Paper
14 April 2005 Evaluation of arterial blood flow heterogeneity via an image-based computational model
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Abstract
A computational model of blood flow through the human pulmonary arterial tree has been developed to investigate the relative influence of branching structure and gravity on blood flow distribution in the human lung. A geometric model of the largest arterial vessels and definitions of the lobar boundaries were first derived using multi-detector row x-ray computed tomography (MDCT) scans from the Lung Atlas. Further accompanying arterial vessels were generated from the MDCT vessel end points into the lobar volumes using a volume filling branching algorithm. A reduced form of the Navier-Stokes equations were solved within the geometric model to simulate pressure, velocity and vessel radius throughout the network. Blood flow results in the anatomically-based model, with and without gravity, and in a symmetric arterial model were compared in order to investigate their relative contributions to blood flow heterogeneity. Results showed a persistent blood flow gradient and flow heterogeneity in the absence of gravitational forces in the anatomically-based model. Results revealed that the asymmetric branching structure of the model was largely responsible for producing this heterogeneity. Analysis of average results in different slice thicknesses illustrated a clear flow gradient due to gravity in 'lower-resolution’ data (thicker slices), but on examination of higher resolution data a trend was less obvious. Results suggest that while gravity does influence flow distribution, the influence of the tree branching structure is also a dominant factor. These results are consistent with high-resolution experimental studies that have demonstrated gravity to be only a minor determinant of blood flow distribution.
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Kelly S. Burrowes, Merryn H. Tawhai, and Peter J. Hunter "Evaluation of arterial blood flow heterogeneity via an image-based computational model", Proc. SPIE 5746, Medical Imaging 2005: Physiology, Function, and Structure from Medical Images, (14 April 2005); https://doi.org/10.1117/12.600718
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Cited by 4 scholarly publications.
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KEYWORDS
Lung

Blood circulation

Data modeling

Blood

Animal model studies

Algorithm development

Arteries

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