Noninvasive hepatic fibrosis staging using mr elastography: The usefulness of the bayesian prediction method

J Magn Reson Imaging. 2017 Aug;46(2):375-382. doi: 10.1002/jmri.25551. Epub 2016 Nov 9.


Purpose: To evaluate the usefulness of the Bayesian method for hepatic fibrosis staging with magnetic resonance elastography (MRE).

Materials and methods: The sample of this retrospective study comprised patients with chronic liver disease (n = 309), in whom histopathological fibrosis staging and MRE using either a 1.5T (n = 214) or a 3T magnetic resonance imaging (MRI) system (n = 95) had been performed. The optimal cutoff stiffness value was determined and used to calculate the discrimination ability of fibrosis staging by the cutoff method. The Bayesian method calculated post-MRE probability of each fibrosis stage, yielding MRE-based fibrosis staging without a cutoff value as well as the confidence of staging. We compared the discrimination ability in all patients and in a subgroup of patients with high (≥90%) posterior probability.

Results: The discrimination ability for hepatic fibrosis staging was comparable between the Bayesian method and the cutoff method in all patients because the accuracy of staging with the Bayesian method and the cutoff method in all patients was not different (P = 1.0000). However, in patients with high posterior probability by the Bayesian method, the accuracy of staging with the Bayesian method was significantly improved compared with that of the cutoff method in all patients; for discriminating stage ≥F2 from F0-F1 (98.9% vs. 94.8%, P = 0.0069); for ≥F3 (99.6% vs. 92.6%, P < 0.0001); and for F4 (100% vs. 94.2%, P = 0.0002).

Conclusion: The Bayesian method has a highly accurate discrimination ability for noninvasive hepatic fibrosis staging using MRE, if the posterior probability is high.

Level of evidence: 3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:375-382.

Keywords: hepatic fibrosis; magnetic resonance elastography; posterior probability; stiffness; the Bayesian method.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Bayes Theorem
  • Elasticity Imaging Techniques*
  • Female
  • Humans
  • Image Interpretation, Computer-Assisted*
  • Liver Cirrhosis / diagnostic imaging*
  • Liver Cirrhosis / pathology
  • Magnetic Resonance Imaging*
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • Probability
  • ROC Curve
  • Reproducibility of Results
  • Retrospective Studies
  • Sensitivity and Specificity
  • Young Adult