AOP report: Development of an adverse outcome pathway for deposition of energy leading to cataracts.

Cataracts are one of the leading causes of blindness, with an estimated 95 million people affected worldwide. A hallmark of cataract development is lens opacification, typically associated not only with aging but also radiation exposure as encountered by interventional radiologists and astronauts during the long-term space mission. To better understand radiation-induced cataracts, the adverse outcome pathway (AOP) framework was used to structure and evaluate knowledge across biological levels of organization (e.g., macromolecular, cell, tissue, organ, organism and population). AOPs identify a sequence of key events (KEs) causally connected by key event relationships (KERs) beginning with a molecular initiating event to an adverse outcome (AO) of relevance to regulatory decision-making. To construct the cataract AO and retrieve evidence to support it, a scoping review methodology was used to filter, screen, and review studies based on the modified Bradford Hill criteria. Eight KEs were identified that were moderately supported by empirical evidence (e.g., dose-, time-, incidence-concordance) across the adjacent (directly linked) relationships using well-established endpoints. Over half of the evidence to justify the KER linkages was derived from the evidence stream of biological plausibility. Early KEs of oxidative stress and protein modifications had strong linkages to downstream KEs and could be the focus of countermeasure development. Several identified knowledge gaps and inconsistencies related to the quantitative understanding of KERs which could be the basis of future research, most notably directed to experiments in the range of low or moderate doses and dose-rates, relevant to radiation workers and other occupational exposures.

Interlaboratory comparison of high-throughput protein biomarker assay quantifications for radiation exposure classification.

In the event of a widespread radiological incident, thousands of individuals will require rapid assessment of exposure using validated biodosimetry assays to inform clinical triage. In this scenario, multiple biodosimetry laboratories may be necessary for large-volume sample processing. To meet this need, we have developed a high-throughput assay for the rapid measurement of intracellular protein biomarkers in human peripheral blood samples using an Imaging Flow Cytometry (IFC) platform. The objective of this work was to harmonize and validate the reproducibility of our blood biomarker assay for radiation exposure across three IFC instruments, two located at Columbia University (CU) and the third at Health Canada. The Center for Radiological Research (CRR) at CU served as the central laboratory and reference instrument, where samples were prepared in triplicate, labeled with two radiation responsive leukocyte biomarkers (BAX and phosphor-p53 (Ser37)), and distributed for simultaneous interrogation by each IFC. Initial tests showed that significantly different baseline biomarker measurements were generated on each instrument when using the same acquisition settings, suggesting that harmonization of signal intensities is necessary. Subsequent tests harmonized biomarker measurements after irradiation by modulating laser intensity using two reference materials: unstained samples and standardized rainbow beads. Both methods generated measurements on each instrument without significant differences between the new and references instruments, allowing for the use of one master template to quantify biomarker expression across multiple instruments. Deming regression analyses of 0-5 Gy dose-response curves showed overall good correlation of BAX and p53 values across new and reference instruments. While Bland-Altman analyses indicated low to moderate instrument biases, ROC Curve analyses ultimately show successful discrimination between exposed and unexposed samples on each instrument (AUC values > 0.85).

Development of high-throughput systems for biodosimetry.

Biomarkers for ionising radiation exposure have great utility in scenarios where there has been a potential exposure and physical dosimetry is missing or in dispute, such as for occupational and accidental exposures. Biomarkers that respond as a function of dose are particularly useful as biodosemeters to determine the dose of radiation to which an individual has been exposed. These dose measurements can also be used in medical scenarios to track doses from medical exposures and even have the potential to identify an individual's response to radiation exposure that could help tailor treatments. The measurement of biomarkers of exposure in medicine and for accidents, where a larger number of samples would be required, is limited by the throughput of analysis (i.e. the number of samples that could be processed and analysed), particularly for microscope-based methods, which tend to be labour-intensive. Rapid analysis in an emergency scenario, such as a large-scale accident, would provide dose estimates to medical practitioners, allowing timely administration of the appropriate medical countermeasures to help mitigate the effects of radiation exposure. In order to improve sample throughput for biomarker analysis, much effort has been devoted to automating the process from sample preparation through automated image analysis. This paper will focus mainly on biological endpoints traditionally analysed by microscopy, specifically dicentric chromosomes, micronuclei and gamma-H2AX. These endpoints provide examples where sample throughput has been improved through automated image acquisition, analysis of images acquired by microscopy, as well as methods that have been developed for analysis using imaging flow cytometry.

Application of the Cytokinesis-Block Micronucleus Assay for High-Dose Exposures Using Imaging Flow Cytometry.

The cytokinesis-block micronucleus assay is a well-established method to assess radiation-induced genetic damage in human cells. This assay has been adapted to imaging flow cytometry (IFC), allowing automated analysis of many cells, and eliminating the need to create microscope slides. Furthermore, to improve the efficiency of assay performance, a small-volume method previously developed was employed. Irradiated human blood samples were cultured, stained, and analyzed by IFC to produce images of the cells. Samples were run using both manual and 96-well plate automated acquisition. Multiple parameter-based image features were collected for each sample, and the results were compared to confirm that these acquisition methods are functionally identical. This paper details the multi-parametric analysis developed and the resulting calibration curves up to 10 Gy. The calibration curves were created using a quadratic random coefficient model with Poisson errors, as well as a logistic discriminant function. The curves were then validated with blinded, irradiated samples, using relative bias and relative mean square error. Overall, the accuracy of the dose estimates was adequate for triage dosimetry (within 1 Gy of the true dose) over 90% of the time for lower doses and about half the time for higher doses, with the lowest success rate between 5 and 6 Gy where the calibration curve reached its peak and there was the smallest change in MN/BNC with dose. This work describes the application of a novel multi-parametric analysis that fits the calibration curves and allows dose estimates up to 10 Gy, which were previously limited to 4 Gy. Furthermore, it demonstrates that the results from samples acquired manually and with the autosampler are functionally similar.

Comparison of Isolated Lymphocyte and Whole Blood-Based CBMN Assays for Radiation Triage.

Following a mass-casualty nuclear/radiological event, there will be an important need for rapid and accurate estimation of absorbed dose for biological triage. The cytokinesis-block micronucleus (CBMN) assay is an established and validated cytogenetic biomarker used to assess DNA damage in irradiated peripheral blood lymphocytes. Here, we describe an intercomparison experiment between two biodosimetry laboratories, located at Columbia University (CU) and Health Canada (HC) that performed different variants of the human blood CBMN assay to reconstruct dose in human blood, with CU performing the assay on isolated lymphocytes and using semi-automated scoring whereas HC used the more conventional whole blood assay. Although the micronucleus yields varied significantly between the two assays, the predicted doses closely matched up to 4 Gy - the range from which the HC calibration curve was previously established. These results highlight the importance of a robust calibration curve(s) across a wide age range of donors that match the exposure scenario as closely as possible and that will account for differences in methodology between laboratories. We have seen that at low doses, variability in the results may be attributed to variation in the processing while at higher doses the variation is dominated by inter-individual variation in cell proliferation. This interlaboratory collaboration further highlights the usefulness of the CBMN endpoint to accurately reconstruct absorbed dose in human blood after ionizing radiation exposure.

Improving radiation dosimetry with an automated micronucleus scoring system: correction of automated scoring errors.

Radiation dose estimations performed by automated counting of micronuclei (MN) have been studied for their utility for triage following large-scale radiological incidents; although speed is essential, it also is essential to estimate radiation doses as accurately as possible for long-term epidemiological follow-up. Our goal in this study was to evaluate and improve the performance of automated MN counting for biodosimetry using the cytokinesis-block micronucleus (CBMN) assay. We measured false detection rates and used them to improve the accuracy of dosimetry. The average false-positive rate for binucleated cells was 1.14%; average false-positive and -negative MN rates were 1.03% and 3.50%, respectively. Detection errors seemed to be correlated with radiation dose. Correction of errors by visual inspection of images used for automated counting, called the semi-automated and manual scoring method, increased accuracy of dose estimation. Our findings suggest that dose assessment of the automated MN scoring system can be improved by subsequent error correction, which could be useful for performing biodosimetry on large numbers of people rapidly, accurately, and efficiently.

The Imaging Flow Cytometry-Based Cytokinesis-Block MicroNucleus (CBMN) Assay.

The dose of ionizing radiation received by an individual can be determined using biodosimetry methods which measure biomarkers of exposure in tissue samples from that individual. These markers can be expressed in many ways, including DNA damage and repair processes. Following a mass casualty event involving radiological or nuclear material, it is important to rapidly provide this information to medical responders to assist in the medical management of potentially exposed casualties. Traditional methods of biodosimetry rely on microscope analysis, making them time-consuming and labor-intensive. To increase sample throughput following a large-scale radiological mass casualty event, several biodosimetry assays have been adapted for analysis by imaging flow cytometry. This chapter briefly reviews these methods with a focus on the most current methodology to identify and quantify micronuclei in binucleated cells within the cytokinesis-block micronucleus assay using an imaging flow cytometer.

Considerations for application of benchmark dose modeling in radiation research: workshop highlights.

BACKGROUND: Exposure to different forms of ionizing radiation occurs in diverse occupational, medical, and environmental settings. Improving the accuracy of the estimated health risks associated with exposure is therefore, essential for protecting the public, particularly as it relates to chronic low dose exposures. A key aspect to understanding health risks is precise and accurate modeling of the dose-response relationship. Toward this vision, benchmark dose (BMD) modeling may be a suitable approach for consideration in the radiation field. BMD modeling is already extensively used for chemical hazard assessments and is considered statistically preferable to identifying low and no observed adverse effects levels. BMD modeling involves fitting mathematical models to dose-response data for a relevant biological endpoint and identifying a point of departure (the BMD, or its lower bound). Recent examples in chemical toxicology show that when applied to molecular endpoints (e.g. genotoxic and transcriptional endpoints), BMDs correlate to points of departure for more apical endpoints such as phenotypic changes (e.g. adverse effects) of interest to regulatory decisions. This use of BMD modeling may be valuable to explore in the radiation field, specifically in combination with adverse outcome pathways, and may facilitate better interpretation of relevant in vivo and in vitro dose-response data. To advance this application, a workshop was organized on June 3rd, 2022, in Ottawa, Ontario that brought together BMD experts in chemical toxicology and the radiation scientific community of researchers, regulators, and policy-makers. The workshop's objective was to introduce radiation scientists to BMD modeling and its practical application using case examples from the chemical toxicity field and demonstrate the BMDExpress software using a radiation dataset. Discussions focused on the BMD approach, the importance of experimental design, regulatory applications, its use in supporting the development of adverse outcome pathways, and specific radiation-relevant examples. CONCLUSIONS: Although further deliberations are needed to advance the use of BMD modeling in the radiation field, these initial discussions and partnerships highlight some key steps to guide future undertakings related to new experimental work.

Application of a semi-automated dicentric scoring system in triage and monitoring occupational radiation exposure.

The dicentric chromosome assay (DCA) is considered the gold standard for radiation biodosimetry, but it is limited by its long dicentric scoring time and need for skilled scorers. The automation of scoring dicentrics has been considered a strategy to overcome the constraints of DCA. However, the studies on automated scoring methods are limited compared to those on conventional manual DCA. Our study aims to assess the performance of a semi-automated scoring method for DCA using ex vivo and in vivo irradiated samples. Dose estimations of 39 blind samples irradiated ex vivo and 35 industrial radiographers occupationally exposed in vivo were estimated using the manual and semi-automated scoring methods and subsequently compared. The semi-automated scoring method, which removed the false positives of automated scoring using the dicentric chromosome (DC) scoring algorithm, had an accuracy of 94.9% in the ex vivo irradiated samples. It also had more than 90% accuracy, sensitivity, and specificity to distinguish binary dose categories reflecting clinical, diagnostic, and epidemiological significance. These data were comparable to those of manual DCA. Moreover, Cohen's kappa statistic and McNemar's test showed a substantial agreement between the two methods for categorizing in vivo samples into never and ever radiation exposure. There was also a significant correlation between the two methods. Despite of comparable results with two methods, lower sensitivity of semi-automated scoring method could be limited to assess various radiation exposures. Taken together, our findings show the semi-automated scoring method can provide accurate dose estimation rapidly, and can be useful as an alternative to manual DCA for biodosimetry in large-scale accidents or cases to monitor radiation exposure of radiation workers.

Benchmark dose modeling of transcriptional data: a systematic approach to identify best practices for study designs used in radiation research.

PURPOSE: Benchmark dose (BMD) modeling is a method commonly used in chemical toxicology to identify the point of departure (POD) from a dose-response curve linked to a health-related outcome. Recently, its application in the analysis of transcriptional data for quantitative adverse outcome pathway (AOP) development is being explored. As AOPs are informed by diverse data types, it is important to understand the impact of study parameters such as dose selection, the number of replicates and dose range on BMD outputs for radiation-induced genes and pathways. MATERIALS AND METHODS: Data were selected from the Gene Expression Omnibus (GSE52403) that featured gene expression profiles of peripheral blood samples from C57BL/6 mice 6 hours post-exposure to 137Cs gamma-radiation at 0, 1, 2, 3, 4.5, 6, 8 and 10.5 Gy. The dataset comprised a broad dose range over multiple dose points with consistent dose spacing and multiple biological replicates. This dataset was ideal for systematically transforming across three categories: (1) dose range, (2) dose-spacing and (3) number of controls/replicates. Across these categories, 29 transformed datasets were compared to the original dataset to determine the impact of each transformation on the BMD outputs. RESULTS: Most of the experimental changes did not impact the BMD outputs. The transformed datasets were largely consistent with the original dataset in terms of the number of reproduced genes modeled and absolute BMD values for genes and pathways. Variations in dose selection identified the importance of the absolute value of the lowest and second dose. It was determined that dose selection should include at least two doses <1 Gy and two >5 Gy to achieve meaningful BMD outputs. Changes to the number of biological replicates in the control and non-zero dose groups impacted the overall accuracy and precision of the BMD outputs as well as the ability to fit dose-response models consistent with the original dataset. CONCLUSION: Successful application of transcriptomic BMD modeling for radiation datasets requires considerations of the exposure dose and the number of biological replicates. Most important is the selection of the lowest doses and dose spacing. Reflections on these parameters in experimental design will provide meaningful BMD outputs that could correlate well to apical endpoints of relevance to radiation exposure assessment.

Expert consultation is vital for adverse outcome pathway development: a case example of cardiovascular effects of ionizing radiation.

BACKGROUND: The circulatory system distributes nutrients, signaling molecules, and immune cells to vital organs and soft tissues. Epidemiological, animal, and in vitro cellular mechanistic studies have highlighted that exposure to ionizing radiation (IR) can induce molecular changes in cellular and subcellular milieus leading to long-term health impacts, particularly on the circulatory system. Although the mechanisms for the pathologies are not fully elucidated, endothelial dysfunction is proven to be a critical event via radiation-induced oxidative stress mediators. To delineate connectivities of events specifically to cardiovascular disease (CVD) initiation and progression, the adverse outcome pathway (AOP) approach was used with consultation from field experts. AOPs are a means to organize information around a disease of interest to a regulatory question. An AOP begins with a molecular initiating event and ends in an adverse outcome via sequential linkages of key event relationships that are supported by evidence in the form of the modified Bradford-Hill criteria. Detailed guidelines on building AOPs are provided by the Organisation for Economic Cooperation and Development (OECD) AOP program. Here, we report on the questions and discussions needed to develop an AOP for CVD resulting from IR exposure. A recent workshop jointly organized by the MELODI (Multidisciplinary European Low Dose Initiative) and the ALLIANCE (European Radioecology Alliance) associations brought together experts from the OECD to present the AOP approach and tools with examples from the toxicology field. As part of this workshop, four working groups were formed to discuss the identification of adverse outcomes relevant to radiation exposures and development of potential AOPs, one of which was focused on IR-induced cardiovascular effects. Each working group comprised subject matter experts and radiation researchers interested in the specific disease area and included an AOP coach. CONCLUSION: The CVD working group identified the critical questions of interest for AOP development, including the exposure scenario that would inform the evidence, the mechanisms of toxicity, the initiating event, intermediate key events/relationships, and the type of data currently available. This commentary describes the four-day discussion of the CVD working group, its outcomes, and demonstrates how collaboration and expert consultation is vital to informing AOP construction.

RENEB Inter-Laboratory comparison 2017: limits and pitfalls of ILCs.

PURPOSE: In case of a mass-casualty radiological event, there would be a need for networking to overcome surge limitations and to quickly obtain homogeneous results (reported aberration frequencies or estimated doses) among biodosimetry laboratories. These results must be consistent within such network. Inter-laboratory comparisons (ILCs) are widely accepted to achieve this homogeneity. At the European level, a great effort has been made to harmonize biological dosimetry laboratories, notably during the MULTIBIODOSE and RENEB projects. In order to continue the harmonization efforts, the RENEB consortium launched this intercomparison which is larger than the RENEB network, as it involves 38 laboratories from 21 countries. In this ILC all steps of the process were monitored, from blood shipment to dose estimation. This exercise also aimed to evaluate the statistical tools used to compare laboratory performance. MATERIALS AND METHODS: Blood samples were irradiated at three different doses, 1.8, 0.4 and 0 Gy (samples A, C and B) with 4-MV X-rays at 0.5 Gy min-1, and sent to the participant laboratories. Each laboratory was requested to blindly analyze 500 cells per sample and to report the observed frequency of dicentric chromosomes per metaphase and the corresponding estimated dose. RESULTS: This ILC demonstrates that blood samples can be successfully distributed among laboratories worldwide to perform biological dosimetry in case of a mass casualty event. Having achieved a substantial harmonization in multiple areas among the RENEB laboratories issues were identified with the available statistical tools, which are not capable to advantageously exploit the richness of results of a large ILCs. Even though Z- and U-tests are accepted methods for biodosimetry ILCs, setting the number of analyzed metaphases to 500 and establishing a tests' common threshold for all studied doses is inappropriate for evaluating laboratory performance. Another problem highlighted by this ILC is the issue of the dose-effect curve diversity. It clearly appears that, despite the initial advantage of including the scoring specificities of each laboratory, the lack of defined criteria for assessing the robustness of each laboratory's curve is a disadvantage for the 'one curve per laboratory' model. CONCLUSIONS: Based on our study, it seems relevant to develop tools better adapted to the collection and processing of results produced by the participant laboratories. We are confident that, after an initial harmonization phase reached by the RENEB laboratories, a new step toward a better optimization of the laboratory networks in biological dosimetry and associated ILC is on the way.

Intercomparison of conventional and QuickScan dicentric scoring for the validation of individual biodosimetry analysis in Taiwan.

PURPOSE: The dicentric chromosome assay (DCA), the gold standard for radiation biodosimetry, evaluates an individual absorbed radiation dose by the analysis of DNA damage in human lymphocytes. The conventional (C-DCA) and QuickScan (QS-DCA) scoring methods are sensitive for estimating radiation dose. The Biodosimetry Laboratory at Institute of Nuclear Energy Research (INER), Taiwan, participated in intercomparison exercises conducted by Health Canada (HC) in 2014, 2015 and 2018 to validate the laboratory's accuracy and performance. MATERIAL AND METHODS: Blood samples for the conventional dose response curve for Taiwan were irradiated with 0, 0.25, 0.5, 1, 2, 3, 4 and 5 Gy. Ten blind blood samples were provided by HC. Either or both of two methods of conventional (C) or QuickScan (QS) scoring could be chosen for the HC's intercomparison. For C-DCA triage scoring, only cells with 46 centromeres were counted and each scorer recorded the number of dicentrics in the first 50 metaphases or stopped scoring when 30 dicentrics were reached. Scorers also recorded how much time it took to analyze 10, 20, and 50 cells. Subsequently, the data were entered into the Dose Estimate software (DoseEstimate_v5.1) and dose estimates were calculated. With QS-DCA scoring, a minimum of 50 metaphase cells (or 30 dicentrics) were scored in apparently complete metaphases without verification of exactly 46 centromeres. RESULTS: For the blinded blood samples irradiated at HC and shipped to INER, the mean absolute deviation (MAD) derived after scoring 50 cells for C-DCA and QS-DCA was <0.5 Gy for all three intercomparisons, meeting the criteria for acceptance. CONCLUSION: The results indicated that the Biodosimetry Laboratory at INER can provide reliable dose estimates in the case of a large-scale radiation accident.

Bringing together scientific disciplines for collaborative undertakings: a vision for advancing the adverse outcome pathway framework.

BACKGROUND: Decades of research to understand the impacts of various types of environmental occupational and medical stressors on human health have produced a vast amount of data across many scientific disciplines. Organizing these data in a meaningful way to support risk assessment has been a significant challenge. To address this and other challenges in modernizing chemical health risk assessment, the Organisation for Economic Cooperation and Development (OECD) formalized the adverse outcome pathway (AOP) framework, an approach to consolidate knowledge into measurable key events (KEs) at various levels of biological organisation causally linked to disease based on the weight of scientific evidence (http://oe.cd/aops). Currently, AOPs have been considered predominantly in chemical safety but are relevant to radiation. In this context, the Nuclear Energy Agency's (NEA's) High-Level Group on Low Dose Research (HLG-LDR) is working to improve research co-ordination, including radiological research with chemical research, identify synergies between the fields and to avoid duplication of efforts and resource investments. To this end, a virtual workshop was held on 7 and 8 October 2020 with experts from the OECD AOP Programme together with the radiation and chemical research/regulation communities. The workshop was a coordinated effort of Health Canada, the Electric Power Research Institute (EPRI), and the Nuclear Energy Agency (NEA). The AOP approach was discussed including key issues to fully embrace its value and catalyze implementation in areas of radiation risk assessment. CONCLUSIONS: A joint chemical and radiological expert group was proposed as a means to encourage cooperation between risk assessors and an initial vision was discussed on a path forward. A global survey was suggested as a way to identify priority health outcomes of regulatory interest for AOP development. Multidisciplinary teams are needed to address the challenge of producing the appropriate data for risk assessments. Data management and machine learning tools were highlighted as a way to progress from weight of evidence to computational causal inference.

Challenges in the quantification approach to a radiation relevant adverse outcome pathway for lung cancer.

PURPOSE: Adverse outcome pathways (AOPs) provide a modular framework for describing sequences of biological key events (KEs) and key event relationships (KERs) across levels of biological organization. Empirical evidence across KERs can support construction of quantified AOPs (qAOPs). Using an example AOP of energy deposition from ionizing radiation onto DNA leading to lung cancer incidence, we investigate the feasibility of quantifying data from KERs supported by all types of stressors. The merits and challenges of this process in the context of AOP construction are discussed. MATERIALS AND METHODS: Empirical evidence across studies of dose-response from four KERs of the AOP were compiled independently for quantification. Three upstream KERs comprised of evidence from various radiation types in line with AOP guidelines. For these three KERs, a focused analysis of data from alpha-particle studies was undertaken to better characterize the process to the adverse outcome (AO) for a radon gas stressor. Numerical information was extracted from tables and graphs to plot and tabulate the response of KEs. To complement areas of the AOP quantification process, Monte Carlo (MC) simulations in TOPAS-nBio were performed to model exposure conditions relevant to the AO for an example bronchial compartment of the lung with secretory cell nuclei targets. RESULTS: Quantification of AOP KERs highlighted the relevance of radiation types under the stressor-agnostic intent of AOP design, motivating a focus on specific types. For a given type, significant differences of KE response indicate meaningful data to derive linkages from the MIE to the AO is lacking and that better response-response focused studies are required. The MC study estimates the linear energy transfer (LET) of alpha-particles emitted by radon-222 and its progeny in the secretory cell nuclei of the example lung compartment to range from 94-5+5 to 192-18+15 keV/µm. CONCLUSION: Quantifying AOP components provides a means to assemble empirical evidence across different studies. This highlights challenges in the context of studies examining similar endpoints using different radiation types. Data linking KERs to a MIE of 'deposition of energy' is shown to be non-compatible with the stressor-agnostic principles of AOP design. Limiting data to that describing response-response relationships between adjacent KERs may better delineate studies relevant to the damage that drives a pathway to the next KE and still support an 'all hazards' approach. Such data remains limited and future investigations in the radiation field may consider this approach when designing experiments and reporting their results and outcomes.

Estimating partial-body ionizing radiation exposure by automated cytogenetic biodosimetry.

PURPOSE: Inhomogeneous exposures to ionizing radiation can be detected and quantified with the dicentric chromosome assay (DCA) of metaphase cells. Complete automation of interpretation of the DCA for whole-body irradiation has significantly improved throughput without compromising accuracy, however, low levels of residual false positive dicentric chromosomes (DCs) have confounded its application for partial-body exposure determination. MATERIALS AND METHODS: We describe a method of estimating and correcting for false positive DCs in digitally processed images of metaphase cells. Nearly all DCs detected in unirradiated calibration samples are introduced by digital image processing. DC frequencies of irradiated calibration samples and those exposed to unknown radiation levels are corrected subtracting this false positive fraction from each. In partial-body exposures, the fraction of cells exposed, and radiation dose can be quantified after applying this modification of the contaminated Poisson method. RESULTS: Dose estimates of three partially irradiated samples diverged 0.2-2.5 Gy from physical doses and irradiated cell fractions deviated by 2.3%-15.8% from the known levels. Synthetic partial-body samples comprised of unirradiated and 3 Gy samples from 4 laboratories were correctly discriminated as inhomogeneous by multiple criteria. Root mean squared errors of these dose estimates ranged from 0.52 to 1.14 Gy2 and from 8.1 to 33.3%2 for the fraction of cells irradiated. CONCLUSIONS: Automated DCA can differentiate whole- from partial-body radiation exposures and provides timely quantification of estimated whole-body equivalent dose.

Construction of fluorescence in situ hybridization (FISH) translocation dose-response calibration curve with multiple donor data sets using R, based on ISO 20046:2019 recommendations.

Purpose: Dose-response curve (DRC) generation is an important aspect in cytogenetic biodosimetry for accurate dose estimation for individuals suspected of prior irradiation. DRC construction with dicentric chromosomes after acute radiation is well-established following the publication of the IAEA EPR-Biodosimetry 2011 and ISO 19238:2014. However, the short half-life of dicentrics might not be suitable for retrospective dose estimation in radiation medical workers, radiation accident clean-up workers and the general public living in areas with higher than average amount of radiation. There is an urgent need for a chromosome translocation-based DRC, which is constructed based on translocation identification with fluorescence in situ hybridization (FISH). Despite several attempts to generate such a DRC in the past 40 years, no internationally standardized protocol has been developed until 2019, resulting in possible statistical uncertainties between DRCs previously generated.Materials and methods: Using the recently published ISO 20049:2019, a DRC from five healthy donors (four males: 23, 35, 44, 55 years old, one female: 33 years old) was generated with age-adjusted translocations scored per cell equivalent (age-adjusted Tr/CE), using a modified R-script previously published in EPR-Biodosimetry, for 60Co gamma-ray doses of 0, 0.01, 0.02, 0.05, 0.1, 0.2, 0.5 and 1 Gy. The translocation data set used, based on probes used for chromosomes number 1, 2, and 4, was previously published by Abe et al. in 2018.Results: The results output from R include the DRC coefficients (C, α, ß), their p-values, the goodness-of-fit Pearson's chi square value and its corresponding p-value, and the DRC with its 95% confidence interval (CI). The equation of the DRC obtained was 0.0005 (±0.0001) +0.0178 (±0.0037) D + 0.0901 (±0.0054) D2. DRC generated with averaged Tr/CE had a wider 95% CI than DRC generated with pooled Tr/CE, resulting in a 1.3-1.5 times increase in estimated dose range. No outliers between α coefficients from previously published modified DRCs and our DRC were detected with robust Z-score.Conclusions: ISO 20046:2019 should be referenced for future FISH translocation-based DRC generation to ensure statistical reliability of dose estimation. Important considerations for FISH translocation-based DRC up to 1 Gy include scoring more than 2000 CE per dose, the use of multiple donors, age-adjustment of observed translocations, the use of a minimum of 5 dose points including 0 Gy, scoring of total simple translocations in only stable cells and the decision of using pooled or averaged age-adjusted Tr/CE.

Validation of the dicentric chromosome assay for radiation biological dosimetry in South Korea.

The dicentric chromosome assay (DCA) is a well-established biodosimetry test to estimate exposure to ionizing radiation. The Korea Institute of Radiological and Medical Sciences (KIRAMS) established a DCA protocol as a medical response to radiation emergencies in South Korea. To maintain its accuracy and performance, intercomparison exercises with Health Canada (HC) have been conducted; herein, we aimed to validate our capacity of DCA analysis based on those results. Blood samples irradiated at HC were shipped to KIRAMS to assess the irradiation dose to blinded samples using conventional DCA full scoring and triage-based techniques (conventional DCA scoring in triage mode and DCA QuickScan method). Actual doses fell within the 95% confidence intervals of dose estimates for 70-100% of the blinded samples in 2015-2018. All methods discriminated binary dose categories, reflecting clinical significance. This DCA can be used as a reliable radiation biodosimetry tool in preparation for radiation accidents in South Korea.