Monte Carlo radiation transport simulations and biophysical models are powerful tools to evaluate the biological effects after exposure to ionizing radiation in radiation protection and radiation therapy. During human body exposure to radiation, DNA lesions as an early biological response are induced by energy deposition, leading to cell death with a certain probability. Thus, conducting translational studies focusing on radiation physics, cellular biology, and oncology is warranted. Herein, two simulation tools for predicting biological effects are introduced, that is, Particle and Heavy-Ion Transport code System (PHITS) and integrated microdosimetric-kinetic model (IMKM). To date, the PHITS code, which implements track-structure calculation at a DNA scale, allows estimation of the DNA damage yields through electrons and protons in various forms, such as single-strand break (SSB), double-strand break (DSB), and complex DSB (that is DSB coupled with additional strand breaks within 10-bp separation). Meanwhile, the IMKM which was developed to consider microdosimetry, the DSB damage responses and heterogeneous cell population can successfully reproduce experimental cell surviving fraction for various irradiation conditions, which can realize the translational study between in vitro cell survival and clinical tumor control probability in cancer treatment. These models would allow a precise understanding of cellular responses after exposure to ionizing radiation. Throughout this review, we discuss the latest status and future prospects of these simulation tools.
Anytime that someone travels by air they will receive a dose of ionising radiation in the form of cosmic radiation. The aim of this study was to estimate the average dose of cosmic radiation received by a member of the Irish public over the period of a typical year due to air travel. The frequency of air travel by Irish residents to several regions was determined using data from various sources. The total dose that one would receive for a typical flight to and from the region was then calculated using software available for flight crews to estimate the radiation dose that they have received through flying. The annual effective dose for an Irish person as a result of cosmic radiation from air travel was estimated to be 68 µSv.
The ion recombination factor (ks) of a beam without a flattening filter differs from that of a filtered beam. In this study, we examined the effect of changing the measurement conditions on ks in the off-axis direction, and clarified the effect on the beam profile. We calculated ks using the Jaffe plot and two-voltage method (TVM) by varying the measurement conditions, adding ks,rel, off-ax to the beam profile, and comparing the changes via local gamma analysis. The central value of ks increased with X-ray energy, and the effect become more pronounced when the measurement depth is varied. For the beam profile with high energy and a field size of 40 × 40 cm2, the results of the local gamma analysis are lower than the reference value. At the maximum dose depth, the results are poor, even when the field size is 30× 30 cm2. At 40× 40 cm2, the results are lower than the reference value even when the criteria are further relaxed. Our results indicate that ks differs depending on the measurement method, and thus, ks,rel,off-ax should be considered when measuring beam profiles with field sizes larger than 30 × 30 cm2.
In Japan, there are 33 types of supercomputers with registered specifications. One of these is jointly owned by the National Institutes for Quantum Science and Technology (QST) and the Japan Atomic Energy Agency (JAEA). This supercomputer has been used in some studies, and information on using it in other research (i.e., natural radiation research) is limited. This supercomputer was used to perform two cases related to natural radiation research (Case 1–Monte Carlo radiation transport calculation and Case 2–Building Artificial Intelligence image recognition model) in this study. This study describes the expected benefits and drawbacks of using this supercomputer from the viewpoint of general natural radiation researchers.
Activities involved with naturally occurring radioactive material (NORM) cover broad industrial sectors with very diverse characteristics. The main contributors to the NORM releases are mining and mineral processing industries. Releases from industries involving NORM are often produced in large amounts, but not well characterised radiologically; as a result, data are lacking to characterize public and worker exposures. The National Pollutant Release Inventory (NPRI) contains a total of 323 pollutants released to air, water and land from all industries in Canada. However, all major radionuclides from uranium and thorium series are not in the reporting list of NPRI. Given this constraint, this report advances our understanding of releases from NORM industries by describing the nature and magnitude of releases for pollutant substances reported in NPRI that are known to have naturally occurring radioactive isotopes other than in uranium and thorium series, and total particulate matters with great potential containing radionuclides from uranium and thorium series. The results indicate that NORM industries are responsible for almost all of the releases to air for the pollutant substances reviewed here: 100% for thallium and its compounds, 97% for lead and its compounds, 95% for cadmium and its compounds, 91% for selenium and its compounds, and 86% for total particulate matter (< 100μm).
In the case of nuclear or radiological emergencies, biodosimetry has been used to estimate radiation dose to exposed persons and provide information to physicians for clinical treatment and counselling of possible future stochastic consequences. There are currently several biological endpoints and techniques available for assessing partial or whole-body radiological exposure in peripheral blood lymphocytes. However, the use of dicentric chromosomes (Dic) in biodosimetry is still recognized as the main dose-assessment method for estimating exposure to ionizing radiation and has become a routine component of radiation protection. Dics are specific to radiation exposure and the background level is low in non-exposed individuals, making them advantageous in biodosimetry. Here, we provide a review of Dics and its role in biodosimetry as research efforts on assay optimization and high throughput have been published since the mid-1960s. Additionally, we provide recommended technical information (e.g., colcemid addition, scoring, generating doseresponse curves) needed to implement the dicentric chromosome assay (DCA) in laboratories and to allow comparable dose assessment following exposure to acute ionizing radiation. While DCA has been optimized for nuclear or radiological emergencies, increased uncertainty in dose estimation can be caused by the scoring of Dic and variation of calibration curves. Total dose, doserate, radiation quality, and sampling time after exposure are some of the factors that influence the results of DCA. Future consideration is also needed as no single assay is sufficient for all radiation scenarios.