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

Area of Science:

• Radiology
• Hepatology
• Medical Imaging

Background:

• Chronic hepatitis C viral infection (HCV) is a significant cause of liver disease.
• Assessing liver fibrosis, inflammation, and steatosis is crucial for managing HCV.
• Unenhanced magnetic resonance imaging (MRI) offers a non-invasive approach to evaluate liver pathology.

Purpose of the Study:

• To investigate the correlation between unenhanced MRI findings and histopathologic features of liver disease in patients with compensated HCV.
• To determine the predictive value of specific MRI parameters for fibrosis, inflammation, and steatosis.
• To assess the combined diagnostic performance of MRI and laboratory tests in staging liver disease.

Main Methods:

• Prospective study of 64 patients with compensated HCV undergoing unenhanced MRI within one month of liver biopsy.
• Pathologic assessment of liver biopsy specimens for fibrosis, inflammation (HAI), and steatosis by two independent pathologists.
• Radiologic assessment of MRI scans for morphologic features (cirrhosis, lymph nodes, gallbladder fossa) and MR fat signal ratio by two independent radiologists.
• Correlation analysis using Spearman correlation and stepwise multiple regression to relate MRI findings and laboratory results to pathologic outcomes.

Main Results:

• MR fat signal ratio strongly correlated with pathologic steatosis (r=0.71, p<0.0001).
• Surface nodularity and expanded gallbladder fossa showed significant correlations with fibrosis stage (r=0.47 and r=0.42, respectively).
• Lymph node size, surface nodularity, expanded gallbladder fossa, and caudate/right lobe ratio correlated with inflammatory activity index (HAI).
• Combined laboratory and MRI variables achieved the highest prediction accuracy for fibrosis stage (R²=0.656) and HAI (R²=0.597).

Conclusions:

• Unenhanced MRI can non-invasively detect and quantify liver steatosis, fibrosis, and inflammation in patients with chronic hepatitis C.
• Specific MRI findings, such as surface nodularity and MR fat signal ratio, are valuable indicators of liver disease severity.
• Integrating MRI findings with laboratory results provides a robust, combined approach for predicting liver fibrosis and inflammation in HCV patients.