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Patient specific study of human airway fluid dynamics and particle transport

Sprays – Modelling Versus Experimentation, UK – Israel Workshop, 16th – 18 th July 2007, Queens Hotel, Brighton, UK. Patient specific study of human airway fluid dynamics and particle transport. P. Nithiarasu 1. School of Engineering University of Wales Swansea Swansea SA2 8PP, UK.

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Patient specific study of human airway fluid dynamics and particle transport

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  1. Sprays – Modelling Versus Experimentation, UK – Israel Workshop, 16th – 18th July 2007, Queens Hotel, Brighton, UK Patient specific study of human airway fluid dynamics and particle transport P. Nithiarasu1 School of Engineering University of Wales Swansea Swansea SA2 8PP, UK Clinical Collaborators: P. Ebden, C Fielder, H. Whittet, Singleton Hospital, Swansea K.R. Lewis, Swansea Clinical School. Academic Collaborators: J Bonet, O Hassan, K Morgan, N.P. Weatherill, UWS, Swansea R Löhner, George Mason University, USA Acknowledgements EPSRC, UK; British Council, Israel

  2. Outline • Background • Geometry extraction • Mesh generation • Numerical solution • Human upper airway fluid dynamics • Particle transport • Some conclusions

  3. Traditional Approaches: One-Dimensional Blood flow With stenosis Straight

  4. Turbulent flow through model human airways Unstructured mesh Pressure distribution Shear stress distribution Velocity distribution Nithiarasu, Liu and Massarotti, CNME, 2007.

  5. Patient specific numerical modelling - Objectives • Use patient specific information to numerically model biomedical problems • Use the numerical results to understand biomedical problems • Derive useful information, such as cure for illnesses or design a biomedical instrument • Help clinicians and patients

  6. Human upper airways

  7. Human upper airway disorders Nasal passage • Nasal corrective surgeries • High failure rate Vocal-cord • Vocal-cord paralysis • Prosthesis insertion • High failure rate • Particle dynamics • Pollution • Pulmonary delivery • Nozzle design • Sleep apnoea • Poor understanding • Need for better diagnosis • Need for a better treatment Airway Collapse

  8. Flow chart Scans Computational biomechanics Help patients and community

  9. Amira – Geometry reconstruction

  10. Geometry modelling - difficulties Epiglottis Nasal passage Vocal folds

  11. Reconstruction - Mimics Extracted airway geometry Airway reconstruction from DICOM images

  12. Unstructured mesh – In house Meshing code: O. Hassan, K. Morgan and N.P. Weatherill UWS, Swansea

  13. Summary of the Unified approach (CBS) Step 1 Step 2 Step 3 Overview: P. Nithiarasu, R. Codina and O.C. Zienkiewicz, IJNME, 2006.

  14. Spatial discretizaion Equation discretization (CBS) Defining we get the equation where

  15. Model airway Mesh Pressure drop

  16. Patient specific airway Final geometry 33.76 l/min

  17. Patient specific airway Modelling – flow 33.76 l/min Pressure distribution Max value: 63.33 Pa Min value: - 23.90 Pa Pressure drop: 41.95 Pa Shear stress distribution Max value: 0.513 Pa

  18. Patient specific airway - Pressure drop

  19. Patient specific airway - Anterior

  20. Patient specific airway - Posterior

  21. Patient specific airway – Particle transport • Simple model • No density difference between the fluid and particle • The velocity of the particle is equal to the fluid velocity • Trace the position of the particle using any standard • method • Better model • Density difference between the fluid and particle • The velocity of the particle is not equal to the fluid velocity • Trace the position of the particle using any standard • method Using convection transport equation is also possible

  22. Patient specific airway – Particle transport – Better model Zhang et al., (2002) St – Stokes number = ρp dp uα /18 μ L ФD = CDp Rep/24 CDp = CD/CSlip CD = 24/REp vp – particle velocity; v – fluid velocity; Rep – particle Reynolds number; CSlip – slip factor

  23. Flow pattern at 33.6 l/min

  24. Particle trajectories Particle transport (101 particles) Deposited particles 55.4%

  25. Particle transport (101 particles) Z = -5.65 xz Z = -7.6 yz

  26. Particle transport (1001 particles) Deposited particles 61.3%

  27. Particle transport (10001 particles) Deposited particles 61.3%

  28. Conclusions • Patient specifically studying airway fluid dynamics is possible. • Implementation of such studies in clinical environment needs to be investigated. • Particle deposition is less predictable than using standard circular geometries. • Further progress is necessary to employ patient specific studies at clinical environment. • More advanced models for particle deposition may improve results.

  29. Thank You for Your Attention

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