2012 Proceedings - International Tissue Elasticity Conference

60
Session CVE–1: Cardiovascular Elasticity – I
Wednesday, October 3 2:45P – 4:00P
020 MULTI–BAND CONFIDENCE PROCESSING FOR TWO–PASS SPECKLE TRACKING IN
ECHOCARDIOGRAPHY.
Emily Y. Wong 1 , Colin B. Compas 2 , Ben A. Lin 2 , Albert J. Sinusas 2 , James S. Duncan 2 ,
Matthew O’Donnell 1 .
1 University of Washington, Seattle, WA, USA; 2 Yale University, New Haven, CT, USA.
Background: In myocardial strain imaging using ultrasound speckle tracking, large interframe strains
can cause significant peak–hopping artifacts. An iterative, or multi–pass, process for speckle tracking,
using displacement estimates from the previous pass as an initial guess for a subsequent pass, can
improve displacement accuracy if initial guesses are close to the true correlation coefficient peak [1,2].
Different peak–hopping patterns are observed when speckle tracking is performed on different frequency
components of the radiofrequency (RF) data.
Aims: The goal is to reduce peak–hopping artifacts using a two–pass approach in combination with a
multi–band confidence algorithm to assess the quality of the displacement guess at each pixel by
comparing correlation results from multiple sub–bands.
Methods: In this study, RF data were acquired from the anterior wall of the left ventricle in an
open–chest dog using a commercial 2–D phased array (iE33, Philips, Andover, MA). RF images were
filtered into five frequency bands (centered about 2.0–4.0MHz). In the first pass, 2–D phase–sensitive
correlation–based tracking (search region 33x9 pixels (axial x lateral)) was applied to adjacent frames of
the broadband image and each sub–band image to produce six sets of 2–D displacement estimates.
Following the first pass, a confidence index was found for each pixel based on the number of sub–bands
with matching displacement estimates, the magnitude of the correlation coefficient and estimated strain
values. Cubic interpolation was performed between pixels in the broadband image for which the
confidence weight exceeded a threshold. Second pass tracking using the resultant displacements was
performed with a small search region (5x3 pixels (axial x lateral)) to reduce peak–hopping (resolution of
0.2mm and 2.5º (axial and azimuthal)). Displacements were compared to results from a single pass
approach using identical tracking resolution.
Results: The two–pass approach with multi–band selection criteria reduced peak–hopping compared to
the single pass method without sacrificing spatial resolution. With the two–pass method, the variance of
the interframe displacement was reduced by 42% axially and 60% laterally. The variance of axial and
lateral displacements accumulated from end diastole to peak systole (Figure 1) was reduced by 57% and
87%, respectively.
Conclusions: Two–pass multi–band confidence processing can improve the quantification of myocardial
deformation using speckle tracking and may be valuable in the assessment of cardiac function using
echocardiography.
Acknowledgements: This work was supported by NIH Grant 5R01HL082640–04.
Figure 1: Accumulated axial
displacements for an
open–chest canine
experiment using
(A) single pass and
(B) multi–band
two–pass methods.
References:
[1] Yeung, et al.: Multilevel and Motion Model–Based Ultrasonic Speckle Tracking Algorithms. Ultrasound Med Biol,
24, pp. 427–441, 1998.
[2] Chen, et al.: Improvement of Elastographic Displacement Estimation Using A Two–Step Cross–Correlation
Method. Ultrasound Med Biol, 33, pp. 48–56, 2007.
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