions remained low. Therefore, when track structure simulations are used to investigate the biological damage of FLASH irradiation, these intertrack reactions should be considered. The TOPAS-nBio framework with the expansion to intertrack chemistry simulation provides a useful tool to assist in this task.

Simulations of deoxyribonucleic acid (DNA) molecular damage use the traversal algorithm that has the disadvantages of being time-consuming, slowly converging, and requiring high-performance computer clusters. This work presents an improved version of the algorithm, “density-based spatial clustering of applications with noise” (DBSCAN), using a KD-tree approach to find neighbors of each point for calculating clustered DNA damage. The resulting algorithm considers the spatial distributions for sites of energy deposition and hydroxyl radical attack, yielding the statistical probability of (single and double) DNA strand breaks. This work achieves high accuracy and high speed at calculating clustered DNA damage that has been induced by proton treatment at the molecular level while running on an i7 quad-core CPU. The simulations focus on the indirect effect generated by hydroxyl radical attack on DNA. The obtained results are consistent with those of other published experiments and simulations. Due to the array of chemical processes triggered by proton treatment, it is possible to predict the effects that different track structures of various energy protons produce on eliciting direct and indirect damage of DNA.

The effect of low-dose-rate exposure to ionizing radiation on cancer risk is a major issue associated with radiation protection. Tissue stem cells are regarded as one of the targets of radiation-induced carcinogenesis. However, it is hypothesized that the effect of radiation may be reduced if damaged stem cells are eliminated via stem cell competition between damaged and intact stem cells. This would be particularly effective under very low-dose-rate conditions, in which only a few stem cells in a stem cell pool may be affected by radiation. Following this hypothesis, we constructed a simple mathematical model to discuss the influence of stem cell competition attenuating the accumulation of damaged cells under very low-dose-rate conditions. In this model, a constant number of cells were introduced into a cell pool, and the numbers of intact and damaged cells were calculated via transition and turnover events. A transition event emulates radiation dose, whereby an intact cell is changed into a damaged cell with a given probability. On the other hand, a turnover event expresses cell competition, where reproduction and elimination of cells occur depending on the properties of cells. Under very low-dose-rate conditions, this model showed that radiation damage to the stem cell pool was strongly suppressed when the damaged cells were less reproductive and tended to be eliminated compared to the intact cells. Furthermore, the size of the stem cell pool was positively correlated with reduction in radiation damage.

Owing to recent advances in computational dosimetry tools, an update is warranted for the dosimetry system for atomic bomb survivors that was established by the Joint U.S.Japan Working Group on the Reassessment of Atomic Bomb Dosimetry in 2002 (DS02). The DS02 system, and its predecessor, DS86, at the Radiation Effects Research Foundation (RERF), are based on adjoint Monte Carlo particle transport simulations coupled with stylized computational human phantoms. In our previous studies, we developed the J45 series of computational voxel phantoms representative of 1945 Japanese adults, children and pregnant females. The dosimetric impact of replacing the DS02/DS86 stylized phantoms by the J45 phantom series was also discussed through computation of organ doses for several idealized exposure scenarios. In the current study, we investigated the possible impact of introducing not only the J45 phantom series but also various methodological upgrades to the DS02 dosimetry system. For this purpose, we calculated organ doses in adults for 12 representative exposure scenarios having realistic particle energy and angular fluence, using different combinations of phantoms and dose calculation methods. Those doses were compared with survivor organ doses given by the DS02 system. It was found that the anatomical improvement in the J45 phantom series is the most important factor leading to potential changes in survivor organ doses. However, methodological upgrades, such as replacement of the adjoint Monte Carlo simulation with kerma approximation by the forward Monte Carlo simulation with secondary electron transport, can also improve the accuracy of organ doses by up to several percent.In addition, this study established a series of response functions, which allows for the rapid conversion of the unidirectional quasi-monoenergetic photon and neutron fluences from the existing DS02 system to organ doses within the J45 adult phantoms. The overall impact of introducing the response functions in the dosimetry system is not so significant, less than 10% in most cases, except for organs in which the calculation method or definition was changed, e.g., colon and bone marrow. This system of response functions can be implemented within a revision to the DS02 dosimetry system and used for future updates to organ doses within the Life Span Study of the atomic bomb survivors.

In this work, we present a methodology to analytically determine microdosimetric quantities in radioimmunotherapy and targeted radiotherapy with alpha particles. Monte Carlo simulations using the Geant4-DNA toolkit, which provides interaction models at the microscopic level, are performed for monoenergetic alpha particles traversing spherical sites with diameters of 1, 5 and 10 µm. An analytical function is fitted against the data in each case to model the energy imparted by monoenergetic particles to the site, as well as the variance of the distribution of energy imparted. Those models allow us to obtain the mean and dose-mean values of specific energy (z) and lineal energy (y) for polyenergetic arrangements of alpha particles. The energetic spectrum is estimated by considering the distance that each particle needs to travel to reach the sensitive target. We apply this methodology to a simple case in radioimmunotherapy: a spherical cell that has its membrane uniformly covered by ²¹¹At, an alpha emitter, with a spherical target representing the nucleus, placed at the center of the cell. We compare the results of our analytical method with calculations using Geant4-DNA of this specific setup for three nucleus sizes corresponding to our three functions. For nuclei with diameter of 1 µm and 5 µm, all mean and dose-mean quantities for y and z were in an agreement within 4% to Geant4-DNA calculations. This agreement improves to approximately 1% for dose-mean lineal energy and dose-mean specific energy. For the 10-µm-diameter case, discrepancies scale to approximately 9% for mean values and 3% for dose-mean values. Dose-mean values are within Geant4-DNA uncertainties in all cases. Our method provides accurate analytical calculations of dose-mean quantities that may be further employed to characterize radiobiological effectiveness of targeted radiotherapy. The spatial distributions of sources and targets are required to calculate microdosimetric-relevant quantities.

In the event of a major accidental or intentional radiation exposure incident, the affected population could suffer from total- or partial-body exposures to ionizing radiation with acute exposure to organs that would produce life-threatening injury. Therefore, it is necessary to identify markers capable of predicting organ-specific damage so that appropriate directed or encompassing therapies can be applied. In the current work, gene expression changes in response to total-body irradiation (TBI) were identified in heart, lungs and liver tissue of Göttingen minipigs. Animals received 1.7, 1.9, 2.1 or 2.3 Gy TBI and were followed for 45 days. Organ samples were collected at the end of day 45 or sooner if the animal displayed morbidity necessitating euthanasia. Our findings indicate that different organs respond to TBI in a very specific and distinct manner. We also found that the liver was the most affected organ in terms of gene expression changes, and that lipid metabolic pathways were the most deregulated in the liver samples of non-survivors (survival time <45 days). We identified organ-specific gene expression signatures that accurately differentiated non-survivors from survivors and control animals, irrespective of dose and time postirradiation. At what point did these radiation-induced injury markers manifest and how this information could be used for applying intervention therapies are under investigation.

Epidemiological studies have suggested a link between low-level radiation exposure and an increased risk of cardiovascular disease, but the possibility of bias or confounding must be considered. We analyzed data from a matched case-control study nested in a cohort of British male industrial (i.e., blue-collar) nuclear fuel cycle workers using paired conditional logistic regression. The cases were comprised of workers from two nuclear sites who had died from ischemic heart disease (IHD) and were matched to controls on nuclear site, date of birth and first year of employment (1,220 pairs). Radiation doses from external sources and to the liver from internally deposited plutonium and uranium were obtained. Models were adjusted for age at start of employment at either site, decade of start, age at exit from study (death or censoring), process/other worker and socio-economic status. Included potential confounding factors of interest were occupational noise, shift work, pre-employment blood pressure, body mass index and tobacco smoking. Cumulative external doses ranged from 0–1,656 mSv and cumulative internal doses for those monitored for radioactive intakes ranged from 0.004–5,732 mSv. In a categorical analysis, additionally adjusted for whether or not a worker was monitored for internal exposure, IHD mortality risk was associated with cumulative external unlagged dose with a 42% excess risk (95% CI: 4%, 95%) at >103 mSv (highest quartile relative to lowest quartile), and 35% (95% CI: –1%, 84%) at >109 mSv 15-year lagged dose. The log-linear increase in risk per 100 mSv was 2% (95% CI: –4%, 8%) for unlagged external dose and 5% (95% CI: –2%, 11%) for 15-year lagged dose. Associations with external dose for workers monitored only for exposure to external radiation reflected those previously reported for the cohort from which the cases and controls were drawn. There was little evidence of excess risk associated with cumulative doses from internal sources, which had not been assessed in the cohort study. The impact of the included potential confounding variables was minimal, with the possible exception of occupational noise exposure. Subgroup analyses indicated evidence of heterogeneity between sites, occupational groups and employment duration, and an important factor was whether workers were monitored for the potential presence of internal emitters, which was not explained by other factors included in the study. In summary, we found evidence for an increased IHD mortality risk associated with external radiation dose, but little evidence of an association with internal dose. External dose associations were minimally affected by important confounders. However, the considerable heterogeneity in the associations with external doses observed between subgroups of workers is difficult to explain and requires further work.