Elsevier

Applied Radiation and Isotopes

Volume 126, August 2017, Pages 134-137
Applied Radiation and Isotopes

Computational Approaches on Photon-Attenuation and Coincidence-summing Corrections for the detection of gamma-emitting radionuclides IN foods

https://doi.org/10.1016/j.apradiso.2017.02.034Get rights and content

Highlights

  • Computation of efficiencies by using Monte Carlo methods.

  • Density corrections and coincidence summing can be effectively accounted for.

  • Accurate measurements of radioactive food samples for emergency response scenarios.

Abstract

Source-based calibration methods used for photon attenuation and coincidence summing corrections are time consuming and require multiple certified standards that match sample geometry with varying densities. Three programs which are capable of simulating a variety of sample geometries, matrix compositions, and sample densities have been examined as alternatives. LabSOCS, ANGLE 3 and GESPECOR are effective at generating efficiency curves for food matrices with a range with different densities. The curves generated have been successfully used to determine activity in food samples.

Introduction

The risk of food being tainted with radioactive materials due to accidents at nuclear facilities, proliferation of nuclear war or deliberate contamination by terroristic threats, is of critical concern to the U.S. Food and Drug Administration (FDA). In order to prepare for these potential radiological threats, significant efforts are needed to develop radioanalytical capabilities for emergency response situations. Even though there are methods for detecting radionuclides in a large number of food samples (Lin et al., 2016), improvements must be made that allow for rapid and high-throughput detection. The radionuclides of greatest concern for food safety and public health have been previously categorized with respect to their principal emissions, many of which are radionuclides with gamma radiation as the principal emission (Lin et al., 2016).

In order to effectively respond to a large-scale nuclear or radiological emergency, the method of detection must be quick, simple, and capable of high-throughput applications. Gamma-ray spectroscopy is an advantageous technique to use because it allows for the identification and quantification of gamma-emitting radionuclides without extensive sample preparation (Debertin and Helmer, 1988, Knoll, 2010). A high resolution sample gamma spectrum, which exhibits energies and intensities of different gamma radionuclides, can be used to identify and quantify unknown radionuclides present in a food sample.

Although gamma spectroscopy is a powerful technique that is very useful for characterizing and quantifying radioactive material, applying this method for rapid quantification of radionuclides in food faces several challenges. A major issue that affects the speed in which measurements are taken in emergency response operation is the calibration of the instrument. Traditionally, calibration of gamma ray spectrometer requires use of a physical standard comprised of mixed gamma sources. The matrix of the standard sample must match that of the unknown in order to replicate its composition and density and the radioactive material within the sample must be dispersed homogeneously. These requirements of having a physical calibration standard match each unknown sample is difficult to meet quickly. There are very limited food-based gamma standards available for purchase and they are high in cost. Preparing unique gamma food standards that are accurate and stable is challenging and generates radioactive waste which is difficult to dispose of. In addition, these standards also have limited useful shelf life due to radionuclides of interest being short lived. Coincidence-summing that leads loss or addition of a count from summed-out or summed-in photons must also be accounted for in order to ensure the accuracy of efficiency curve, which is used to ultimately derive the amount of unknown in the sample.

The ability to develop a simple and practical approach to emulate physical and chemical properties of the sample, compute counting efficiency, and correct coincidence summing effects is critically needed to achieve rapid instrument calibration for high throughput sample analysis. This work focused on examining computational methods as a way to address the issues and challenges related to instrument calibration and sample analysis.

Section snippets

Materials and methods

This study compares the activities calculated for food samples spiked with known radioactivity, based on both traditional multi-line efficiency calibration and detection efficiencies from calculation methods. Mathematical calibration software has been previously used across the nuclear measurement industry (Bell et al., 2012, Długosz-Lisiecka and Ziomek, 2015, Done et al., 2016). Three software packages evaluated are LabSOCS by Canberra (Canberra, 2013), ANGLE 3 (Jovanovic et al., 2010,

Results and discussion

The efficiencies and coincidence-summing effect for food-based sources in cylindrical geometry were computed using LabSOCS, ANGLE 3 and GESPECOR software. The efficiencies for each of these food-based standards were measured and compared with the calculated results as shown in Fig. 1. The calculations for each of the software closely resemble the measured efficiency for all of the different foods. Although the detector for the LabSOCS simulation is precisely characterized at the factory and

Conclusion

The computational software programs LabSOCS, ANGLE 3 and GESPECOR are all effective at accounting for density corrections in food matrices. These programs can also account for coincidence summing effects and improve the determination of activity levels in unknown samples. However, it is not safe to apply this procedure without checking the correctness of the detector model. This can be tested in advance using readily available point sources. This method has several advantages such as the

Acknowledgements

This project was funded by US FDA Commissioner's Fellowship Program. Special thanks go to Winchester Engineering and Analytical Center management: Brian Baker and Patrick Regan.

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