title: Comparison of cardiac displacement and strain imaging using ultrasound radiofrequency and envelope signals.
abstract: Echocardiographic strain imaging is a promising new method for quantifying and displaying the health of cardiac muscle. Accurate regional myocardial function analysis requires high spatial and temporal resolution in addition to fidelity to the underlying deformation. However, all current clinical approaches use speckle-tracking algorithms applied to B-mode images derived from envelope signals. Such approaches are inherently of lower spatial resolution, since they require larger data blocks for deformation tracking due to the absence of phase information. In this paper, we compare the strain estimation performance using B-mode, envelope and radiofrequency signals, utilizing data acquired from a uniformly elastic tissue mimicking phantom, cardiac simulation, and clinical in vivo data. Signal-to-noise ratio improvements using radiofrequency signals for linear and phased array geometries were 5.80 dB and 9.48 dB over that obtained with envelope signals (at peak strain) in phantom studies, respectively. Cardiac simulation studies demonstrate that when averaged over the two cardiac cycles, the mean standard deviation of estimated strain using envelope signals from two of the six segments for a short-axes view (anterior and anterolateral) were 48% and 44% higher than that obtained using radiofrequency signals. These segments were chosen since one was along while the other was situated lateral to the beam propagation direction. In a similar manner, in vivo analysis on a volunteer also indicate that the standard deviation of the estimated strain using B-mode and envelope signals were 16% and 42% higher than that obtained using radiofrequency signals in the anteroseptal segment, and 45% and 27% in the anterior segment. These results demonstrate the significant reduction in the variability of strain estimated along with improvements in the spatial resolution and signal-to-noise ratios obtained using radiofrequency signals.
authors.affiliation: Department of Medical Physics, University of Wisconsin-Madison, Madison, WI 53705, United States. cma8@wisc.edu
authors.forename: Chi
authors.initials: C
authors.lastname: Ma
authors.forename: Tomy
authors.initials: T
authors.lastname: Varghese
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D004285:Dogs; D004452:Echocardiography / Q000379:methods*; D054459:Elasticity Imaging Techniques / Q000379:methods*; D020342:Finite Element Analysis; D006321:Heart / Q000502:physiology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D019047:Phantoms, Imaging; D014159:Transducers