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Rhinosurgical therapy planning via endonasal airflow simulation
U Bockholt1, G Mlynski, W Müller
1Darmstadt University of Technology, Interactive Graphics Systems Group (GRIS), Darmstadt, Germany. bockholt@igd.fhg.de
Summary
Computational Fluid Dynamics (CFD) aids automotive aerodynamics. A new tool, STAN, uses CFD with patient CT scans for 3D nasal airflow simulation, improving surgical planning for respiratory disorders.
Area of Science:
- Biomedical Engineering
- Computational Fluid Dynamics
- Medical Imaging
Background:
- Computational Fluid Dynamics (CFD) is advanced in automotive aerodynamics.
- Sophisticated airflow-simulation models are crucial for engineering optimization.
- The Simulation Tool for Airflow in the human Nose (STAN) leverages CFD for medical applications.
Purpose of the Study:
- To support rhinosurgeons in diagnosing and planning therapy using CFD.
- To develop a system for 3D reconstruction of endonasal cavities from CT scans.
- To enable patient-specific airflow simulations for improved surgical outcomes.
Main Methods:
- Semiautomatic 3D reconstruction of endonasal cavities from CT scans.
- Creation of unstructured 3D volume mesh for finite volume simulations.
- Development of the Simulation Tool for Airflow in the human Nose (STAN).
Main Results:
- Individual, patient-specific nasal airflow simulations are achievable.
- The system provides a 3D surface model for mesh generation.
- Experimental investigations in nasal models verify simulation accuracy.
Conclusions:
- STAN facilitates diagnosis and therapy planning for nasal conditions.
- Simulating disordered respiration pre-surgery enhances surgical planning effectiveness.
- This approach aids in investigating nasal complaints and detecting respiratory disorders.