4.5 Article

Image-based fluid-structure interaction model of the human mitral valve

期刊

COMPUTERS & FLUIDS
卷 71, 期 -, 页码 417-425

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compfluid.2012.10.025

关键词

Human mitral valve; Clinical imaging; Magnetic resonance imaging; Fluid-structure interaction; Immersed boundary method

资金

  1. China Scholarship Council
  2. University of Glasgow
  3. American Heart Association (AHA award) [10SDG4320049]
  4. National Science Foundation (NSF) [DMS-1016554, OCI-1047734]
  5. UK EPSRC [EP/I1029990]
  6. British Heart Foundation
  7. Medical Research Scotland
  8. Royal Society of Edinburgh
  9. Royal Academy of Engineering
  10. EPSRC [EP/I029990/1] Funding Source: UKRI
  11. Engineering and Physical Sciences Research Council [EP/I029990/1] Funding Source: researchfish
  12. Direct For Mathematical & Physical Scien
  13. Division Of Mathematical Sciences [1016554, 1460368] Funding Source: National Science Foundation
  14. Office of Advanced Cyberinfrastructure (OAC)
  15. Direct For Computer & Info Scie & Enginr [1047734, 1460334] Funding Source: National Science Foundation

向作者/读者索取更多资源

The mitral valve (MV) is one of the four cardiac valves. It consists of two leaflets that are connected to the left ventricular papillary muscles via multiple fibrous chordae tendinae. The primary functions of the MV are to allow for the free flow of blood into the left ventricle (LV) of the heart from the left atrium (LA) during the diastolic and early systolic phases of the cardiac cycle, and to prevent regurgitant flow from the LV to the LA in deep systole. MV disorders such as mitral stenosis and regurgitation cause significant morbidity and mortality, and an improved understanding of MV biomechanics could lead to improved medical and surgical procedures to restore normal MV function in patients with such disorders. Computational models can realistically capture the anatomical and functional features of the MV and hence can provide detailed spatial and temporal data that may not be easily obtained clinically or experimentally. In this study, an anatomical model of a human MV is derived from in vivo magnetic resonance imaging (MRI) data. Using this clinical imaging-derived model, fluid-structure interaction (FSI) simulations are performed using the immersed boundary (IB) method under physiological, dynamic transvalvular pressure loads. Computational analyses show that the subject-specific MV geometry has a significant influence on the simulation results. An initial validation of the model is achieved by comparing the opening height and flow rates to clinical measurements. (c) 2012 Elsevier Ltd. All rights reserved.

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