Development and validation of an ex vivo electron paramagnetic resonance fingernail biodosimetric method
Autor: | Jason W. Sidabras, Jiang Gui, Ann Barry Flood, Michael Mariani, Oleg Y. Grinberg, Steven Swarts, Harold M. Swartz, Dmitry Tipikin, Dean E. Wilcox, Eugene Demidenko, Andres E. Ruuge, Stephen D.P. Marsh, Xiaoming He |
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Rok vydání: | 2014 |
Předmět: |
Accuracy and precision
Materials science Radiation Dosage Mechanotransduction Cellular Signal Matrix (chemical analysis) Sampling (signal processing) Biodosimetry medicine Humans Dosimetry Radiology Nuclear Medicine and imaging Radiometry Radiation integumentary system Radiological and Ultrasound Technology business.industry Electron Spin Resonance Spectroscopy Public Health Environmental and Occupational Health General Medicine medicine.anatomical_structure Nails Papers Nail (anatomy) Biological Assay Nuclear medicine business Nail matrix Biomedical engineering |
Zdroj: | Radiation Protection Dosimetry. 159:172-181 |
ISSN: | 1742-3406 0144-8420 |
DOI: | 10.1093/rpd/ncu129 |
Popis: | There is an imperative need to develop methods that can rapidly and accurately determine individual exposure to radiation for screening (triage) populations and guiding medical treatment in an emergency response to a large-scale radiological/nuclear event. To this end, a number of methods that rely on dose-dependent chemical and/or physical alterations in biomaterials or biological responses are in various stages of development. One such method, ex vivo electron paramagnetic resonance (EPR) nail dosimetry using human nail clippings, is a physical biodosimetry technique that takes advantage of a stable radiation-induced signal (RIS) in the keratin matrix of fingernails and toenails. This dosimetry method has the advantages of ubiquitous availability of the dosimetric material, easy and non-invasive sampling, and the potential for immediate and rapid dose assessment. The major challenge for ex vivo EPR nail dosimetry is the overlap of mechanically induced signals and the RIS. The difficulties of analysing the mixed EPR spectra of a clipped irradiated nail were addressed in the work described here. The following key factors lead to successful spectral analysis and dose assessment in ex vivo EPR nail dosimetry: (1) obtaining a thorough understanding of the chemical nature, the decay behaviour, and the microwave power dependence of the EPR signals, as well as the influence of variation in temperature, humidity, water content, and O₂ level; (2) control of the variability among individual samples to achieve consistent shape and kinetics of the EPR spectra; (3) use of correlations between the multiple spectral components; and (4) use of optimised modelling and fitting of the EPR spectra to improve the accuracy and precision of the dose estimates derived from the nail spectra. In the work described here, two large clipped nail datasets were used to test the procedures and the spectral fitting model of the results obtained with it. A 15-donor nail set with 90 nail samples from 15 donors was used to validate the sample handling and spectral analysis methods that have been developed but without the interference of a native background signal. Good consistency has been obtained between the actual RIS and the estimated RIS computed from spectral analysis. In addition to the success in RIS estimation, a linear dose response has also been achieved for all individuals in this study, where the radiation dose ranges from 0 to 6 Gy. A second 16-donor nail set with 96 nail samples was used to test the spectral fitting model where the background signal was included during the fitting of the clipped nail spectra data. Although the dose response for the estimated and actual RIS calculated in both donor nail sets was similar, there was an increased variability in the RIS values that was likely due to the variability in the background signal between donors. Although the current methods of sample handling and spectral analysis show good potential for estimating the RIS in the EPR spectra of nail clippings, there is a remaining degree of variability in the RIS estimate that needs to be addressed; this should be achieved by identifying and accounting for demographic sources of variability in the background nail signal and the composition of the nail matrix. |
Databáze: | OpenAIRE |
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