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

G0-PCC-FISH derived multi-parametric biodosimetry methodology for accidental high dose and partial body exposures

High dose radiation exposures are rare. However, medical management of such incidents is crucial due to mortality and tissue injury risks. Rapid radiation biodosimetry of high dose accidental exposures is highly challenging, considering that they usually involve non uniform fields leading to partial body exposures. The gold standard, dicentric assay and other conventional methods have limited application in such scenarios. As an alternative, we propose Premature Chromosome Condensation combined with Fluorescent In-situ Hybridization (G0-PCC-FISH) as a promising tool for partial body exposure biodosimetry. In the present study, partial body exposures were simulated ex-vivo by mixing of uniformly exposed blood with unexposed blood in varying proportions. After G0-PCC-FISH, Dolphin's approach with background correction was used to provide partial body exposure dose estimates and these were compared with those obtained from conventional dicentric assay and G0-PCC-Fragment assay (conventional G0-PCC). Dispersion analysis of aberrations from partial body exposures was carried out and compared with that of whole-body exposures. The latter was inferred from a multi-donor, wide dose range calibration curve, a-priori established for whole-body exposures. With the dispersion analysis, novel multi-parametric methodology for discerning the partial body exposure from whole body exposure and accurate dose estimation has been formulated and elucidated with the help of an example. Dose and proportion dependent reduction in sensitivity and dose estimation accuracy was observed for Dicentric assay, but not in the two PCC methods. G0-PCC-FISH was found to be most accurate for the dose estimation. G0-PCC-FISH has potential to overcome the shortcomings of current available methods and can provide rapid, accurate dose estimation of partial body and high dose accidental exposures. Biological dose estimation can be useful to predict progression of disease manifestation and can help in pre-planning of appropriate & timely medical intervention.

Cytogenetic effects of β-particles in Allium cepa cells used as a biological indicator for radiation damages

Analysis of cytogenetics effects of ionizing radiation for flora and fauna is essential to determine the impact on these communities and may produce an efficient warning system to avoid harm to human health. Onion (Allium cepa) is a well-established in vivo standard model, and it is widely used in cytogenetics studies for different environmental pollutants. In this work, onion roots were exposed to 0.04-1.44 Gy of β-particles from a ⁹⁰Sr/⁹⁰Y source. We investigated the capacity of brief external exposures to β-particles on inducing cytogenetic damages in root meristematic cells of onion aiming to verify if onion can be used as a radiation-sensitive cytogenetic bioindicator. A nonlinear increase in the frequencies of chromosomal aberrations and cells with micronuclei was observed. Onion roots exposed to doses 0.13 Gy or higher of β-particles showed a significant difference (p<0.05) in these frequencies when compared to the unirradiated group. The frequencies of these endpoints showed to be suitable to assess the difference in the dose of beta radiation received from 0.36 Gy. Our research shows the potential of using cytogenetic effects in Allium cepa cells as a biological indicator for a first screening of genotoxic damages induced by brief external exposures to β-particles.

Machine learning approach for quantitative biodosimetry of partial-body or total-body radiation exposures by combining radiation-responsive biomarkers

During a large-scale radiological event such as an improvised nuclear device detonation, many survivors will be shielded from radiation by environmental objects, and experience only partial-body irradiation (PBI), which has different consequences, compared with total-body irradiation (TBI). In this study, we tested the hypothesis that applying machine learning to a combination of radiation-responsive biomarkers (ACTN1, DDB2, FDXR) and B and T cell counts will quantify and distinguish between PBI and TBI exposures. Adult C57BL/6 mice of both sexes were exposed to 0, 2.0-2.5 or 5.0 Gy of half-body PBI or TBI. The random forest (RF) algorithm trained on ½ of the data reconstructed the radiation dose on the remaining testing portion of the data with mean absolute error of 0.749 Gy and reconstructed the product of dose and exposure status (defined as 1.0 × Dose for TBI and 0.5 × Dose for PBI) with MAE of 0.472 Gy. Among irradiated samples, PBI could be distinguished from TBI: ROC curve AUC = 0.944 (95% CI: 0.844-1.0). Mouse sex did not significantly affect dose reconstruction. These results support the hypothesis that combinations of protein biomarkers and blood cell counts can complement existing methods for biodosimetry of PBI and TBI exposures.

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.

Prediction of Total-Body and Partial-Body Exposures to Radiation Using Plasma Proteomic Expression Profiles

There is a need to identify new biomarkers of radiation exposure for not only systemic total-body irradiation (TBI) but also to characterize partial-body irradiation and organ specific radiation injury. In the current study, we sought to develop novel biodosimetry models of radiation exposure using TBI and organ specific partial-body irradiation to only the brain, lung or gut using a multivariate proteomics approach. Subset panels of significantly altered proteins were selected to build predictive models of radiation exposure in a variety of sample cohort configurations relevant to practical field application of biodosimetry diagnostics during future radiological or nuclear event scenarios. Female C57BL/6 mice, 8-15 weeks old, received a single total-body or partial-body dose of 2 or 8 Gy TBI or 2 or 8 Gy to only the lung or gut, or 2, 8 or 16 Gy to only the brain using a Pantak X-ray source. Plasma was collected by cardiac puncture at days 1, 3 and 7 postirradiation for total-body exposures and only the lung and brain exposures, and at days 3, 7 and 14 postirradiation for gut exposures. Plasma was then screened using the aptamer-based SOMAscan proteomic assay technology, for changes in expression of 1,310 protein analytes. A subset panel of protein biomarkers which demonstrated significant changes (P < 0.01) in expression after irradiation were used to build predictive models of radiation exposure using different sample cohorts. Model 1 compared controls vs. all pooled irradiated samples, which included TBI and all organ specific partial irradiation. Model 2 compared controls vs. TBI vs. partial irradiation (with all organ specific partial exposure pooled within the partial-irradiated group), and model 3 compared controls vs. each individual organ specific partial-body exposure separately (brain, gut and lung). Detectable values were obtained for all 1,310 proteins included in the SOMAscan assay for all samples. Each model algorithm built using a unique sample cohort was validated with a training set of samples and tested with a separate new sample series. Overall predictive accuracies of 89%, 78% and 55% resulted for models 1-3, respectively, representing novel predictive panels of radiation responsive proteomic biomarkers. Though relatively high overall predictive accuracies were achieved for models 1 and 2, all three models showed limited accuracy at differentiating between the controls and partial-irradiated body samples. In our study we were able to identify novel panels of radiation responsive proteins useful for predicting radiation exposure and to create predictive models of partial-body exposure including organ specific radiation exposures. This proof-of-concept study also illustrates the inherent physiological limitations of distinguishing between small-body exposures and the unirradiated using proteomic biomarkers of radiation exposure. As use of biodosimetry diagnostics in future mass casualty settings will be complicated by the heterogeneity of partial-body exposure received in the field, further work remains in adapting these diagnostic tools for practical use.

Chromosome aberration dynamics in breast cancer patients treated with radiotherapy: Implications for radiation biodosimetry

Although radiological accidents often result in partial-body radiation exposure, most biodosimetry studies focus on estimating whole-body exposure doses. We have evaluated time-dependent changes in chromosomal aberrations before, during, and after localized fractionated radiotherapy. Twelve patients with carcinoma in situ of the breast who underwent identical adjuvant radiation therapy (50 Gy in 25 fractions) were included in the study. Lymphocytes were collected from patients before, during, and after radiotherapy, to measure chromosome aberrations, such as dicentric chromosomes and translocations. Chromosome aberrations were then used to calculate whole- and partial-body biological absorbed doses of radiation. Dicentric chromosome frequencies in all study participants increased during radiotherapy (p < 0.05 in Kruskal-Wallis test). Increases of translocation frequencies during radiotherapy were observed in seven of the twelve patients. The increased levels of dicentric chromosomes and translocations persisted throughout our 1-year follow-up, and evidence of partial-body exposure (such as Papworth's U-value > 1.96) was observed more than 1 year after radiotherapy. We found that cytogenetic biomarkers reflected partial-body fractionated radiation exposure more than 1 year post-exposure. Our findings suggest that chromosome aberrations can be used to estimate biological absorbed radiation doses and can inform medical intervention for individuals suspected of fractionated or partial-body radiation exposure.

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.

Towards the characterization of neutron carcinogenesis through direct action simulations of clustered DNA damage

Neutron exposure poses a unique radiation protection concern because neutrons have a large, energy-dependent relative biological effectiveness (RBE) for stochastic effects. Recent computational studies on the microdosimetric properties of neutron dose deposition have implicated clustered DNA damage as a likely contributor to this marked energy dependence. So far, publications have focused solely on neutron RBE for inducing clusters of DNA damage containing two or more DNA double strand breaks (DSBs). In this study, we have conducted a novel assessment of neutron RBE for inducing all types of clustered DNA damage that contain two or more lesions, stratified by whether the clusters contain DSBs (complex DSB clusters) or not (non-DSB clusters). This assessment was conducted for eighteen initial neutron energies between 1 eV and 10 MeV as well as a reference radiation of 250 keV x-rays. We also examined the energy dependence of cluster length and cluster complexity because these factors are believed to impact the DNA repair process. To carry out our investigation, we developed a user-friendly TOPAS-nBio application that includes a custom nuclear DNA model and a novel algorithm for recording clustered DNA damage. We found that neutron RBE for inducing complex DSB clusters exhibited similar energy dependence to the canonical neutron RBE for stochastic radiobiological effects, at multiple depths in human tissue. Qualitatively similar results were obtained for non-DSB clusters, although the quantitative agreement was lower. Additionally we identified a significant neutron energy dependence in the average length and complexity of clustered lesions. These results support the idea that many types of clustered DNA damage contribute to the energy dependence of neutron RBE for stochastic radiobiological effects and imply that the size and constituent lesions of individual clusters should be taken into account when modeling DNA repair. Our results were qualitatively consistent for (i) multiple radiation doses (including a low-dose 0.1 Gy irradiation), (ii) variations in the maximal lesion separation distance used to define a cluster, and (iii) two distinct collections of physics models used to govern particle transport. Our complete TOPAS-nBio application has been released under an open-source license to enable others to independently validate our work and to expand upon it.

Cytogenetic Damage of Human Lymphocytes in Humanized Mice Exposed to Neutrons and X Rays 24 h After Exposure

Detonation of an improvised nuclear device highlights the need to understand the risk of mixed radiation exposure as prompt radiation exposure could produce significant neutron and gamma exposures. Although the neutron component may be a relatively small percentage of the total absorbed dose, the large relative biological effectiveness (RBE) can induce larger biological DNA damage and cell killing. The objective of this study was to use a hematopoietically humanized mouse model to measure chromosomal DNA damage in human lymphocytes 24 h after in vivo exposure to neutrons (0.3 Gy) and X rays (1 Gy). The human dicentric and cytokinesis-block micronucleus assays were performed to measure chromosomal aberrations in human lymphocytes in vivo from the blood and spleen, respectively. The mBAND assay based on fluorescent in situ hybridization labeling was used to detect neutron-induced chromosome 1 inversions in the blood lymphocytes of the neutron-irradiated mice. Cytogenetics endpoints, dicentrics and micronuclei showed that there was no significant difference in yields between the 2 irradiation types at the doses tested, indicating that neutron-induced chromosomal DNA damage in vivo was more biologically effective (RBE ∼3.3) compared to X rays. The mBAND assay, which is considered a specific biomarker of high-LET neutron exposure, confirmed the presence of clustered DNA damage in the neutron-irradiated mice but not in the X-irradiated mice, 24 h after exposure.

Neutron Radiobiology and Dosimetry

As the U.S. prepares for the possibility of a radiological or nuclear incident, or anticipated lunar and Mars missions, the exposure of individuals to neutron radiation must be considered. More information is needed on how to determine the neutron dose to better estimate the true biological effects of neutrons and mixed-field (i.e., neutron and photon) radiation exposures. While exposure to gamma-ray radiation will cause significant health issues, the addition of neutrons will likely exacerbate the biological effects already anticipated after radiation exposure. To begin to understand the issues and knowledge gaps in these areas, the National Institute of Allergy and Infectious Diseases (NIAID), Radiation Nuclear Countermeasures Program (RNCP), Department of Defense (DoD), Defense Threat Reduction Agency (DTRA), and National Aeronautics and Space Administration (NASA) formed an inter-agency working group to host a Neutron Radiobiology and Dosimetry Workshop on March 7, 2019 in Rockville, MD. Stakeholder interests were clearly positioned, given the differences in the missions of each agency. An overview of neutron dosimetry and neutron radiobiology was included, as well as a historical overview of neutron exposure research. In addition, current research in the fields of biodosimetry and diagnostics, medical countermeasures (MCMs) and treatment, long-term health effects, and computational studies were presented and discussed.

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.

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.