Aerosol Bolus Dispersion and Aerosol-Derived Airway Morphometry: Assessment of Lung Pathology and Response to Therapy, Part 2

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.

Charting the human respiratory tract with airborne nanoparticles: evaluation of the Airspace Dimension Assessment technique

Airspace Dimension Assessment (AiDA) is a technique to assess lung morphology by measuring lung deposition of inhaled nanoparticles. Nanoparticles deposit in the lungs predominately by diffusion, and average diffusion distances, corresponding to effective airspace radii ( rAiDA), can be inferred from measurements of particle recovery after varied breath holds. Also, particle recovery after a 0-s breath hold ( R0) may hold information about the small conducting airways. This study investigates rAiDA at different volumetric sample depths in the lungs of healthy subjects. Measurements were performed with 50-nm polystyrene nanospheres on 19 healthy subjects aged 17–67 yr. Volumetric sample depths ranged from 200 to 5,000 ml and breath-hold times from 5 to 20 s. At the examined volumetric sample depths, rAiDA values ranged from ~200–600 μm, which correspond to dimensions of the bronchiolar and the gas-exchanging regions of the lungs. R0 decreased with volumetric sample depth and showed more intersubject variation than rAiDA. Correlations were found between the AiDA parameters, anthropometry, and lung function tests, but not between rAiDA and R0. For repeated measurements on 3 subjects over an 18-mo period, rAiDA varied on average within ± 7 μm (± 2.4%). The results indicate that AiDA has potential as an efficient new in vivo technique to assess individual lung properties. The information obtained by such measurements may be of value for lung diagnostics, especially for the distal lungs, which are challenging to examine directly by other means.

NEW & NOTEWORTHY This is the first study to measure effective airspace radii ( rAiDA) at volumetric sample depths 200–5,000 ml in healthy subjects by Airspace Dimension Assessment (AiDA). Observed rAiDA were 200–600 μm, which corresponds to airspaces for the bronchiolar and the gas-exchanging regions around airway generation 14–17. rAiDA correlated with lung function tests and anthropometry. Measurements of rAiDA on 3 subjects over 11–18 mo were within ± 7 μm.

Altered deposition of inhaled nanoparticles in subjects with chronic obstructive pulmonary disease

Background

Respiratory tract deposition of airborne particles is a key link to understand their health impact. Experimental data are limited for vulnerable groups such as individuals with respiratory diseases. The aim of this study is to investigate the differences in lung deposition of nanoparticles in the distal lung for healthy subjects and subjects with respiratory disease.

Methods

Lung deposition of nanoparticles (50 and 100 nm) was measured after a 10 s breath-hold for three groups: healthy never-smoking subjects (n = 17), asymptomatic (active and former) smokers (n = 15) and subjects with chronic obstructive pulmonary disease (n = 16). Measurements were made at 1300 mL and 1800 mL volumetric lung depth. Each subject also underwent conventional lung function tests, including post bronchodilator FEV₁, VC, and diffusing capacity for carbon monoxide, D_L,CO. Patients with previously diagnosed respiratory disease underwent a CT-scan of the lungs. Particle lung deposition fraction, was compared between the groups and with conventional lung function tests.

Results

We found that the deposition fraction was significantly lower for subjects with emphysema compared to the other subjects (p = 0.001–0.01), but no significant differences were found between healthy never-smokers and smokers. Furthermore, the particle deposition correlated with pulmonary function tests, FEV_1%Pred (p < 0.05), FEV₁/VC_%Pred (p < 0.01) and D_L,CO (p < 0.0005) when all subjects were included. Furthermore, for subjects with emphysema, deposition fraction correlated strongly with D_L,CO (Pearson’s r = 0.80–0.85, p < 0.002) while this correlation was not found within the other groups.

Conclusions

Lower deposition fraction was observed for emphysematous subjects and this can be explained by enlarged distal airspaces in the lungs. As expected, deposition increases for smaller particles and deeper inhalation. The observed results have implications for exposure assessment of air pollution and dosimetry of aerosol-based drug delivery of nanoparticles.

A new method for measuring lung deposition efficiency of airborne nanoparticles in a single breath

Assessment of respiratory tract deposition of nanoparticles is a key link to understanding their health impacts. An instrument was developed to measure respiratory tract deposition of nanoparticles in a single breath. Monodisperse nanoparticles are generated, inhaled and sampled from a determined volumetric lung depth after a controlled residence time in the lung. The instrument was characterized for sensitivity to inter-subject variability, particle size (22, 50, 75 and 100 nm) and breath-holding time (3–20 s) in a group of seven healthy subjects. The measured particle recovery had an inter-subject variability 26–50 times larger than the measurement uncertainty and the results for various particle sizes and breath-holding times were in accordance with the theory for Brownian diffusion and values calculated from the Multiple-Path Particle Dosimetry model. The recovery was found to be determined by residence time and particle size, while respiratory flow-rate had minor importance in the studied range 1–10 L/s. The instrument will be used to investigate deposition of nanoparticles in patients with respiratory disease. The fast and precise measurement allows for both diagnostic applications, where the disease may be identified based on particle recovery, and for studies with controlled delivery of aerosol-based nanomedicine to specific regions of the lungs.

Exhaled aerosol pattern discloses lung structural abnormality: a sensitivity study using computational modeling and fractal analysis

BACKGROUND

Exhaled aerosol patterns, also called aerosol fingerprints, provide clues to the health of the lung and can be used to detect disease-modified airway structures. The key is how to decode the exhaled aerosol fingerprints and retrieve the lung structural information for a non-invasive identification of respiratory diseases.

OBJECTIVE AND METHODS

In this study, a CFD-fractal analysis method was developed to quantify exhaled aerosol fingerprints and applied it to one benign and three malign conditions: a tracheal carina tumor, a bronchial tumor, and asthma. Respirations of tracer aerosols of 1 µm at a flow rate of 30 L/min were simulated, with exhaled distributions recorded at the mouth. Large eddy simulations and a Lagrangian tracking approach were used to simulate respiratory airflows and aerosol dynamics. Aerosol morphometric measures such as concentration disparity, spatial distributions, and fractal analysis were applied to distinguish various exhaled aerosol patterns.

FINDINGS

Utilizing physiology-based modeling, we demonstrated substantial differences in exhaled aerosol distributions among normal and pathological airways, which were suggestive of the disease location and extent. With fractal analysis, we also demonstrated that exhaled aerosol patterns exhibited fractal behavior in both the entire image and selected regions of interest. Each exhaled aerosol fingerprint exhibited distinct pattern parameters such as spatial probability, fractal dimension, lacunarity, and multifractal spectrum. Furthermore, a correlation of the diseased location and exhaled aerosol spatial distribution was established for asthma.

CONCLUSION

Aerosol-fingerprint-based breath tests disclose clues about the site and severity of lung diseases and appear to be sensitive enough to be a practical tool for diagnosis and prognosis of respiratory diseases with structural abnormalities.

[Monte-Carlo-Model for the aerosol bolus dispersion in the human lung--part 2: model predictions for the diseased lung]

After a mathematical extension of the existing model for the theoretical description of the aerosol bolus dispersion, the behavior of particle pulses in diseased lung structures was simulated. The geometry usedJbr healthy lungs was modified in two aspects: First, a modelling of possible airway obstructions, which usually occur in patients with chronic bronchitis, chronic asthma or cystic fibrosis, was carried out and, second, a theoretical approximation of the emphysema, being observed in lungs of smokers, but also as an accompanying phenomenon in obstructive diseases, was established. According to the modified model, in lungs with airway obstructions the exhaled bolus exhibited a decreased dispersion with respect to healthy subjects, whereas in emphysematous lungs the respective half-width of the peak was increased. Standard deviation and skewness of the bolus were similarly influenced by the modified lung architecture. A combination of airway obstruction and emphysema caused an extensive compensation of individual dispersion effects, complicating a secure distinction from the healthy lung. According to the model, a special diagnostic value may be assigned to the bolus deposition, showing significant deviations from the normal case for all simulated diseases.

Noninvasive diagnosis of emphysema. Aerosol morphometry and aerosol bolus dispersion in comparison to HRCT

Aerosol-derived airway morphometry (ADAM) and aerosol bolus dispersion (ABD) test are altered in patients with emphysema. We examined the diagnostic power of these aerosol methods in comparison with the noninvasive "gold-standard" HRCT in 50 consecutive patients with various lung diseases. The severity of airflow limitation was mild to moderate in the group of patients without emphysema and moderate to severe in the group of patients with HRCT-confirmed emphysema (FEV(1), 78 +/- 23% pred versus 53 +/- 33% pred; p < 0. 001). Among all lung function parameters under consideration ADAM showed the highest sensitivity and specificity for separating patients with emphysema from those without emphysema (area under the operating characteristics curve: p(ROC), 0.92), followed by ABD (p(ROC), 0.90), a marker for ventilation inhomogeneities. In patients with HRCT-confirmed macroscopic emphysema, peripheral air-space dimensions (EAD) at a relative volumetric lung depth V(pr) of 0.20 measured by ADAM were 155% larger, and bolus dispersion (ABD) at a lung depth of V(p) 600 ml was 53% larger than those observed in patients with other lung diseases (EAD = 0.84 +/- 0.53 mm versus 0.33 +/- 0.10 mm, p < 0.0001; ABD = 706 +/- 154 cm(3) versus 462 +/- 109 cm(3); p < 0.0001). EAD showed a significant correlation with the HRCT visual score (r = 0.78, p = 0.01). ABD showed weak significant correlations with all HRCT parameters under consideration (visual score, pixel density, mean lung density) (r = 0.45 to 0.66; p < 0.05). ADAM and ABD are powerful tools for the noninvasive diagnosis of macroscopic emphysema.