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

Autor: Grbic S; Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ, United States. Electronic address: sasa.grbic@siemens.com., Easley TF; The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, Georgia., Mansi T; Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ, United States., Bloodworth CH; The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, Georgia., Pierce EL; The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, Georgia., Voigt I; Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ, United States., Neumann D; Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ, United States., Krebs J; Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ, United States., Yuh DD; Section of Cardiac Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT, United States., Jensen MO; The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, Georgia., Comaniciu D; Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ, United States., Yoganathan AP; The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, Georgia.
Jazyk: angličtina
Zdroj: Medical image analysis [Med Image Anal] 2017 Jan; Vol. 35, pp. 238-249. Date of Electronic Publication: 2016 May 17.
DOI: 10.1016/j.media.2016.03.011
Abstrakt: 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.)
Databáze: MEDLINE
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