Radiation biodosimetry deals with the measurement of a biological response that serves as a surrogate for estimating the absorbed radiation dose in exposed humans. The radiation biodosimetry field is rapidly advancing with exciting developments, and the biodosimetry tools that are currently used are shown in Figure 1. These tools can be broadly categorized into 5 groups: (1) prodromal signs/symptoms; (2) hematological analysis; (3) cytogenetics (Dicentric Chromosome Assay [DCA], Chromosome Translocation Assay, Premature Chromosome Condensation Assay, and Cytokinesis Blocked Micronucleus Assay [CBMN]); (4) omics (genomics, transcriptomics, proteomics, and metabolomics); and (5) physical dosimetry involving electron paramagnetic resonance [Rothkamm et al., 2013; Sproull et al., 2017]. This special issue on “Radiation Biodosimetry: Current Developments and Future Perspectives” is intended to provide the readers with the present status of knowledge on some of the exciting new advancements in the field and to promote future research initiatives for developing novel biodosimetry assays.

Fig. 1.

Radiation biodosimetry tools that are currently used for absorbed dose estimation in exposed humans: prodromal signs/symptoms, Cytokinesis Blocked Micronucleus Assay (CBMN), Dicentric Chromosome Assay (DCA), Premature Chromosome Condensation (PCC) Assay, γ-H2AX Assay, electron paramagnetic resonance (EPR), lymphocyte depletion kinetics (LDK), neutrophil-to-lymphocyte ratio (NLR), transcriptomics, proteomics, genomics, and metabolomics.

Fig. 1.

Radiation biodosimetry tools that are currently used for absorbed dose estimation in exposed humans: prodromal signs/symptoms, Cytokinesis Blocked Micronucleus Assay (CBMN), Dicentric Chromosome Assay (DCA), Premature Chromosome Condensation (PCC) Assay, γ-H2AX Assay, electron paramagnetic resonance (EPR), lymphocyte depletion kinetics (LDK), neutrophil-to-lymphocyte ratio (NLR), transcriptomics, proteomics, genomics, and metabolomics.

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The special issue contains 3 reviews and 10 research articles by well-known experts in the biodosimetry field. The article by Satyamitra et al. [2023] provides an overview of the operational aspects of the biodosimetry program by the National Institute of Allergy and Infectious Diseases (NIAID)/Radiological Nuclear Countermeasure Program (RNCP), followed by the manuscript of Aryankalayil et al. [2023] on biomarkers for biodosimetry and their potential role(s) in predicting radiation injury. The special issue features three manuscripts on CBMN assay [(1) evaluation of comparative efficacy of CBMN assay in whole blood and isolated lymphocytes for triage application by Bertucci et al. [2023], (2) assessment of fractionated total body radiation-induced micronuclei frequency in the peripheral blood of adult and pediatric populations by Kanagaraj et al. [2023], and (3) application of CBMN for high radiation dose exposures using imaging flow cytometry by Beaton-Green et al. [2023]] and three manuscripts on cytogenetic biodosimetry [(1) scoring of Calyculin-A-induced G2-premature chromosome condensation objects for dose assessment in ex-vivo irradiated human blood samples and in the blood samples of radiotherapy patients by Sun et al. [2023], (2) a 27-year follow-up study on internal radioiodine-induced chromosome aberrations in a thyroid cancer survivor by Livingston et al. [2023], and (3) an international comparison exercise performed at two irradiation facilities in the USA and Germany for biodosimetry after neutron exposures by Endesfelder et al. [2023]]. The manuscript from the group of Dr. Lacombe [Lacombe et al., 2023] presents a paper-based vertical flow immunoassay method for the point-of-care multiplex detection of radiation dosimetry genes. Using a murine model system, the potential implications of sex as a crucial confounding factor in developing medical countermeasures are described in the manuscript by Holmes-Hampton et al. [2023]. Three manuscripts on transcriptomics are also included in this special issue: (1) effect of age and gender on radiation-induced gene expression profiles in mouse peripheral blood by Broustas et al. [2023], (2) relevance of gene expression in regional population and its relevance for triage by Kannan et al. [2023], and (3) challenges and promises for using gene expression profiles for biodosimetry and clinical outcome prediction by Abend et al. [2023].

Ever since Bender and Gooch published their findings in 1962 [Bender and Gooch 1962a, 1962b] that the frequency of radiation-induced dicentric chromosomes can be used for estimating the absorbed radiation dose, DCA has gained importance to become the gold standard for absorbed dose estimation. Although DCA is frequently used for estimating the absorbed radiation dose for occupationally, accidently, and incidentally exposed individuals, its laborious and time-consuming attributes have led to the realization that DCA may not be able to provide timely assessment of absorbed dose to several hundreds and thousands of people in the aftermath of large-scale radiological/nuclear incidents. Realizing the critical need for timely assessment of absorbed dose for guiding medical treatment decisions, researchers started exploring the possibilities of discovering novel biodosimetry tools that can rapidly predict the absorbed dose within a few minutes to hours. To expedite the dose assessment, efforts have also been made to develop high-throughput automation for some of the biodosimetry tools [Garty et al., 2011; Sullivan et al., 2013; Achel et al., 2016; Pannkuk et al., 2016; Nongrum et al., 2017; Jacobs et al., 2020; Nemzow et al., 2023; Wilkins and Beaton-Green, 2023]. Development of such automated tools will be beneficial for providing rapid biodosimetry for individuals involved in small and large-scale radiological and nuclear incidents/accidents.

The biodosimetry field has seen tremendous advancements with the development of either new or modified versions of many assays/tools in the fields of cytogenetics, omics and electron paramagnetic resonance but most tools remain to be experimentally and clinically validated for their specificity and sensitivity as well as dose prediction accuracy against the gold standard DCA. Until now, most studies were conducted using acute doses of low LET radiation involving γ-rays and X-rays, but the dose rate effect has not been vigorously investigated [Swartz et al., 2010]. Although a few studies are available [Blumenthal et al., 2014; Laiakis et al., 2019; Mukherjee et al., 2019; Bai et al., 2023; Royba et al., 2023], the existing dose assessment tools need to be vigorously tested for various exposure scenarios: internal exposures through ingestion/inhalation of radionuclides, combination of external and internal exposures, cumulative fractionated exposures and exposures of mixed radiation fields. Also, discovery of suitable biomarkers for identifying total and partial body irradiation exposures is a top priority for determining the course of medical management for moderately and severely exposed populations. A few recent studies have started addressing this issue [Maan et al., 2020; Pazzaglia et al., 2022; Sproull et al., 2022; Shuryak et al., 2023], but more studies are needed for additional biomarkers that can efficiently distinguish between partial and whole-body exposures.

There are several confounding factors such as age, sex, lifestyle, genetic predisposition to radiation sensitivity, and susceptibility that may affect the dose prediction accuracy of currently available biodosimetry tools. The modulatory effects of age and sex on gene expression profiles and for developing medical countermeasures have been addressed by two articles in this special issue [Holmes-Hampton et al., 2023; Broustas et al., 2023]. Among the confounding factors, inter-individual variation in radiation response is the key factor to consider for formulating the radiation protection measures, and therefore, biodosimetry tools need to be modeled for special populations with pre-existing disease states, inherent radiation sensitivity (owing to gene mutations), pediatric and geriatric populations. Importantly, biodosimetry modeling should include combined injury as inflammatory response and trauma-associated biological pathways may complicate the interpretation of data obtained from the expression analysis “omics” biomarkers. It would be highly beneficial if the biomarkers/biodosimeters chosen for dose assessment could also serve as predictors of health outcomes in exposed individuals. Existence of heterogeneity in radiation response among different tissues/organs is well documented in the literature [Ryan, 2012]. The heterogeneity in radiosensitivity and radiosusceptibility of different organs necessitates the need for developing organ-specific biomarkers to predict organ-specific dysfunction and disease outcome retrospectively. Organ-specific biomarkers can help not only in assessing the long-term adverse effects of radiation in exposed populations and radiotherapy patients but may also lead to the future development of organ-specific therapeutics.

As stated above, several technical challenges remain in the biodosimetry field that need to be resolved to fill the gaps in our scientific knowledge. In addition, special consideration is needed for developing potential point-of-care testing tools for triage following mass casualty incidents that can potentially expose several thousands of people to substantial doses of radiation. We sincerely hope that this special issue will motivate aspiring, emerging, and experienced researchers to take this fascinating field of radiation biodosimetry to new heights by bridging some of the gaps to protect human safety and health from the adverse effects of incidental, accidental, and occupational radiation exposures.

The editors thank all the authors and co-authors for their contributions to the special issue. Our apologies to those scientists whose valuable contributions could not be included for want of space.

The authors do not have any conflict of interest.

No funding was received for the manuscript.

A.S.B. wrote the manuscript with significant inputs from H.T. and R.W.

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