Title

Computational fluid dynamics as surgical planning tool: a pilot study on middle turbinate resection.

Document Type

Article

Publication Date

11-1-2014

Comments

This article has been peer reviewed. It was published in: Anatomical Record.

Volume 297, Issue 11, 1 November 2014, Pages 2187-2195.

The published version is available at DOI: 10.1002/ar.23033

Copyright © 2014 Wiley Periodicals, Inc.

Abstract

Controversies exist regarding the resection or preservation of the middle turbinate (MT) during functional endoscopic sinus surgery. Any MT resection will perturb nasal airflow and may affect the mucociliary dynamics of the osteomeatal complex. Neither rhinometry nor computed tomography (CT) can adequately quantify nasal airflow pattern changes following surgery. This study explores the feasibility of assessing changes in nasal airflow dynamics following partial MT resection using computational fluid dynamics (CFD) techniques. We retrospectively converted the pre- and postoperative CT scans of a patient who underwent isolated partial MT concha bullosa resection into anatomically accurate three-dimensional numerical nasal models. Pre- and postsurgery nasal airflow simulations showed that the partial MT resection resulted in a shift of regional airflow towards the area of MT removal with a resultant decreased airflow velocity, decreased wall shear stress and increased local air pressure. However, the resection did not strongly affect the overall nasal airflow patterns, flow distributions in other areas of the nose, nor the odorant uptake rate to the olfactory cleft mucosa. Moreover, CFD predicted the patient's failure to perceive an improvement in his unilateral nasal obstruction following surgery. Accordingly, CFD techniques can be used to predict changes in nasal airflow dynamics following partial MT resection. However, the functional implications of this analysis await further clinical studies. Nevertheless, such techniques may potentially provide a quantitative evaluation of surgical effectiveness and may prove useful in preoperatively modeling the effects of surgical interventions.