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• W841551141 abstract "Radiation dose to biota is generally calculated using Monte Carlo simulations of whole body ellipsoids with homogeneously distributed radioactivity throughout. More complex anatomical phantoms, termed voxel phantoms, have been developed to test the validity of these simplistic geometric models. In most voxel models created to date, human tissue composition and density values have been used in lieu of biologically accurate values for non-human biota. This has raised questions regarding variable tissue composition and density effects on the fraction of radioactive emission energy absorbed within tissues (e.g. the absorbed fraction - AF), along with implications for age-dependent dose rates as organisms mature. The results of this study on rabbits indicates that the variation in composition between two mammalian tissue types (e.g. human vs rabbit bones) made little difference in self-AF (SAF) values (within 5% over most energy ranges). However, variable tissue density (e.g. bone vs liver) can significantly impact SAF values. An examination of differences across life-stages revealed increasing SAF with testis and ovary size of over an order of magnitude for photons and several factors for electrons, indicating the potential for increasing dose rates to these sensitive organs as animals mature. AFs for electron energies of 0.1, 0.2, 0.4, 0.5, 0.7, 1.0, 1.5, 2.0, and 4.0 MeV and photon energies of 0.01, 0.015, 0.02, 0.03, 0.05, 0.1, 0.2, 0.5, 1.0, 1.5, 2.0, and 4.0 MeV are provided for eleven rabbit tissues. The data presented in this study can be used to calculate accurate organ dose rates for rabbits and other small rodents; to aide in extending dose results among different mammal species; and to validate the use of ellipsoidal models for regulatory purposes." @default.
• W841551141 created "2016-06-24" @default.
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• W841551141 date "2016-01-01" @default.
• W841551141 modified "2023-10-08" @default.
• W841551141 title "Voxel modeling of rabbits for use in radiological dose rate calculations" @default.
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• W841551141 doi "https://doi.org/10.1016/j.jenvrad.2015.04.008" @default.
• W841551141 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/25971772" @default.
• W841551141 hasPublicationYear "2016" @default.
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