Physical and geometrical modeling for image-based recovery of left ventricular deformation.

Information about left ventricular (LV) mechanical performance is of critical importance in understanding the etiology of ischemic heart disease. Regional measurements derived from non-invasive imaging to assist in assessing this performance have been in use for decades, and certain parameters derived from these measurements often are useful clinically, as they correlate to some extent with gross physiological hypotheses. However, relatively little work has been done to date to carefully understand the relationship of regional myocardial injury to the local mechanical performance of the heart as derived from image data acquired non-invasively for a particular patient in 3 spatial dimensions over time. This paper describes efforts to take advantage of recent developments in 3D non-invasive imaging and biomechanical modeling to design an integrated computational platform capable of assembling a variety of displacement and velocity data derived from each image frame to deform a volumetric model representation of a portion of the myocardium. A brief description of the reasoning behind this strategy an overview of the approach and some initial results are described.

[1]  C. Kambhamettu,et al.  Curvature-based approach to point correspondence recovery in conformal nonrigid motion , 1994 .

[2]  Jerry L Prince,et al.  3D displacement field reconstruction from planar tagged cardiac MR images , 1994, Proceedings of IEEE Workshop on Biomedical Image Analysis.

[3]  N B Ingels,et al.  Measurement of Midwall Myocardial Dynamics in Intact Man by Radiography of Surgically Implanted Markers , 1975, Circulation.

[4]  J. Dieudonné,et al.  Gradients de directions et de déformations principales dans la paroi ventriculaire gauche normale. , 1969 .

[5]  H. Saunders Book Reviews : NUMERICAL METHODS IN FINITE ELEMENT ANALYSIS K.-J. Bathe and E.L. Wilson Prentice-Hall, Inc, Englewood Cliffs, NJ , 1978 .

[6]  François G. Meyer,et al.  TRACKING MYOCARDIAL DEFORMATION USING SPATIALLY-CONSTRAINED VELOCITIES , 1995 .

[7]  Alistair A. Young,et al.  Epicardial surface estimation from coronary angiograms , 1989, Comput. Vis. Graph. Image Process..

[8]  L. Axel,et al.  MR imaging of motion with spatial modulation of magnetization. , 1989, Radiology.

[9]  P. Dijk Direct cardiac NMR imaging of heart wall and blood flow velocity. , 1984 .

[10]  Nicholas Ayache,et al.  Tracking Points on Deformable Objects Using Curvature Information , 1992, ECCV.

[11]  C. Nastar,et al.  Classification of nonrigid motion in 3D images using physics-based vibration analysis , 1994, Proceedings of IEEE Workshop on Biomedical Image Analysis.

[12]  A. McCulloch,et al.  Passive material properties of intact ventricular myocardium determined from a cylindrical model. , 1991, Journal of biomechanical engineering.

[13]  E. Zerhouni,et al.  Noninvasive quantification of principal strains in normal canine hearts using tagged MRI images in 3-D. , 1993, The American journal of physiology.

[14]  D. Kraitchman,et al.  Deformable models for tagged MR images: reconstruction of two- and three-dimensional heart wall motion , 1994, Proceedings of IEEE Workshop on Biomedical Image Analysis.

[15]  R. Herfkens,et al.  Phase contrast cine magnetic resonance imaging. , 1991, Magnetic resonance quarterly.

[16]  Jerry L. Prince,et al.  Tag and contour detection in tagged MR images of the left ventricle , 1994, IEEE Trans. Medical Imaging.

[17]  A. Young,et al.  Three-dimensional motion and deformation of the heart wall: estimation with spatial modulation of magnetization--a model-based approach. , 1992, Radiology.

[18]  G. A. Klassen,et al.  Transmural myocardial deformation in the canine left ventricular wall , 1978 .

[19]  J. Duncan,et al.  Point – Tracked Quantitative Analysis of Left Ventricular Motion from 3 D Image Sequences , 2000 .

[20]  J C Gore,et al.  Development and evaluation of tracking algorithms for cardiac wall motion analysis using phase velocity MR imaging , 1994, Magnetic resonance in medicine.

[21]  F. G. Evans,et al.  Strength of biological materials , 1970 .

[22]  E L Bolson,et al.  Variability in the measurement of regional left ventricular wall motion from contrast angiograms. , 1983, Circulation.

[23]  V. Wedeen Magnetic resonance imaging of myocardial kinematics. technique to detect, localize, and quantify the strain rates of the active human myocardium , 1992, Magnetic resonance in medicine.

[24]  James S. Duncan,et al.  Point-tracked quantitative analysis of left ventricular surface motion from 3-D image sequences , 2000, IEEE Transactions on Medical Imaging.

[25]  Peter Hunter,et al.  Theory of heart , 1991 .

[26]  D. King,et al.  Three-dimensional echocardiography. Advances for measurement of ventricular volume and mass. , 1994, Hypertension.

[27]  Jinah Park,et al.  Deformable models with parameter functions: application to heart-wall modeling , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[28]  A. McCulloch,et al.  Non-homogeneous analysis of three-dimensional transmural finite deformation in canine ventricular myocardium. , 1991, Journal of biomechanics.

[29]  G A Klassen,et al.  Transmural myocardial deformation in the canine left ventricular wall. , 1978, The American journal of physiology.

[30]  G. D. Meier,et al.  Kinematics of the Beating Heart , 1980, IEEE Transactions on Biomedical Engineering.

[31]  Pengcheng Shi,et al.  Energy-minimizing deformable grids for tracking tagged MR cardiac images , 1992, Proceedings Computers in Cardiology.

[32]  G Osakada,et al.  Nonuniformity of inner and outer systolic wall thickening in conscious dogs. , 1985, The American journal of physiology.

[33]  Alex Pentland,et al.  Recovery of Nonrigid Motion and Structure , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[34]  L. Waldman,et al.  Multidimensional Measurement of Regional Strains in the Intact Heart , 1991 .

[35]  Y. Fung,et al.  Transmural Myocardial Deformation in the Canine Left Ventricle: Normal in Vivo Three‐Dimensional Finite Strains , 1985, Circulation research.

[36]  James S. Duncan,et al.  Toward reliable, noninvasive measurement of myocardial function from 4D images , 1994, Medical Imaging.

[37]  Fred L. Bookstein,et al.  A geometric foundation for the study of left ventricular motion: Some tensor considerations , 1985 .

[38]  Carolyn A. Bucholtz,et al.  Shape-based interpolation , 1992, IEEE Computer Graphics and Applications.

[39]  A D McCulloch,et al.  Nonhomogeneous analysis of epicardial strain distributions during acute myocardial ischemia in the dog. , 1993, Journal of biomechanics.

[40]  James S. Duncan,et al.  Tracking myocardial deformation using phase contrast MR velocity fields: a stochastic approach , 1996, IEEE Trans. Medical Imaging.

[41]  Edward L. Wilson,et al.  Numerical methods in finite element analysis , 1976 .

[42]  P. V. van Dijk Direct cardiac NMR imaging of heart wall and blood flow velocity. , 1984, Journal of computer assisted tomography.

[43]  James S. Duncan,et al.  Shape-based tracking of left ventricular wall motion , 1997, IEEE Transactions on Medical Imaging.

[44]  D N Firmin,et al.  Blood flow imaging by cine magnetic resonance. , 1986, Journal of computer assisted tomography.

[45]  James S. Duncan,et al.  A model-based integrated approach to track myocardial deformation using displacement and velocity constraints , 1995, Proceedings of IEEE International Conference on Computer Vision.

[46]  J D Humphrey,et al.  Biomechanical experiments on excised myocardium: theoretical considerations. , 1989, Journal of biomechanics.

[47]  James S. Duncan,et al.  Model-based deformable surface finding for medical images , 1996, IEEE Trans. Medical Imaging.