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Compensated hepatitis C: Unenhanced MR imaging correlated with pathologic grading and staging

  • Donald G. Mitchell
  • , Victor J. Navarro
  • , Steven K. Herrine
  • , Diane Bergin
  • , Laurence Parker
  • , Andrea Frangos
  • , Peter McCue
  • , Raphael Rubin

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Background: We prospectively examined unenhanced MR imaging findings in relation to pathologic fibrosis, inflammation and steatosis in patients with compensated chronic hepatitis C viral infection (HCV). Methods: Unenhanced MRI at 1.5 T was obtained within one month of core liver biopsy in 64 consecutive candidates for antiviral therapy for compensated HCV. Two pathologists independently graded inflammatory activity index (HAI) and steatosis, and staged fibrosis (grades 0-6). Morphologic MRI findings of cirrhosis, periportal lymph nodes, and MR fat signal ratio from dual gradient echo images were assessed independently by two radiologists blinded to clinical data. MRI and laboratory liver function results were correlated with pathologic results, using Spearman correlation coefficient and stepwise multiple regression. Results: MR fat signal ratio correlation coefficient with pathologic steatosis was 0.71 (p < 0.0001). Coefficients with fibrosis stage were highest for surface nodularity (r s = 47, p < 0.0001) and expanded gallbladder fossa (r s = 0.42, p = 0.0006). Coefficients with HAI were highest for lymph node size (r s = 0.355, p = 0.0040), surface nodularity (r = 0.47, p < 0.0001), expanded gallbladder fossa (r = 0.332, p = 0.0073), and caudate/right lobe ratio (r = 0.326, p = 0.0110). Combined lab and MRI variables provided the best prediction of fibrosis stage (r 2 = 0.656) and HAI (r 2 = 0.597). Conclusions: A combination of MRI and laboratory findings was most predictive of fibrosis and inflammation.

Original languageEnglish
Pages (from-to)58-64
Number of pages7
JournalAbdominal Imaging
Volume33
Issue number1
DOIs
StatePublished - Jan 2008

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Cirrhosis
  • Hepatitis
  • Liver
  • MRI

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