Simultaneous estimation of shear elastic modulus and backscatter coefficient: Phantom and in human liver in vivo study

Julien Rouyer, Gabriela Torres, Carolina Amador, Matthew W Urban, Roberto Lavarello

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The use of quantitative ultrasound (QUS) parameters to characterize tissue has shown potential to improve current clinical diagnosis. However, most studies in QUS have used parameters derived from either ultrasonic compressional or low frequency shear wave in isolation, thereby discarding additional information these parameters may carry. In this study, the feasibility of estimating both shear wave speed (SWS) and backscatter coefficient (BSC) when using a unique data set is demonstrated both with physical phantoms and in vivo human liver data. The phantom results showed contrast values of 8.16 and 1.71 for BSC and SWS. The in vivo liver results for BSC and SWS were in good agreement with previously reported values in the literature. Therefore, these results demonstrate that multi-parameter tissue characterization using BSC and SWS have a promising potential to track changes in both microscopic and macroscopic properties of tissue.

Original languageEnglish (US)
Title of host publication2016 IEEE International Ultrasonics Symposium, IUS 2016
PublisherIEEE Computer Society
Volume2016-November
ISBN (Electronic)9781467398978
DOIs
StatePublished - Nov 1 2016
Event2016 IEEE International Ultrasonics Symposium, IUS 2016 - Tours, France
Duration: Sep 18 2016Sep 21 2016

Other

Other2016 IEEE International Ultrasonics Symposium, IUS 2016
CountryFrance
CityTours
Period9/18/169/21/16

Keywords

  • backscatter coefficient
  • quantitative ultrasound
  • shear wave speed

ASJC Scopus subject areas

  • Acoustics and Ultrasonics

Fingerprint Dive into the research topics of 'Simultaneous estimation of shear elastic modulus and backscatter coefficient: Phantom and in human liver in vivo study'. Together they form a unique fingerprint.

Cite this