Creation and Application of Voxelized Dosimetric Models : An Evaluation of Dose Conversion Factor in Apis Mellifera Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/bn9999449

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  • Over the past decade the International Commission on Radiological Protection has developed a comprehensive approach to environmental protection that includes the use of Reference Animals and Plants (RAPs) to assess radiological impacts on the environment. For the purposes of calculating radiation dose, the RAPs are approximated as simple shapes that contain homogeneous tissue densities and radionuclide distributions. The objective of these models is to generate energy deposition data of radionuclides within the organism. As the uncertainties in environmental dose effects are larger than uncertainties in the radiation dose calculations, some have argued against more realistic dose calculation methodologies. However, owing to the complexity of organism morphology, internal structures and density, and biological aging, all of which can affect the calculated dose rates, a homogeneous model may be too simplistic. The purpose of this study is to examine the benefits of a voxelized phantom versus simple shapes for small organism dose modeling, i.e. a honeybee. Both techniques typically use Monte Carlo methods to calculate absorbed dose. However, voxelized modeling, a reverse engineering method, uses a three-dimensional replica of an organism. Consequently, additional information can be included, such as measured tissue composition and density, for a more comprehensive study on absorbed fractions and dose distributions in different structures. This multi-stage procedure couples imaging modalities, imaging processing software, and Monte Carlo N-Particle (MCNP) code to generate a detailed phantom. Ultimately, these additional features increase dosimetric accuracy and reduce uncertainty in non-human biota (NHB) dose-effects studies by providing a more robust data generator of radionuclide sources for environmental impact analysis.
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