Ex Vivo Methods for Informing Computational Models of the Mitral Valve

• Type of Material: Article
• Authors: Charles H. Bloodworth, Georgia Institute of Technology; Eric L. Pierce, Georgia Institute of Technology; Thomas F. Easley, Georgia Institute of Technology; Andrew Drach, University of Texas Austin; Amir H. Khalighi, University of Texas Austin; Milan Toma, Georgia Institute of Technology; Morten O. Jensen, Georgia Institute of Technology; Michael S. Sacks, University of Texas Austin; Ajit Yoganathan, Emory University
• Language: English
• Date: 2017-02-01
• Publisher: Springer Verlag (Germany)
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2016, Biomedical Engineering Society.
• Final Published Version (URL): http://dx.doi.org/10.1007/s10439-016-1734-z
• Title of Journal or Parent Work: Annals of Biomedical Engineering
• ISSN: 0090-6964
• Volume: 45
• Issue: 2
• Start Page: 496
• End Page: 507
• Grant/Funding Information: This work was partially supported by the National Science Foundation Graduate Research Fellowship (ELP) under Grant DGE-1148903, as well as by the National Heart, Lung, and Blood Institute under Grant R01HL119297.
• Keywords: Engineering; Micro-computed tomography; Engineering, Biomedical; STRAINS; Simulation; Cardiovascular; Technology; OVINE MODEL; GEOMETRY; REPLACEMENT; ANTERIOR LEAFLET; ANNULOPLASTY; Science & Technology; Mitral repair; Mitral regurgitation; SIMULATIONS; REGURGITATION; Imaging; FINITE-ELEMENT; REPAIR
• Research Categories: Engineering, Biomedical

Abstract

Computational modeling of the mitral valve (MV) has potential applications for determining optimal MV repair techniques and risk of recurrent mitral regurgitation. Two key concerns for informing these models are (1) sensitivity of model performance to the accuracy of the input geometry, and, (2) acquisition of comprehensive data sets against which the simulation can be validated across clinically relevant geometries. Addressing the first concern, ex vivo micro-computed tomography (microCT) was used to image MVs at high resolution (~40 micron voxel size). Because MVs distorted substantially during static imaging, glutaraldehyde fixation was used prior to microCT. After fixation, MV leaflet distortions were significantly smaller (p  <  0.005), and detail of the chordal tree was appreciably greater. Addressing the second concern, a left heart simulator was designed to reproduce MV geometric perturbations seen in vivo in functional mitral regurgitation and after subsequent repair, and maintain compatibility with microCT. By permuting individual excised ovine MVs (n = 5) through each state (healthy, diseased and repaired), and imaging with microCT in each state, a comprehensive data set was produced. Using this data set, work is ongoing to construct and validate high-fidelity MV biomechanical models. These models will seek to link MV function across clinically relevant states.