• Cecilia Besa, Mathilde Wagner, Grace Lo, Sonja Gordic, Manjil Chatterji, Paul Kennedy, Ashley Stueck, Swan Thung, James Babb, Andrew Smith, and Bachir Taouli.
• Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
• J Magn Reson Imaging. 2018 Jun 1; 47 (6): 1552-1561.

BackgroundMultiparametric magnetic resonance imaging (mpMRI) combining different techniques such as MR elastography (MRE) has emerged as a noninvasive approach to diagnose and stage liver fibrosis with high accuracy allowing for anatomical and functional information.PurposeTo assess the diagnostic performance of mpMRI including qualitative and quantitative assessment of MRE, liver surface nodularity (LSN) measurement, hepatic enhancement ratios postgadoxetic acid, and serum markers (APRI, FIB-4) for the detection of liver fibrosis.Study TypeIRB-approved retrospective.SubjectsEighty-three adult patients.Field Strength/Sequence1.5T and 3.0T MR systems. MRE and T1 -weighted postgadoxetic acid sequences.AssessmentTwo independent observers analyzed qualitative color-coded MRE maps on a scale of 0-3. Regions of interest were drawn to measure liver stiffness on MRE stiffness maps and on pre- and postcontrast T1 -weighted images to measure hepatic enhancement ratios. Software was used to generate LSN measurements. Histopathology was used as the reference standard for diagnosis of liver fibrosis in all patients.Statistical TestsA multivariable logistic analysis was performed to identify independent predictors of liver fibrosis. Receiver operating characteristic (ROC) analysis evaluated the performance of each imaging technique for detection of fibrosis, in comparison with serum markers.ResultsLiver stiffness measured with MRE provided the strongest correlation with histopathologic fibrosis stage (r = 0.74, P < 0.001), and the highest diagnostic performance for detection of stages F2-F4, F3-F4, and F4 (areas under the curve [AUCs] of 0.87, 0.91, and 0.89, respectively, P < 0.001) compared to other methods. Qualitative assessment of MRE maps showed fair to good accuracy for detection of fibrosis (AUC range 0.76-0.84). Multivariable logistic analysis identified liver stiffness and FIB-4 as independent predictors of fibrosis with AUCs of 0.90 (F2-F4), 0.93 (F3-F4) and 0.92 (F4) when combined.Data ConclusionLiver stiffness measured with MRE showed the best performance for detection of liver fibrosis compared to LSN and gadoxetic acid uptake, with slight improvement when combined with FIB-4.Level Of Evidence3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1552-1561.© 2017 International Society for Magnetic Resonance in Medicine.

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