Computer-aided assessment of hepatic contour abnormalities as an imaging biomarker for the prediction of hepatocellular carcinoma development in patients with chronic hepatitis C. Issue 5 (May 2015)

• Record Type: Journal Article
• Authors: Goshima, Satoshi; Kanematsu, Masayuki; Kondo, Hiroshi; Watanabe, Haruo; Noda, Yoshifumi; Fujita, Hiroshi; Bae, Kyongtae T.
• Is Part Of: European journal of radiology. Volume 84:Issue 5(2015)
• Page Start: 811
• Page End: 815
• Publication Date: 2015-05
• Subjects: MRI -- Liver -- Gadoxetic-acid -- Cirrhosis -- HCC; Medical radiology -- Periodicals; Radiology -- Periodicals; Radiologie médicale -- Périodiques; Medical radiology; Periodicals; 616.075705
• DOI: 10.1016/j.ejrad.2015.01.009
• Languages: English
• ISSNs: 0720-048X

Abstract

Highlights: Hepatic contour was quantified and converted to hepatic fibrosis index (HFI). HFI was a significant risk factor for HCC with an odds ratio of 26.4. HFI may be an important imaging biomarker for managing cirrhotic patients. Abstract: Purpose: To evaluate whether a hepatic fibrosis index (HFI), quantified on the basis of hepatic contour abnormality, is a risk factor for the development of hepatocellular carcinoma (HCC) in patients with chronic hepatitis C. Materials and methods: Our institutional review board approved this retrospective study and written informed consent was waved. During a 14-month period, consecutive 98 patients with chronic hepatitis C who had no medical history of HCC treatment (56 men and 42 women; mean age, 70.7 years; range, 48–91 years) were included in this study. Gadoxetic acid-enhanced hepatocyte specific phase was used to detect and analyze hepatic contour abnormality. Hepatic contour abnormality was quantified and converted to HFI using in-house proto-type software. We compared HFI between patients with ( n = 54) and without HCC ( n = 44). Serum levels of albumin, total bilirubin, aspartate transferase, alanine transferase, percent prothrombin time, platelet count, alpha-fetoprotein, protein induced by vitamin K absence-II, and HFI were tested as possible risk factors for the development of HCC by determining the odds ratio with logistic regression analysis. Results: HFIs were significantly higher in patients with HCC (0.58 ± 0.86) than those without (0.36 ± 0.11) ( P < 0.001). Logistic analysis revealed that only HFI was a significant risk factor for HCC development with an odds ratio (95% confidence interval) of 26.4 (9.0–77.8) using a cutoff value of 0.395. Conclusion: The hepatic fibrosis index, generated using a computer-aided assessment of hepatic contour abnormality, may be a useful imaging biomarker for the prediction of HCC development in patients with chronic hepatitis C.