Local Phase Velocity Based Imaging: A New Technique Used for Ultrasound Shear Wave Elastography

Piotr Kijanka, Matthew W. Urban

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Ultrasound shear wave elastography is an imaging modality for noninvasive evaluation of tissue mechanical properties. However, many current techniques overestimate lesions dimension or shape especially when small inclusions are taken into account. In this paper, we propose a new method called local phase velocity-based imaging (LPVI) as an alternative technique to measure tissue elasticity. Two separate acquisitions with ultrasound push beams focused once on the left side and once on the right side of the inclusion were generated. A local shear wave velocity is then recovered in the frequency domain (for a single frequency or frequency band) for both acquired data sets. Finally, a two-dimensional shear wave velocity map is reconstructed by combining maps from two separate acquisitions. Robust and accurate shear wave velocity maps are reconstructed using the proposed LPVI method in calibrated liver fibrosis tissue mimicking homogeneous phantoms, a calibrated elastography phantom with stepped cylinder inclusions and a homemade gelatin phantom with ex vivo porcine liver inclusion. Results are compared with an existing phase velocity-based imaging approach and a group velocity-based method considered as the state of the art. Results from the phantom study showed that increased frequency improved the shape of the reconstructed inclusions and contrast-to-noise ratio between the target and background.

Original languageEnglish (US)
Article number8485657
Pages (from-to)894-908
Number of pages15
JournalIEEE transactions on medical imaging
Volume38
Issue number4
DOIs
StatePublished - Apr 2019

Keywords

  • Shear wave elastography (SWE)
  • imaging
  • lesion
  • local wavenumber
  • phantom
  • soft tissue
  • ultrasound

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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