title: A maximum likelihood approach to diffeomorphic speckle tracking for 3D strain estimation in echocardiography.
abstract: The strain and strain-rate measures are commonly used for the analysis and assessment of regional myocardial function. In echocardiography (EC), the strain analysis became possible using Tissue Doppler Imaging (TDI). Unfortunately, this modality shows an important limitation: the angle between the myocardial movement and the ultrasound beam should be small to provide reliable measures. This constraint makes it difficult to provide strain measures of the entire myocardium. Alternative non-Doppler techniques such as Speckle Tracking (ST) can provide strain measures without angle constraints. However, the spatial resolution and the noisy appearance of speckle still make the strain estimation a challenging task in EC. Several maximum likelihood approaches have been proposed to statistically characterize the behavior of speckle, which results in a better performance of speckle tracking. However, those models do not consider common transformations to achieve the final B-mode image (e.g. interpolation). This paper proposes a new maximum likelihood approach for speckle tracking which effectively characterizes speckle of the final B-mode image. Its formulation provides a diffeomorphic scheme than can be efficiently optimized with a second-order method. The novelty of the method is threefold: First, the statistical characterization of speckle generalizes conventional speckle models (Rayleigh, Nakagami and Gamma) to a more versatile model for real data. Second, the formulation includes local correlation to increase the efficiency of frame-to-frame speckle tracking. Third, a probabilistic myocardial tissue characterization is used to automatically identify more reliable myocardial motions. The accuracy and agreement assessment was evaluated on a set of 16 synthetic image sequences for three different scenarios: normal, acute ischemia and acute dyssynchrony. The proposed method was compared to six speckle tracking methods. Results revealed that the proposed method is the most accurate method to measure the motion and strain with an average median motion error of 0.42 mm and a median strain error of 2.0 ± 0.9%, 2.1 ± 1.3% and 7.1 ± 4.9% for circumferential, longitudinal and radial strain respectively. It also showed its capability to identify abnormal segments with reduced cardiac function and timing differences for the dyssynchrony cases. These results indicate that the proposed diffeomorphic speckle tracking method provides robust and accurate motion and strain estimation.
authors.affiliation: Laboratorio de Procesado de Imagen (LPI), E.T.S. Ingenieros de Telecomunicación, Universidad de Valladolid, Valladolid, Spain. Electronic address: ariel@lpi.tel.uva.es.
authors.forename: Ariel H
authors.initials: AH
authors.lastname: Curiale
authors.affiliation: Applied Chest Imaging Laboratory (ACIL), Brigham and Womens Hospital, Harvard Medical School, 1249 Boylston St., Boston, MA 02115, USA; Biomedical Image Technologies Laboratory (BIT), ETSI Telecomunicacion, Universidad Politecnica de Madrid, and CIBER-BBN, Avenida Complutense 30, Madrid, 28040, Spain.
authors.forename: Gonzalo
authors.initials: G
authors.lastname: Vegas-Sánchez-Ferrero
authors.affiliation: Thoraxcenter Biomedical Engineering, Erasmus University Medical Center, Rotterdam, The Netherlands.
authors.forename: Johan G
authors.initials: JG
authors.lastname: Bosch
authors.affiliation: Laboratorio de Procesado de Imagen (LPI), E.T.S. Ingenieros de Telecomunicación, Universidad de Valladolid, Valladolid, Spain.
authors.forename: Santiago
authors.initials: S
authors.lastname: Aja-Fernández
mesh_terms: D000465:Algorithms; D003627:Data Interpretation, Statistical; D019560:Echocardiography, Three-Dimensional / Q000379:methods*; D055119:Elastic Modulus; D054459:Elasticity Imaging Techniques / Q000379:methods; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016013:Likelihood Functions; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D018487:Ventricular Dysfunction, Left / Q000000981:diagnostic imaging* / Q000503:physiopathology*
keywords: Diffeomorphic registration; Maximum likelihood; Mixture model; Speckle tracking; Strain and motion estimation