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Multiscale image‐based modeling and simulation of gas flow and particle transport in the human lungs
Author(s) -
Lin ChingLong,
Tawhai Merryn H.,
Hoffman Eric A.
Publication year - 2013
Publication title -
wiley interdisciplinary reviews: systems biology and medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.087
H-Index - 51
eISSN - 1939-005X
pISSN - 1939-5094
DOI - 10.1002/wsbm.1234
Subject(s) - computational fluid dynamics , turbulence , computational model , multiscale modeling , computer science , airway , human lung , image (mathematics) , biological system , lung , simulation , mechanics , artificial intelligence , physics , medicine , bioinformatics , biology , meteorology
Improved understanding of structure and function relationships in the human lungs in individuals and subpopulations is fundamentally important to the future of pulmonary medicine. Image‐based measures of the lungs can provide sensitive indicators of localized features, however to provide a better prediction of lung response to disease, treatment, and environment, it is desirable to integrate quantifiable regional features from imaging with associated value‐added high‐level modeling. With this objective in mind, recent advances in computational fluid dynamics ( CFD ) of the bronchial airways—from a single bifurcation symmetric model to a multiscale image‐based subject‐specific lung model—will be reviewed. The interaction of CFD models with local parenchymal tissue expansion—assessed by image registration—allows new understanding of the interplay between environment, hot spots where inhaled aerosols could accumulate, and inflammation. To bridge ventilation function with image‐derived central airway structure in CFD , an airway geometrical modeling method that spans from the model ‘entrance’ to the terminal bronchioles will be introduced. Finally, the effects of turbulent flows and CFD turbulence models on aerosol transport and deposition will be discussed. WIREs Syst Biol Med 2013, 5:643–655. doi: 10.1002/wsbm.1234 This article is categorized under: Analytical and Computational Methods > Computational Methods Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models

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