A spatiotemporal statistical atlas of motion for the quantification of abnormal myocardial tissue velocities

In this paper, we present a new method for the automatic comparison of myocardial motion patterns and the characterization of their degree of abnormality, based on a statistical atlas of motion built from a reference healthy population. Our main contribution is the computation of atlas-based indexes that quantify the abnormality in the motion of a given subject against a reference population, at every location in time and space. The critical computational cost inherent to the construction of an atlas is highly reduced by the definition of myocardial velocities under a small displacements hypothesis. The indexes we propose are of notable interest for the assessment of anomalies in cardiac mobility and synchronicity when applied, for instance, to candidate selection for cardiac resynchronization therapy (CRT). We built an atlas of normality using 2D ultrasound cardiac sequences from 21 healthy volunteers, to which we compared 14 CRT candidates with left ventricular dyssynchrony (LVDYS). We illustrate the potential of our approach in characterizing septal flash, a specific motion pattern related to LVDYS and recently introduced as a very good predictor of response to CRT.

[1]  Michael I. Miller,et al.  Time sequence diffeomorphic metric mapping and parallel transport track time-dependent shape changes , 2009, NeuroImage.

[2]  S. Shapiro,et al.  An Analysis of Variance Test for Normality (Complete Samples) , 1965 .

[3]  Alejandro F. Frangi,et al.  Automatic Construction of 3D Statistical Deformation Models Using Non-rigid Registration , 2001, MICCAI.

[4]  Olivier Clatz,et al.  Detection of DTI White Matter Abnormalities in Multiple Sclerosis Patients , 2008, MICCAI.

[5]  Daniel Rueckert,et al.  Fast Spatio-temporal Free-Form Registration of Cardiac MR Image Sequences , 2004, FIMH.

[6]  K. Worsley,et al.  Unified univariate and multivariate random field theory , 2004, NeuroImage.

[7]  Christophe Leclercq,et al.  Echocardiographic evaluation of cardiac resynchronization therapy: ready for routine clinical use? A critical appraisal. , 2004, Journal of the American College of Cardiology.

[8]  Marcel L Geleijnse,et al.  Usefulness of left ventricular systolic dyssynchrony by real-time three-dimensional echocardiography to predict long-term response to cardiac resynchronization therapy. , 2009, The American journal of cardiology.

[9]  Alejandro F Frangi,et al.  Automatic construction of 3-D statistical deformation models of the brain using nonrigid registration , 2003, IEEE Transactions on Medical Imaging.

[10]  Peter Hanrath,et al.  How to discriminate responders from non-responders to cardiac resynchronisation therapy , 2004 .

[11]  J. McMurray,et al.  Selecting patients for cardiac resynchronization therapy: electrical or mechanical dyssynchrony? , 2006, European heart journal.

[12]  Nicholas Ayache,et al.  A Log-Euclidean Framework for Statistics on Diffeomorphisms , 2006, MICCAI.

[13]  D. Delurgio,et al.  Effect of Cardiac Resynchronization Therapy on Left Ventricular Size and Function in Chronic Heart Failure , 2003, Circulation.

[14]  Jean Meunier,et al.  Average Brain Models: A Convergence Study , 2000, Comput. Vis. Image Underst..

[15]  H. Hotelling The Generalization of Student’s Ratio , 1931 .

[16]  Jeroen J. Bax,et al.  Assessment of left ventricular dyssynchrony by speckle tracking strain imaging comparison between longitudinal, circumferential, and radial strain in cardiac resynchronization therapy. , 2008, Journal of the American College of Cardiology.

[17]  Jorge Nocedal,et al.  A Limited Memory Algorithm for Bound Constrained Optimization , 1995, SIAM J. Sci. Comput..

[18]  Peter Boesiger,et al.  Left ventricular dyssynchrony in patients with left bundle branch block and patients after myocardial infarction: integration of mechanics and viability by cardiac magnetic resonance. , 2009, European heart journal.

[19]  J. Daubert,et al.  The effect of cardiac resynchronization on morbidity and mortality in heart failure. , 2005, The New England journal of medicine.

[20]  Nicolas Duchateau,et al.  Temporal Diffeomorphic Free-Form Deformation for Strain Quantification in 3D-US Images , 2010, MICCAI.

[21]  U. Grenander,et al.  Computational anatomy: an emerging discipline , 1998 .

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

[23]  Ali R. Khan,et al.  Representation of time-varying shapes in the large deformation diffeomorphic framework , 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[24]  Alain Trouvé,et al.  Diffeomorphisms Groups and Pattern Matching in Image Analysis , 1998, International Journal of Computer Vision.

[25]  Guido Gerig,et al.  Spatiotemporal Atlas Estimation for Developmental Delay Detection in Longitudinal Datasets , 2009, MICCAI.

[26]  Maja Cikes,et al.  Velocity and deformation imaging for the assessment of myocardial dysfunction. , 2008, European journal of echocardiography : the journal of the Working Group on Echocardiography of the European Society of Cardiology.

[27]  Alejandro F. Frangi,et al.  Large Diffeomorphic FFD Registration for Motion and Strain Quantification from 3D-US Sequences , 2009, FIMH.

[28]  Paul M. Thompson,et al.  Generalized Tensor-Based Morphometry of HIV/AIDS Using Multivariate Statistics on Deformation Tensors , 2008, IEEE Transactions on Medical Imaging.

[29]  Alejandro F Frangi,et al.  Computational cardiac atlases: from patient to population and back , 2009, Experimental physiology.

[30]  Simon K. Warfield,et al.  A Continuous STAPLE for Scalar, Vector, and Tensor Images: An Application to DTI Analysis , 2009, IEEE Transactions on Medical Imaging.

[31]  Alejandro F. Frangi,et al.  Cardiac Motion Estimation from Intracardiac Electrical Mapping Data: Identifying a Septal Flash in Heart Failure , 2009, FIMH.

[32]  Jens-Uwe Voigt,et al.  Rocking will tell it. , 2008, European heart journal.

[33]  P. Grenier,et al.  Quantification of myocardial function using tagged MR and cine MR images , 2004, The International Journal of Cardiovascular Imaging.

[34]  John N Oshinski,et al.  It's time for a paradigm shift in the quantitative evaluation of left ventricular dyssynchrony. , 2009, Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography.

[35]  Alejandro F. Frangi,et al.  A groupwise mutual information metric for cost efficient selection of a suitable reference in cardiac computational atlas construction , 2010, Medical Imaging.

[36]  H. Lilliefors On the Kolmogorov-Smirnov Test for Normality with Mean and Variance Unknown , 1967 .

[37]  Loring W. Tu,et al.  An introduction to manifolds , 2007 .

[38]  Alejandro F. Frangi,et al.  Septal Flash Assessment on CRT Candidates Based on Statistical Atlases of Motion , 2009, MICCAI.

[39]  Piet Claus,et al.  Toward understanding response to cardiac resynchronization therapy: left ventricular dyssynchrony is only one of multiple mechanisms. , 2009, European heart journal.

[40]  Daniel Rueckert,et al.  Diffeomorphic Registration Using B-Splines , 2006, MICCAI.

[41]  Kiyoshi Yoshida,et al.  Real-time 3-dimensional echocardiographic assessment of left ventricular dyssynchrony: pitfalls in patients with dilated cardiomyopathy. , 2009, JACC. Cardiovascular imaging.

[42]  Hervé Delingette,et al.  Registration of 4D Cardiac CT Sequences Under Trajectory Constraints With Multichannel Diffeomorphic Demons , 2010, IEEE Transactions on Medical Imaging.

[43]  Karl J. Friston,et al.  Voxel-Based Morphometry—The Methods , 2000, NeuroImage.

[44]  Nick C Fox,et al.  Computer-assisted imaging to assess brain structure in healthy and diseased brains , 2003, The Lancet Neurology.

[45]  Daniel Rueckert,et al.  Comparison of Cardiac Motion Fields from Tagged and Untagged MR Images Using Nonrigid Registration , 2005, FIMH.

[46]  Daniel Rueckert,et al.  Spatial transformation of motion and deformation fields using nonrigid registration , 2004, IEEE Transactions on Medical Imaging.

[47]  Bart Bijnens,et al.  Low-dose dobutamine stress echo to quantify the degree of remodelling after cardiac resynchronization therapy. , 2008, European heart journal.

[48]  Daniel Rueckert,et al.  Analysis of 3-D myocardial motion in tagged MR images using nonrigid image registration , 2004, IEEE Transactions on Medical Imaging.

[49]  Françoise J. Prêteux,et al.  Building and using a statistical 3D motion atlas for analyzing myocardial contraction in MRI , 2004, SPIE Medical Imaging.