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An inverse modeling approach for stress estimation in mitral valve anterior leaflet valvuloplasty for in-vivo valvular biomaterial assessment
Authors:Chung-Hao Lee  Rouzbeh Amini  Robert C Gorman  Joseph H Gorman III  Michael S Sacks
Institution:1. Center for Cardiovascular Simulation, Institute for Computational Engineering and Sciences (ICES), Department of Biomedical Engineering, The University of Texas at Austin, 201 East 24th Street, ACES 5.236, 1 University Station C0200, Austin, TX 78712, USA;2. Department of Biomedical Engineering, The University of Akron, Auburn Science and Engineering Center 275, West Tower, Akron, OH 44325, USA;3. Gorman Cardiovascular Research Group, University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA 19104, USA
Abstract:Estimation of regional tissue stresses in the functioning heart valve remains an important goal in our understanding of normal valve function and in developing novel engineered tissue strategies for valvular repair and replacement. Methods to accurately estimate regional tissue stresses are thus needed for this purpose, and in particular to develop accurate, statistically informed means to validate computational models of valve function. Moreover, there exists no currently accepted method to evaluate engineered heart valve tissues and replacement heart valve biomaterials undergoing valvular stresses in blood contact. While we have utilized mitral valve anterior leaflet valvuloplasty as an experimental approach to address this limitation, robust computational techniques to estimate implant stresses are required. In the present study, we developed a novel numerical analysis approach for estimation of the in-vivo stresses of the central region of the mitral valve anterior leaflet (MVAL) delimited by a sonocrystal transducer array. The in-vivo material properties of the MVAL were simulated using an inverse FE modeling approach based on three pseudo-hyperelastic constitutive models: the neo-Hookean, exponential-type isotropic, and full collagen–fiber mapped transversely isotropic models. A series of numerical replications with varying structural configurations were developed by incorporating measured statistical variations in MVAL local preferred fiber directions and fiber splay. These model replications were then used to investigate how known variations in the valve tissue microstructure influence the estimated ROI stresses and its variation at each time point during a cardiac cycle. Simulations were also able to include estimates of the variation in tissue stresses for an individual specimen dataset over the cardiac cycle. Of the three material models, the transversely anisotropic model produced the most accurate results, with ROI averaged stresses at the fully-loaded state of  432.6±46.5 kPa and 241.4±40.5 kPa in the radial and circumferential directions, respectively. We conclude that the present approach can provide robust instantaneous mean and variation estimates of tissue stresses of the central regions of the MVAL.
Keywords:In-vivo stress estimation  Finite element (FE) inverse modeling  Genetic algorithm  Mapped collagen fiber architecture
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