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Biomechanics and Modeling in Mechanobiology

, Volume 15, Issue 6, pp 1619–1630 | Cite as

High-resolution subject-specific mitral valve imaging and modeling: experimental and computational methods

  • Milan Toma
  • Charles H. BloodworthIV
  • Daniel R. Einstein
  • Eric L. Pierce
  • Richard P. Cochran
  • Ajit P. Yoganathan
  • Karyn S. Kunzelman
Article

Abstract

The diversity of mitral valve (MV) geometries and multitude of surgical options for correction of MV diseases necessitates the use of computational modeling. Numerical simulations of the MV would allow surgeons and engineers to evaluate repairs, devices, procedures, and concepts before performing them and before moving on to more costly testing modalities. Constructing, tuning, and validating these models rely upon extensive in vitro characterization of valve structure, function, and response to change due to diseases. Micro-computed tomography (\(\mu \)CT) allows for unmatched spatial resolution for soft tissue imaging. However, it is still technically challenging to obtain an accurate geometry of the diastolic MV. We discuss here the development of a novel technique for treating MV specimens with glutaraldehyde fixative in order to minimize geometric distortions in preparation for \(\mu \)CT scanning. The technique provides a resulting MV geometry which is significantly more detailed in chordal structure, accurate in leaflet shape, and closer to its physiological diastolic geometry. In this paper, computational fluid–structure interaction (FSI) simulations are used to show the importance of more detailed subject-specific MV geometry with 3D chordal structure to simulate a proper closure validated against \(\mu \)CT images of the closed valve. Two computational models, before and after use of the aforementioned technique, are used to simulate closure of the MV.

Keywords

Fluid–structure interaction Mitral valve Comprehensive computational model Smooth particle hydrodynamics  Chordal structure Chordae tendineae Fixation Glutaraldehyde 

Notes

Acknowledgments

This study was supported by a grant from the National Heart Lung and Blood Institute (R01-HL092926) and by a grant from the National Science Foundation Graduate Research Fellowship (DGE-1148903).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Milan Toma
    • 1
  • Charles H. BloodworthIV
    • 1
  • Daniel R. Einstein
    • 2
  • Eric L. Pierce
    • 1
  • Richard P. Cochran
    • 3
  • Ajit P. Yoganathan
    • 1
  • Karyn S. Kunzelman
    • 3
  1. 1.Wallace H. Coulter Department of Biomedical EngineeringGeorgia Institute of TechnologyAtlantaUSA
  2. 2.Computational Biology and BioinformaticsPacific Northwest National LaboratoryRichlandUSA
  3. 3.Department of Mechanical EngineeringUniversity of MaineOronoUSA

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