Computational fluid dynamics endpoints for assessment of adenotonsillectomy outcome in obese children with obstructive sleep apnea syndrome
- PMID: 24840295
- PMCID: PMC4057952
- DOI: 10.1016/j.jbiomech.2014.03.023
Computational fluid dynamics endpoints for assessment of adenotonsillectomy outcome in obese children with obstructive sleep apnea syndrome
Abstract
Background: Improvements in obstructive sleep apnea syndrome (OSAS) severity may be associated with improved pharyngeal fluid mechanics following adenotonsillectomy (AT). The study objective is to use image-based computational fluid dynamics (CFD) to model changes in pharyngeal pressures after AT, in obese children with OSAS and adenotonsillar hypertrophy.
Methods: Three-dimensional models of the upper airway from nares to trachea, before and after AT, were derived from magnetic resonance images obtained during wakefulness, in a cohort of 10 obese children with OSAS. Velocity, pressure, and turbulence fields during peak tidal inspiratory flow were computed using commercial software. CFD endpoints were correlated with polysomnography endpoints before and after AT using Spearman׳s rank correlation (rs).
Results: Apnea hypopnea index (AHI) decreases after AT was strongly correlated with reduction in maximum pressure drop (dPTAmax) in the region where tonsils and adenoid constrict the pharynx (rs=0.78, P=0.011), and with decrease of the ratio of dPTAmax to flow rate (rs=0.82, P=0.006). Correlations of AHI decrease to anatomy, negative pressure in the overlap region (including nasal flow resistance), or pressure drop through the entire pharynx, were not significant. In a subgroup of subjects with more than 10% improvement in AHI, correlations between flow variables and AHI decrease were stronger than in all subjects.
Conclusions: The correlation between change in dPTAmax and improved AHI suggests that dPTAmax may be a useful index for internal airway loading due to anatomical narrowing, and may be better correlated with AHI than direct airway anatomic measurements.
Keywords: Airway resistance; Computer simulation; Humans; Magnetic resonance imaging; Pediatrics.
Copyright © 2014 Elsevier Ltd. All rights reserved.
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