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Sproull M, Camphausen K. Partial-body Models of Radiation Exposure. Radiat Res 2025; 203:129-141. [PMID: 39923796 PMCID: PMC11973700 DOI: 10.1667/rade-24-00189.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2024] [Accepted: 01/29/2025] [Indexed: 02/11/2025]
Abstract
The events of 9/11 sparked a revitalization of civil defense in the U.S. for emergency planning and preparedness for future radiological or nuclear event scenarios and specifically for mass casualty medical management of radiation exposure and injury. Research in medical countermeasure development in the form of novel pharmaceuticals to treat radiation injury and new radiation biodosimetry diagnostics, primarily focused on development of research models of uniform total-body irradiation (TBI). With the success of those models, it was recognized that most radiation exposures in the field will involve non-uniform heterogeneous irradiations and many partial-body or organ-specific irradiation models have been utilized. This review examines partial-body models of irradiations developed in the last decade for heterogeneous radiation exposures and organ-specific radiation exposure patterns. These research models have been used to further our understanding of radiation injury, novel medical countermeasures and biodosimetry diagnostics in development for future radiological and nuclear event scenarios.
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Affiliation(s)
- M. Sproull
- Radiation Oncology Branch, National Cancer Institute, Bethesda, Maryland
| | - K. Camphausen
- Radiation Oncology Branch, National Cancer Institute, Bethesda, Maryland
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Shuryak I, Nemzow L, Bacon BA, Taveras M, Wu X, Deoli N, Ponnaiya B, Garty G, Brenner DJ, Turner HC. Machine learning approach for quantitative biodosimetry of partial-body or total-body radiation exposures by combining radiation-responsive biomarkers. Sci Rep 2023; 13:949. [PMID: 36653416 PMCID: PMC9849198 DOI: 10.1038/s41598-023-28130-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 01/13/2023] [Indexed: 01/19/2023] Open
Abstract
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.
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Affiliation(s)
- Igor Shuryak
- Center for Radiological Research, Columbia University Irving Medical Center, 630 West 168th street, VC-11-234/5, New York, NY, 10032, USA.
| | - Leah Nemzow
- Center for Radiological Research, Columbia University Irving Medical Center, 630 West 168th street, VC-11-234/5, New York, NY, 10032, USA
| | - Bezalel A Bacon
- Center for Radiological Research, Columbia University Irving Medical Center, 630 West 168th street, VC-11-234/5, New York, NY, 10032, USA
| | - Maria Taveras
- Center for Radiological Research, Columbia University Irving Medical Center, 630 West 168th street, VC-11-234/5, New York, NY, 10032, USA
| | - Xuefeng Wu
- Center for Radiological Research, Columbia University Irving Medical Center, 630 West 168th street, VC-11-234/5, New York, NY, 10032, USA
| | - Naresh Deoli
- Radiological Research Accelerator Facility, Columbia University Irving Medical Center, Irvington, NY, USA
| | - Brian Ponnaiya
- Radiological Research Accelerator Facility, Columbia University Irving Medical Center, Irvington, NY, USA
| | - Guy Garty
- Radiological Research Accelerator Facility, Columbia University Irving Medical Center, Irvington, NY, USA
| | - David J Brenner
- Center for Radiological Research, Columbia University Irving Medical Center, 630 West 168th street, VC-11-234/5, New York, NY, 10032, USA
| | - Helen C Turner
- Center for Radiological Research, Columbia University Irving Medical Center, 630 West 168th street, VC-11-234/5, New York, NY, 10032, USA
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Farese AM, Drouet M, Herodin F, Bertho JM, Thrall KD, Authier S, Doyle-Eisele M, MacVittie TJ. Acute Radiation Effects, the H-ARS in the Non-human Primate: A Review and New Data for the Cynomolgus Macaque with Reference to the Rhesus Macaque. HEALTH PHYSICS 2021; 121:304-330. [PMID: 34546214 DOI: 10.1097/hp.0000000000001442] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
ABSTRACT Medical countermeasure development under the US Food and Drug Administration animal rule requires validated animal models of acute radiation effects. The key large animal model is the non-human primate, rhesus macaque. To date, only the rhesus macaque has been used for both critical supportive data and pivotal efficacy trials seeking US Food and Drug Administration approval. The potential for use of the rhesus for other high priority studies such as vaccine development underscores the need to identify another non-human primate model to account for the current lack of rhesus for medical countermeasure development. The cynomolgus macaque, Macaca fascicularis, has an existing database of medical countermeasure development against the hematopoietic acute radiation syndrome, as well as the use of radiation exposure protocols that mimic the likely nonuniform and heterogenous exposure consequent to a nuclear terrorist event. The review herein describes published studies of adult male cynomolgus macaques that used two exposure protocols-unilateral, nonuniform total-body irradiation and partial-body irradiation with bone marrow sparing-with the administration of subject-based medical management to assess mitigation against the hematopoietic acute radiation syndrome. These studies assessed the efficacy of cytokine combinations and cell-based therapy to mitigate acute radiation-induced myelosuppression. Both therapeutics were shown to mitigate the myelosuppression of the hematopoietic acute radiation syndrome. Additional studies being presented herein further defined the dose-dependent hematopoietic acute radiation syndrome of cynomolgus and rhesus macaques and a differential dose-dependent effect with young male and female cynomolgus macaques. The database supports the investigation of the cynomolgus macaque as a comparable non-human primate for efficacy testing under the US Food and Drug Administration animal rule. Critical gaps in knowledge required to validate the models and exposure protocols are also identified.
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Affiliation(s)
- Ann M Farese
- University of Maryland, School of Medicine, Department of Radiation Oncology, Baltimore
| | - Michel Drouet
- Armed Forces Biomedical Research Institute, France, Department of Radiobiology, Brétigny-sur-Orge, France
| | | | - Jean-Marc Bertho
- Institute of Radiation Protection and Nuclear Safety (IRSN), 31 avenue de la division Leclerc, 92260, Fontenay-aux-Roses, France; Present address: French Nuclear Safety Authority (ASN), 15 rue Louis Lejeune 92540 Montrouge, France
| | | | - Simon Authier
- Charles River, 445 Armand Frappier, Laval, QC, Canada, H7V 4B3
| | - Melanie Doyle-Eisele
- Lovelace Biomedical Research Institute, Laboratory Animal Sciences (Life Sciences), Albuquerque, NM
| | - Thomas J MacVittie
- University of Maryland, School of Medicine, Department of Radiation Oncology, Baltimore
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Wang Q, Lee Y, Shuryak I, Pujol Canadell M, Taveras M, Perrier JR, Bacon BA, Rodrigues MA, Kowalski R, Capaccio C, Brenner DJ, Turner HC. Development of the FAST-DOSE assay system for high-throughput biodosimetry and radiation triage. Sci Rep 2020; 10:12716. [PMID: 32728041 PMCID: PMC7392759 DOI: 10.1038/s41598-020-69460-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2020] [Accepted: 07/09/2020] [Indexed: 11/09/2022] Open
Abstract
Following a large-scale radiological incident, there is a need for FDA-approved biodosimetry devices and biomarkers with the ability to rapidly determine past radiation exposure with sufficient accuracy for early population triage and medical management. Towards this goal, we have developed FAST-DOSE (Fluorescent Automated Screening Tool for Dosimetry), an immunofluorescent, biomarker-based system designed to reconstruct absorbed radiation dose in peripheral blood samples collected from potentially exposed individuals. The objective of this study was to examine the performance of the FAST-DOSE assay system to quantify intracellular protein changes in blood leukocytes for early biodosimetry triage from humanized NOD-scid-gamma (Hu-NSG) mice and non-human primates (NHPs) exposed to ionizing radiation up to 8 days after radiation exposure. In the Hu-NSG mice studies, the FAST-DOSE biomarker panel was able to generate delivered dose estimates at days 1, 2 and 3 post exposure, whereas in the NHP studies, the biomarker panel was able to successfully classify samples by dose categories below or above 2 Gy up to 8 days after total body exposure. These results suggest that the FAST-DOSE bioassay has large potential as a useful diagnostic tool for rapid and reliable screening of potentially exposed individuals to aid early triage decisions within the first week post-exposure.
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Affiliation(s)
- Qi Wang
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, 10032, USA.
- Radiation Oncology, Columbia University Irving Medical Center, New York, NY, 10032, USA.
| | - Younghyun Lee
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Igor Shuryak
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Monica Pujol Canadell
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Maria Taveras
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Jay R Perrier
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, 10032, USA
- ASELL, LLC, Owings Mills, MD, 21117, USA
| | - Bezalel A Bacon
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | | | | | | | - David J Brenner
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Helen C Turner
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, 10032, USA.
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Shuryak I, Turner HC, Perrier JR, Cunha L, Canadell MP, Durrani MH, Harken A, Bertucci A, Taveras M, Garty G, Brenner DJ. A High Throughput Approach to Reconstruct Partial-Body and Neutron Radiation Exposures on an Individual Basis. Sci Rep 2020; 10:2899. [PMID: 32076014 PMCID: PMC7031285 DOI: 10.1038/s41598-020-59695-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 01/27/2020] [Indexed: 11/28/2022] Open
Abstract
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.
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Affiliation(s)
- Igor Shuryak
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, USA.
| | - Helen C Turner
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, USA
| | - Jay R Perrier
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, USA
| | - Lydia Cunha
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, USA
| | - Monica Pujol Canadell
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, USA
| | - Mohammad H Durrani
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, USA
| | - Andrew Harken
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, USA
| | - Antonella Bertucci
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, USA
| | - Maria Taveras
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, USA
| | - Guy Garty
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, USA
| | - David J Brenner
- Center for Radiological Research, Columbia University Irving Medical Center, New York, NY, USA
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