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Comparison of physiological motion filters for in vivo cardiac ARFI.

Publication ,  Journal Article
Giannantonio, DM; Dumont, DM; Trahey, GE; Byram, BC
Published in: Ultrasonic imaging
April 2011

Acoustic radiation force impulse (ARFI) imaging is being utilized to investigate mechanical properties ofcardiac tissue. The underlying physiological motion, however, presents a major challenge. This paper aims to investigate the effectiveness of various physiological motion filters using in vivo canine data with a simulated ARFI push pulse. Ideally, the motion filter will exactly model the physiological motion and, when subtracted from the total displacement, leave only the simulated ARFI displacement profile. We investigated three temporal quadratic motion filters: (1)interpolation, (2) extrapolation and (3) a weighted technique. Additionally, the various motion filters were compared when using 1-D versus 2-D autocorrelation methods to estimate motion. It was found that 2D-autocorrelation always produced better physiological motion estimates regardless of the type of filter used. The extrapolation filter gives the most accurate estimate of the physiological motion at times immediately after the ARFI push (0.1 ms) while a close-time interpolation filter using displacement estimates at times before full tissue recovery gives the most accurate estimates at later times after the ARFI push (0.7 ms). While improvements to the motion filter during atrial systole and the onset of ventricular systole are needed, the weighted, close-time interpolation and extrapolation motion filters all offer promising results for estimating cardiac physiological motion more accurately, while allowing faster ARFI frame rates than previous motion filters. This study demonstrates the ability to eliminate physiological motion in a clinically-feasible manner, opening the door for more extensive clinical experimentation.

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Published In

Ultrasonic imaging

DOI

EISSN

1096-0910

ISSN

0161-7346

Publication Date

April 2011

Volume

33

Issue

2

Start / End Page

89 / 108

Related Subject Headings

  • Signal Processing, Computer-Assisted
  • Myocardial Contraction
  • Least-Squares Analysis
  • Image Interpretation, Computer-Assisted
  • Elasticity Imaging Techniques
  • Dogs
  • Coronary Circulation
  • Animals
  • Acoustics
  • Acoustics
 

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Giannantonio, D. M., Dumont, D. M., Trahey, G. E., & Byram, B. C. (2011). Comparison of physiological motion filters for in vivo cardiac ARFI. Ultrasonic Imaging, 33(2), 89–108. https://doi.org/10.1177/016173461103300201
Giannantonio, Doug M., Douglas M. Dumont, Gregg E. Trahey, and Brett C. Byram. “Comparison of physiological motion filters for in vivo cardiac ARFI.Ultrasonic Imaging 33, no. 2 (April 2011): 89–108. https://doi.org/10.1177/016173461103300201.
Giannantonio DM, Dumont DM, Trahey GE, Byram BC. Comparison of physiological motion filters for in vivo cardiac ARFI. Ultrasonic imaging. 2011 Apr;33(2):89–108.
Giannantonio, Doug M., et al. “Comparison of physiological motion filters for in vivo cardiac ARFI.Ultrasonic Imaging, vol. 33, no. 2, Apr. 2011, pp. 89–108. Epmc, doi:10.1177/016173461103300201.
Giannantonio DM, Dumont DM, Trahey GE, Byram BC. Comparison of physiological motion filters for in vivo cardiac ARFI. Ultrasonic imaging. 2011 Apr;33(2):89–108.
Journal cover image

Published In

Ultrasonic imaging

DOI

EISSN

1096-0910

ISSN

0161-7346

Publication Date

April 2011

Volume

33

Issue

2

Start / End Page

89 / 108

Related Subject Headings

  • Signal Processing, Computer-Assisted
  • Myocardial Contraction
  • Least-Squares Analysis
  • Image Interpretation, Computer-Assisted
  • Elasticity Imaging Techniques
  • Dogs
  • Coronary Circulation
  • Animals
  • Acoustics
  • Acoustics