# Non-Invasive Assessment of Liver Fibrosis in Hepatitis B Patients

## TL;DR

This review discusses non-invasive tests for assessing liver fibrosis in hepatitis B patients, comparing their accuracy and usefulness against traditional methods like liver biopsy.

## Contribution

The paper provides an updated overview of non-invasive tests for liver fibrosis in hepatitis B, emphasizing their clinical utility and limitations.

## Key findings

- Non-invasive tests like APRI and FIB-4 are useful for initial fibrosis assessment but have limitations in accuracy.
- Elastography techniques offer better accuracy for advanced fibrosis but have variable cut-offs based on patient factors.
- Combining serum and imaging tests shows promise for improved fibrosis staging and prognosis in hepatitis B patients.

## Abstract

The aim of this review is to provide updated information on the clinical use of non-invasive serum and imaging-based tests for fibrosis assessment in chronic hepatitis B (CHB) virus infection. In recent years, non-invasive tests (NIT) have been increasingly used to determine eligibility for treatment. Liver biopsy is still considered the gold standard for assessing inflammatory activity and fibrosis staging, but it is an invasive procedure with inherent limitations. Simple serum markers such as APRI and FIB-4 are limited by indeterminate results but remain useful initial tests for fibrosis severity if imaging elastography is not available. Point-of-care US-based elastography techniques, such as vibration-controlled transient elastography or 2D shear wave elastography, are increasingly available and have better accuracy than simple serum tests for advanced fibrosis or cirrhosis, although stiffness cut-offs are variable based on E-antigen status and inflammatory activity. Current NITs have poor diagnostic performance for following changes in fibrosis with antiviral therapy. However, NITs may have greater clinical utility for determining prognosis in patients with CHB that have advanced disease, especially for the development of hepatocellular carcinoma and/or liver decompensation. Algorithms combining serum and imaging NITs appear promising for advanced fibrosis and prognostic risk stratification.