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2002
Conference Paper
Title
Nasal airflow diagnosis. Comparison of experimental studies and computer simulations
Abstract
The lack of situed diagnostic tools providing insight into patient specific flow characteristics of the nasal airflow is one of the main problems in functional diagnosis. Diagnostics methods currently used do not provide the necessary information for flow analysis. But the flow distribution is essential for a physiological repiration, in particular for cleaning moistening and tempering of the inhaled air as well as for the olfactory function of the nose. To overcome this current situation a cooperation project of the ENT surgeons and computer graphic engineers was established to develop the computer assisted planning system STAN (Simulation Tool for Airflow in the human Nose) combining Computer Fluid Dynamics (CFD) with advanced Computer Graphic Technology. The idea of the STAN system is to perform patient specific airflow simulations in the patient's nasal cavities. Therefore a geometrical model of the nasal airways is derived form the patient's tomography scans. A discretization of the surrounded flow volume is made by a computational grid. To establish the flow simulation Finite Element Methods are performed on the grid. A tailored visualization is offered to the surgeon that overlaps the flow pattern to the patient's tomography data shown in the coronal sagittal and transversal plane. The surgeon can not only analyze the patient's current respiration situation he has also the possibility to describe the planned surgical intervention. The goal is to simulate the flow distribution that can be expected after the surgical intervention and to offer a possibility to validate various surgical strategies. To verify the simulation results experimental investigation and measurements are made in nasal models. Silicon Models of patient's nose channels are made to analyze flow characteristics the CT or MR scans of the same patients are used as input data for the simulation. The experimental outcome is compared to the simulation results to validate this diagnostic approach.
Author(s)