Chronic liver diseases can lead to hepatic fibrosis, cirrhosis, the development of hepatocellular carcinoma, and contribute substantially to healthcare costs.1 Detection and grading of hepatic fibrosis currently requires a biopsy, which subjects the patient to a risk of serious complications.2 Liver surface nodularity reflects the presence of regenerative nodules and fibrous septa, which are the essential histologic findings for the diagnosis of cirrhosis.3, 4 Gadolinium ethoxybenzyl diethylenetriaminepentaacetic acid (Gd-EOB-DTPA) is a liver-specific magnetic resonance imaging (MRI) contrast medium and its hepatocyte-phase images yield excellent hepatic enhancement and the objective delineation of hepatic contour morphology. We thus conducted a computer-aided diagnosis algorithm based on the hepatic contour morphological features such as surface nodularity for predicting hepatic fibrosis stages.
Between February 2010 and January 2011, 87 patients (56 male, 31 female; age range, 39-85 years, hepatitis C in 72, hepatitis B in 12, alcohol abuse in 2, and cryptogenic in 1) with pathologically proven hepatic fibrosis stages underwent Gd-EOB-DTPA-enhanced MRI with a 3T superconducting system. Stage was determined by: hepatectomy (n = 32) to treat hepatic tumors or percutaneous liver biopsy (n = 55). Fibrosis stages were determined according to the established criteria5: F0 (n = 9); F1 (n = 16); F2 (n = 13); F3 (n = 21); and F4 (n = 28).
According to our algorithm (Fig. 1), the mean ± SD was significantly higher in patients with ≥F3 than with ≤F2 (P < 0.001, Tukey criterion). No significant difference was found among F0, F1, and F2. Although the mean ± SD of F4 was higher than that of F3 (P < 0.05), there was a considerable overlap in their distribution. Post-hoc power analysis showed that we had 80.9% power to detect a 15% difference in linear multiple regression analysis between fibrosis stages. Both the sensitivity and specificity of SD for the diagnosis of hepatic fibrosis stages ≥F3 were 100% using a cutoff value of 0.65 (Fig. 1c).
We have successfully applied a computer-aided analysis of hepatic contour that was highly accurate in diagnosing hepatic fibrosis stages F3 and F4 and may be a useful imaging biomarker for staging hepatic fibrosis.