The Virtual Nose: Assessment of Static Nasal Airway Obstruction Using Computational Simulations and 3D-Printed Models

Background: The use of virtual noses to predict the outcome of surgery is of increasing interests, particularly, as detailed and objective pre- and postoperative assessments of nasal airway obstruction (NAO) are difficult to perform. The objective of this article is to validate predictions using virtual noses against their experimentally measured counterpart in rigid 3D-printed models. Methods: Virtual nose models, with and without NAO, were reconstructed from patients' cone beam computed tomography scans, and used to evaluate airflow characteristics through computational fluid dynamics simulations. Prototypes of the reconstructed models were 3D printed and instrumented experimentally for pressure measurements. Results: Correlation between the numerical predictions and experimental measurements was shown. Analysis of the flow field indicated that the NAO in the nasal valve increases significantly the wall pressure, shear stress, and incremental nasal resistance behind the obstruction. Conclusions: Airflow predictions in static virtual noses correlate well with detailed experimental measurements on 3D-printed replicas of patient airways.