Simulation of blood flow in deformable vessels using subject-specific geometry and spatially varying wall properties
Simulation of blood flow using image‐based models and computational fluid dynamics has found widespread application to quantifying hemodynamic factors relevant to the initiation and progression of cardiovascular diseases and for planning interventions. Methods for creating subject‐specific geometric...
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Published in | International journal for numerical methods in biomedical engineering Vol. 27; no. 7; pp. 1000 - 1016 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Chichester, UK
John Wiley & Sons, Ltd
01.07.2011
Wiley |
Subjects | |
Online Access | Get full text |
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Summary: | Simulation of blood flow using image‐based models and computational fluid dynamics has found widespread application to quantifying hemodynamic factors relevant to the initiation and progression of cardiovascular diseases and for planning interventions. Methods for creating subject‐specific geometric models from medical imaging data have improved substantially in the last decade but for many problems, still require significant user interaction. In addition, while fluid–structure interaction methods are being employed to model blood flow and vessel wall dynamics, tissue properties are often assumed to be uniform. In this paper, we propose a novel workflow for simulating blood flow using subject‐specific geometry and spatially varying wall properties. The geometric model construction is based on 3D segmentation and geometric processing. Variable wall properties are assigned to the model based on combining centerline‐based and surface‐based methods. We finally demonstrate these new methods using an idealized cylindrical model and two subject‐specific vascular models with thoracic and cerebral aneurysms. Copyright © 2010 John Wiley & Sons, Ltd. |
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Bibliography: | ArticleID:CNM1404 ark:/67375/WNG-09HR9V6Z-Q istex:E22D26D14B3E47D9A4A2C8CFBD602D527CB2471D ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 taylorca@stanford.edu |
ISSN: | 2040-7939 2040-7947 2040-7947 |
DOI: | 10.1002/cnm.1404 |