Abstract

Computational fluid dynamics (CFD) allows quantitative assessment of transport phenomena in the human nasal cavity, including heat exchange, moisture transport, odorant uptake in the olfactory cleft, and regional delivery of pharmaceutical aerosols. The first step when applying CFD to investigate nasal airflow is to create a 3-dimensional reconstruction of the nasal anatomy from computed tomography (CT) scans or magnetic resonance images (MRI). However, a method to identify the exact location of the air-tissue boundary from CT scans or MRI is currently lacking. This introduces some uncertainty in the nasal cavity geometry. The radiodensity threshold for segmentation of the nasal airways has received little attention in the CFD literature. The goal of this study is to quantify how uncertainty in the segmentation threshold impacts CFD simulations of transport phenomena in the human nasal cavity. Three patients with nasal airway obstruction were included in the analysis. Pre-surgery CT scans were obtained after mucosal decongestion with oxymetazoline. For each patient, the nasal anatomy was reconstructed using three different thresholds in Hounsfield units (-800HU, -550HU, and -300HU). Our results demonstrate that some CFD variables (pressure drop, flowrate, airflow resistance) and anatomic variables (airspace cross-sectional area and volume) are strongly dependent on the segmentation threshold, while other CFD variables (intranasal flow distribution, surface area) are less sensitive to the segmentation threshold. These findings suggest that identification of an optimal threshold for segmentation of the nasal airway from CT scans will be important for good agreement between in vivo measurements and patient-specific CFD simulations of transport phenomena in the nasal cavity, particularly for processes sensitive to the transnasal pressure drop. We recommend that future CFD studies should always report the segmentation threshold used to reconstruct the nasal anatomy.

Highlights

  • Computational fluid dynamics (CFD) technology has great potential as an objective tool in rhinology, given that it can quantify all the main physiological functions of the nose, including airflow conductance, delivery of odorant molecules to the olfactory cleft, and heating, humidification, and filtration of inspired air [1,2,3,4,5]

  • The authors found that inferior turbinate reduction (ITR) reduced nasal resistance in 3 patients who had a high resistance in the turbinate region pre-operatively, but ITR had a minimal effect on nasal resistance in 2 patients

  • Our results demonstrate that some CFD variables are strongly dependent on the threshold used for airway segmentation, while other CFD variables are less sensitive to the segmentation threshold

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Summary

Introduction

Computational fluid dynamics (CFD) technology has great potential as an objective tool in rhinology, given that it can quantify all the main physiological functions of the nose, including airflow conductance, delivery of odorant molecules to the olfactory cleft, and heating, humidification, and filtration of inspired air [1,2,3,4,5]. The authors found that inferior turbinate reduction (ITR) reduced nasal resistance in 3 patients who had a high resistance in the turbinate region pre-operatively, but ITR had a minimal effect on nasal resistance in 2 patients. These studies illustrate how CFD-based virtual surgery planning has the potential to improve the outcomes of nasal surgery [9,10,11,12]

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