Development and validation of a computational finite element model of the rabbit upper airway

simulations of mandibular advancement and tracheal displacement

Jason Amatoury*, Shaokoon Cheng, Kristina Kairaitis, John R. Wheatley, Terence C. Amis, Lynne E. Bilston

*Corresponding author for this work

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

The mechanisms leading to upper airway (UA) collapse during sleep are complex and poorly understood. We previously developed an anesthetized rabbit model for studying UA physiology. On the basis of this body of physiological data, we aimed to develop and validate a two-dimensional (2D) computational finite element model (FEM) of the passive rabbit UA and peripharyngeal tissues. Model geometry was reconstructed from a midsagittal computed tomographic image of a representative New Zealand White rabbit, which included major soft (tongue, soft palate, constrictor muscles), cartilaginous (epiglottis, thyroid cartilage), and bony pharyngeal tissues (mandible, hard palate, hyoid bone). Other UA muscles were modeled as linear elastic connections. Initial boundary and contact definitions were defined from anatomy and material properties derived from the literature. Model parameters were optimized to physiological data sets associated with mandibular advancement (MA) and caudal tracheal displacement (TD), including hyoid displacement, which featured with both applied loads. The model was then validated against independent data sets involving combined MA and TD. Model outputs included UA lumen geometry, peripharyngeal tissue displacement, and stress and strain distributions. Simulated MA and TD resulted in UA enlargement and nonuniform increases in tissue displacement, and stress and strain. Model predictions closely agreed with experimental data for individually applied MA, TD, and their combination. We have developed and validated an FEM of the rabbit UA that predicts UA geometry and peripharyngeal tissue mechanical changes associated with interventions known to improve UA patency. The model has the potential to advance our understanding of UA physiology and peripharyngeal tissue mechanics.

Original languageEnglish
Pages (from-to)743-757
Number of pages15
JournalJournal of Applied Physiology
Volume120
Issue number7
DOIs
Publication statusPublished - 1 Apr 2016

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