Earticle

Background: Computed tomography (CT) is one of the crucial diagnostic tools in modern medicine. However, careful monitoring of radiation dose for CT patients is essential since the procedure involves ionizing radiation, a known carcinogen. Materials and Methods: The most desirable CT dose descriptor for risk analysis is the organ absorbed dose. A variety of CT organ dose calculators currently available were reviewed in this article. Results and Discussion: Key common elements included in CT dose calculators were discussed and compared, such as computational human phantoms, CT scanner models, organ dose database, effective dose calculation methods, tube current modulation modeling, and user interface platforms. Conclusion: It is envisioned that more research needs to be conducted to more accurately map CT coverage on computational human phantoms, to automatically segment organs and tissues for patient-specific dose calculations, and to accurately estimate radiation dose in the cone beam computed tomography process during image-guided radiation therapy.

Background: Dual-energy X-ray images (DEI) can distinguish or improve materials of interest in a two-dimensional radiographic image, by combining two images obtained from separate low and high energies. The concepts of DEI performance describing the performance of doubleexposure DEI systems in the Fourier domain been previously introduced, however, the performance of double-exposure DEI itself in terms of various parameters, has not been reported. Materials and Methods: To investigate the DEI performance, signal-difference-to-noise ratio, modulation transfer function, noise power spectrum, and noise equivalent quanta were used. Low- and high-energy were 60 and 130 kVp with 0.01–0.09 mGy, respectively. The energyseparation filter material and its thicknesses were tin (Sn) and 0.0–1.0 mm, respectively. Noisereduction (NR) filtering used the Gaussian-filter NR, median-filter NR, and anti-correlated NR. Results and Discussion: DEI performance was affected by Sn-filter thickness, weighting factor, and dose allocation. All NR filtering successfully reduced noise, when compared with the dual-energy (DE) images without any NR filtering. Conclusion: The results indicated the significance of investigating, and evaluating suitable DEI performance, for DE images in chest radiography applications. Additionally, all the NR filtering methods were effective at reducing noise in the resultant DE images.

Background: The International Commission on Radiological Protection is preparing to provide reference dose coefficients for environmental radioiodine intake based on newly developed age-specific biokinetic models. However, the biokinetics of iodine has been reported to be strongly dependent on the dietary intake of stable iodine; for example, the thyroidal uptake of iodine may be substantially lower in iodine-rich regions than in iodine-deficient regions. Therefore, this study attempted to establish a system of age-specific thyroid dose estimation for South Koreans, whose daily iodine intakes are significantly higher than that of the world population. Materials and Methods: Korean age-specific biokinetic parameters and thyroid masses were derived based on the previously developed Korean adult model and the Korean anatomical reference data for adults, respectively. This study complied with the principles used in the development of age-specific biokinetic models for world population and used the ratios of baseline values for each age group relative to the value for adults to derive age-specific values. Results and Discussion: Biokinetic model predictions based on the Korean age-specific parameters showed significant differences in iodine behaviors in the body compared to those predicted using the model for the world population. In particular, the Korean age-specific thyroid dose coefficients for 129I and 131I were considerably lower than those calculated for the world population (25%–76% of the values for the world population). Conclusion: These differences stress the need for Korean-specific internal dose assessments for infants and children, which can be achieved by using the data calculated in this study.

Background: This study was carried out to provide environmental transfer parameter values to estimate activity concentrations of these radionuclides in agricultural crops when direct contamination occurred. Materials and Methods: Mass interception fractions (FBs) and weathering half-lives (Tws) of 131I and radiocesium were calculated using openly available monitoring data obtained after the Fukushima Daiichi Nuclear Power Plant accident. FB is the ratio between the initial radioactivity concentration of a radionuclide retained by the edible part of the plant (Bq‧ kg-1 fresh weight [FW]) and the amount of deposited radionuclide in that area (Bq‧m-2). Tw values can be calculated using activity concentrations of crops decreased with time after the initial contamination. Results and Discussion: Calculated FB and Tw values for 131I and radiocesium were mostly obtained for leafy vegetables. The analytical results showed that there was no difference of FBs between 131I and radiocesium by t-test; geometric mean values for leafy vegetables cultivated under outdoor conditions were 0.058 and 0.12 m2 ‧ kg-1 FW, respectively. Geometric mean Tw value of 131I in leafy vegetables grown under outdoor conditions was 8.6 days, and that of radiocesium was 6.6 days; there was no significant difference between Tw values of these radionuclides by Wilcoxon rank sum test. Conclusion: There was no difference between 131I and radiocesium for FBs and Tws. By using these factors, we would be able to carry out a rough estimation of the activity concentrations of 131I and radiocesium in the edible part of leafy crops when a nuclear accident occurred.

Background: The radionuclides released by the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident 9 years ago are still being monitored by various research teams and the Japanese government. Comparison of different surveys’ results could help evaluate the exposure doses and the mechanism of radiocesium behavior in the urban environment in the area. In this study, we clarified the relationship between land use and temporal changes in the ambient dose rates (air dose rates) using big data. Materials and Methods: We set a series of 1 × 1 km2 meshes within the 80 km zone of the FDNPP to compare the different survey results. We then prepared an analysis dataset from all survey meshes to analyze the temporal change in the air dose rate. The selected meshes included data from all survey types (airborne, fixed point, backpack, and carborne) obtained through the all-time survey campaigns. Results and Discussion: The characteristics of each survey’s results were then evaluated using this dataset, as they depended on the measurement object. The dataset analysis revealed that, for example, the results of the carborne survey were smaller than those of the other surveys because the field of view of the carborne survey was limited to paved roads. The location factor of different land uses was also evaluated considering the characteristics of the four survey methods. Nine years after the FDNPP accident, the location factor ranged from 0.26 to 0.49, while the half-life of the air dose rate ranged from 1.2 to 1.6. Conclusion: We found that the decreasing trend in the air dose rate of the FDNPP accident was similar to the results obtained after the Chernobyl accident. These parameters will be useful for the prediction of the future exposure dose at the post-accident.

Background: Surface soil radiation monitoring around nuclear facilities is important to classify and characterize the contaminated areas. A scanning and direct measurement technique can survey the sites rapidly before starting sampling analysis. Materials and Methods: Regarding this, we test and suggest a measurement technique for gross alpha/beta and 90Sr activities in surface soil based on a mobile ZnS(Ag)/PVT (polyvinyltoluene) array and a handheld PVT rod, respectively. To detect 90Sr selectively in soil mixed with naturally occurring radioactive materials, chosen energy channel counts from the multichannel analyzers were used instead of whole channel counts. Soil samples contaminated with exempt liquid 90Sr with 1 Bq· g-1, 3 Bq· g-1, and 10 Bq· g-1 were prepared and hardened by flocculation. Results and Discussion: The mobile ZnS(Ag)/PVT array could discriminate gross alpha, gross beta, and gamma radiation by the different pulse-shaped signal features of each sensor material. If the array is deployed on a vehicle, the scan minimum detectable concentration (MDC) range will be about 0.11–0.17 Bq· g-1 at 18 km·h-1 speed, highly sensitive to actual sites. The handheld PVT rod with 12 mm (Φ) × 20 mm (H) size can directly measure 90Sr selectively if channels on which energies are from 1,470 and 2,279 keV are gated, minimizing crossdetection of other radionuclides. These methods were verified by measuring soil samples fabricated with homogeneous 90Sr concentrations, showing static MDC of 2.16 Bq· g-1 at a measurement time of 300 seconds. Conclusion: Based on the results, comprehensive procedures using these detectors are suggested to optimize soil sites survey.

Background: Identification of radioisotopes for plastic scintillation detectors is challenging because their spectra have poor energy resolutions and lack photo peaks. To overcome this weakness, many researchers have conducted radioisotope identification studies using machine learning algorithms; however, the effect of data normalization on radioisotope identification has not been addressed yet. Furthermore, studies on machine learning-based radioisotope identifiers for plastic scintillation detectors are limited. Materials and Methods: In this study, machine learning-based radioisotope identifiers were implemented, and their performances according to data normalization methods were compared. Eight classes of radioisotopes consisting of combinations of 22Na, 60Co, and 137Cs, and the background, were defined. The training set was generated by the random sampling technique based on probabilistic density functions acquired by experiments and simulations, and test set was acquired by experiments. Support vector machine (SVM), artificial neural network (ANN), and convolutional neural network (CNN) were implemented as radioisotope identifiers with six data normalization methods, and trained using the generated training set. Results and Discussion: The implemented identifiers were evaluated by test sets acquired by experiments with and without gain shifts to confirm the robustness of the identifiers against the gain shift effect. Among the three machine learning-based radioisotope identifiers, prediction accuracy followed the order SVM >ANN>CNN, while the training time followed the order SVM>ANN>CNN. Conclusion: The prediction accuracy for the combined test sets was highest with the SVM. The CNN exhibited a minimum variation in prediction accuracy for each class, even though it had the lowest prediction accuracy for the combined test sets among three identifiers. The SVM exhibited the highest prediction accuracy for the combined test sets, and its training time was the shortest among three identifiers.

Background: Radiation exposure can occur as a result of occupational activities utilizing sources of radiation. The average level of occupational exposure is generally similar to the global average, but some workers receive more than this. In this study, the occupational exposure data for workers in Korea to check the recent trend of radiation exposure. Materials and Methods: The data collection and analysis are carried out by two separate periods based on the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) survey. One is the year 2003 to 2014 for a recent survey, and the other is 2015 to 2019. All available data were collected by annual reports from radiation dose registry organizations. Results and Discussion: The annual dose over the record level to the total workers did not change much compared with the total increasing number of workers in this period. The dose to the nuclear fuel cycle field has a tendency to decrease. It resulted from the efforts of radiation dose reduction with high technology introduced to this area. Also, it is important result that the radiation dose to the workers in radiography is remarkably reduced. Conclusion: The number of radiation workers and average doses were analyzed for occupational categories in Korea. It still needs cooperative efforts between the dose registry organizations for the efficient dose management of Korean radiation workers.