Normative ranges of nasal airflow variables in healthy adults

Borojeni, Azadeh A.T.; Garcia, Guilherme J. M.; Moghaddam, Masoud Gh.; Frank‐Ito, Dennis O.; Kimbell, Julia S.; Laud, Purushottam W.; Koenig, Lisa J.; Rhee, John S.

doi:10.1007/s11548-019-02023-y

Cited by 55 publications

(45 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, there were also healthy geometries featuring lower resistances or smaller wall shear stress and velocity values than the average geometry. Furthermore, the values of lateral and total resistances as well as the minimal cross-sectional area calculated for the individual geometries as well as for the average geometry agree well with normative ranges of healthy nasal airflow that were identified by Borojeni et al based on a sample of 47 symptom-free subjects 13 .…”

Section: Figuresupporting

confidence: 82%

See 1 more Smart Citation

Characterization of the Airflow within an Average Geometry of the Healthy Human Nasal Cavity

Brüning

Hildebrandt

Heppt

et al. 2020

Sci Rep

View full text Add to dashboard Cite

This study's objective was the generation of a standardized geometry of the healthy nasal cavity. An average geometry of the healthy nasal cavity was generated using a statistical shape model based on 25 symptom-free subjects. Airflow within the average geometry and these geometries was calculated using fluid simulations. Integral measures of the nasal resistance, wall shear stresses (WSS) and velocities were calculated as well as cross-sectional areas (CSA). Furthermore, individual WSS and static pressure distributions were mapped onto the average geometry. The average geometry featured an overall more regular shape that resulted in less resistance, reduced WSS and velocities compared to the median of the 25 geometries. Spatial distributions of WSS and pressure of the average geometry agreed well compared to the average distributions of all individual geometries. The minimal CSA of the average geometry was larger than the median of all individual geometries (83.4 vs. 74.7 mm²). The airflow observed within the average geometry of the healthy nasal cavity did not equal the average airflow of the individual geometries. While differences observed for integral measures were notable, the calculated values for the average geometry lay within the distributions of the individual parameters. Spatially resolved parameters differed less prominently.The nose is the main passageway for respired air to flow from ambient to the lungs and vice versa. Air flowing through the nose is humidified, tempered and cleansed from particles, which could harm the intricate structures of the lungs. While the anatomy of the nose can easily be investigated from the outside using either a speculum or an endoscope, the nature of healthy nasal airflow is not yet fully understood. Nonetheless, there were extensive efforts as well as remarkable progress to better understand the complex airflow within the nose.While investigation of the airflow within the nasal cavity began with in-vitro experiments using either cadaver castings or upscaled models 1-3 , numerical simulation of nasal airflow became the quasi standard within the last decade and is now widely used 4-6 . Here, the patient-specific geometry of the nasal cavity is reconstructed using computed tomography (CT) scans.Recently, first studies were able to reveal correlations between numerically calculated flow parameters and the perceived nasal patency of a patient. Zhao et al. were able to show, that a significant correlation between cooling of the mucosal layer, a process that is associated with trigeminal function, is correlated with patency ratings of the nose 7,8 . In more recent studies, they were able to reveal differences in wall shear stress and heat flux between symptomatic and asymptomatic patients with septal perforations 9 and they were also able to show, that numerical simulations might help to understand complex relationships between surgical procedures and the development of empty nose syndrome 10 . Sanmiguel-Rojas et al. proposed another approach, where two non-dimensional par...

show abstract

Section: Figuresupporting

confidence: 82%

“…One issue that impedes progress in this field is the large heterogeneity of the human nasal cavity and the resulting aerodynamic variance even in healthy subjects 12,13 . The human nasal cavity is not only an extremely complex geometry, but its individual features differ grossly even if the main anatomical structure remains similar.…”

mentioning

confidence: 99%

Characterization of the Airflow within an Average Geometry of the Healthy Human Nasal Cavity

Brüning

Hildebrandt

Heppt

et al. 2020

Sci Rep

View full text Add to dashboard Cite

show abstract

“…With the increase in computational power, large numbers of nasal samples have been considered in recent studies to incorporate the impact of diversity in nasal anatomy but only on flow dynamics. These include both patient ( Liu et al, 2012 ; Zhao et al, 2014 ) and healthy subjects ( Borojeni et al, 2020 ; K. Wang, Denney, Morrison, & Vodyanoy, 2006 ; Zhao & Jiang, 2014 ). Golshahi and Hosseini ( Golshahi & Hosseini, 2018 ) studied total particle deposition in the nasal cavity of infants, children, and adults experimentally and clinically.…”

Section: Introductionmentioning

confidence: 99%

Regional deposition of the allergens and micro-aerosols in the healthy human nasal airways

Hazeri

Faramarzi

Sadrizadeh

et al. 2021

Journal of Aerosol Science

View full text Add to dashboard Cite

The nasal cavity is the inlet to the human respiratory system and is responsible for the olfactory sensation, filtering pollutant particulate matter, and humidifying the air. Many research studies have been performed to numerically predict allergens, contaminants, and/or drug particle deposition in the human nasal cavity; however, the majority of these investigations studied only one or a small number of nasal passages. In the present study, a series of Computed Tomography (CT) scan images of the nasal cavities from ten healthy subjects were collected and used to reconstruct accurate 3D models. All models were divided into twelve anatomical regions in order to study the transport and deposition features of different regions of the nasal cavity with specific functions. The flow field and micro-particle transport equations were solved, and the total and regional particle deposition fractions were evaluated for the rest and low activity breathing conditions. The results show that there are large variations among different subjects. The standard deviation of the total deposition fraction in the nasal cavities was the highest for

show abstract

“…To facilitate clinical applications, the normative ranges of these variables were identified from 47 healthy adults. 14 Similarly, Frank-Ito et al 15 developed a stepwise virtual surgery method to optimize surgical outcomes for the treatment of nasal airway obstruction and demonstrated its promising usage in treatment planning in two septoplasty patients. Procedures for snore diagnosis are still limited to specialized sleep laboratories with patients staying overnight, which are costly and time-consuming.…”

Section: Introductionmentioning

confidence: 99%

“…The success of such tools to a large degree depends on the knowledge of how measurable symptoms like breathing sounds relate to underlying airway abnormities. Borojeni et al 14 correlated the subjective sensation of nasal patency to several airflow‐related variables such as nasal resistance, heat flux, and surface area of mucosa cooling. To facilitate clinical applications, the normative ranges of these variables were identified from 47 healthy adults 14 .…”

Section: Introductionmentioning

confidence: 99%

Extracting signature responses from respiratory flows: Low‐dimensional analyses on Direct Numerical Simulation‐predicted wakes of a flapping uvula

Wang

April

et al. 2020

Numer Methods Biomed Eng

View full text Add to dashboard Cite

Uvula-induced snoring and associated obstructive sleep apnea is a complex phenomenon characterized by vibrating structures and highly transient vortex dynamics. This study aimed to extract signature features of uvula wake flows of different pathological origins and develop a linear reduced-order surrogate model for flow control. Six airway models were developed with two uvula kinematics and three pharynx constriction levels. A direct numerical simulation (DNS) flow solver based on the immersed boundary method was utilized to resolve the wake flows induced by the flapping uvula. Key spatial and temporal responses of the flow to uvula kinematics and pharynx constriction were investigated using continuous wavelet transform (CWT), proper orthogonal decomposition (POD), and dynamic mode decomposition (DMD). Results showed highly complex patterns in flow topologies. CWT analysis revealed multiscale correlations in both time and space between the flapping uvular and wake flows. POD analysis successfully separated the flows among the six models by projecting the datasets in the vector space spanned by the first three eigenmodes. Perceivable differences were also captured in the time evolution of the DMD modes among the six models. A linear reduced-order surrogate model was constructed from the predominant eigenmodes obtained from the DMD analysis and predicted vortex patterns from this surrogate model agreed well with the corresponding DNS simulations. The computational and analytical platform presented in this study could bring a variety of applications in breathing-related disorders and beyond. The computational efficiency of surrogate modeling makes it well suited for flow control, forecasting, and uncertainty analyses.

show abstract

Normative ranges of nasal airflow variables in healthy adults

Cited by 55 publications

References 64 publications

Characterization of the Airflow within an Average Geometry of the Healthy Human Nasal Cavity

Characterization of the Airflow within an Average Geometry of the Healthy Human Nasal Cavity

Regional deposition of the allergens and micro-aerosols in the healthy human nasal airways

Extracting signature responses from respiratory flows: Low‐dimensional analyses on Direct Numerical Simulation‐predicted wakes of a flapping uvula

Contact Info

Product

Resources

About