A multiscale MDCT image-based breathing lung model with time-varying regional ventilation

A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm con...

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Vydáno v:	Journal of computational physics Ročník 244; s. 168 - 192
Hlavní autoři:	Yin, Youbing, Choi, Jiwoong, Hoffman, Eric A., Tawhai, Merryn H., Lin, Ching-Long
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Elsevier Inc 01.07.2013
Témata:	AIR FLOW Airways ALGORITHMS ANIMAL TISSUES Boundary condition Breathing COMPARATIVE EVALUATIONS COMPUTERIZED TOMOGRAPHY ENGINEERING FLOW RATE FLUID MECHANICS Image registration INTERPOLATION LAMINAR FLOW LARGE-EDDY SIMULATION LUNGS Mathematical analysis Mathematical models MDCT Multiscale Pulmonary air flow Regional Regional ventilation RESPIRATION Ventilation Image registration Pulmonary air flow Boundary condition MDCT Multiscale Regional ventilation boundary condition pulmonary air flow regional ventilation image registration
ISSN:	0021-9991, 1090-2716
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Abstract	A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C1 continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung.
AbstractList	A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung. A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C{sub 1} continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung. A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C1 continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung. A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C1 continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung.A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C1 continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung. A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C(1) continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (ID) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung.
Author	Tawhai, Merryn H. Choi, Jiwoong Hoffman, Eric A. Yin, Youbing Lin, Ching-Long
AuthorAffiliation	c Department of Radiology, The University of Iowa, Iowa City, IA 52242, US d Department of Biomedical Engineering, The University of Iowa, Iowa City, IA 52242, US f Auckland Bioengineering Institute, The University of Auckland, Auckland, NZ a Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242, US e Department of Internal Medicine, The University of Iowa, Iowa City, IA 52242, US b IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242, US
AuthorAffiliation_xml	– name: c Department of Radiology, The University of Iowa, Iowa City, IA 52242, US – name: e Department of Internal Medicine, The University of Iowa, Iowa City, IA 52242, US – name: d Department of Biomedical Engineering, The University of Iowa, Iowa City, IA 52242, US – name: b IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242, US – name: a Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242, US – name: f Auckland Bioengineering Institute, The University of Auckland, Auckland, NZ
Author_xml	– sequence: 1 givenname: Youbing surname: Yin fullname: Yin, Youbing email: youbing-yin@uiowa.edu organization: Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242, USA – sequence: 2 givenname: Jiwoong surname: Choi fullname: Choi, Jiwoong email: jiwoong-choi@uiowa.edu organization: Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242, USA – sequence: 3 givenname: Eric A. surname: Hoffman fullname: Hoffman, Eric A. email: eric-hoffman@uiowa.edu organization: Department of Radiology, The University of Iowa, Iowa City, IA 52242, USA – sequence: 4 givenname: Merryn H. surname: Tawhai fullname: Tawhai, Merryn H. email: m.tawhai@auckland.ac.nz organization: Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand – sequence: 5 givenname: Ching-Long surname: Lin fullname: Lin, Ching-Long email: ching-long-lin@uiowa.edu organization: Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242, USA
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/23794749$$D View this record in MEDLINE/PubMed https://www.osti.gov/biblio/22233603$$D View this record in Osti.gov
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Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 E. A. Hoffman is a founder and shareholder of VIDA Diagnostics which is commercializing some of the software utilized in this work. youbing-yin@uiowa.edu (Y. Yin), jiwoong-choi@uiowa.edu (J. Choi), eric-hoffman@uiowa.edu (E.A. Hoffman), m.tawhai@auckland.ac.nz (M. H. Tawhai), ching-long-lin@uiowa.edu (C.-L. Lin)
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10.1016/j.jcp.2012.12.007_b0020 article-title: Role of mechanical stress in regulating airway surface hydration and mucus clearance rates publication-title: Respiratory Physiology & Neurobiology doi: 10.1016/j.resp.2008.04.020 – volume: 9 start-page: 62 issue: 1 year: 1979 ident: 10.1016/j.jcp.2012.12.007_b0170 article-title: A threshold selection method from gray-level histograms publication-title: IEEE Transactions on Systems, Man, and Cybernetics doi: 10.1109/TSMC.1979.4310076 – volume: 10 start-page: 1104 issue: 10 year: 2003 ident: 10.1016/j.jcp.2012.12.007_b0180 article-title: Characterization of the interstitial lung diseases via density-based and texture-based analysis of computed tomography images of lung structure and function publication-title: Academic Radiology doi: 10.1016/S1076-6332(03)00330-1
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Snippet	A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung...
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SubjectTerms	AIR FLOW Airways ALGORITHMS ANIMAL TISSUES Boundary condition Breathing COMPARATIVE EVALUATIONS COMPUTERIZED TOMOGRAPHY ENGINEERING FLOW RATE FLUID MECHANICS Image registration INTERPOLATION LAMINAR FLOW LARGE-EDDY SIMULATION LUNGS Mathematical analysis Mathematical models MDCT Multiscale Pulmonary air flow Regional Regional ventilation RESPIRATION Ventilation
Title	A multiscale MDCT image-based breathing lung model with time-varying regional ventilation
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