Upper airway reconstruction using long-range optical coherence tomography: Effects of airway curvature on airflow resistance.

Published

Journal Article

OBJECTIVES: Adenotonsillectomy (AT) is commonly used to treat upper airway obstruction in children, but selection of patients who will benefit most from AT is challenging. The need for diagnostic evaluation tools without sedation, radiation, or high costs has motivated the development of long-range optical coherence tomography (LR-OCT), providing real-time cross-sectional airway imaging during endoscopy. Since the endoscope channel location is not tracked in conventional LR-OCT, airway curvature must be estimated and may affect predicted airway resistance. The study objective was to assess effects of three realistic airway curvatures on predicted airway resistance using computational fluid dynamics (CFD) in LR-OCT reconstructions of the upper airways of pediatric patients, before and after AT. METHODS: Eight subjects (five males, three females, aged 4-9 years) were imaged using LR-OCT before and after AT during sedated endoscopy. Three-dimensional (3D) airway reconstructions included three airway curvatures. Steady-state, inspiratory airflow simulations were conducted under laminar conditions, along with turbulent simulations for one subject using the k-ω turbulence model. Airway resistance (pressure drop/flow) was compared using two-tailed Wilcoxon signed rank tests. RESULTS: Regardless of the airway curvatures, CFD findings corroborate a surgical end-goal with computed post-operative airway resistance significantly less than pre-operative (P < 0.01). The individual resistances did not vary significantly for different airway curvatures (P > 0.25). Resistances computed using turbulent simulations differed from laminar results by less than ∼5%. CONCLUSIONS: The results suggest that reconstruction of the upper airways from LR-OCT imaging data may not need to account for airway curvature to be predictive of surgical effects on airway resistance. Lasers Surg. Med. 51:150-160, 2019. © 2018 Wiley Periodicals, Inc.

Full Text

Duke Authors

Cited Authors

  • Kimbell, JS; Basu, S; Garcia, GJM; Frank-Ito, DO; Lazarow, F; Su, E; Protsenko, D; Chen, Z; Rhee, JS; Wong, BJ

Published Date

  • February 2019

Published In

Volume / Issue

  • 51 / 2

Start / End Page

  • 150 - 160

PubMed ID

  • 30051633

Pubmed Central ID

  • 30051633

Electronic International Standard Serial Number (EISSN)

  • 1096-9101

Digital Object Identifier (DOI)

  • 10.1002/lsm.23005

Language

  • eng

Conference Location

  • United States