Forward Computational Modeling of Respiratory Airflow

The simulation of gas flow in the bronchial tree using computational fluid dynamics (CFD) has become a useful tool for the analysis of gas flow mechanics, structural deformation, ventilation, and particle deposition for drug delivery during spontaneous and assisted breathing. CFD allows for new hypotheses to be tested <i>in silico</i>, and detailed results generated without performing expensive experimental procedures that could be potentially harmful to patients. Such computational techniques are also useful for analyzing structure-function relationships in healthy and diseased lungs, assessing regional ventilation at various time points over the course of clinical treatment, or elucidating the changes in airflow patterns over the life span. CFD has also allowed for the development and use of image-based (i.e., patient-specific) models of three-dimensional (3D) airway trees with realistic boundary conditions to achieve more meaningful and personalized data that may be useful for planning effective treatment protocols. This focused review will present a summary of the techniques used in generating realistic 3D airway tree models, the limitations of such models, and the methodologies used for CFD airflow simulation. We will discuss mathematical and image-based geometric models, as well as the various boundary conditions that may be imposed on these geometric models. The results from simulations utilizing mathematical and image-based geometric models of the airway tree will also be discussed in terms of similarities to actual gas flow in the human lung.

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Publication Details

Journal
Applied Sciences
Published
2024-12-12
DOI
https://doi.org/10.3390/app142411591
Citations
2
Primary Topic
Inhalation and Respiratory Drug Delivery
Type
article
Field-Weighted Citation Impact
0.84

Funders

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article

Forward Computational Modeling of Respiratory Airflow

Mingchao Cai, Ching‐Long Lin, David W. Kaczka, E.A. Akor et al.
2 citations
Applied Sciences
Inhalation and Respiratory Drug Delivery
0.84
article

Forward Computational Modeling of Respiratory Airflow

Mingchao Cai, Ching‐Long Lin, David W. Kaczka, E.A. Akor, Bing Han
article en
2 citations

Abstract

The simulation of gas flow in the bronchial tree using computational fluid dynamics (CFD) has become a useful tool for the analysis of gas flow mechanics, structural deformation, ventilation, and particle deposition for drug delivery during spontaneous and assisted breathing. CFD allows for new hypotheses to be tested <i>in silico</i>, and detailed results generated without performing expensive experimental procedures that could be potentially harmful to patients. Such computational techniques are also useful for analyzing structure-function relationships in healthy and diseased lungs, assessing regional ventilation at various time points over the course of clinical treatment, or elucidating the changes in airflow patterns over the life span. CFD has also allowed for the development and use of image-based (i.e., patient-specific) models of three-dimensional (3D) airway trees with realistic boundary conditions to achieve more meaningful and personalized data that may be useful for planning effective treatment protocols. This focused review will present a summary of the techniques used in generating realistic 3D airway tree models, the limitations of such models, and the methodologies used for CFD airflow simulation. We will discuss mathematical and image-based geometric models, as well as the various boundary conditions that may be imposed on these geometric models. The results from simulations utilizing mathematical and image-based geometric models of the airway tree will also be discussed in terms of similarities to actual gas flow in the human lung.

Applied SciencesVol. 14(24)
University of Iowa (US), Morgan State University (US)
U.S. Department of Defense, Morgan State University, National Institutes of Health, Army Research Office
Good health and well-being
Openalex Percentile: Top 22%
Inhalation and Respiratory Drug Delivery
0.84
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