Diagnostic accuracy of texture analysis and machine learning for quantification of liver fibrosis in MRI: correlation with MR elastography and histopathology.

Journal: European radiology
Published Date: Aug 1, 2020

Abstract

OBJECTIVES: To compare the diagnostic accuracy of texture analysis (TA)-derived parameters combined with machine learning (ML) of non-contrast-enhanced T1w and T2w fat-saturated (fs) images with MR elastography (MRE) for liver fibrosis quantification.

Authors

  • Khoschy Schawkat
    Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland.
  • Alexander Ciritsis
    From the *Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland.
  • Sophie von Ulmenstein
    Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland.
  • Hanna Honcharova-Biletska
    University of Zurich, Zurich, Switzerland.
  • Christoph Jüngst
    University of Zurich, Zurich, Switzerland.
  • Achim Weber
    University of Zurich, Zurich, Switzerland.
  • Christoph Gubler
    University of Zurich, Zurich, Switzerland.
  • Joachim Mertens
    University of Zurich, Zurich, Switzerland.
  • Caecilia S Reiner
    Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland. caecilia.reiner@usz.ch.

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