Search

The energy needed to drive airflow through the trachea normally constitutes a minor component of the work of breathing. However, with progressive tracheal compression, patient subjective symptoms can include severe breathing difficulties. Many patients suffer multiple respiratory co-morbidities and so it is important to assess compression effects when evaluating the need for surgery. This work describes the use of computational prediction to determine airflow resistance in compressed tracheal geometries reconstructed from a series of CT scans. Using energy flux analysis, the regions that contribute the most to airway resistance during inhalation are identified. The principal such region is where flow emerging from the zone of maximum constriction undergoes breakup and turbulent mixing. Secondary regions are also found below the tongue base and around the glottis, with overall airway resistance scaling nearly quadratically with flow rate. Since the anatomical extent of the imaged airway varied between scans-as commonly occurs with clinical data and when assessing reported differences between research studies-the effect of sub-glottic inflow truncation is considered. Analysis shows truncation alters the location of jet breakup and weakly influences the pattern of pressure recovery. Tests also show that placing a simple artificial glottis in the inflow to a truncated model can replicate patterns of energy loss in more extensive models, suggesting a means to assess sensitivity to domain truncation in tracheal airflow simulations.

This paper describes the simulation of airflow in human nasal airways using voxel-based modeling characterized by robust, automatic, and objective grid generation. Computed tomography scans of a healthy adult nose are used to reconstruct 3D virtual models of the nasal airways. Voxel-based simulations of restful inspiratory flow are then performed using various mesh sizes to determine the level of granularity required to adequately resolve the airflow. For meshes with close voxel spacings, the model successfully reconstructs the nasal structure and predicts the overall pressure drop through the nasal cavity.

The dynamics of unsteady flow in the human large airways during a rapid inhalation were investigated using highly detailed large-scale computational fluid dynamics on a subject-specific geometry. The simulations were performed to resolve all the spatial and temporal scales of the flow, thanks to the use of massive computational resources. A highly parallel finite element code was used, running on two supercomputers, solving the transient incompressible Navier-Stokes equations on unstructured meshes. Given that the finest mesh contained 350 million elements, the study sets a precedent for large-scale simulations of the respiratory system, proposing an analysis strategy for mean flow, fluctuations and wall shear stresses on a rapid and short inhalation (a so-called sniff). The geometry used encompasses the exterior face and the airways from the nasal cavity, through the trachea and up to the third lung bifurcation; it was derived from a contrast-enhanced computed tomography (CT) scan of a 48-year-old male. The transient inflow produces complex flows over a wide range of Reynolds numbers (Re). Thanks to the high fidelity simulations, many features involving the flow transition were observed, with the level of turbulence clearly higher in the throat than in the nose. Spectral analysis revealed turbulent characteristics persisting downstream of the glottis, and were captured even with a medium mesh resolution. However a fine mesh resolution was found necessary in the nasal cavity to observe transitional features. This work indicates the potential of large-scale simulations to further understanding of airway physiological mechanics, which is essential to guide clinical diagnosis; better understanding of the flow also has implications for the design of interventions such as aerosol drug delivery., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Background: This study quantifies the time-varying flow rate during inspiration at rest and in sniffing, both predecongestion and postdecongestion. It aims to provide a better understanding of nasal airflow mechanics, for application to the physiological modeling of nasal respiration and to therapeutic drug delivery., Methods: The temporal profiles of nasal inspiration were measured at high fidelity in 14 healthy individuals using simultaneous bilateral hot-wire anemometry. Peak nasal inspiratory flow (PNIF) rate, acoustic rhinometry (AR), and the sinonasal outcome test (SNOT) provided complementary clinical measurements. The impact of decongestion was also investigated., Results: In the initial phase of inspiration, a rapid rise in flow rate was observed. Flow first exceeded 150 mL/second in either passage within a median time of approximately 120 ms for inspiration at rest and approximately 60 ms in sniffing (∼20 ms in the fastest sniffs). The mean sustained flow rate attained and the overall period of each measured inspiratory profile were analyzed. AR showed a significant change in nasal volume with decongestion, although these change were not manifest in the temporal profiles of inspiratory flow (barring a weak effect associated with the most vigorous sniffs)., Conclusion: Novel methods were applied to investigate the temporal profiles of nasal inspiration. Characteristic features of the profile were identified and found to be significantly different between inspiration at rest and sniffing. Decongestion was found to have little effect on the temporal profiles for the flow regimes studied., (Copyright © 2011 American Rhinologic Society-American Academy of Otolaryngic Allergy, LLC.)