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Estimation of 3D Left Ventricular Deformation

from Medical Images Using Biomechanical Models.

A Dissertation

Presented to the Faculty of the Graduate School

of

Yale University

in Candidacy for the Degree of

Doctor of Philosophy


by

Xenophon Papademetris


Dissertation Director: James Scott Duncan

May 2000

Abstract

The non-invasive quantitative estimation of regional cardiac deformation has important clinical implications for the assessment of viability in the heart wall. In this work we describe a general framework for estimating soft tissue deformation from sequences of three-dimensional medical images. We also explore some of their theoretical constraints which can be used to guide the selection of an appropriate model for the displacement field. We then apply this framework to the problem of estimating left ventricular deformations from sequences of 3D image sequences. The images are segmented interactively to extract the endocardial and epicardial surfaces. Then, initial frame-to-frame correspondences are established between points on the surfaces using a shape-tracking approach. The myocardium is modeled using a transversely isotropic linear elastic model, which accounts for the preferential stiffness of the left ventricular myocardium along its fiber directions. The measurements and the model are integrated within a Bayesian estimation framework. The resulting equations are solved using the finite element method, to produce a dense displacement field for the whole of the left ventricle. The dense displacement field is, in turn, used to calculate the deformation of the heart wall in terms of the strains. This method was tested on over 40 image sequences, and the strains produced using this non-invasive technique exhibit high correlation with strains simultaneously obtained from invasive measurements using implanted markers and sonomicrometers. We also demonstrate that these strains are useful as predictors of the viability of the underlying tissue and can be used to distinguish between classes of subjects in which there was moderate or severe injury. This proposed method provides quantitative regional 3D estimates of left ventricular deformation from three-dimensional sequences of Magnetic Resonance, Ultrasound, and X-Ray CT images.

BibTeX Entry

@PhDthesis(PapademetrisThesis,
author =  "Xenophon Papademetris",
title =   "Estimation of 3D Left Ventricular Deformation 
           from Medical Images Using Biomechanical Models.",
school =  "Yale University",
month =   "May",
year =    "2000")









 
 


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