Numerical Simulation of Nasal Resistance Using Three-dimensional Models of the Nasal Cavity and Paranasal Sinus.

OBJECTIVE: Previously, we used a nasal cavity model to analyze the intranasal airflow dynamics and numerically calculate the nasal resistance value. In this study, We attempted clarify the parameters influencing nasal resistance by newly developed computer model. METHODS: The computer simulation model was developed from the structures of nasal airway tract adopted from 1.0-mm slice computed tomography (CT) obtained from the 2 of the healthy volunteers. (model 1: the one at 35-year-old man, model 2: 25-year-old man.) We have calculated the nasal resistance by computer simulation calculations of both model 1 and model 2. These calculated values were compared with the values obtained from the established method of rhinomanometry. For the simulation, Fluent 17.2® (ANSYS, American) was employed for f luid a nalysis u sing the continuity equation for 3D incompressible flow and the Navies-Stokes equation for the basic equations. Both models were laminar models. The SIMPLE calculation method using the finite volume method was employed here, and the quadratic precision upwind difference method was used to discretize the convection terms. RESULTS: The measured (simulation) values in Model 1 were 0.69 (0.48), 1.10 (0.41), and 0.42 (0.22) Pa/cm3/s on the right, left, and both sides, whereas those in Model 2 were 0.72 (0.21), 0.32 (0.09), and 0.22 (0.06) Pa/cm3/s, respectively. CONCLUSION: Our results suggest that nasal resistance is possibly affected by the length of the inferior turbinate and the cross-sectional area of the choana and nasopharynx. Further experiments using additional nasal cavity and paranasal sinus models are warranted.

Evaluation of Nasal Airflow and Resistance: Computational Modeling for Experimental Measurements.

OBJECTIVE: When evaluating nasal obstruction, conventional measurements of nasal patency do not necessarily correspond to a patient's subjective symptoms. The aim of this research is to seek an objective evaluation method by establishing computational modeling for nasal patency measurements. METHODS: We created a computer-generated geometrical model of the nasal cavity from computed-tomography scans of an adult male, presented a computational modeling method for evaluating the nasal patency in the deep-breathing state, and simulated numerically the airflow within the nasal cavity in the natural- and deep-breathing states. RESULTS: During inhalation in the natural-breathing state, the airflow was higher in the center of the nasal cavity and lower in the upper and lower portions, with the airflow characteristics being associated with the nasal functions. In the deep-breathing state, the computed nasal patency was compared with that measured experimentally by rhinomanometry. The quantitative accordance between computation and experiment was unsatisfactory, but the qualitative tendencies were similar. CONCLUSION: Through natural- and deep-breathing computations, the roles and functions of the olfactory region, nasal valve, and middle and inferior meatuses were evaluated from the flow patterns and pressure, with correlation to the nasal resistance and physiology. Above all, from the deep-breathing computation using the present computational modeling, it was deduced that the pressure difference is essential for determining the nasal sites at which the nasal resistance was produced. Thus, numerical simulation with computational modeling is potentially an objective method for evaluating nasal obstruction.