Published online Oct 28, 2014. doi: 10.3748/wjg.v20.i40.14568
Revised: January 10, 2014
Accepted: June 2, 2014
Published online: October 28, 2014
Processing time: 346 Days and 3.5 Hours
The goal of this review is to provide a comprehensive picture of the role, clinical applications and future perspectives of the most widely used non-invasive techniques for the evaluation of hepatitis B virus (HBV) infection. During the past decade many non-invasive methods have been developed to reduce the need for liver biopsy in staging fibrosis and to overcome whenever possible its limitations, mainly: invasiveness, costs, low reproducibility, poor acceptance by patients. Elastographic techniques conceived to assess liver stiffness, in particular transient elastography, and the most commonly used biological markers will be assessed against their respective role and limitations in staging hepatic fibrosis. Recent evidence highlights that both liver stiffness and some bio-chemical markers correlate with survival and major clinical end-points such as liver decompensation, development of hepatocellular carcinoma and portal hypertension. Thus the non-invasive techniques here discussed can play a major role in the management of patients with chronic HBV-related hepatitis. Given their prognostic value, transient elastography and some bio-chemical markers can be used to better categorize patients with advanced fibrosis and cirrhosis and assign them to different classes of risk for clinically relevant outcomes. Very recent data indicates that the combined measurements of liver and spleen stiffness enable the reliable prediction of portal hypertension and esophageal varices development.
Core tip: Several non-invasive techniques for the assessment of liver disease severity, including transient elastography and serological markers, have been developed to overcome the limitations and invasivity of liver biopsy. The application of these techniques in the setting of hepatitis B viral disease for both the assessment of liver fibrosis and the prediction of liver-related complications can lead to improved patient management.