Non-invasive assessment of liver fibrosis and prognosis

Abstract

Over the past decade, several advances have been made in the non-invasive assessment of liver fibrosis. Both serum markers and imaging-based tissue elastography predict the presence of advanced fibrosis compared with liver biopsy. Serum markers may be indirect or direct markers of liver structure and function. Imaging-based techniques measure liver stiffness as a surrogate for fibrosis and include ultrasound and MRI-based methods. Most non-invasive techniques work well at identifying subjects at the extremes of fibrosis but may not accurately discern intermediate stages. In addition to being a diagnostic tool, elastography may have an evolving role in prognosis. Increasing stiffness is associated with higher rates of liver decompensation, need for transplantation, hepatocellular carcinoma, and death. There are special populations of patients where elastography may serve as a non-invasive method to impart useful clinical information, such as patients after liver transplantation, those with congenital heart disease and those being treated for chronic viral hepatitis. The role of non-invasive markers in accurately predicting the presence of fibrosis in obese patients needs to be further refined.

Diagnostic Accuracy of 2D-Shear Wave Elastography for Liver Fibrosis Severity: A Meta-Analysis

“…Acoustic radiation force impulse (ARFI) measures the average elasticity value in the region of interested (ROI) with the standard deviation, which can not provide elastic measurement in real time. Most imaging-based techniques do well at discerning patients at the extremes of fibrosis but could not exactly distinguish intermediate stages [ 4 ]. More recently, real-time shear wave elastography (SWE) that was first reported by Bercoff J et al in 2004, is a two-dimensional transient elastography technique based on the principle of Mach Cones for noninvasive evaluation of liver fibrosis [ 5 , 6 ].…”

Non-Invasively Distinguishing Progress of Liver Fibrosis by Visualizing Hepatic Platelet Derived Growth Factor Receptor-Beta Expression with an MRI Modality in Mice

“…At present, liver brosis can be assessed by invasive biopsy and non-invasive approaches including imaging techniques based on measuring liver stiffness (such as transient elastography) and serum markers. 18 Liver biopsy is still widely acknowledged as the gold standard for the diagnosis and stage of liver brosis, but it is an invasive procedure with a risk of rare but potentially life-threatening complications, which limit its use in the long-time follow-up and wide-scale screening of CLD. 19 Over the past decade, there has been tremendous advance in the development of non-invasive approaches to assess liver brosis.…”

“…Most of these non-invasive approaches show good work at identifying the extremes of brosis but is undesirable in accurately differentiating intermediate stages. [18][19][20] In addition, liver brosis is a dynamic process, and the total amount of brous tissue depends on the synthesis, deposition, accumulation and degradation of ECM. 21 More importantly, in the past decades, it has been convincingly demonstrated that after the etiologies are successfully removed, the brotic liver can revert to a less brotic or even normal architecture in both rodent model of liver brosis and patients with CLD, especially at the early stage of brosis.…”

Progress in non-invasive detection of liver fibrosis

“…US, CT, and MRI have traditionally been used to explore the liver 31 . They are able to detect biological changes in the liver parenchyma when there is significant fibrosis (bridging fibrosis and cirrhosis) and signs of portal hypertension.…”

“…These methods make use of the fact that image texture analysis is a very common diagnostic method for liver fibrosis. For this reason, many scholars focus on the analysis of the image texture features of different fibrosis stage 31 . By using a series of mathematical equations to generate a range of parameters associated with image texture, texture analysis characterizes the spatial variation of gray levels throughout an image 86 .…”