Hepatic steatosis assessment using quantitative ultrasound parametric imaging based on backscatter envelope statistics

  • Zhuhuang Zhou
  • , Qiyu Zhang
  • , Weiwei Wu
  • , Shuicai Wu*
  • , Po Hsiang Tsui
  • *Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

32 Scopus citations

Abstract

Hepatic steatosis is a key manifestation of non-alcoholic fatty liver disease (NAFLD). Early detection of hepatic steatosis is of critical importance. Currently, liver biopsy is the clinical golden standard for hepatic steatosis assessment. However, liver biopsy is invasive and associated with sampling errors. Ultrasound has been recommended as a first-line diagnostic test for the management of NAFLD. However, B-mode ultrasound is qualitative and can be affected by factors including image post-processing parameters. Quantitative ultrasound (QUS) aims to extract quantified acoustic parameters from the ultrasound backscattered signals for ultrasound tissue characterization and can be a complement to conventional B-mode ultrasound. QUS envelope statistics techniques, both statistical model-based and non-model-based, have shown potential for hepatic steatosis characterization. However, a state-of-the-art review of hepatic steatosis assessment using envelope statistics techniques is still lacking. In this paper, envelope statistics-based QUS parametric imaging techniques for characterizing hepatic steatosis are reviewed and discussed. The reviewed ultrasound envelope statistics parametric imaging techniques include acoustic structure quantification imaging, ultrasound Nakagami imaging, homodyned-K imaging, kurtosis imaging, and entropy imaging. Future developments are suggested.

Original languageEnglish
Article number661
JournalApplied Sciences (Switzerland)
Volume9
Issue number4
DOIs
StatePublished - 15 02 2019

Bibliographical note

Publisher Copyright:
© 2019 by the authors.

Keywords

  • Envelope statistics
  • Hepatic steatosis
  • Noninvasive assessment
  • Parametric imaging
  • Quantitative ultrasound
  • Ultrasound tissue characterization

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