Yonago Acta Medica
Online ISSN : 1346-8049
ISSN-L : 0513-5710
Original Article
Risk Assessment of Hepatocellular Carcinoma in General Population by Liver Stiffness in Combination with Controlled Attenuation Parameter using Transient Elastography: A Cross Sectional Study
Elastography in detecting high-risk liver diseases
Takaaki Sugihara Masahiko KodaTomomitsu MatonoKinya OkamotoYoshikazu MurawakiHajime IsomotoShiho Tokunaga
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JOURNAL OPEN ACCESS

2017 Volume 60 Issue 2 Pages 106-112

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Abstract
Background Hepatocellular carcinoma (HCC) in patients without hepatitis B (HBV) and -C virus (HCV) infection are increasing in Japan. Method for detecting high-risk liver diseases of HCC in general population has still not been established. Liver stiffness measurement (LSM) and Controlled Attenuation Parameter (CAP) using transient elastography (TE; FibroScan System) are useful for detecting liver fibrosis and steatosis. The aim of this study is to clarify TE for risk assessment of HCC in general population.
Methods This cross-sectional study was performed for residents aged ≥ 40 years in an intermountain town in Japan with a population of 3,493. Blood laboratory testing included tumor markers, abdominal ultrasound (AUS), and TE was performed.
Results Among 175 subjects (64 men, 111 women), TE was evaluated and three patients with HCC were detected by AUS. For detecting HCC, the cut-off value of LSM was 5.3 kPa sensitivity 100%, specificity 75%, AUROC 0.88). The combination of LSM and CAP (LSM > 5.3 kPa with any CAP and CAP > 248 dB/m with any LSM) could detect the high-risk liver diseases of HCC (HCC, nonalcoholic fatty liver/steatohepatitis, HBV or HCV related chronic viral hepatitis with alanine transaminase (ALT) > 30 IU/L for men or > 19 IU/L for women or cirrhosis of any cause) with high sensitivity (sensitivity 90%, specificity 55%, positive predictive value 10%, negative predictive value 99%, P = 0.006).
Conclusion The combination of LSM and CAP can be useful in detecting high-risk liver diseases of HCC out of general population.
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© 2017 Tottori University Faculty of Medicine
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