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DOE OSTI · 3378125

Statistical Uncertainty of Inhalation Dose Coefficients: Impact of Particle Deposition in ICRP 66 Human Respiratory Tract Model

Abstract

Inhaled radioactive materials can pose a long-term health concern, as the material can be incorporated into the body’s metabolic pathways and remain in organs and tissues for extended durations. During the retention period, the radioactive material may localize in a source organ and irradiate adjacent target organs and tissues. Distribution of these materials changes over time, requiring biokinetic modeling to evaluate their movement through various tissues and organs. The evolving distribution depends on multiple inputs characterizing the inhaled material, such as particle size and size distribution, particle density, aspect ratio, specific radionuclide, the chemical form, and solubility. In addition, biological parameters such as breathing rate, breathing type (nasal or nasal/oral), respiratory system morphometry, tidal volume, functional residual capacity, and anatomical dead space all influence material transport. These aerosol properties and physiological characteristics of the respiratory tract jointly define a range of initial conditions that influence the time-dependent distribution of radioactive material. To evaluate both uncertainty in the initial conditions of inhalation exposure and the final output (committed effective dose) from biokinetic models, a Python-based software tool, Radiological Exposure Dose Calculator (REDCAL), was developed to propagate uncertainty within the human respiratory tract model. Focusing on deposition fraction uncertainty, the primary objective was to characterize the initial activity distribution across respiratory regions as a function of anticipated particle sizes and distributions. The impact of the deposition fraction uncertainty was propagated to committed effective dose coefficients for selected radionuclides in a companion publication. For each particle size, a lognormal distribution, characterized by its geometric mean as defined within ICRP Publication 66, serves as the basis for introducing uncertainty into the physical processes governing deposition in various lung regions. Finally, this study addresses the deposition process and examines how uncertainty in deposition mechanisms affects activity distribution in the airways, ultimately presenting the expected range and standard deviation of deposited activity as a function of particle size.

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Margot, Dmitri Edward [Georgia Institute of Technology, Atlanta, GA (United States)] (ORCID:0000000327289871), Mate-Kole, Emmanuel M. [Georgia Institute of Technology, Atlanta, GA (United States)], Cochran, Lainy Dromgoole [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)] (ORCID:0009000951356609), Jelsema, Casey Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)] (ORCID:0009000554678030), Graffigna, Martin [Georgia Institute of Technology, Atlanta, GA (United States)], Buchbinder Shadur, Lotem [Georgia Institute of Technology, Atlanta, GA (United States)], Kalinowski, Autumn Elizabeth [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)], Dewji, Shaheen Azim [Georgia Institute of Technology, Atlanta, GA (United States)]. 2026-03-24. Statistical Uncertainty of Inhalation Dose Coefficients: Impact of Particle Deposition in ICRP 66 Human Respiratory Tract Model. https://doi.org/10.1097/hp.0000000000002047

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