Automated liver stiffness measurements with magnetic resonance elastography

Bogdan Dzyubak, Kevin Glaser, Meng Yin, Jayant Talwalkar, Jun Chen, Armando Manduca, Richard L. Ehman

Research output: Contribution to journalArticlepeer-review

39 Scopus citations


Purpose To provide a fully automated algorithm for obtaining stiffness measurements from hepatic magnetic resonance elastography (MRE) images that are consistent with measurements performed by expert readers. Materials and Methods An initial liver contour was found using an adaptive threshold and expanded using an active contour to select a homogeneous area of the liver. The confidence map generated during the stiffness calculation was used to select a region of reliable wave propagation. The average stiffness within the automatically generated region of interest (ROI) was compared to measurements by two trained readers in a set of 88 clinical test cases ranging from healthy to severely fibrotic. Results The stiffness measurements reported by the readers differed by -6.76% ± 22.8% (95% confidence) and had an intraclass correlation coefficient (ICC) of 0.972 (P < 0.05). The algorithm and the more experienced reader differed by 4.32% ± 14.9 with an ICC of 0.987. Conclusion The automated algorithm performed reliably, even though MRE acquisitions often have motion artifacts present. The correlation between the automated measurements and those from the trained readers was superior to the correlation between the readers. © 2013 Wiley Periodicals, Inc.

Original languageEnglish (US)
Pages (from-to)371-379
Number of pages9
JournalJournal of Magnetic Resonance Imaging
Issue number2
StatePublished - Aug 2013


  • MR elastography
  • automation
  • hepatic fibrosis
  • liver
  • segmentation

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging


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