ANSYS CFX Simulation of Nasal Airflow - Flow Investigation and Evaluation of Nasal Anatomy to

Support Treatment Planning for Functional Rhinosurgery

Dr.-Ing. Alexander Steinmann1, Dr.-Ing. Peter Bartsch1, Dr.-Ing. Stefan Zachow2, Dipl. med. Thomas Hildebrandt3

1 CFX Berlin Software GmbH, Alexander.Steinmann@cfx-berlin.de 2 Zuse-Institut Berlin (ZIB), Medical Planning Systems

3 Asklepios Klinik Birkenwerder, Brandenburg

1. Introduction A major requirement for normal nose breathing is an undisturbed passage through the nasal airways. In cases where this condition is not given due to any obstruction or deformity a surgical correction might be indicated. ANSYS CFX simulations are presented for a highly detailed anatomy of a nasal airway being reconstructed from tomographic data. The simulation of complex airflow characteristics with regard to individual anatomy enables to study the physiology and pathophysiology of nasal breathing, thus being able to support treatment planning in functional rhinosurgery [1].

2. Geometry The foundation of the investigation is a reference model of the nasal airways, derived from a real human anatomy without obvious pathologic symptoms. For the study a helical CT scan (Toshiba Aquilion 64) of a male volunteer was acquired after local administration of a decongestant (Xylometa-zoline) and systemic application of Methylprednisolon. High resolution tomography with an almost isotropic spatial resolution of 0.37x0.37x0.4 mm allows the reconstruction of anatomical structures with sufficient detail. The resulting anatomic model of the nasal and paranasal cavities is shown in Fig. 1 and Fig. 2.

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Fig. 1. Coronal slice of the CT data and visualization of the respiratory airways in a mid-sagittal cut

Fig. 2. Reconstructed nasal airways and facial skin surface

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3. Numerical Grid For the reconstruction of the flow domain from the CT scans the software AMIRA [2] was used. The resulting high resolution non-manifold surface model consisting of approx. 825 000 triangles has been simplified and remeshed, thus providing a high quality mesh of tissue boundaries consisting of 220 000 triangles. From these polygonal tissue boundaries a tetrahedral grid is generated using an Advancing Front technique. Afterwards the grid was optimized with regard to dihedral angles and tetrahedral aspect ratios, while keeping the polygonal surface model unchanged (Fig. 3 and Fig. 4).

Fig. 3. Numerical grid I

Fig. 4. Numerical grid II

In addition to the volumetric grid of inner airway structures, the facial soft tissue was reconstructed and a grid of the anterior inflow region was generated to address individual inflow via the external nose. The geometric model of the nasal airways with locally controlled resolution and suitable element

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quality is finally exported in CGNS format for CFD simulations with ANSYS CFX. The grid consists of 2 763 007 Tetrahedrons (609 750 Nodes).

4. Numerical Fluid Flow Calculations The transient flow representing a total of 7 breathing cycles was calculated. The pressure difference between inlet and outlet (lung) as a function of time has been applied as boundary condition. This data was derived from a series of active anterior rhinomanometry (AAR) measurements. These measurements were taken on the same subject in a comparable mucous membrane swelling condition, gathering 2000 samples per measurement (RhinoLab, HR2). The measurements will be used for a validation of simulation results, too.

5. Results Results are shown in Fig. 5 to Fig. 11.

Fig. 5. Streamlines coloured by velocity for inhalation

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Fig. 6. Streamlines coloured by pressure for inhalation

Fig. 7. Streamlines coloured by total pressure for inhalation

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Fig. 8. Streamlines coloured by velocity for exhalation

Fig. 9. Streamlines coloured by pressure for exhalation

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Fig. 10. Streamlines coloured by velocity for inhalation (ventilation of frontal sinus and maxillary sinus)

Fig. 11. Streamlines coloured by time for inhalation (ventilation of frontal sinus and maxillary sinus)

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6. Further Work In further investigations the humidification of nasal air flow will be considered as a multi-component flow with an additional transport equation for water vapour. On that account the humidity charge of the nasal mucosa will be modeled by appropriate boundary sources at the fluid walls thus realizing the humidity transfer between mucosa and air. In order to ensure an accurate numerical simulation of fluid shear stresses, e.g. changes of air velocity at the mucosal walls, several dense layers of pentahedral prism elements at the air-mucosa interface will be introduced. The modeling and simulation approach also enables the studying of pharmacokinetic issues, such as the application of drugs via the respiratory system. The delivery of medication particles can be regarded as a multi-phase flow consisting of liquid droplets (disperse distributed particle flow) in a continuous air stream. Furthermore heat transfer mechanism will be included. For a better understanding of the relationship between nose morphology and respiration the effect of changes of the external nose is currently investigated. using an advanced biomechanical tissue model the shape of the external nose can be varied in a relistic manner, i.e. increasing or decreasing the nasolabial angle or the cross-section of the nasal valve. Such deformities may disturb the inspiratory inflow resulting in an increased resistance, an impaired distribution of the airstream, or pathological turbulence behavior. An interactive alteration of the geometry of the nasal airways in combination with CFD analysis is a basis for a sophisticated planning tool in virtual rhinosurgery. The conclusions that can be drawn might have an important impact on future surgical and conservative therapeutic concepts, thus driving clinical research.

Keywords

surgery planning, computational fluid dynamics, CFD, functional rhinosurgery, nasal airflow

References

[1] Zachow S., Steinmann A., Hildebrandt T., Weber R., Heppt W.: "CFD simulation of nasal airflow: Towards treatment planning for functional rhinosurgery", Int. J. of Computer Assisted Radiology and Surgery, Springer, pp. 165-167 (2006)

[2] Stalling D, M Westerhoff, HC Hege et al.: Amira: A Highly Interactive System for Visual Data Analysis. (amira.zib.de) In: Hansen, CD and CR Johnson (eds.): The Visualization Handbook. Elsevier (2005), chapter 38, pp. 749-767 (2005)

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