Name
Title | ||
|---|---|---|
Measurement, Reconstruction, and Flow-Field Computation of the Human Pharynx With Application to Sleep Apnea. |
Abstract | ||
|---|---|---|
Repetitive closure of the upper airway characterizes obstructive sleep apnea. It disrupts sleep causing excessive daytime drowsiness and is linked to hypertension and cardiovascular disease. Previous studies simulating the underlying fluid mechanics are based upon geometries, time-averaged over the respiratory cycle, obtained usually via MRI or CT scans. Here, we generate an anatomically correct geometry from data captured in vivo by an endoscopic optical technique. This allows quantitative real-time imaging of the internal cross section with minimal invasiveness. The steady inhalation flow field is computed using a k-omega shear-stress transport (SST) turbulence model. Simulations reveal flow mechanisms that produce low-pressure regions on the sidewalls of the pharynx and on the soft palate within the pharyngeal section of minimum area. Soft-palate displacement and side-wall deformations further reduce the pressures in these regions, thus creating forces that would tend to narrow the airway. These phenomena suggest a mechanism for airway closure in the lateral direction as clinically observed. Correlations between pressure and airway deformation indicate that quantitative prediction of the low-pressure regions for an individual are possible. The present predictions warrant and can guide clinical investigation to confirm the phenomenology and its quantification, while the overall approach represents an advancement toward patient-specific modeling. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/TBME.2010.2052808 | IEEE Trans. Biomed. Engineering |
Keywords | Field | DocType |
Computational fluid dynamics, image processing, optical coherence tomography (OCT), sleep apnea, upper airway anatomy | Biomedical engineering,Obstructive sleep apnea,Soft palate,Anatomy,Sleep apnea,Computer science,Fluid mechanics,Turbulence,Artificial intelligence,Airway,Iterative reconstruction,Computer vision,Magnetic resonance imaging | Journal |
Volume | Issue | ISSN |
57 | 10 | 0018-9294 |
Citations | PageRank | References |
2 | 0.43 | 3 |
Authors | ||
11 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| A. D. Lucey | 1 | 8 | 1.93 |
| A. J. C. King | 2 | 35 | 7.29 |
| G. A. Tetlow | 3 | 2 | 0.43 |
| I-Jeng Wang | 4 | 277 | 31.46 |
| Julian J. Armstrong | 5 | 3 | 0.90 |
| Matthew S. Leigh | 6 | 3 | 0.90 |
| Alexandre Paduch | 7 | 3 | 0.90 |
| Jennifer H. Walsh | 8 | 3 | 0.90 |
| David D. Sampson | 9 | 3 | 1.91 |
| Peter R. Eastwood | 10 | 11 | 1.34 |
| David R. Hillman | 11 | 3 | 0.90 |