Evaluation of liver fibrosis: a concise review

Noninvasive assessment of liver fibrosis

Understanding of the pathogenesis of hepatic fibrosis on a molecular level has led to the identification of several putative serum markers of hepatic fibrosis. Either individually or in combination, these serum markers appear capable of determining early and advanced hepatic fibrosis. Radiological determination of hepatic fibrosis has insufficient sensitivity and specificity other than for detection of features of portal hypertension or features of end-stage cirrhosis. Transient hepatic elastography is a novel technology demonstrating promise as a noninvasive means of fibrosis determination. This article outlines the accuracy of all these modalities in the diagnosis of hepatic fibrosis and discusses how they may be incorporated into clinical practice.

Ultrasonographic and biochemical parameters in the non-invasive evaluation of liver fibrosis in hepatitis C virus chronic hepatitis

BACKGROUND

Prior studies suggest that platelet counts of <140 000/microL can discriminate patients with different stages of fibrosis.

AIM

To determine the added value of abdominal ultrasound analysis of morphological liver features in increasing the diagnostic accuracy of platelet counts for the prediction of liver fibrosis at histology.

METHODS

In a retrospective study, clinical records of 1143 chronic hepatitis C patients at their first presentation, naives to both liver biopsy and anti-viral treatment, were reviewed. Sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios of following indices were evaluated singularly or in combination: platelet counts <140 000/microL; nodular liver surface, spleen and portal vein size.

RESULTS

All indices had specificity rate of > or =90% in excluding bridging fibrosis/cirrhosis, whereas sensitivity was acceptable (51%) for only platelet counts <140 000/microL. None of the ultrasonographic parameters singularly evaluated and reached an acceptable sensitivity rate. For ruling cirrhosis in or out, specificity rate was > or =82% for all tests, with the highest value reported by portal vein size. Low platelet counts plus nodular liver surface had the best sensitivity.

CONCLUSIONS

No additional significant predictive value was given by adding ultrasonographic parameters to low platelet counts, whereas only a mild non-significant improvement in sensitivity was obtained combining platelet counts <140 000/microL with the presence of nodular liver surface. The platelet counts <140 000/microL showed the best predictive value for including both significant fibrosis and cirrhosis.

Assessment of the Patient Who Failed Treatment for Chronic Hepatitis C

Chronic hepatitis C virus (HCV) infection affects more than 4 million people in the United States and 170 million people in the world, making it a major public health problem. Currently, about one half of the patients undergoing hepatitis C treatment do not experience a sustained viral response. With time, this high nonresponse rate has created a large pool of such patients (nonresponders), many of whom have advanced fibrosis or cirrhosis. Patients who are selected for re-treatment need healthcare providers with experience, knowledge, and the time available to manage the side effects to maximize adherence to therapy. This article discusses the assessment of patients being re-treated for HCV and approaches to caring for this patient population.

Prediction of fibrosis in HCV-infected liver transplant recipients with a simple noninvasive index

Recurrent hepatitis C is a frequent event in liver transplantation (LT). Serial liver biopsies remain the best way of monitoring disease progression. Due to the limitations of a liver biopsy, there is an interest in developing noninvasive markers of liver fibrosis. While several models for predicting fibrosis have been constructed in patients who have not undergone transplantation, these are lacking in the transplant population. The aim of this study was to construct one simple model based on routine laboratory data to predict fibrosis in hepatitis C virus (HCV)-infected LT patients. A total of 510 yearly protocol liver biopsies performed in 188 LT patients (67% male; median age 54 years) were divided into 2 groups: training set (n = 414) and validation set (n = 96). Laboratory variables at time of biopsies were recorded. Multivariate analysis identified 4 variables as independent predictors of fibrosis: prothrombin time (PT), albumin/total protein ratio, aspartate aminotransferase (AST), and time since LT. The area under the receiver operating characteristic (ROC) curves (AUCs) were 0.80 and 0.84 for the training and the validation set, respectively. In the training set, using a cutoff of 0.2, the model had a sensitivity, specificity, positive predictive value, and negative predictive value of 74%, 69%, 42%, and 90%, respectively, to differentiate significant (bridging fibrosis and cirrhosis) from mild fibrosis (none or portal). In the validation cohort, these values increased to 87%, 71%, 49%, and 95%, respectively. In conclusion, in the LT setting, a simple fibrosis index is useful to select HCV-infected patients with a very low risk of significant fibrosis in whom protocol liver biopsies may be avoided.

Liver fibrosis

Liver fibrosis is the excessive accumulation of extracellular matrix proteins including collagen that occurs in most types of chronic liver diseases. Advanced liver fibrosis results in cirrhosis, liver failure, and portal hypertension and often requires liver transplantation. Our knowledge of the cellular and molecular mechanisms of liver fibrosis has greatly advanced. Activated hepatic stellate cells, portal fibroblasts, and myofibroblasts of bone marrow origin have been identified as major collagen-producing cells in the injured liver. These cells are activated by fibrogenic cytokines such as TGF-beta1, angiotensin II, and leptin. Reversibility of advanced liver fibrosis in patients has been recently documented, which has stimulated researchers to develop antifibrotic drugs. Emerging antifibrotic therapies are aimed at inhibiting the accumulation of fibrogenic cells and/or preventing the deposition of extracellular matrix proteins. Although many therapeutic interventions are effective in experimental models of liver fibrosis, their efficacy and safety in humans is unknown. This review summarizes recent progress in the study of the pathogenesis and diagnosis of liver fibrosis and discusses current antifibrotic strategies.

Liver fibrosis

Liver fibrosis is the excessive accumulation of extracellular matrix proteins including collagen that occurs in most types of chronic liver diseases. Advanced liver fibrosis results in cirrhosis, liver failure, and portal hypertension and often requires liver transplantation. Our knowledge of the cellular and molecular mechanisms of liver fibrosis has greatly advanced. Activated hepatic stellate cells, portal fibroblasts, and myofibroblasts of bone marrow origin have been identified as major collagen-producing cells in the injured liver. These cells are activated by fibrogenic cytokines such as TGF-beta1, angiotensin II, and leptin. Reversibility of advanced liver fibrosis in patients has been recently documented, which has stimulated researchers to develop antifibrotic drugs. Emerging antifibrotic therapies are aimed at inhibiting the accumulation of fibrogenic cells and/or preventing the deposition of extracellular matrix proteins. Although many therapeutic interventions are effective in experimental models of liver fibrosis, their efficacy and safety in humans is unknown. This review summarizes recent progress in the study of the pathogenesis and diagnosis of liver fibrosis and discusses current antifibrotic strategies.

Liver fibrosis

Liver fibrosis is the excessive accumulation of extracellular matrix proteins including collagen that occurs in most types of chronic liver diseases. Advanced liver fibrosis results in cirrhosis, liver failure, and portal hypertension and often requires liver transplantation. Our knowledge of the cellular and molecular mechanisms of liver fibrosis has greatly advanced. Activated hepatic stellate cells, portal fibroblasts, and myofibroblasts of bone marrow origin have been identified as major collagen-producing cells in the injured liver. These cells are activated by fibrogenic cytokines such as TGF-beta1, angiotensin II, and leptin. Reversibility of advanced liver fibrosis in patients has been recently documented, which has stimulated researchers to develop antifibrotic drugs. Emerging antifibrotic therapies are aimed at inhibiting the accumulation of fibrogenic cells and/or preventing the deposition of extracellular matrix proteins. Although many therapeutic interventions are effective in experimental models of liver fibrosis, their efficacy and safety in humans is unknown. This review summarizes recent progress in the study of the pathogenesis and diagnosis of liver fibrosis and discusses current antifibrotic strategies.

Liver fibrosis

Liver fibrosis is the excessive accumulation of extracellular matrix proteins including collagen that occurs in most types of chronic liver diseases. Advanced liver fibrosis results in cirrhosis, liver failure, and portal hypertension and often requires liver transplantation. Our knowledge of the cellular and molecular mechanisms of liver fibrosis has greatly advanced. Activated hepatic stellate cells, portal fibroblasts, and myofibroblasts of bone marrow origin have been identified as major collagen-producing cells in the injured liver. These cells are activated by fibrogenic cytokines such as TGF-beta1, angiotensin II, and leptin. Reversibility of advanced liver fibrosis in patients has been recently documented, which has stimulated researchers to develop antifibrotic drugs. Emerging antifibrotic therapies are aimed at inhibiting the accumulation of fibrogenic cells and/or preventing the deposition of extracellular matrix proteins. Although many therapeutic interventions are effective in experimental models of liver fibrosis, their efficacy and safety in humans is unknown. This review summarizes recent progress in the study of the pathogenesis and diagnosis of liver fibrosis and discusses current antifibrotic strategies.

Prediction of liver fibrosis and cirrhosis in chronic hepatitis B infection by serum proteomic fingerprinting: a pilot study

BACKGROUND

Most noninvasive predictive models of liver fibrosis are complicated and have suboptimal sensitivity. This study was designed to identify serum proteomic signatures associated with liver fibrosis and to develop a proteome-based fingerprinting model for prediction of liver fibrosis.

METHODS

Serum proteins from 46 patients with chronic hepatitis B (CHB) were profiled quantitatively on surface-enhanced laser desorption/ionization (SELDI) ProteinChip arrays. The identified liver fibrosis-associated proteomic fingerprint was used to construct an artificial neural network (ANN) model that produced a fibrosis index with a range of 0-6. The clinical value of this index was evaluated by leave-one-out cross-validation.

RESULTS

Thirty SELDI proteomic features were significantly associated with the degree of fibrosis. Cross-validation showed that the ANN fibrosis indices derived from the proteomic fingerprint strongly correlated with Ishak scores (r = 0.831) and were significantly different among stages of fibrosis. ROC curve areas in predicting significant fibrosis (Ishak score >or=3) and cirrhosis (Ishak score >or=5) were 0.906 and 0.921, respectively. At 89% specificity, the sensitivity of the ANN fibrosis index in predicting fibrosis was 89%. The sensitivity for prediction increased with degree of fibrosis, achieving 100% for patients with Ishak scores >4. The accuracy for prediction of cirrhosis was also 89%. Inclusion of International Normalized Ratio, total protein, bilirubin, alanine transaminase, and hemoglobin in the ANN model improved the predictive power, giving accuracies >90% for the prediction of fibrosis and cirrhosis.

CONCLUSIONS

A unique serum proteomic fingerprint is present in the sera of patients with fibrosis. An ANN fibrosis index derived from this fingerprint could differentiate between different stages of fibrosis and predict fibrosis and cirrhosis in CHB infection.