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

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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.

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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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Authors and Affiliations

  1. Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Technology Enterprise Park, Suite 200, 387 Technology Circle, Atlanta, GA, 30313-2412, USA

    Milan Toma, Charles H. Bloodworth IV, Eric L. Pierce & Ajit P. Yoganathan

  2. Computational Biology and Bioinformatics, Pacific Northwest National Laboratory, Richland, WA, 99352, USA

    Daniel R. Einstein

  3. Department of Mechanical Engineering, University of Maine, 219 Boardman Hall, Orono, ME, 04469-5711, USA

    Richard P. Cochran & Karyn S. Kunzelman

Authors
  1. Milan Toma
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  2. Charles H. Bloodworth IV
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  3. Daniel R. Einstein
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  4. Eric L. Pierce
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  5. Richard P. Cochran
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  6. Ajit P. Yoganathan
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  7. Karyn S. Kunzelman
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Corresponding author

Correspondence to Karyn S. Kunzelman.

Appendix

Appendix

The 1D microstructural model, \(\sigma \), is based on the physiology of crimped collagen fibers (Freed and Doehring 2005) that we have altered to meet our needs (see Algorithm 1); specifically, given a fiber stretch \(\lambda \), this model returns the engineering stress \(\sigma / \lambda \) and tangent modulus \(\mathrm {d}\sigma / \mathrm {d}\lambda \) of the fiber. There are four physiologic parameters (material constants defined at the top of the algorithm) that the user must supply; three if failure is not to be considered.

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Toma, M., Bloodworth, C.H., Einstein, D.R. et al. High-resolution subject-specific mitral valve imaging and modeling: experimental and computational methods. Biomech Model Mechanobiol 15, 1619–1630 (2016). https://doi.org/10.1007/s10237-016-0786-1

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