Optimized automated data analysis for the cytokinesis-block micronucleus assay using imaging flow cytometry for high throughput radiation biodosimetry

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.

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.

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.

Imaging flow cytometry: a primer

Imaging flow cytometry combines the high throughput nature of flow cytometry with the advantages of single cell image acquisition associated with microscopy. The measurement of large numbers of features from the resulting images provides rich datasets which have resulted in a wide range of novel biomedical applications. In this primer we discuss the typical imaging flow instrumentation, the form of data acquired and the typical analysis tools that can be applied to this data. Using examples from the literature we discuss the progression of the analysis methods that have been applied to imaging flow cytometry data. These methods start from the use of simple single image features and multiple channel gating strategies, followed by the design and use of custom features for phenotype classification, through to powerful machine and deep learning methods. For each of these methods, we outline the processes involved in analyzing typical datasets and provide details of example applications. Finally we discuss the current limitations of imaging flow cytometry and the innovations which are addressing these challenges.

Inter-laboratory automation of the in vitro micronucleus assay using imaging flow cytometry and deep learning

The in vitro micronucleus assay is a globally significant method for DNA damage quantification used for regulatory compound safety testing in addition to inter-individual monitoring of environmental, lifestyle and occupational factors. However, it relies on time-consuming and user-subjective manual scoring. Here we show that imaging flow cytometry and deep learning image classification represents a capable platform for automated, inter-laboratory operation. Images were captured for the cytokinesis-block micronucleus (CBMN) assay across three laboratories using methyl methanesulphonate (1.25-5.0 μg/mL) and/or carbendazim (0.8-1.6 μg/mL) exposures to TK6 cells. Human-scored image sets were assembled and used to train and test the classification abilities of the "DeepFlow" neural network in both intra- and inter-laboratory contexts. Harnessing image diversity across laboratories yielded a network able to score unseen data from an entirely new laboratory without any user configuration. Image classification accuracies of 98%, 95%, 82% and 85% were achieved for 'mononucleates', 'binucleates', 'mononucleates with MN' and 'binucleates with MN', respectively. Successful classifications of 'trinucleates' (90%) and 'tetranucleates' (88%) in addition to 'other or unscorable' phenotypes (96%) were also achieved. Attempts to classify extremely rare, tri- and tetranucleated cells with micronuclei into their own categories were less successful (≤ 57%). Benchmark dose analyses of human or automatically scored micronucleus frequency data yielded quantitation of the same equipotent concentration regardless of scoring method. We conclude that this automated approach offers significant potential to broaden the practical utility of the CBMN method across industry, research and clinical domains. We share our strategy using openly-accessible frameworks.

COHERE - strengthening cooperation within the Canadian government on radiation research

PURPOSE

Canadian Organization on Health Effects from Radiation Exposure (COHERE) is a government initiative to better understand biological and human health risks from ionizing radiation exposures relevant to occupational and environmental settings (<100 mGy, <6 mGy/h). It is currently a partnership between two federal agencies, Health Canada (HC) and the Canadian Nuclear Safety Commission (CNSC). COHERE's vision is to contribute knowledge to reduce scientific uncertainties from low dose and dose-rate exposures. COHERE will advance our understanding by bridging the knowledge gap between human health risks and linkages to molecular- and cellular-level responses to radiation. Research focuses on identifying sensitive, early, and key molecular events of relevance to risk assessment.

CONCLUSIONS

The initiative will address questions of relevance to better apprize Canadians, including radiation workers and members of the public and Indigenous peoples, on health risks from low dose radiation exposure and inform radiation protection frameworks at a national and international level. Furthermore, it will support global efforts to conduct collaborative undertakings and better coordinate research. Here, we describe a historical overview of the research conducted, the strategic research agenda that outlines the scientific framework, stakeholders, opportunities to harmonize internationally, and how research outcomes will better inform communication of risk to Canadians.

The in vitro micronucleus assay using imaging flow cytometry and deep learning

The in vitro micronucleus (MN) assay is a well-established assay for quantification of DNA damage, and is required by regulatory bodies worldwide to screen chemicals for genetic toxicity. The MN assay is performed in two variations: scoring MN in cytokinesis-blocked binucleated cells or directly in unblocked mononucleated cells. Several methods have been developed to score the MN assay, including manual and automated microscopy, and conventional flow cytometry, each with advantages and limitations. Previously, we applied imaging flow cytometry (IFC) using the ImageStream® to develop a rapid and automated MN assay based on high throughput image capture and feature-based image analysis in the IDEAS® software. However, the analysis strategy required rigorous optimization across chemicals and cell lines. To overcome the complexity and rigidity of feature-based image analysis, in this study we used the Amnis® AI software to develop a deep-learning method based on convolutional neural networks to score IFC data in both the cytokinesis-blocked and unblocked versions of the MN assay. We show that the use of the Amnis AI software to score imagery acquired using the ImageStream® compares well to manual microscopy and outperforms IDEAS® feature-based analysis, facilitating full automation of the MN assay.

The 3D reconstructed skin micronucleus assay using imaging flow cytometry and deep learning: A proof-of-principle investigation

The reconstructed skin micronucleus (RSMN) assay was developed in 2006, as an in vitro alternative for genotoxicity evaluation of dermally applied chemicals or products. In the years since, significant progress has been made in the optimization of the assay, including publication of a standard protocol and extensive validation. However, the diverse morphology of skin cells makes cell preparation and scoring of micronuclei (MN) tedious and subjective, thus requiring a high level of technical expertise for evaluation. This ultimately has a negative impact on throughput and the assay would benefit by the development of an automated method which could reduce scoring subjectivity while also improving the robustness of the assay by increasing the number of cells that can be scored. Imaging flow cytometry (IFC) with the ImageStream^®X Mk II can capture high-resolution transmission and fluorescent imagery of cells in suspension. This proof-of-principle study describes protocol modifications that enable such automated measurement in 3D skin cells following exposure to mitomycin C and colchicine. IFC was then used for automated image capture and the Amnis® Artificial Intelligence (AAI) software permitted identification of binucleated (BN) cells with 91% precision. On average, three times as many BN cells from control samples were evaluated using IFC compared to the standard manual analysis. When IFC MNBN cells were visually scored from within the BN cell images, their frequency compared well with manual slide scoring, showing that IFC technology can be applied to the RSMN assay. This method enables faster time to result than microscope-based scoring and the initial studies presented here demonstrate its capability for the detection of statistically significant increases in MNBN frequencies. This work therefore demonstrates the feasibility of combining IFC and AAI to automate scoring for the RSMN assay and to improve its throughput and statistical robustness.

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.

Combination of Gas Plasma and Radiotherapy Has Immunostimulatory Potential and Additive Toxicity in Murine Melanoma Cells in Vitro

Despite continuous advances in therapy, malignant melanoma is still among the deadliest types of cancer. At the same time, owing to its high plasticity and immunogenicity, melanoma is regarded as a model tumor entity when testing new treatment approaches. Cold physical plasma is a novel anticancer tool that utilizes a plethora of reactive oxygen species (ROS) being deposited on the target cells and tissues. To test whether plasma treatment would enhance the toxicity of an established antitumor therapy, ionizing radiation, we combined both physical treatment modalities targeting B16F10 murine melanoma cell in vitro. Repeated rather than single radiotherapy, in combination with gas plasma-introduced ROS, induced apoptosis and cell cycle arrest in an additive fashion. In tendency, gas plasma treatment sensitized the cells to subsequent radiotherapy rather than the other way around. This was concomitant with increased levels of TNFα, IL6, and GM-CSF in supernatants. Murine JAWS dendritic cells cultured in these supernatants showed an increased expression of cell surface activation markers, such as MHCII and CD83. For PD-L1 and PD-L2, increased expression was observed. Our results are the first to suggest an additive therapeutic effect of gas plasma and radiotherapy, and translational tumor models are needed to develop this concept further.

Automated Identification and Scoring of Micronuclei

Micronucleus (MN) assays are used as a measure of cellular damage, and are often preferred over other chromosomal aberration assays since they possess similar statistical robustness for detection of genotoxins and require less technical expertise, making them easier to perform. However, the traditional visual scoring methods are tedious and prone to scorer subjectivity. A number of techniques to automate the MN assays have been developed using a variety of technologies. This chapter will provide an overview of several current methods used to automate MN assays, including automated slide-scoring and laser scanning cytometry, as well as conventional and imaging flow cytometry techniques.

Differentiation of Aneugens and Clastogens in the In Vitro Micronucleus Test by Kinetochore Scoring Using Automated Image Analysis

The in vitro micronucleus test according to OECD Test Guideline 487 (TG 487) is widely used to investigate the genotoxic potential of drugs. Besides the identification of in vitro genotoxicants, the assay can be complemented with kinetochore staining for the differentiation between clastogens and aneugens. This differentiation constitutes a major contribution to risk assessment as especially aneugens show a threshold response. Thus, a novel method for automated MN plus kinetochore (k+) scoring by image analysis was developed based on the OECD TG 487. Compound-induced increases in MN frequency can be detected using the cytokinesis-block (cytochalasin B) method in V79 cells after 24 h in a 96-well format. Nuclei, MN, and kinetochores were labeled with nuclear counterstain and anti-kinetochore antibodies, respectively, to score MN in binuclear or multinuclear cells and to differentiate compound-induced MN by the presence of kinetochores. First, a reference data set was created by manual scoring using two clastogens and aneugens. After developing the automated scoring process, a set of 14 reference genotoxicants were studied. The automated image analysis yielded the expected results: 5/5 clastogens and 6/6 aneugens (sensitivity: 100%) as well as 3/3 non-genotoxicants (specificity: 100%) were correctly identified. Further, a threshold was determined for identifying aneugens. Based on the data for our internally characterized reference compounds, unknown compounds that induce ≥53.8% k+ MN are classified as aneugens. The current data demonstrate excellent specificity and sensitivity and the methodology is superior to manual microscopic analysis in terms of speed and throughput as well as the absence of human bias. Environ. Mol. Mutagen. 60:227-242, 2019. © 2018 Wiley Periodicals, Inc.

Automated Triage Radiation Biodosimetry: Integrating Imaging Flow Cytometry with High-Throughput Robotics to Perform the Cytokinesis-Block Micronucleus Assay

The cytokinesis-block micronucleus (CBMN) assay has become a fully-validated and standardized method for radiation biodosimetry. The assay is typically performed using microscopy, which is labor intensive, time consuming and impractical after a large-scale radiological/nuclear event. Imaging flow cytometry (IFC), which combines the statistical power of traditional flow cytometry with the sensitivity and specificity of microscopy, has been recently used to perform the CBMN assay. Since this technology is capable of automated sample acquisition and multi-file analysis, we have integrated IFC into our Rapid Automated Biodosimetry Technology (RABiT-II). Assay development and optimization studies were designed to increase the yield of binucleated cells (BNCs), and improve data acquisition and analysis templates to increase the speed and accuracy of image analysis. Human peripheral blood samples were exposed ex vivo with up to 4 Gy of c rays at a dose rate of 0.73 Gy/min. After irradiation, samples were transferred to microtubes (total volume of 1 ml including blood and media) and organized into a standard 8 × 12 plate format. Sample processing methods were modified by increasing the blood-to-media ratio, adding hypotonic solution prior to cell fixation and optimizing nuclear DRAQ5 staining, leading to an increase of 81% in BNC yield. Modification of the imaging processing algorithms within IFC software also improved BNC and MN identification, and reduced the average time of image analysis by 78%. Finally, 50 ll of irradiated whole blood was cultured with 200 ll of media in 96-well plates. All sample processing steps were performed automatically using the RABiT-II cell: :explorer robotic system adopting the optimized IFC-CBMN assay protocol. The results presented here detail a novel, high-throughput RABiT-IFC CBMN assay that possesses the potential to increase capacity for triage biodosimetry during a large-scale radiological/nuclear event.

BIODOSIMETRY AND BIODOSIMETRY NETWORKS FOR MANAGING RADIATION EMERGENCY

Biological dosimetry enables individual dose reconstruction in the case of unclear or inconsistent radiation exposure situations, especially when a direct measurement of ionizing radiation is not or is no longer possible. To be prepared for large-scale radiological incidents, networking between well-trained laboratories has been identified as a useful approach for provision of the fast and trustworthy dose assessments needed in such circumstances. To this end, various biodosimetry laboratories worldwide have joined forces and set up regional and/or nationwide networks either on a formal or informal basis. Many of these laboratories are also a part of global networks such as those organized by World Health Organization, International Atomic Energy Agency or Global Health Security Initiative. In the present report, biodosimetry networks from different parts of the world are presented, and the partners, activities and cooperation actions are detailed. Moreover, guidance for situational application of tools used for individual dosimetry is given.

Automation of the in vitro micronucleus assay using the Imagestream® imaging flow cytometer

The in vitro micronucleus (MN) assay is a well‐established test for evaluating genotoxicity and cytotoxicity. The use of manual microscopy to perform the assay can be laborious and often suffers from user subjectivity and interscorer variability. Automated methods including slide‐scanning microscopy and conventional flow cytometry have been developed to eliminate scorer bias and improve throughput. However, these methods possess several limitations such as lack of cytoplasmic visualization using slide‐scanning microscopy and the inability to visually confirm the legitimacy of MN or storage of image data for re‐evaluation using flow cytometry. The ImageStream^X® MK II (ISX) imaging flow cytometer has been demonstrated to overcome all of these limitations. The ISX combines the speed, statistical robustness, and rare event capture capability of conventional flow cytometry with high resolution fluorescent imagery of microscopy and possesses the ability to store all collected image data. This paper details the methodology developed to perform the in vitro MN assay in human lymphoblastoid TK6 cells on the ISX. High resolution images of micronucleated mono‐ and bi‐nucleated cells as well as polynucleated cells can be acquired at a high rate of capture. All images can then be automatically identified, categorized and enumerated in the data analysis software that accompanies the ImageStream, allowing for the scoring of both genotoxicity and cytotoxicity. The results demonstrate that statistically significant increases in MN frequency when compared with solvent controls can be detected at varying levels of cytotoxicity following exposure to well‐known aneugens and clastogens. This work demonstrates a fully automated method for performing the in vitro micronucleus assay on the ISX imaging flow cytometry platform. © 2018 The Author. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of ISAC.

The potential for complete automated scoring of the cytokinesis block micronucleus cytome assay using imaging flow cytometry

The lymphocyte Cytokinesis-Block Micronucleus (CBMN) assay was originally developed for the measurement of micronuclei (MN) exclusively in binucleated (BN) cells, which represent the population of cells that can express MN because they completed nuclear division. Recently the assay has evolved into a comprehensive cytome method to include biomarkers that measure chromosomal instability and cytotoxicity by quantification of nuclear buds (NBUDs), nucleoplasmic bridges (NPBs) and apoptotic/necrotic cells. Furthermore, enumeration of mono- and polynucleated cells allows for computation of the nuclear division index (NDI) to assess mitotic activity. Typically performed by manual microscopy, the CBMN cytome assay is laborious and subject to scorer bias and fatigue, leading to inter- and intra-scorer variability. Automated microscopy and conventional flow cytometry methods have been developed to automate scoring of the traditional and cytome versions of the assay. However, these methods have several limitations including the requirement to create high-quality microscope slides, lack of staining consistency and sub-optimal nuclear/cytoplasmic visualization. In the case of flow cytometry, stripping of the cytoplasmic membrane makes it impossible to measure MN in BN cells, calculate the NDI or to quantify apoptotic or necrotic cells. Moreover, the absence of cellular visualization using conventional flow cytometry, makes it impossible to quantify NBUDs and NPBs. In this review, we propose that imaging flow cytometry (IFC), which combines high resolution microscopy with flow cytometry, may overcome these limitations. We demonstrate that by using IFC, images from cells in suspension can be captured, removing the need for microscope slides and allowing visualization of intact cytoplasmic membranes and DNA content. Thus, mono-, bi- and polynucleated cells with and without MN can be rapidly and automatically identified and quantified. Finally, we present high-resolution cell images containing NBUDs and NPBs, illustrating that IFC possesses the potential for completely automated scoring of all components of the CBMN cytome assay.

RABiT-II: Implementation of a High-Throughput Micronucleus Biodosimetry Assay on Commercial Biotech Robotic Systems

We demonstrate the use of high-throughput biodosimetry platforms based on commercial high-throughput/high-content screening robotic systems. The cytokinesis-block micronucleus (CBMN) assay, using only 20 μl whole blood from a fingerstick, was implemented on a PerkinElmer cell::explorer and General Electric IN Cell Analyzer 2000. On average 500 binucleated cells per sample were detected by our FluorQuantMN software. A calibration curve was generated in the radiation dose range up to 5.0 Gy using the data from 8 donors and 48,083 binucleated cells in total. The study described here demonstrates that high-throughput radiation biodosimetry is practical using current commercial high-throughput/high-content screening robotic systems, which can be readily programmed to perform and analyze robotics-optimized cytogenetic assays. Application to other commercial high-throughput/high-content screening systems beyond the ones used in this study is clearly practical. This approach will allow much wider access to high-throughput biodosimetric screening for large-scale radiological incidents than is currently available.

The Application of Imaging Flow Cytometry to High-Throughput Biodosimetry

Biodosimetry methods, including the dicentric chromosome assay, the cytokinesis-block micronucleus assay and the γH2AX marker of DNA damage are used to determine the dose of ionizing radiation. These techniques are particularly useful when physical dosimetry is absent or questioned. While these assays can be very sensitive and specific, the standard methods need to be adapted to increase sample throughput in the case of a large-scale radiological/nuclear event. Recent modifications to the microscope-based assays have resulted in some increased throughput, and a number of biodosimetry networks have been, and continue to be, established and strengthened. As the imaging flow cytometer (IFC) is a technology that can automatically image and analyze processed blood samples for markers of radiation damage, the microscope-based biodosimetry techniques can be modified for the IFC for high-throughput biological dosimetry. Furthermore, the analysis templates can be easily shared between networked biodosimetry laboratories for increased capacity and improved standardization. This review describes recent advances in IFC methodology and their application to biodosimetry.

Connected component masking accurately identifies the ratio of phagocytosed and cell-bound particles in individual cells by imaging flow cytometry

Innate immune cell-mediated recognition, capture, and engulfment of large particulate targets such as bacteria is known as phagocytosis. This highly dynamic cellular process involves a series of steps including receptor-mediated target binding, phagocytic cup formation, pseudopod extension, and phagosome closure, which depend on distinct actin polymerization events. Using flow cytometry, precise determination of target locations relative to cell membranes (i.e., surface-bound vs. fully engulfed/internalized) during the phagocytic process is difficult to quantify. Here, we describe the application of new analysis features within the IDEAS® software to distinguish internalized and surface-bound particles on individual cells with a high degree of accuracy and reproducibility. Through the use of connected component masks, the accurate discrimination of surface-bound beads versus those internalized is clearly demonstrated. In addition, we were able to further analyze the ratio of beads that had been surface-bound or internalized within individual cells. This novel method of analyzing the phagocytic process provides more accurate determination of target-cell interactions that will assist in examination of the signalling events that occur during the various stages of phagocytosis. © 2017 International Society for Advancement of Cytometry.

Flow cytometry what you see matters: Enhanced clinical detection using image-based flow cytometry

Image-based flow cytometry combines the throughput of traditional flow cytometry with the ability to visually confirm findings and collect novel data that would not be possible otherwise. Since image-based flow cytometry borrows measurement parameters and analysis techniques from microscopy, it is possible to collect unique measures (i.e. nuclear translocation, co-localization, cellular synapse, cellular endocytosis, etc.) that would not be possible with traditional flow cytometry. The ability to collect unique outcomes has led many researchers to develop novel assays for the monitoring and detection of a variety of clinical conditions and diseases. In many cases, investigators have innovated and expanded classical assays to provide new insight regarding clinical conditions and chronic disease. Beyond human clinical applications, image-based flow cytometry has been used to monitor marine biology changes, nano-particles for solar cell production, and particle quality in pharmaceuticals. This review article summarizes work from the major scientists working in the field of image-based flow cytometry.

Foundations of identifying individual chromosomes by imaging flow cytometry with applications in radiation biodosimetry

Biodosimetry is an important tool for triage in the case of large-scale radiological or nuclear emergencies, but traditional microscope-based methods can be tedious and prone to scorer fatigue. While the dicentric chromosome assay (DCA) has been adapted for use in triage situations, it is still time-consuming to create and score slides. Recent adaptations of traditional biodosimetry assays to imaging flow cytometry (IFC) methods have dramatically increased throughput. Additionally, recent improvements in image analysis algorithms in the IFC software have resulted in improved specificity for spot counting of small events. In the IFC method for the dicentric chromosome analysis (FDCA), lymphocytes isolated from whole blood samples are cultured with PHA and Colcemid. After incubation, lymphocytes are treated with a hypotonic solution and chromosomes are isolated in suspension, labelled with a centromere marker and stained for DNA content with DRAQ5. Stained individual chromosomes are analyzed on the ImageStream®^X (EMD-Millipore, Billerica, MA) and mono- and dicentric chromosome populations are identified and enumerated using advanced image processing techniques. Both the preparation of the isolated chromosome suspensions as well as the image analysis methods were fine-tuned in order to optimize the FDCA. In this paper we describe the method to identify and score centromeres in individual chromosomes by IFC and show that the FDCA method may further improve throughput for triage biodosimetry in the case of large-scale radiological or nuclear emergencies.