The effect of oral and nasal breathing on the deposition of inhaled particles in upper and tracheobronchial airways

Abstract

The inhalation route has a substantial influence on the fate of inhaled particles. An outbreak of infectious diseases such as COVID-19, influenza or tuberculosis depends on the site of deposition of the inhaled pathogens. But the knowledge of respiratory deposition is important also for occupational safety or targeted delivery of inhaled pharmaceuticals. Simulations utilizing computational fluid dynamics are becoming available to a wide spectrum of users and they can undoubtedly bring detailed predictions of regional deposition of particles. However, if those simulations are to be trusted, they must be validated by experimental data. This article presents simulations and experiments performed on a geometry of airways which is available to other users and thus those results can be used for intercomparison between different research groups. In particular, three hypotheses were tested. First: Oral breathing and combined breathing are equivalent in terms of particle deposition in TB airways, as the pressure resistance of the nasal cavity is so high that the inhaled aerosol flows mostly through the oral cavity in both cases. Second: The influence of the inhalation route (nasal, oral or combined) on the regional distribution of the deposited particles downstream of the trachea is negligible. Third: Simulations can accurately and credibly predict deposition hotspots. The maximum spatial resolution of predicted deposition achievable by current methods was searched for. The simulations were performed using large-eddy simulation, the flow measurements were done by laser Doppler anemometry and the deposition has been measured by positron emission tomography in a realistic replica of human airways. Limitations and sources of uncertainties of the experimental methods were identified. The results confirmed that the high-pressure resistance of the nasal cavity leads to practically identical velocity profiles, even above the glottis for the mouth, and combined mouth and nose breathing. The distribution of deposited particles downstream of the trachea was not influenced by the inhalation route. The carina of the first bifurcation was not among the main deposition hotspots regardless of the inhalation route or flow rate. On the other hand, the deposition hotspots were identified by both CFD and experiments in the second bifurcation in both lungs, and to a lesser extent also in both the third bifurcations in the left lung.

Keywords: Airways; Computational fluid mechanics; Deposition hotspots; Flow; Laser Doppler anemometry; Lungs; Numerical simulations; Particle deposition; Positron emission tomography.

Fig. 1

Visualization of the airway replica for deposition (a) and flow (b) measurements, and a scheme of the segment numbers (c). The face mask is not depicted.

Fig. 2

Details of the computational mesh generated on model geometry. The number in each respective cross-section indicates the used amplification factor. Settings of the flow simulations.

Fig. 3

A scheme of the test rig for flow velocity measurement with LDA and the airway replica. LDA configuration, data acquisition and processing.

Fig. 4

A scheme of the test rig for the measurement of particle deposition.

Fig. 5

The scheme of measuring lines in the airway geometry, and visualization of the central sagittal plane and the coronal plane with an indication of the cross-section positions.

Fig. 6

The mean axial velocity (left) and turbulence intensity (right) profiles in consequent positions of the central sagittal plane in the upper airways for nasal, oral and combined inhalation at 30 and 60 L/min flow rates. Negative values of the D_N stand for anterior direction and positive for posterior.

Fig. 7

The mean axial velocity (left) and turbulence intensity (right) profiles in cross-sections of the trachea (CA), the right main bronchus (CrB) and bronchus intermedius (CC) of the coronal plane in the TB airways for nasal, oral and combined inhalation at 30 and 60 L/min flowrates. Negative values of the D_N stand for lateral direction and positive for medial.

Fig. 8

The course of turbulence kinetic energy (TKE) along the centreline passing from oropharynx through the airway with the largest diameter in the left and right lung down to 7th generation of branching for 30 and 60 L/min.

Fig. 9

Comparison of deposition fraction (DF) measured experimentally and calculated by CFD for a flow rate of 30 L/min and all three inhalation routes.

Fig. 10

Comparison of deposition fraction (DF) measured experimentally and calculated by CFD for a flow rate of 60 L/min and all three inhalation routes.

Fig. 11

Deposition efficiency (DE) as a function of the Stokes number. Current results are compared to previously published data.

Fig. 12

Deposition hotspots scanned by PET in coronal (a), sagittal (b), and transaxial (c) slices, and comparison with CFD simulated deposition (d) for MB and 60 L/min. The yellow lines indicate positions of slices. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 13

Comparison of size-segregated deposition fraction (DF) calculated by CFD for the flow rate of 30 L/min, combined breathing route, with experimental data for polydisperse aerosol with CMAD 2.8 μm.