Abstract
Liver fibrosis is an important pathological precondition for hepatocellular carcinoma. The degree of hepatic fibrosis is positively correlated with liver cancer. Liver fibrosis is a series of pathological and physiological process related to liver cell necrosis and degeneration after chronic liver injury, which finally leads to extracellular matrix and collagen deposition. The early detection and precise staging of fibrosis and cirrhosis are very important for early diagnosis and timely initiation of appropriate therapeutic regimens. The risk of severe liver fibrosis finally progressing to liver carcinoma is >50%. It is known that biopsy is the gold standard for the diagnosis and staging of liver fibrosis. However, this method has some limitations, such as the potential for pain, sampling variability, and low patient acceptance. Furthermore, the necessity of obtaining a tissue diagnosis of liver fibrosis still remains controversial. An increasing number of reliable non-invasive approaches are now available that are widely applied in clinical practice, mostly in cases of viral hepatitis, resulting in a significantly decreased need for liver biopsy. In fact, the non-invasive detection and evaluation of liver cirrhosis now has good accuracy due to current serum markers, ultrasound imaging, and magnetic resonance imaging quantification techniques. A prominent advantage of the non-invasive detection and assessment of liver fibrosis is that liver fibrosis can be monitored repeatedly and easily in the same patient. Serum biomarkers have the advantages of high applicability (>95%) and good reproducibility. However, their results can be influenced by different patient conditions because none of these markers are liver-specific. The most promising techniques appear to be transient elastography and magnetic resonance elastography because they provide reliable results for the detection of fibrosis in the advanced stages, and future developments promise to increase the reliability and accuracy of the staging of hepatic fibrosis. This article aims to describe the recent progress in the development of non-invasive assessment methods for the staging of liver fibrosis, with a special emphasize on computer-aided quantitative and deep learning methods.