Magnetic resonance elastography for staging liver fibrosis in chronic hepatitis C

Magn Reson Med Sci. 2012;11(4):291-7. doi: 10.2463/mrms.11.291.

Abstract

Purpose: We evaluated the use of magnetic resonance (MR) elastography (MRE) for staging liver fibrosis in patients with chronic hepatitis C and compared the ability of MRE and serum fibrosis markers for discriminating each stage of fibrosis.

Methods: We evaluated 114 patients with chronic hepatitis C in whom the pathological fibrosis stage was determined (fibrosis stage 0 [F0], 3; F1, 15; F2, 28; F3, 25; and F4, 43). All patients underwent MRE using a 1.5-tesla MR system and pneumatic driver system. We measured stiffness values (kPa) of the liver in a circular region of interest placed on elastograms. We determined the optimal cutoff value and diagnostic ability for discriminating each stage of fibrosis using receiver operating characteristic (ROC) curve analysis and compared the discriminative ability of MRE with that of serum fibrosis markers.

Results: The mean stiffness values of the liver increased with stage of fibrosis: F0, 2.10±0.10 kPa; F1, 2.42±0.29 kPa; F2, 3.16±0.32 kPa; F3, 4.21±0.78 kPa; and F4, 6.20±1.08 kPa. The mean area under the ROC curve (Az) values for discriminating liver fibrosis stages were: ≥F1, 0.984 (95% confidence interval, 0.933-0.996); ≥F2, 0.986 (0.956-0.996); ≥F3, 0.973 (0.935-0.989); and ≥F4, 0.976 (0.945-0.990). The Az values for discriminating fibrosis stages were significantly higher for MRE than serum fibrosis markers.

Conclusion: MRE is a reliable technique for staging liver fibrosis and discriminating liver fibrosis stages in patients with chronic hepatitis C.

MeSH terms

  • Aged
  • Biomarkers / blood
  • Elasticity Imaging Techniques / methods*
  • Female
  • Hepatitis C, Chronic / blood
  • Hepatitis C, Chronic / complications
  • Hepatitis C, Chronic / pathology*
  • Humans
  • Liver / pathology
  • Liver Cirrhosis / blood
  • Liver Cirrhosis / complications
  • Liver Cirrhosis / diagnosis*
  • Male
  • Middle Aged
  • ROC Curve
  • Retrospective Studies
  • Severity of Illness Index

Substances

  • Biomarkers