Radiation Dosimetry of Inhaled Radioactive Aerosols: CFPD and MCNP Transport Simulations of Radionuclides in the Lung

Detecting radioactive particles in complex environmental samples using real-time autoradiography

Radioactive particles often contain very high radioactivity concentrations and are widespread. They pose a potential risk to human health and the environment. Their detection, quantification, and characterization are crucial if we are to understand their impact. Here, we present the use of a real-time autoradiography gaseous detector (using parallel ionization multiplier) to expedite and improve the accuracy of radioactive particle screening in complex environmental samples. First, standard particles were used to assess the detector capabilities (spatial resolution, spectrometry, and artefact contributions), then, we applied the technique to more complex and environmentally relevant samples. The real-time autoradiography technique provides data with a spatial resolution (≲100 µm) suitable for particle analysis in complex samples. Further, it can differentiate between particles predominantly emitting alpha and beta radiation. Here, the technique is applied to radioactive cesium-rich microparticles collected from the Fukushima Daiichi nuclear exclusion zone, showing their accurate detection, and demonstrating the viability of real-time autoradiography in environmental scenarios. Indeed, for more complex samples (radioactive particles in a less radioactive heterogeneous background mix of minerals), the technique permits relatively high selectivity for radioactive particle screening (up to 61.2% success rate) with low false positive percentages (~ 1%).

Improved Radio-Cesium Detection Using Quantitative Real-Time Autoradiography

Cesium-134 and -137 are prevalent, long-lived, radio-toxic contaminants released into the environment during nuclear accidents. Large quantities of insoluble, respirable Cs-bearing microparticles (CsMPs) were released into the environment during the Fukushima Daiichi nuclear accident. Monitoring for CsMPs in environmental samples is essential to understand the impact of nuclear accidents. The current detection method used to screen for CsMPs (phosphor screen autoradiography) is slow and inefficient. We propose an improved method: real-time autoradiography that uses parallel ionization multiplier gaseous detectors. This technique permits spatially resolved measurement of radioactivity while providing spectrometric data from spatially heterogeneous samples-a potential step-change technique for use after nuclear accidents for forensic analysis. With our detector configuration, the minimum detectable activities are sufficiently low for detecting CsMPs. Further, for environmental samples, sample thickness does not detrimentally affect detector signal quality. The detector can measure and resolve individual radioactive particles ≥465 μm apart. Real-time autoradiography is a promising tool for radioactive particle detection.

Public Health Decision Making in the Case of the Use of a Nuclear Weapon

The current geopolitical situation and the war on Ukraine's territory generate questions about the possible use of a nuclear weapon and create the need to refresh emergency protective plans for the population. Ensuring the protection of public health is a national responsibility, but the problem is of international size and global scale. Radiological or nuclear disasters need suitable decision making at the right time, which determine large effective radiation protection activities to ensure public health is protected, reduce fatalities, radiation disease, and other effects. In this study, a simulation of a single nuclear weapon detonation with an explosion yield of 0.3 and 1 Mt was applied for a hypothetical location, to indicate the required decision making and the need to trigger protocols for the protection of the population. The simulated explosion was located in a city center, in a European country, for the estimation of the size of the effects of the explosion and its consequences for public health. Based on the simulation results and knowledge obtained from historical nuclear events, practical suggestions, discussion, a review of the recommendations was conducted, exacerbated by the time constraints of a public health emergency. Making science-based decisions should encompass clear procedures with specific activities triggered immediately based on confirmed information, acquired from active or/and passive warning systems and radiometric specific analysis provided by authorized laboratories. This study has the potential to support the preparedness of decision makers in the event of a disaster or crisis-related emergency for population health management and summarizes the strengths and weaknesses of the current ability to respond.

Health Effects of Particulate Uranium Exposure

Uranium contamination has become a nonnegligible global health problem. Inhalation of particulate uranium is one of the predominant routes of occupational and environmental exposure. Uranium particle is a complex two-phase flow of matter that is both particulate and flowable. This particular physicochemical property may alter its biological activity. Epidemiological studies from occupationally exposed populations in the uranium industry have concluded that there is a possible association between lung cancer risk and uranium exposure, while the evidence for the risk of other tumors is not sufficient. The toxicological effects of particulate uranium exposure to animals have been shown in laboratory tests to focus on respiratory and central nervous system damage. Fibrosis and tumors can occur in the lung tissue of the respiratory tract. Uranium particles can also induce a concentration-dependent increase in cytotoxicity, targeting mitochondria. The understanding of the health risks and potential toxicological mechanisms of particulate uranium contamination is still at a preliminary stage. The diversity of particle parameters has limited the in-depth exploration. This review summarizes the current evidence on the toxicology of particulate uranium and highlights the knowledge gaps and research prospects.

Human exposure to metals in consumer-focused fused filament fabrication (FFF)/ 3D printing processes

Fused filament fabrication (FFF) or 3D printing is a growing technology used in industry, cottage industry and for consumer applications. Low-cost 3D printing devices have become increasingly popular among children and teens. Consequently, 3D printers are increasingly common in households, schools, and libraries. Because the operation of 3D printers is associated with the release of inhalable particles and volatile organic compounds (VOCs), there are concerns of possible health implications, particularly for use in schools and residential environments that may not have adequate ventilation such as classrooms bedrooms and garages, etc. Along with the growing consumer market for low-cost printers and printer pens, there is also an expanding market for a range of specialty filaments with additives such as inorganic colorants, metal particles and nanomaterials as well as metal-containing flame retardants, antioxidants, heat stabilizers and catalysts. Inhalation of particulate-associated metals may represent a health risk depending on both the metal and internal dose to the respiratory tract. Little has been reported, however, about the presence, speciation, and source of metals in the emissions; or likewise the effect of metals on emission processes and toxicological implications of these 3D printer generated emissions. This report evaluates various issues including the following: metals in feedstock with a focus on filament characteristics and function of metals; the effect of metals on the emissions and metals detected in emissions; printer emissions, particle formation, transport, and transformation; exposure and translation to internal dose; and potential toxicity on inhaled dose. Finally, data gaps and potential areas of future research are discussed within these contexts.

A comparison of CFPD, compartment, and uniform distribution models for radiation dosimetry of radionuclides in the lung

Radioactive aerosols that arise from natural sources and nuclear accidents can be a long-term hazard to human health. Despite the heterogeneous particle deposition in the respiratory tract, uniform aerosol doses have long been assumed in respiratory radiation dosimetry predictions, such as in the compartment and uniform distribution models. It is unclear how these deposition patterns affect internal radiation doses, which are critical in the health assessment of radioactive hazards. This work seeks to quantify the radio-dosimetry sensitivity to initial deposition patterns by comparing computational and compartment/uniform models. A new approach was developed to implement the compartment model into voxel phantoms (e.g. VIP-man) for radiation dosimetry. The calculated radiation fluence, energy deposition density and organ doses were compared to those obtained from coupling computational fluid-particle dynamics (CFPD) with Monte Carlo radiation transport and to those obtained from uniform source distribution approximation. The results show that the source particle distribution within the respiratory system substantially influences the radiation dosimetry distribution. The compartment and uniform models underestimated aerosol deposition in the crania ridge, leading to lower doses in the trachea and surrounding organs. For 0.5 MeV gammas, the CFPD-Monte Carlo N-particle (MCNP) model predicted a tracheal dose twice that of the compartment model and four times the uniform model. For 1 MeV betas, the CFPD-MCNP-predicted tracheal dose is 2.6 times that of the compartment model and 14 times the uniform model. Compared to the compartment/uniform models, the CFPD approach predicted a 50% lower beta dose in the lung but higher beta doses in the heart (six times), liver (four times) and stomach (2.5 times). It is suggested that including compartments for the lung periphery and tracheal carina ridge may improve the dosimetry accuracy of compartment models.

Deciphering Exhaled Aerosol Fingerprints for Early Diagnosis and Personalized Therapeutics of Obstructive Respiratory Diseases in Small Airways

Respiratory diseases often show no apparent symptoms at their early stages and are usually diagnosed when permanent damages have been made to the lungs. A major site of lung pathogenesis is the small airways, which make it highly challenging to detect using current techniques due to the diseases’ location (inaccessibility to biopsy) and size (below normal CT/MRI resolution). In this review, we present a new method for lung disease detection and treatment in small airways based on exhaled aerosols, whose patterns are uniquely related to the health of the lungs. Proof-of-concept studies are first presented in idealized lung geometries. We subsequently describe the recent developments in feature extraction and classification of the exhaled aerosol images to establish the relationship between the images and the underlying airway remodeling. Different feature extraction algorithms (aerosol density, fractal dimension, principal mode analysis, and dynamic mode decomposition) and machine learning approaches (support vector machine, random forest, and convolutional neural network) are elaborated upon. Finally, future studies and frequent questions related to clinical applications of the proposed aerosol breath testing are discussed from the authors’ perspective. The proposed breath testing has clinical advantages over conventional approaches, such as easy-to-perform, non-invasive, providing real-time feedback, and is promising in detecting symptomless lung diseases at early stages.

Liquid Film Translocation Significantly Enhances Nasal Spray Delivery to Olfactory Region: A Numerical Simulation Study

Previous in vivo and ex vivo studies have tested nasal sprays with varying head positions to enhance the olfactory delivery; however, such studies often suffered from a lack of quantitative dosimetry in the target region, which relied on the observer’s subjective perception of color changes in the endoscopy images. The objective of this study is to test the feasibility of gravitationally driven droplet translocation numerically to enhance the nasal spray dosages in the olfactory region and quantify the intranasal dose distribution in the regions of interest. A computational nasal spray testing platform was developed that included a nasal spray releasing model, an airflow-droplet transport model, and an Eulerian wall film formation/translocation model. The effects of both device-related and administration-related variables on the initial olfactory deposition were studied, including droplet size, velocity, plume angle, spray release position, and orientation. The liquid film formation and translocation after nasal spray applications were simulated for both a standard and a newly proposed delivery system. Results show that the initial droplet deposition in the olfactory region is highly sensitive to the spray plume angle. For the given nasal cavity with a vertex-to-floor head position, a plume angle of 10° with a device orientation of 45° to the nostril delivered the optimal dose to the olfactory region. Liquid wall film translocation enhanced the olfactory dosage by ninefold, compared to the initial olfactory dose, for both the baseline and optimized delivery systems. The optimized delivery system delivered 6.2% of applied sprays to the olfactory region and significantly reduced drug losses in the vestibule. Rheological properties of spray formulations can be explored to harness further the benefits of liquid film translocation in targeted intranasal deliveries.

Septal destruction enhances chaotic mixing and increases cellular doses of nanoparticles in emphysematous acinus

One hallmark of emphysema is the breakdown of inter-alveolar septal walls in pulmonary acini. How the acinar dosimetry of environmental aerosols varies at different stages of emphysema remains unclear; this is specifically pertinent to users of tobacco products, which is the leading cause of emphysema. The objective of this study is to systematically assess the impacts of septal destruction on the behavior and fate of nanoparticles (1–800 nm) in a pyramid-shaped sub-acinar model consisting of 496 alveoli. Four diseased geometry variants were created by gradually removing the septal walls from the base model. Particle motions within the acinar region were tracked for particles raging 1–800 nm at four emphysema stages using a well-tested Lagrangian tracking model. Both spatial profile and temporal variation of particle deposition were predicted in healthy and diseased sub-acinar geometries on both a total and regional basis. Results show large differences in airflow and particle dynamics among different emphysema stages. Large differences in particle dynamics are also observed among different particle sizes, with one order of magnitude’s variation in the speeds of particles of 1, 10, and 200 nm. The destruction of septal walls also changed the deposition mechanisms, shifting from connective diffusion to chaotic mixing with emphysema progression. The sub-acinar dosimetry became less sensitive to particle size variation with more septal destructions. The lowest retention rate was found at 200–500 nm in the healthy sub-acinar geometry, but at 800 nm in all emphysematous models considered. The acinus-averaged dose for nanoparticles (1–800 nm) increases with aggravating septal destructions, indicating an even higher risk to the acinus at later emphysema stages.

SARS COV-2 virus-laden droplets coughed from deep lungs: Numerical quantification in a single-path whole respiratory tract geometry

When an infected person coughs, many virus-laden droplets will be exhaled out of the mouth. Droplets from deep lungs are especially infectious because the alveoli are the major sites of coronavirus replication. However, their exhalation fraction, size distribution, and exiting speeds are unclear. This study investigated the behavior and fate of respiratory droplets (0.1-4 μm) during coughs in a single-path respiratory tract model extending from terminal alveoli to mouth opening. An experimentally measured cough waveform was used to control the alveolar wall motions and the flow boundary conditions at lung branches from G2 to G18. The mouth opening was modeled after the image of a coughing subject captured using a high-speed camera. A well-tested k-ω turbulence model and Lagrangian particle tracking algorithm were applied to simulate cough flow evolutions and droplet dynamics under four cough depths, i.e., tidal volume ratio (TVR) = 0.13, 0.20. 0.32, and 0.42. The results show that 2-μm droplets have the highest exhalation fraction, regardless of cough depths. A nonlinear relationship exists between the droplet exhalation fraction and cough depth due to a complex deposition mechanism confounded by multiscale airway passages, multiregime flows, and drastic transient flow effects. The highest exhalation fraction is 1.6% at the normal cough depth (TVR = 0.32), with a mean exiting speed of 20 m/s. The finding that most exhaled droplets from deep lungs are 2 μm highlights the need for more effective facemasks in blocking 2-μm droplets and smaller both in infectious source control and self-protection from airborne virus-laden droplets.

Numerical investigation of aerosol transport in a classroom with relevance to COVID-19

The present study investigates aerosol transport and surface deposition in a realistic classroom environment using computational fluid-particle dynamics simulations. Effects of particle size, aerosol source location, glass barriers, and windows are explored. While aerosol transport in air exhibits some stochasticity, it is found that a significant fraction (24%-50%) of particles smaller than 15 µm exit the system within 15 min through the air conditioning system. Particles larger than 20 µm almost entirely deposit on the ground, desks, and nearby surfaces in the room. Source location strongly influences the trajectory and deposition distribution of the exhaled aerosol particles and affects the effectiveness of mitigation measures such as glass barriers. Glass barriers are found to reduce the aerosol transmission of 1 µm particles from the source individual to others separated by at least 2.4 m by ∼92%. By opening windows, the particle exit fraction can be increased by ∼38% compared to the case with closed windows and reduces aerosol deposition on people in the room. On average, ∼69% of 1 µm particles exit the system when the windows are open.