A Quasi-3D compartmental multi-scale approach to detect and quantify diseased regional lung constriction using spirometry data

International Journal for Numerical Methods in Biomedical Engineering
Ravishekar KannanAndrzej Przekwas

Abstract

Spirometry is a widely used pulmonary function test to detect the airflow limitations associated with various obstructive lung diseases, such as asthma, chronic obstructive pulmonary disease, and even obesity-related complications. These conditions arise due to the change in the airway resistance, alveolar compliance, and inductance values. Currently, zero-dimensional compartmental models are commonly used for calibrating these resistance, compliance, and inductance values, ie, solving the inverse spirometry problem. However, zero-dimensional compartments cannot capture the flow physics or the spatial geometry effects, thereby generating a low fidelity prediction of the diseased lung. Computational fluid dynamics (CFD) models offer higher fidelity solutions but may be impractical for certain applications due to the duration of these simulations. Recently, a novel, fast-running, and robust Quasi-3D (Q3D) wire model for simulating the airflow in the human lung airway was developed by CFD Research Corporation. This Q3D method preserved the 3D spatial nature of the airways and was favorably validated against CFD solutions. In the present study, the Q3D compartmental multi-scale combination is further improved to predict regional lu...Continue Reading

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Citations

Jun 4, 2019·Biomechanics and Modeling in Mechanobiology·A Pandal-BlancoA Fernández-Tena
Feb 6, 2020·International Journal for Numerical Methods in Biomedical Engineering·Ravishekar Kannan, Andrzej Przekwas
Feb 14, 2020·International Journal for Numerical Methods in Biomedical Engineering·Ravishekar KannanJulia Hoeng
Apr 3, 2020·International Journal for Numerical Methods in Biomedical Engineering·Ana Fernández-TenaAdrián Pandal-Blanco
Sep 19, 2018·Respiratory Research·Miriam BarrechegurenMarc Miravitlles

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