Evaluation of Exposure Pathway, Internalized Uptakes, and Dosimetry for Military Personnel from Radiological and Toxic Metal Sources

Funding: Department of Defense – Peer Reviewed Medical Research Program via Northwestern University (G. Woloschak) Award Number W81XWH-21-1-0984 – Aligning Dosimetry and Biomarkers of Lung Injury with Prophylaxis and Mitigation of Damage from Radionuclides and Metals
Period of Performance: Oct. 1, 2021-Sept. 30, 2025
Project Website: https://sites.northwestern.edu/allrems/

There are a variety of operational scenarios where military Service personnel, Warfighters, and military first responders can become exposed to inhaled contaminants while deployed, which can later lead to lung injury whether short term/acute (e.g., pneumonitis – lung tissue inflammation) or long-term/chronic (e.g., pulmonary fibrosis – lung tissue scarring). Contamination can originate from particles containing radiation from nuclear powerplant accidents, nuclear weapons, or dirty bombs. Contamination may also occur from non-radioactive sources, such as exposure to toxic metals like tungsten alloy or depleted uranium in military munitions.

ICRP Publication 130 revised HRTM (from ICRP 66) used for updated documents on occupational intake of radionuclides. Numbers shown are particle transport rates (d-1) along the directed paths (ICRP, 2015).

Algorithm-generated lung mesh model for CFPD simulation.

This project is focused on creating realistic contamination sources from radioactive particles and heavy metal particles, including defining the particle sizes, solubilities in the lungs, and the clearance from the lungs in the form of stochastically expanded biokinetic models. Movement of these particles in the respiratory tract have traditionally been modeled as reference/deterministic biokinetic models, which will be expanded using Monte Carlo sampling statistics and computational particle dynamics models to more broadly represent the contamination source and biokinetic retention in the Warfighter.

This project further entails design of a full-body triage scanner leveraging the phantom and biokinetic data, to employ correlated gamma-ray spectroscopic in-vivo assay with machine learning for source uptake reconstruction and estimate of residency and clearance in organs in the body.

The importance of this expanded model is that it further allows us to further determine how the contaminant particles move in the lungs and into the body, thereby telling us how lung injury affects the health of Warfighters.