Michael Lauria, PhD

Medical Physics Resident

Modeling Air Flow in Pathological Human Airway With Patient Specific CT-Data


Journal article


A. Islam, A. Rouhollahi, M. Lauria, A. Santhanam, O. Ilegbusi
Volume 5: Biomedical and Biotechnology, 2021

Semantic Scholar DOI
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APA   Click to copy
Islam, A., Rouhollahi, A., Lauria, M., Santhanam, A., & Ilegbusi, O. (2021). Modeling Air Flow in Pathological Human Airway With Patient Specific CT-Data. Volume 5: Biomedical and Biotechnology.


Chicago/Turabian   Click to copy
Islam, A., A. Rouhollahi, M. Lauria, A. Santhanam, and O. Ilegbusi. “Modeling Air Flow in Pathological Human Airway With Patient Specific CT-Data.” Volume 5: Biomedical and Biotechnology (2021).


MLA   Click to copy
Islam, A., et al. “Modeling Air Flow in Pathological Human Airway With Patient Specific CT-Data.” Volume 5: Biomedical and Biotechnology, 2021.


BibTeX   Click to copy

@article{a2021a,
  title = {Modeling Air Flow in Pathological Human Airway With Patient Specific CT-Data},
  year = {2021},
  journal = {Volume 5: Biomedical and Biotechnology},
  author = {Islam, A. and Rouhollahi, A. and Lauria, M. and Santhanam, A. and Ilegbusi, O.}
}

Abstract

This study investigates the effects of different pathological conditions of human trachea on flow distribution in the tracheo-bronchial tree (TBT) of human airways. Pathological conditions including hereditary Left Pulmonary Artery Sling (LPAS) and Chronic Obstructive Pulmonary Disease (COPD) often cause stenosis in the tracheal airway while a widening of the airway has been reported for patients with pulmonary fibrosis. This study assesses the airflow distribution in the human airway under such pathological conditions relative to normal flow condition, utilizing Computational Fluid Dynamics (CFD). Realistic 3D airway geometry is first reconstructed from anonymized CT scan data of human respiratory system and used for the CFD analysis. Specific pathological conditions are simulated by the modification of the tracheal geometry to account for the consequent shape deviation, and the resulting flow in the central airway is analyzed. Different breathing conditions (rest and mild activity) are modeled by imposing appropriate boundary conditions. The results demonstrate marked dependence of the predicted flow distribution and wall shear stress in the trachea on the pathological conditions. Tracheal stenosis exhibits mass flow split between the right and left bronchi similar to healthy case while bronchial stenosis significantly changes the mass flow split with less air coming out of the left main bronchus compared to the healthy case. The next phase of the study aims to assess the effect of the upstream vessel obstruction on the spatio-temporal airflow distribution in the lung and the overall breathing pattern. Such capabilities will directly address the regional flow distribution associated with diseases such as COPD and LPAS.


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