Stochastic Expansion of Radionuclide Inhalation Dosimetry for Consequence Management Application: Uncertainty and Sensitivity Analysis in the ICRP 130 Human Respiratory Tract Model.

Releases from nuclear or radiological security events can result in significant internal radiation contamination through inhalation of particulate contaminants. The International Commission on Radiological Protection (ICRP) has developed the reference Human Respiratory Tract Model (HRTM), detailed in ICRP Publications 66 and updated in the ICRP Publication 130, to estimate the deposition and clearance of inhaled radionuclides. Biokinetic models further estimate retention and excretion of internalized particulates, aiding the derivation of inhalation dose coefficients (DC). The HRTM developed by the ICRP utilizes deterministic quantities outlined in the ICRP Publication 66 and 130. The overarching goal of this study was to determine the variability from deterministic biokinetic/dosimetry models to represent the stochastic breadth of radionuclide metabolism in an exposed occupational population from realistic source terms, yielding an expanded compendium of inhalation dose coefficients. The analysis was carried out in three phases: (1) Development of an enhanced biokinetic and dose coefficient model and computational module based on ICRP Publication 130 HRTM and associated element specific systemic biokinetics; (2) Investigation of uncertain parameters in the HRTM; and (3) Stochastic analysis using Latin Hypercube Sampling, incorporating non-parametric (Kolmogorov-Smirnov statistics) test and Q-Q plots, informing parametric method, to characterize the distribution of the committed effective dose coefficients. To determine the most impactful parameters among the uncertain parameters, a Random Forest regression model was employed for feature importance, coupled with SHapley Additive exPlanations (SHAP) for comprehensive machine learning interpretation of the features. This study presents a unique stochastic framework for modeling inhaled particulate metabolism, enhancing capabilities in radiation consequence management, medical countermeasure development, and radiation dose reconstruction for epidemiological investigations.