Numerical modelling of inhaled particle transport and deposition in human and rat nasal cavities

Shang, Y 2016, Numerical modelling of inhaled particle transport and deposition in human and rat nasal cavities, Doctor of Philosophy (PhD), Aerospace, Mechanical and Manufacturing Engineering, RMIT University.


Document type: Thesis
Collection: Theses

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Title Numerical modelling of inhaled particle transport and deposition in human and rat nasal cavities
Author(s) Shang, Y
Year 2016
Abstract This thesis focuses on health risk assessment of inhaled particles on human nasal cavities. Inhaled micron- and nano-sized particles may exhibit therapeutic or toxic effects on the human nasal cavity. The nasal cavity play an important role in particle filtering, air-distribution, and air-conditioning. Due to its invasive nature, traditional in-vivo research have been challenging in narrow human nasal airways. Conventionally, laboratory rats have been used to predict human's toxicological response to inhaled particle. Experiments on human nasal replica casts have been widely used to study the fluid dynamics as well as toxicological studies associated with particle deposition.

Two major research gaps remain between these preliminary studies and clinical applications. Because of the intricate nasal geometry, it is difficult to accurately visualise the results inside the nasal cavity or on the nasal wall. Due to significant nasal geometric difference, the reliability of existing extrapolation from rat to human is questioned. Recently, with rapid development of medical imaging and computational algorithm, Computational Fluid Dynamics (CFD) provides a powerful approach to conduct simulation on nasal models, which can be accurately reconstructed from CT-scan.

The main body of this thesis is composed of four parts. In the first part (Chapter 2-3), I performed a comprehensive literature review, including anatomy, \textit{in-vivo} and \textit{in-vitro} experimental studies and numerical stdies, to identify the research gaps between previous studies and real clinical application. In the second part (Chapter 4), I developed an unique surface-mapping technique to project the pressure and wall shear stress distributions from 3D to 2D domain. This technique lays a solid foundation for visualising particle deposition locations on the entire nasal wall. In the third part (Chapter 5), I investigated two factors that influence particle deposition within human nasal cavities. The breathing zone near nostrils dominates micron-sized particles' trajectories and thus influencing both the deposition efficiency and the deposition pattern. With respect to nano-sized particles, I performed simulation for welding particles and found the shape factor of agglomerates play a role in deposition patterns not only in the nasal cavity, but also in the entire upper respiratory airway. In the fourth part (Chapter 6-7), a CAD model of Sprague-Dawley rat was reconstructed from Micro-CT scan and simulation were performed to compare with human case. Despite the visualisation application, the surface-mapping technique also enables an approach to eliminate individual and inter-species variations by normalising the 2D domain. Airflow behaviour, pressure and wall shear stress distributions, microparticle and nanoparticle deposition patterns were compared between two species. I proposed a scaling factor as a first step to establish a practical extrapolation model from rat to human.

In summary, I developed novel techniques to gain insight into the fluid dynamics and particle movement within human and rat nasal cavities. This allows complete data access in the nasal cavity, thus enabling direct inter-individual and inter-species comparisons. Airflow behaviour, pressure and wall shear stress distributions, and detailed particle deposition patterns were examined. Results were compared between human and rat to establish an appropriate extrapolation method. This study lays a solid foundation to perform CFD simulation in lower respiratory system and sub-layers such as mucus, tissue and blood flow, which are critical for future clinical applications.
Degree Doctor of Philosophy (PhD)
Institution RMIT University
School, Department or Centre Aerospace, Mechanical and Manufacturing Engineering
Subjects Numerical Modelling and Mechanical Characterisation
Biomechanical Engineering
Comparative Physiology
Keyword(s) Computational Fluid Dynamics
Nasal cavity
Particle deposition
Surface-mapping
Rat-human extrapolation
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Created: Fri, 13 Jan 2017, 08:21:21 EST by Adam Rivett
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