title: 2-D left ventricular flow estimation by combining speckle tracking with Navier-Stokes-based regularization: an in silico, in vitro and in vivo study.
abstract: Despite the availability of multiple ultrasound approaches to left ventricular (LV) flow characterization in two dimensions, this technique remains in its childhood and further developments seem warranted. This article describes a new methodology for tracking the 2-D LV flow field based on ultrasound data. Hereto, a standard speckle tracking algorithm was modified by using a dynamic kernel embedding Navier-Stokes-based regularization in an iterative manner. The performance of the proposed approach was first quantified in synthetic ultrasound data based on a computational fluid dynamics model of LV flow. Next, an experimental flow phantom setup mimicking the normal human heart was used for experimental validation by employing simultaneous optical particle image velocimetry as a standard reference technique. Finally, the applicability of the approach was tested in a clinical setting. On the basis of the simulated data, pointwise evaluation of the estimated velocity vectors correlated well (mean r = 0.84) with the computational fluid dynamics measurement. During the filling period of the left ventricle, the properties of the main vortex obtained from the proposed method were also measured, and their correlations with the reference measurement were also calculated (radius, r = 0.96; circulation, r = 0.85; weighted center, r = 0.81). In vitro results at 60 bpm during one cardiac cycle confirmed that the algorithm properly measures typical characteristics of the vortex (radius, r = 0.60; circulation, r = 0.81; weighted center, r = 0.92). Preliminary qualitative results on clinical data revealed physiologic flow fields.
authors.affiliation: Lab on Cardiovascular Imaging and Dynamics, KU Leuven, Leuven, Belgium. Electronic address: hang.gao@uzleuven.be.
authors.forename: Hang
authors.initials: H
authors.lastname: Gao
authors.affiliation: Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
authors.forename: Nathalie
authors.initials: N
authors.lastname: Bijnens
authors.affiliation: University Hospital of Poitiers-Hospital of La Miletrie, Poitiers, France.
authors.forename: Damien
authors.initials: D
authors.lastname: Coisne
authors.affiliation: Université de La Rochelle, La Rochelle, France.
authors.forename: Mathieu
authors.initials: M
authors.lastname: Lugiez
authors.affiliation: Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
authors.forename: Marcel
authors.initials: M
authors.lastname: Rutten
authors.affiliation: Lab on Cardiovascular Imaging and Dynamics, KU Leuven, Leuven, Belgium.
authors.forename: Jan
authors.initials: J
authors.lastname: D'hooge
mesh_terms: D000465:Algorithms; D001783:Blood Flow Velocity / Q000502:physiology*; D003198:Computer Simulation; D015150:Echocardiography, Doppler / Q000295:instrumentation / Q000379:methods*; D006352:Heart Ventricles / Q000000981:diagnostic imaging*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008955:Models, Cardiovascular; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016277:Ventricular Function, Left / Q000502:physiology*
keywords: Blood flow field; Cardiovascular system; Echo particle image velocimetry; Echocardiography; Image processing; Motion estimation; Optical particle image velocimetry; Speckle tracking