RABiT-II-DCA: A Fully-automated Dicentric Chromosome Assay in Multiwell Plates

Adaptive Segmentation of DAPI-stained, C-banded, Aggregated and Overlapping Chromosomes

Existing algorithms for automated segmentation of chromosomes and centromeres do not work well for condensed, C-banded and DAPI-stained chromosomes and centromeres. Overlapping and aggregation, which frequently occur in metaphase spreads, introduce additional challenges to the counting of chromosomes and centromeres in the Dicentrics Chromosome Assay (DCA). In this paper, we introduce adaptive algorithms, for segmentation of difficult metaphase spreads that include overlapping and aggregated chromosomes. In order to enhance and segment chromosomes, two optimizations are done: (1) the best algorithm among several options is automatically chosen based on predefined figures of merit, (2) the algorithm is automatically optimized with a binary search to modify its parameters to achieve predefined thresholds. These algorithms are designed to separate mildly or moderately aggregated chromosomal clusters. The clusters are segmented by skeleton junctions, reduction of the overall object thickness, and the watershed algorithm. The chromosomes are characterized by rules we establish, using minimal assumptions. Centromeres are detected by detecting bright spots on the surface of the chromosomes, and then using cluster analysis and shape and intensity profiles to identify them as centromeres. High sensitivity and specificity for chromosome and centromere detection were achieved.

Multiwell-based G0-PCC assay for radiation biodosimetry

In major radiological events, rapid assays to detect ionizing radiation exposure are crucial for effective medical interventions. The purpose of these assays is twofold: to categorize affected individuals into groups for initial treatments, and to provide definitive dose estimates for continued care and epidemiology. However, existing high-throughput cytogenetic biodosimetry assays take about 3 days to yield results, which delays critical interventions. We have developed a multiwell-based variant of the chemical-induced G0-phase Premature Chromosome Condensation Assay that delivers same-day results. Our findings revealed that using a concentration of phosphatase inhibitor lower than recommended significantly increases the yield of cells with highly condensed chromosomes. These chromosomes exhibited increased fragmentation in a dose-dependent manner, enabling to quantify radiation damage using a custom Deep Learning algorithm. This algorithm demonstrated reasonable performance in categorizing doses into distinct treatment groups (84% and 80% accuracy for three and four iso-treatment dose bins, respectively) and showed reliability in determining the actual doses received (correlation coefficient of 0.879). This method is amendable to full automation and has the potential to address the need for same-day, high-throughput cytogenetic test for both dose categorization and dose reconstruction in large-scale radiation emergencies.

RABiT-III: an Automated Micronucleus Assay at a Non-Specialized Biodosimetry Facility

Micronuclei, detected through the cytokinesis-block micronucleus assay, are valuable indicators of ionizing radiation exposure, especially in short-term lymphocyte cultures. The peripheral human blood lymphocyte assay is recognized as a prime candidate for automated biodosimetry. In a prior project at the Columbia University Center for Radiological Research, we automated this assay using the 96-well ANSI/SLAS microplate standard format and relied on established biotech robotic systems named Rapid Automated Biodosimetry Tool (RABiT). In this study, we present the application of a similar automated biotech setup at an external high-throughput facility (RABiT-III) to implement the same automated cytokinesis-block micronucleus assay. Specifically, we employed the Agilent BRAVO liquid-handling system and GE IN Cell Analyzer 6000 imaging system in conjunction with the PerkinElmer Columbus image data storage and analysis system. Notably, this analysis system features an embedded PhenoLOGIC machine learning module, simplifying the creation of cell classification algorithms for CBMN assay image analysis and enabling the generation of radiation dose-response curves. This investigation underscores the adaptability of the RABiT-II CBMN protocol to diverse RABiT-III biotech robotic platforms in non-specialized biodosimetry centers. Furthermore, it highlights the advantages of machine learning in rapidly developing algorithms crucial for the high-throughput automated analysis of RABiT-III images.

Multiwell-based G0-PCC assay for radiation biodosimetry

In cytogenetic biodosimetry, assessing radiation exposure typically requires over 48 hours for cells to reach mitosis, significantly delaying the administration of crucial radiation countermeasures needed within the first 24 hours post-exposure. To improve medical response times, we incorporated the G0-Premature Chromosome Condensation (G0-PCC) technique with the Rapid Automated Biodosimetry Tool-II (RABiT-II), creating a faster alternative for large-scale radiation emergencies. Our findings revealed that using a lower concentration of Calyculin A (Cal A) than recommended effectively increased the yield of highly-condensed G0-PCC cells (hPCC). However, integrating recombinant CDK1/Cyclin B kinase, vital for chromosome condensation, proved challenging due to the properties of these proteins affecting interactions with cellular membranes. Interestingly, Cal A alone was capable of inducing chromosome compaction in some G0 cells even in the absence of mitotic kinases, although these chromosomes displayed atypical morphologies. This suggests that Cal A mechanism for compacting G0 chromatin may differ from condensation driven by mitotic kinases. Additionally, we observed a correlation between radiation dose and extent of hPCC chromosome fragmentation, which allowed us to automate radiation damage quantification using a Convolutional Neural Network (CNN). Our method can address the need for a same-day cytogenetic biodosimetry test in radiation emergency situations.

Sex differences in radiation research

PURPOSE

The Sex Differences in Radiation Research workshop addressed the role of sex as a confounder in radiation research and its implication in real-world radiological and nuclear applications.

METHODS

In April 2022, HHS-wide partners from the Radiation and Nuclear Countermeasures Program, the Office of Research on Women's Health National Institutes of Health Office of Women's Health, U.S. Food and Drug Administration, and the Radiological and Nuclear Countermeasures Branch at the Biomedical Advanced Research and Development Authority conducted a workshop to address the scientific implication and knowledge gaps in understanding sex in basic and translational research. The goals of this workshop were to examine sex differences in 1. Radiation animal models and understand how these may affect radiation medical countermeasure development; 2. Biodosimetry and/or biomarkers used to assess acute radiation syndrome, delayed effects of acute radiation exposure, and/or predict major organ morbidities; 3. medical research that lacks representation from both sexes. In addition, regulatory policies that influence inclusion of women in research, and the gaps that exist in drug development and device clearance were discussed. Finally, real-world sex differences in human health scenarios were also considered.

RESULTS

This report provides an overview of the two-day workshop, and open discussion among academic investigators, industry researchers, and U.S. government representatives.

CONCLUSIONS

This meeting highlighted that current study designs lack the power to determine statistical significance based on sex, and much is unknown about the underlying factors that contribute to these differences. Investigators should accommodate both sexes in all stages of research to ensure that the outcome is robust, reproducible, and accurate, and will benefit public health.

Sex and dose rate effects in automated cytogenetics

Testing and validation of biodosimetry assays is routinely performed using conventional dose rate irradiation platforms, at a dose rate of approximately 1 Gy/min. In contrast, the exposures from an improvised nuclear device will be delivered over a large range of dose rates with a prompt irradiation component, delivered in less than 1 μs, and a protracted component delivered over hours and days. We present preliminary data from a large demographic study we have undertaken for investigation of age, sex and dose rate effects on dicentric and micronucleus yields. Our data demonstrate reduced dicentric and micronucleus yields at very high dose rates. Additionally, we have seen small differences between males and females, with males having slightly fewer micronuclei and slightly more dicentrics than females, at high doses.

Radiation exposure determination in a secure, cloud-based online environment

Rapid sample processing and interpretation of estimated exposures will be critical for triaging exposed individuals after a major radiation incident. The dicentric chromosome (DC) assay assesses absorbed radiation using metaphase cells from blood. The Automated Dicentric Chromosome Identifier and Dose Estimator System (ADCI) identifies DCs and determines radiation doses. This study aimed to broaden accessibility and speed of this system, while protecting data and software integrity. ADCI Online is a secure web-streaming platform accessible worldwide from local servers. Cloud-based systems containing data and software are separated until they are linked for radiation exposure estimation. Dose estimates are identical to ADCI on dedicated computer hardware. Image processing and selection, calibration curve generation, and dose estimation of 9 test samples completed in < 2 days. ADCI Online has the capacity to alleviate analytic bottlenecks in intermediate-to-large radiation incidents. Multiple cloned software instances configured on different cloud environments accelerated dose estimation to within clinically relevant time frames.

Improved prediction of breast cancer risk based on phenotypic DNA damage repair capacity in peripheral blood B cells

Background

Standard Breast Cancer (BC) risk prediction models based only on epidemiologic factors generally have quite poor performance, and there have been a number of risk scores proposed to improve them, such as AI-based mammographic information, polygenic risk scores and pathogenic variants. Even with these additions BC risk prediction performance is still at best moderate. In that decreased DNA repair capacity (DRC) is a major risk factor for development of cancer, we investigated the potential to improve BC risk prediction models by including a measured phenotypic DRC assay.

Methods

Using blood samples from the Breast Cancer Family Registry we assessed the performance of phenotypic markers of DRC in 46 matched pairs of individuals, one from each pair with BC (with blood drawn before BC diagnosis) and the other from controls matched by age and time since blood draw. We assessed DRC in thawed cryopreserved peripheral blood mononuclear cells (PBMCs) by measuring γ-H2AX yields (a marker for DNA double-strand breaks) at multiple times from 1 to 20 hrs after a radiation challenge. The studies were performed using surface markers to discriminate between different PBMC subtypes.

Results

The parameter F res , the residual damage signal in PBMC B cells at 20 hrs post challenge, was the strongest predictor of breast cancer with an AUC (Area Under receiver-operator Curve) of 0.89 [95% Confidence Interval: 0.84-0.93] and a BC status prediction accuracy of 0.80. To illustrate the combined use of a phenotypic predictor with standard BC predictors, we combined F res in B cells with age at blood draw, and found that the combination resulted in significantly greater BC predictive power (AUC of 0.97 [95% CI: 0.94-0.99]), an increase of 13 percentage points over age alone.

Conclusions

If replicated in larger studies, these results suggest that inclusion of a fingerstick-based phenotypic DRC blood test has the potential to markedly improve BC risk prediction.

RENEB Inter-Laboratory Comparison 2021: Inter-Assay Comparison of Eight Dosimetry Assays

Tools for radiation exposure reconstruction are required to support the medical management of radiation victims in radiological or nuclear incidents. Different biological and physical dosimetry assays can be used for various exposure scenarios to estimate the dose of ionizing radiation a person has absorbed. Regular validation of the techniques through inter-laboratory comparisons (ILC) is essential to guarantee high quality results. In the current RENEB inter-laboratory comparison, the performance quality of established cytogenetic assays [dicentric chromosome assay (DCA), cytokinesis-block micronucleus assay (CBMN), stable chromosomal translocation assay (FISH) and premature chromosome condensation assay (PCC)] was tested in comparison to molecular biological assays [gamma-H2AX foci (gH2AX), gene expression (GE)] and physical dosimetry-based assays [electron paramagnetic resonance (EPR), optically or thermally stimulated luminescence (LUM)]. Three blinded coded samples (e.g., blood, enamel or mobiles) were exposed to 0, 1.2 or 3.5 Gy X-ray reference doses (240 kVp, 1 Gy/min). These doses roughly correspond to clinically relevant groups of unexposed to low exposed (0-1 Gy), moderately exposed (1-2 Gy, no severe acute health effects expected) and highly exposed individuals (>2 Gy, requiring early intensive medical care). In the frame of the current RENEB inter-laboratory comparison, samples were sent to 86 specialized teams in 46 organizations from 27 nations for dose estimation and identification of three clinically relevant groups. The time for sending early crude reports and more precise reports was documented for each laboratory and assay where possible. The quality of dose estimates was analyzed with three different levels of granularity, 1. by calculating the frequency of correctly reported clinically relevant dose categories, 2. by determining the number of dose estimates within the uncertainty intervals recommended for triage dosimetry (±0.5 Gy or ±1.0 Gy for doses <2.5 Gy or >2.5 Gy), and 3. by calculating the absolute difference (AD) of estimated doses relative to the reference doses. In total, 554 dose estimates were submitted within the 6-week period given before the exercise was closed. For samples processed with the highest priority, earliest dose estimates/categories were reported within 5-10 h of receipt for GE, gH2AX, LUM, EPR, 2-3 days for DCA, CBMN and within 6-7 days for the FISH assay. For the unirradiated control sample, the categorization in the correct clinically relevant group (0-1 Gy) as well as the allocation to the triage uncertainty interval was, with the exception of a few outliers, successfully performed for all assays. For the 3.5 Gy sample the percentage of correct classifications to the clinically relevant group (≥2 Gy) was between 89-100% for all assays, with the exception of gH2AX. For the 1.2 Gy sample, an exact allocation to the clinically relevant group was more difficult and 0-50% or 0-48% of the estimates were wrongly classified into the lowest or highest dose categories, respectively. For the irradiated samples, the correct allocation to the triage uncertainty intervals varied considerably between assays for the 1.2 Gy (29-76%) and 3.5 Gy (17-100%) samples. While a systematic shift towards higher doses was observed for the cytogenetic-based assays, extreme outliers exceeding the reference doses 2-6 fold were observed for EPR, FISH and GE assays. These outliers were related to a particular material examined (tooth enamel for EPR assay, reported as kerma in enamel, but when converted into the proper quantity, i.e. to kerma in air, expected dose estimates could be recalculated in most cases), the level of experience of the teams (FISH) and methodological uncertainties (GE). This was the first RENEB ILC where everything, from blood sampling to irradiation and shipment of the samples, was organized and realized at the same institution, for several biological and physical retrospective dosimetry assays. Almost all assays appeared comparably applicable for the identification of unexposed and highly exposed individuals and the allocation of medical relevant groups, with the latter requiring medical support for the acute radiation scenario simulated in this exercise. However, extreme outliers or a systematic shift of dose estimates have been observed for some assays. Possible reasons will be discussed in the assay specific papers of this special issue. In summary, this ILC clearly demonstrates the need to conduct regular exercises to identify research needs, but also to identify technical problems and to optimize the design of future ILCs.

International Comparison Exercise for Biological Dosimetry after Exposures with Neutrons Performed at Two Irradiation Facilities as Part of the BALANCE Project

In the case of a radiological or nuclear event, biological dosimetry can be an important tool to support clinical decision-making. During a nuclear event, individuals might be exposed to a mixed field of neutrons and photons. The composition of the field and the neutron energy spectrum influence the degree of damage to the chromosomes. During the transatlantic BALANCE project, an exposure similar to a Hiroshima-like device at a distance of 1.5 km from the epicenter was simulated, and biological dosimetry based on dicentric chromosomes was performed to evaluate the participants ability to discover unknown doses and to test the influence of differences in neutron spectra. In a first step, calibration curves were established by irradiating blood samples with 5 doses in the range of 0-4 Gy at two different facilities in Germany (Physikalisch-Technische Bundesanstalt [PTB]) and the USA (the Columbia IND Neutron Facility [CINF]). The samples were sent to eight participating laboratories from the RENEB network and dicentric chromosomes were scored by each participant. Next, blood samples were irradiated with 4 blind doses in each of the two facilities and sent to the participants to provide dose estimates based on the established calibration curves. Manual and semiautomatic scoring of dicentric chromosomes were evaluated for their applicability to neutron exposures. Moreover, the biological effectiveness of the neutrons from the two irradiation facilities was compared. The calibration curves from samples irradiated at CINF showed a 1.4 times higher biological effectiveness compared to samples irradiated at PTB. For manual scoring of dicentric chromosomes, the doses of the test samples were mostly successfully resolved based on the calibration curves established during the project. For semiautomatic scoring, the dose estimation for the test samples was less successful. Doses >2 Gy in the calibration curves revealed nonlinear associations between dose and dispersion index of the dicentric counts, especially for manual scoring. The differences in the biological effectiveness between the irradiation facilities suggested that the neutron energy spectrum can have a strong impact on the dicentric counts.

High Resolution and Automatable Cytogenetic Biodosimetry Using In Situ Telomere and Centromere Hybridization for the Accurate Detection of DNA Damage: An Overview

In the event of a radiological or nuclear accident, or when physical dosimetry is not available, the scoring of radiation-induced chromosomal aberrations in lymphocytes constitutes an essential tool for the estimation of the absorbed dose of the exposed individual and for effective triage. Cytogenetic biodosimetry employs different cytogenetic assays including the scoring of dicentrics, micronuclei, and translocations as well as analyses of induced premature chromosome condensation to define the frequency of chromosome aberrations. However, inherent challenges using these techniques include the considerable time span from sampling to result, the sensitivity and specificity of the various techniques, and the requirement of highly skilled personnel. Thus, techniques that obviate these challenges are needed. The introduction of telomere and centromere (TC) staining have successfully met these challenges and, in addition, greatly improved the efficiency of cytogenetic biodosimetry through the development of automated approaches, thus reducing the need for specialized personnel. Here, we review the role of the various cytogenetic dosimeters and their recent improvements in the management of populations exposed to genotoxic agents such as ionizing radiation. Finally, we discuss the emerging potentials to exploit these techniques in a wider spectrum of medical and biological applications, e.g., in cancer biology to identify prognostic biomarkers for the optimal triage and treatment of patients.

High-precision automatic identification method for dicentric chromosome images using two-stage convolutional neural network

Dicentric chromosome analysis is the gold standard for biological dose assessment. To enhance the efficiency of biological dose assessment in large-scale radiation catastrophes, automatic identification of dicentric chromosome images is a promising and objective method. In this paper, an automatic identification method for dicentric chromosome images using two-stage convolutional neural network is proposed based on Giemsa-stained automatic microscopic imaging. To automatically segment the adhesive chromosome masses, a k-means based adaptive image segmentation and watershed segmentation algorithm is applied. The first-stage CNN is used to identify the dicentric chromosome images from all the images and the second-stage CNN works to specifically identify the dicentric chromosome images. This two-stage CNN identification method can effectively detects chromosome images with concealed centromeres, poorly expanded and long-armed entangled chromosomes, and tricentric chromosomes. The novel two-stage CNN method has a chromosome identification accuracy of 99.4%, a sensitivity of 85.8% sensitivity, and a specificity of 99.6%, effectively reducing the false positive rate of dicentric chromosome. The analysis speed of this automatic identification method can be 20 times quicker than manual detection, providing a valuable reference for other image identification situations with small target rates.

Linear dose response of acrocentric chromosome associations to gamma irradiation in human lymphocytes

PURPOSE

The frequency of acrocentric chromosome associations (ACA) was studied to determine the possible dose-response relationship of gamma irradiation in human lymphocytes.

METHODS

Peripheral blood collected from three healthy donors was irradiated with 0, 0.1, 0.25, 0.5, 0.75, 1, 2, 3, 4, and 5 Gy of gamma radiation. Chromosomal preparations were made after 48 h of culture as per standard guidelines. The experiment was repeated three times, with a different donor each time.

RESULTS

The ACA frequency in irradiated lymphocytes increased with radiation dose. The D-G type of association was most prominent and showed a significant dose-dependent increase in frequency. The dose response of ACA frequency to radiation was found to be linear: ACA frequency = 0.2923 (±0.0276) + 0.1846 (±0.0307) × D (correlation coefficient r = 0.9442). As expected, dicentric chromosome (DC) frequencies followed the linear quadratic fit model, with DC frequency = 0.0015 (±0.0013) + 0.0220 (±0.0059) × D + 0.0215 (±0.0018) × D^2 (correlation coefficient r = 0.9982). A correlation curve was prepared for ACA frequency versus DC frequency, resulting in the regression equation y = 1.130x + 0.4051 (R² = 0.7408; p = 0.0014).

CONCLUSION

Our results showed an increase in ACA frequency in irradiated lymphocytes with an increase in radiation dose; thus, ACA may serve as a candidate cytogenetic biomarker for radiation biodosimetry.

Validation of a High-Throughput Dicentric Chromosome Assay Using Complex Radiation Exposures

Validation of biodosimetry assays is routinely performed using primarily orthovoltage irradiators at a conventional dose rate of approximately 1 Gy/min. However, incidental/ accidental exposures caused by nuclear weapons can be more complex. The aim of this work was to simulate the DNA damage effects mimicking those caused by the detonation of a several kilotons improvised nuclear device (IND). For this, we modeled complex exposures to: 1. a mixed (photons + IND-neutrons) field and 2. different dose rates that may come from the blast, nuclear fallout, or ground deposition of radionuclides (ground shine). Additionally, we assessed whether myeloid cytokines affect the precision of radiation dose estimation by modulating the frequency of dicentric chromosomes. To mimic different exposure scenarios, several irradiation systems were used. In a mixed field study, human blood samples were exposed to a photon field enriched with neutrons (ranging from 10% to 37%) from a source that mimics Hiroshima's A-bomb's energy spectrum (0.2-9 MeV). Using statistical analysis, we assessed whether photons and neutrons act in an additive or synergistic way to form dicentrics. For the dose rates study, human blood was exposed to photons or electrons at dose rates ranging from low (where the dose was spread over 32 h) to extremely high (where the dose was delivered in a fraction of a microsecond). Potential effects of cytokine treatment on biodosimetry dose predictions were analyzed in irradiated blood subjected to Neupogen or Neulasta for 24 or 48 h at the concentration recommended to forestall manifestation of an acute radiation syndrome in bomb survivors. All measurements were performed using a robotic station, the Rapid Automated Biodosimetry Tool II, programmed to culture lymphocytes and score dicentrics in multiwell plates (the RABiT-II DCA). In agreement with classical concepts of radiation biology, the RABiT-II DCA calibration curves suggested that the frequency of dicentrics depends on the type of radiation and is modulated by changes in the dose rate. The resulting dose-response curves suggested an intermediate dicentric yields and additive effects of photons and IND-neutrons in the mixed field. At ultra-high dose rate (600 Gy/s), affected lymphocytes exhibited significantly fewer dicentrics (P < 0.004, t test). In contrast, we did not find the dose-response modification effects of radiomitigators on the yields of dicentrics (Bonferroni corrected P > 0.006, ANOVA test). This result suggests no bias in the dose predictions should be expected after emergency cytokine treatment initiated up to 48 h prior to blood collection for dicentric analysis.

A machine learning method for improving the accuracy of radiation biodosimetry by combining data from the dicentric chromosomes and micronucleus assays

A large-scale malicious or accidental radiological event can expose vast numbers of people to ionizing radiation. The dicentric chromosome (DCA) and cytokinesis-block micronucleus (CBMN) assays are well-established biodosimetry methods for estimating individual absorbed doses after radiation exposure. Here we used machine learning (ML) to test the hypothesis that combining automated DCA and CBMN assays will improve dose reconstruction accuracy, compared with using either cytogenetic assay alone. We analyzed 1349 blood sample aliquots from 155 donors of different ages (3-69 years) and sexes (49.1% males), ex vivo irradiated with 0-8 Gy at dose rates from 0.08 Gy/day to ≥ 600 Gy/s. We compared the performances of several state-of-the-art ensemble ML methods and found that random forest generated the best results, with R2 for actual vs. reconstructed doses on a testing data subset = 0.845, and mean absolute error = 0.628 Gy. The most important predictor variables were CBMN and DCA frequencies, and age. Removing CBMN or DCA data from the model significantly increased squared errors on testing data (p-values 3.4 × 10-8 and 1.1 × 10-6, respectively). These findings demonstrate the promising potential of combining CBMN and DCA assay data to reconstruct radiation doses in realistic scenarios of heterogeneous populations exposed to a mass-casualty radiological event.

Nuclear and Radiological Emergencies: Biological Effects, Countermeasures and Biodosimetry

Atomic and radiological crises can be caused by accidents, military activities, terrorist assaults involving atomic installations, the explosion of nuclear devices, or the utilization of concealed radiation exposure devices. Direct damage is caused when radiation interacts directly with cellular components. Indirect effects are mainly caused by the generation of reactive oxygen species due to radiolysis of water molecules. Acute and persistent oxidative stress associates to radiation-induced biological damages. Biological impacts of atomic radiation exposure can be deterministic (in a period range a posteriori of the event and because of destructive tissue/organ harm) or stochastic (irregular, for example cell mutation related pathologies and heritable infections). Potential countermeasures according to a specific scenario require considering basic issues, e.g., the type of radiation, people directly affected and first responders, range of doses received and whether the exposure or contamination has affected the total body or is partial. This review focuses on available medical countermeasures (radioprotectors, radiomitigators, radionuclide scavengers), biodosimetry (biological and biophysical techniques that can be quantitatively correlated with the magnitude of the radiation dose received), and strategies to implement the response to an accidental radiation exposure. In the case of large-scale atomic or radiological events, the most ideal choice for triage, dose assessment and victim classification, is the utilization of global biodosimetry networks, in combination with the automation of strategies based on modular platforms.

CytoRADx: A High-Throughput, Standardized Biodosimetry Diagnostic System Based on the Cytokinesis-Block Micronucleus Assay

In a large-scale catastrophe, such as a nuclear detonation in a major city, it will be crucial to accurately diagnose large numbers of people to direct scarce medical resources to those in greatest need. Currently no FDA-cleared tests are available to diagnose radiation exposures, which can lead to complex, life-threatening injuries. To address this gap, we have achieved substantial advancements in radiation biodosimetry through refinement and adaptation of the cytokinesis-block micronucleus (CBMN) assay as a high throughput, quantitative diagnostic test. The classical CBMN approach, which quantifies micronuclei (MN) resulting from DNA damage, suffers from considerable time and expert labor requirements, in addition to a lack of universal methodology across laboratories. We have developed the CytoRADx™ System to address these drawbacks by implementing a standardized reagent kit, optimized assay protocol, fully automated microscopy and image analysis, and integrated dose prediction. These enhancements allow the CytoRADx System to obtain high-throughput, standardized results without specialized labor or laboratory-specific calibration curves. The CytoRADx System has been optimized for use with both humans and non-human primates (NHP) to quantify radiation dose-dependent formation of micronuclei in lymphocytes, observed using whole blood samples. Cell nuclei and resulting MN are fluorescently stained and preserved on durable microscope slides using materials provided in the kit. Up to 1,000 slides per day are subsequently scanned using the commercially based RADxScan™ Imager with customized software, which automatically quantifies the cellular features and calculates the radiation dose. Using less than 1 mL of blood, irradiated ex vivo, our system has demonstrated accurate and precise measurement of exposures from 0 to 8 Gy (90% of results within 1 Gy of delivered dose). These results were obtained from 636 human samples (24 distinct donors) and 445 NHP samples (30 distinct subjects). The system demonstrated comparable results during in vivo studies, including an investigation of 43 NHPs receiving single-dose total-body irradiation. System performance is repeatable across laboratories, operators, and instruments. Results are also statistically similar across diverse populations, considering various demographics, common medications, medical conditions, and acute injuries associated with radiological disasters. Dose calculations are stable over time as well, providing reproducible results for at least 28 days postirradiation, and for blood specimens collected and stored at room temperature for at least 72 h. The CytoRADx System provides significant advancements in the field of biodosimetry that will enable accurate diagnoses across diverse populations in large-scale emergency scenarios. In addition, our technological enhancements to the well-established CBMN assay provide a pathway for future diagnostic applications, such as toxicology and oncology.

The future of biological dosimetry in mass casualty radiation emergency response, personalized radiation risk estimation and space radiation protection

PURPOSE

The aim of this brief personal, high level review is to consider the state of the art for biological dosimetry for radiation routine and emergency response, and the potential future progress in this fascinating and active field. Four areas in which biomarkers may contribute to scientific advancement through improved dose and exposure characterization, as well as potential contributions to personalized risk estimation, are considered: emergency dosimetry, molecular epidemiology, personalized medical dosimetry, and space travel.

CONCLUSION

Ionizing radiation biodosimetry is an exciting field which will continue to benefit from active networking and collaboration with the wider fields of radiation research and radiation emergency response to ensure effective, joined up approaches to triage; radiation epidemiology to assess long term, low dose, radiation risk; radiation protection of workers, optimization and justification of radiation for diagnosis or treatment of patients in clinical uses, and protection of individuals traveling to space.

Whole blood gene expression within days after total-body irradiation predicts long term survival in Gottingen minipigs

Gottingen minipigs mirror the physiological radiation response observed in humans and hence make an ideal candidate model for studying radiation biodosimetry for both limited-sized and mass casualty incidents. We examined the whole blood gene expression profiles starting one day after total-body irradiation with increasing doses of gamma-rays. The minipigs were monitored for up to 45 days or time to euthanasia necessitated by radiation effects. We successfully identified dose- and time-agnostic (over a 1-7 day period after radiation), survival-predictive gene expression signatures derived using machine-learning algorithms with high sensitivity and specificity. These survival-predictive signatures fare better than an optimally performing dose-differentiating signature or blood cellular profiles. These findings suggest that prediction of survival is a much more useful parameter for making triage, resource-utilization and treatment decisions in a resource-constrained environment compared to predictions of total dose received. It should hopefully be possible to build such classifiers for humans in the future.

Transcriptomics for radiation biodosimetry: progress and challenges

PURPOSE

Transcriptomic-based approaches are being developed to meet the needs for large-scale radiation dose and injury assessment and provide population triage following a radiological or nuclear event. This review provides background and definition of the need for new biodosimetry approaches, and summarizes the major advances in this field. It discusses some of the major model systems used in gene signature development, and highlights some of the remaining challenges, including individual variation in gene expression, potential confounding factors, and accounting for the complexity of realistic exposure scenarios.

CONCLUSIONS

Transcriptomic approaches show great promise for both dose reconstruction and for prediction of individual radiological injury. However, further work will be needed to ensure that gene expression signatures will be robust and appropriate for their intended use in radiological or nuclear emergencies.

Transportation container for pre-processing cytogenetic assays in radiation accidents

We report a shipping container that enables a disruptive logistics for cytogenetic biodosimetry for radiation countermeasures through pre-processing cell culture during transportation. The container showed precise temperature control (< 0.01 °C) with uniform sample temperature (< 0.1 °C) to meet the biodosimetry assay requirements. Using an existing insulated shipping box and long shelf life alkaline batteries makes it ideal for national stockpile. Dose curve of cytogenetic biodosimetry assay using the shipping container showed clear dose response and high linear correlation with the control dose curve using a laboratory incubator (Pearson’s correlation coefficient: 0.992). The container’s ability of pre-processing biological samples during transportation could have a significant impact on radiation countermeasure, as well as potential impacts in other applications such as biobanking, novel molecular or cell-based assays or therapies.

Machine learning methodology for high throughput personalized neutron dose reconstruction in mixed neutron + photon exposures

We implemented machine learning in the radiation biodosimetry field to quantitatively reconstruct neutron doses in mixed neutron + photon exposures, which are expected in improvised nuclear device detonations. Such individualized reconstructions are crucial for triage and treatment because neutrons are more biologically damaging than photons. We used a high-throughput micronucleus assay with automated scanning/imaging on lymphocytes from human blood ex-vivo irradiated with 44 different combinations of 0-4 Gy neutrons and 0-15 Gy photons (542 blood samples), which include reanalysis of past experiments. We developed several metrics that describe micronuclei/cell probability distributions in binucleated cells, and used them as predictors in random forest (RF) and XGboost machine learning analyses to reconstruct the neutron dose in each sample. The probability of "overfitting" was minimized by training both algorithms with repeated cross-validation on a randomly-selected subset of the data, and measuring performance on the rest. RF achieved the best performance. Mean R² for actual vs. reconstructed neutron doses over 300 random training/testing splits was 0.869 (range 0.761 to 0.919) and root mean squared error was 0.239 (0.195 to 0.351) Gy. These results demonstrate the promising potential of machine learning to reconstruct the neutron dose component in clinically-relevant complex radiation exposure scenarios.

Gene Expression Profiles from Heart, Lung and Liver Samples of Total-Body-Irradiated Minipigs: Implications for Predicting Radiation-Induced Tissue Toxicity

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.

The RABiT-II DCA in the Rhesus Macaque Model

An automated platform for cytogenetic biodosimetry, the "Rapid Automated Biodosimetry Tool II (RABiT-II)," adapts the dicentric chromosome assay (DCA) for high-throughput mass-screening of the population after a large-scale radiological event. To validate this test, the U.S. Federal Drug Administration (FDA) recommends demonstrating that the high-throughput biodosimetric assay in question correctly reports the dose in an in vivo model. Here we describe the use of rhesus macaques (Macaca mulatta) to augment human studies and validate the accuracy of the high-throughput version of the DCA. To perform analysis, we developed the 17/22-mer peptide nucleic acid (PNA) probes that bind to the rhesus macaque's centromeres. To our knowledge, these are the first custom PNA probes with high specificity that can be used for chromosome analysis in M. mulatta. The accuracy of fully-automated chromosome analysis was improved by optimizing a low-temperature telomere PNA FISH staining in multiwell plates and adding the telomere detection feature to our custom chromosome detection software, FluorQuantDic V4. The dicentric frequencies estimated from in vitro irradiated rhesus macaque samples were compared to human blood samples of individuals subjected to the same ex vivo irradiation conditions. The results of the RABiT-II DCA analysis suggest that, in the lymphocyte system, the dose responses to gamma radiation in the rhesus macaques were similar to those in humans, with small but statistically significant differences between these two model systems.

Dose and Dose-Rate Effects in a Mouse Model of Internal Exposure from 137Cs. Part 2: Integration of Gamma-H2AX and Gene Expression Biomarkers for Retrospective Radiation Biodosimetry

Inhalation and ingestion of 137Cs and other long-lived radionuclides can occur after large-scale accidental or malicious radioactive contamination incidents, resulting in a complex temporal pattern of radiation dose/dose rate, influenced by radionuclide pharmacokinetics and chemical properties. High-throughput radiation biodosimetry techniques for such internal exposure are needed to assess potential risks of short-term toxicity and delayed effects (e.g., carcinogenesis) for exposed individuals. Previously, we used γ-H2AX to reconstruct injected 137Cs activity in experimentally-exposed mice, and converted activity values into radiation doses based on time since injection and 137Cs-elimination kinetics. In the current study, we sought to assess the feasibility and possible advantages of combining γ-H2AX with transcriptomics to improve 137Cs activity reconstructions. We selected five genes (Atf5, Hist2h2aa2, Olfr358, Psrc1, Hist2h2ac) with strong statistically-significant Spearman's correlations with injected activity and stable expression over time after 137Cs injection. The geometric mean of log-transformed signals of these five genes, combined with γ-H2AX fluorescence, were used as predictors in a nonlinear model for reconstructing injected 137Cs activity. The coefficient of determination (R2) comparing actual and reconstructed activities was 0.91 and root mean squared error (RMSE) was 0.95 MBq. These metrics remained stable when the model was fitted to a randomly-selected half of the data and tested on the other half, repeated 100 times. Model performance was significantly better when compared to our previous analysis using γ-H2AX alone, and when compared to an analysis where genes are used without γ-H2AX, suggesting that integrating γ-H2AX with gene expression provides an important advantage. Our findings show a proof of principle that integration of radiation-responsive biomarkers from different fields is promising for radiation biodosimetry of internal emitters.

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.

A High Throughput Approach to Reconstruct Partial-Body and Neutron Radiation Exposures on an Individual Basis

Biodosimetry-based individualized reconstruction of complex irradiation scenarios (partial-body shielding and/or neutron + photon mixtures) can improve treatment decisions after mass-casualty radiation-related incidents. We used a high-throughput micronucleus assay with automated scanning and imaging software on ex-vivo irradiated human lymphocytes to: a) reconstruct partial-body and/or neutron exposure, and b) estimate separately the photon and neutron doses in a mixed exposure. The mechanistic background is that, compared with total-body photon irradiations, neutrons produce more heavily-damaged lymphocytes with multiple micronuclei/binucleated cell, whereas partial-body exposures produce fewer such lymphocytes. To utilize these differences for biodosimetry, we developed metrics that describe micronuclei distributions in binucleated cells and serve as predictors in machine learning or parametric analyses of the following scenarios: (A) Homogeneous gamma-irradiation, mimicking total-body exposures, vs. mixtures of irradiated blood with unirradiated blood, mimicking partial-body exposures. (B) X rays vs. various neutron + photon mixtures. The results showed high accuracies of scenario and dose reconstructions. Specifically, receiver operating characteristic curve areas (AUC) for sample classification by exposure type reached 0.931 and 0.916 in scenarios A and B, respectively. R² for actual vs. reconstructed doses in these scenarios reached 0.87 and 0.77, respectively. These encouraging findings demonstrate a proof-of-principle for the proposed approach of high-throughput reconstruction of clinically-relevant complex radiation exposure scenarios.