Literature DB >> 27475910

Personalized mitral valve closure computation and uncertainty analysis from 3D echocardiography.

Sasa Grbic1, Thomas F Easley2, Tommaso Mansi3, Charles H Bloodworth2, Eric L Pierce2, Ingmar Voigt3, Dominik Neumann3, Julian Krebs3, David D Yuh4, Morten O Jensen2, Dorin Comaniciu3, Ajit P Yoganathan2.   

Abstract

Intervention planning is essential for successful Mitral Valve (MV) repair procedures. Finite-element models (FEM) of the MV could be used to achieve this goal, but the translation to the clinical domain is challenging. Many input parameters for the FEM models, such as tissue properties, are not known. In addition, only simplified MV geometry models can be extracted from non-invasive modalities such as echocardiography imaging, lacking major anatomical details such as the complex chordae topology. A traditional approach for FEM computation is to use a simplified model (also known as parachute model) of the chordae topology, which connects the papillary muscle tips to the free-edges and select basal points. Building on the existing parachute model a new and comprehensive MV model was developed that utilizes a novel chordae representation capable of approximating regional connectivity. In addition, a fully automated personalization approach was developed for the chordae rest length, removing the need for tedious manual parameter selection. Based on the MV model extracted during mid-diastole (open MV) the MV geometric configuration at peak systole (closed MV) was computed according to the FEM model. In this work the focus was placed on validating MV closure computation. The method is evaluated on ten in vitro ovine cases, where in addition to echocardiography imaging, high-resolution μCT imaging is available for accurate validation.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Finite-element biomechanical models; Mitral valve modeling

Mesh:

Year:  2016        PMID: 27475910     DOI: 10.1016/j.media.2016.03.011

Source DB:  PubMed          Journal:  Med Image Anal        ISSN: 1361-8415            Impact factor:   8.545


  6 in total

1.  Extraction of open-state mitral valve geometry from CT volumes.

Authors:  Lennart Tautz; Mathias Neugebauer; Markus Hüllebrand; Katharina Vellguth; Franziska Degener; Simon Sündermann; Isaac Wamala; Leonid Goubergrits; Titus Kuehne; Volkmar Falk; Anja Hennemuth
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-08-03       Impact factor: 2.924

2.  Combining position-based dynamics and gradient vector flow for 4D mitral valve segmentation in TEE sequences.

Authors:  Lennart Tautz; Lars Walczak; Joachim Georgii; Amer Jazaerli; Katharina Vellguth; Isaac Wamala; Simon Sündermann; Volkmar Falk; Anja Hennemuth
Journal:  Int J Comput Assist Radiol Surg       Date:  2019-10-09       Impact factor: 2.924

3.  A Computational Framework for Atrioventricular Valve Modeling Using Open-Source Software.

Authors:  Wensi Wu; Stephen Ching; Steve A Maas; Andras Lasso; Patricia Sabin; Jeffrey A Weiss; Matthew A Jolley
Journal:  J Biomech Eng       Date:  2022-10-01       Impact factor: 1.899

Review 4.  Applications of artificial intelligence in cardiovascular imaging.

Authors:  Maxime Sermesant; Hervé Delingette; Hubert Cochet; Pierre Jaïs; Nicholas Ayache
Journal:  Nat Rev Cardiol       Date:  2021-03-12       Impact factor: 32.419

Review 5.  Geometric description for the anatomy of the mitral valve: A review.

Authors:  Diana Oliveira; Janaki Srinivasan; Daniel Espino; Keith Buchan; Dana Dawson; Duncan Shepherd
Journal:  J Anat       Date:  2020-04-03       Impact factor: 2.921

Review 6.  Heart Valve Biomechanics: The Frontiers of Modeling Modalities and the Expansive Capabilities of Ex Vivo Heart Simulation.

Authors:  Matthew H Park; Yuanjia Zhu; Annabel M Imbrie-Moore; Hanjay Wang; Mateo Marin-Cuartas; Michael J Paulsen; Y Joseph Woo
Journal:  Front Cardiovasc Med       Date:  2021-07-08
  6 in total

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