Speckle Tracking in Intracardiac Echocardiography for the Assessment of Myocardial Deformation

Intracardiac echocardiography (ICE) has proven to be useful for online anatomical imaging during catheterization. Our objective was to develop a speckle tracking method for myocardial motion estimation from ICE image sequences in order to provide a mean for regional functional imaging. Our approach was to solve two problems in motion estimation from 2-D ICE image sequences: nonrigid myocardial deformation and speckle decorrelation. To achieve robust noise resistance, we employed maximum likelihood estimation while fully exploiting ultrasound speckle statistics, and treated the maximization of motion probability as the minimization of an energy function. Nonrigid myocardial deformation was estimated by optimizing this energy function within a framework of parametric elastic registration. Evaluation of the method was carried out using a computer model that synthesized echocardiographic image sequences, and subsequently an animal model that provided continuous ICE images as well as reference measurements using sonomicrometry crystals. In conclusion, accurate estimation of regional myocardial deformation from ICE by novel speckle tracking is feasible. This approach may have important clinical implications for multimodal imaging during catheterization.

[1]  Hirotsugu Yamada,et al.  Phased-Array Intracardiac Echocardiography Monitoring During Pulmonary Vein Isolation in Patients With Atrial Fibrillation: Impact on Outcome and Complications , 2003, Circulation.

[2]  M. Strintzis,et al.  Maximum likelihood motion estimation in ultrasound image sequences , 1997, IEEE Signal Processing Letters.

[3]  Xiaohui Hao,et al.  Characterization of reperfused infarcted myocardium from high-frequency intracardiac ultrasound imaging using homodyned K distribution , 2002, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[4]  P. Shankar.  A general statistical model for ultrasonic backscattering from tissues , 2000 .

[5]  Jorge Nocedal,et al.  Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization , 1997, TOMS.

[6]  Jan D’hooge,et al.  Experimental Validation of a New Ultrasound Method for the Simultaneous Assessment of Radial and Longitudinal Myocardial Deformation Independent of Insonation Angle , 2005, Circulation.

[7]  Roberto M. Lang,et al.  Volumetric Quantification of Global and Regional Left Ventricular Function From Real-Time Three-Dimensional Echocardiographic Images , 2005, Circulation.

[8]  Peter J. Huber,et al.  Robust Statistics , 2005, Wiley Series in Probability and Statistics.

[9]  Craig J. Hartley,et al.  A novel feature-tracking echocardiographic method for the quantitation of regional myocardial function: validation in an animal model of ischemia-reperfusion. , 2008, Journal of the American College of Cardiology.

[10]  David R. Haynor,et al.  PET-CT image registration in the chest using free-form deformations , 2003, IEEE Transactions on Medical Imaging.

[11]  M Tur,et al.  When is speckle noise multiplicative? , 1982, Applied optics.

[12]  K Isaaz,et al.  Quantitation of the motion of the cardiac base in normal subjects by Doppler echocardiography. , 1993, Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography.

[13]  Hemant D. Tagare,et al.  Evaluation of Four Probability Distribution Models for Speckle in Clinical Cardiac Ultrasound Images , 2006, IEEE Transactions on Medical Imaging.

[14]  Maxime Cannesson,et al.  Novel Speckle-Tracking Radial Strain From Routine Black-and-White Echocardiographic Images to Quantify Dyssynchrony and Predict Response to Cardiac Resynchronization Therapy , 2006, Circulation.

[15]  D P Strum,et al.  Quantitative assessment of alterations in regional left ventricular contractility with color-coded tissue Doppler echocardiography. Comparison with sonomicrometry and pressure-volume relations. , 1997, Circulation.

[16]  Gary E. Christensen,et al.  Consistent image registration , 2001, IEEE Transactions on Medical Imaging.

[17]  D L Packer,et al.  Global right atrial mapping of human atrial flutter: the presence of posteromedial (sinus venosa region) functional block and double potentials : a study in biplane fluoroscopy and intracardiac echocardiography. , 2000, Circulation.

[18]  Shunichi Homma,et al.  Parameterization of Left Ventricular Wall Motion for Detection of Regional Ischemia , 2005, Annals of Biomedical Engineering.

[19]  W. Frishman,et al.  Real-Time Three-Dimensional Echocardiography: A Novel Technique to Quantify Global Left Ventricular Mechanical Dyssynchrony , 2006 .

[20]  Liyun Rao,et al.  Dynamic three-dimensional visualization of the left ventricle by intracardiac echocardiography. , 2005, Ultrasound in medicine & biology.

[21]  Girish Dwivedi,et al.  Ventricular Untwisting Rate by Speckle Tracking Echocardiography” , 2008 .

[22]  R. F. Wagner,et al.  Statistics of Speckle in Ultrasound B-Scans , 1983, IEEE Transactions on Sonics and Ultrasonics.

[23]  Michael Unser,et al.  Myocardial motion analysis from B-mode echocardiograms , 2005, IEEE Transactions on Image Processing.

[24]  Kevin J. Parker,et al.  Feature-adaptive motion tracking of ultrasound image sequences using a deformable mesh , 1998, IEEE Transactions on Medical Imaging.

[25]  James F. Greenleaf,et al.  Adaptive speckle reduction filter for log-compressed B-scan images , 1996, IEEE Trans. Medical Imaging.

[26]  Nicholas Ayache,et al.  Unifying maximum likelihood approaches in medical image registration , 2000 .

[27]  Michael Unser,et al.  Spatio-temporal nonrigid registration for ultrasound cardiac motion estimation , 2005, IEEE Transactions on Medical Imaging.

[28]  Thor Edvardsen,et al.  Quantitative Assessment of Intrinsic Regional Myocardial Deformation by Doppler Strain Rate Echocardiography in Humans: Validation Against Three-Dimensional Tagged Magnetic Resonance Imaging , 2002, Circulation.

[29]  H. Torp,et al.  Myocardial Strain by Doppler Echocardiography: Validation of a New Method to Quantify Regional Myocardial Function , 2000, Circulation.

[30]  Its'hak Dinstein,et al.  New maximum likelihood motion estimation schemes for noisy ultrasound images , 2002, Pattern Recognit..

[31]  Renjie He,et al.  Integrated multimodal-catheter imaging unveils principal relationships among ventricular electrical activity, anatomy, and function. , 2008, American journal of physiology. Heart and circulatory physiology.

[32]  Michael Unser,et al.  Fast parametric elastic image registration , 2003, IEEE Trans. Image Process..

[33]  M. Lesh,et al.  Low‐Power Radiofrequency Application and Intracardiac Echocardiography for Creation of Continuous Left Atrial Linear Lesions , 1999, Journal of cardiovascular electrophysiology.

[34]  C. Lamberti,et al.  Evaluation of differential optical flow techniques on synthesized echo images , 1996, IEEE Transactions on Biomedical Engineering.

[35]  F. Marchlinski,et al.  Intracardiac echocardiography (9 MHz) in humans: methods, imaging views and clinical utility. , 1999, Ultrasound in medicine & biology.

[36]  Michael Brady,et al.  Velocity Estimation in Ultrasound Images: A Block Matching Approach , 2003, IPMI.

[37]  Wen-Chun Yeh,et al.  Tissue Motion and Elevational Speckle Decorrelation in Freehand 3D Ultrasound , 2002, Ultrasonic imaging.