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Current Strategies for Quantitating Fibrosis in Liver Biopsy

OBJECTIVE: The present mini-review updated the progress in methodologies based on using liver biopsy. DATA SOURCES: Articles for study of liver fibrosis, liver biopsy or fibrosis assessment published on high impact peer review journals from 1980 to 2014. STUDY SELECTION: Key articles were selected m...

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Autores principales: Wang, Yan, Hou, Jin-Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4837847/
https://www.ncbi.nlm.nih.gov/pubmed/25591571
http://dx.doi.org/10.4103/0366-6999.149223
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author Wang, Yan
Hou, Jin-Lin
author_facet Wang, Yan
Hou, Jin-Lin
author_sort Wang, Yan
collection PubMed
description OBJECTIVE: The present mini-review updated the progress in methodologies based on using liver biopsy. DATA SOURCES: Articles for study of liver fibrosis, liver biopsy or fibrosis assessment published on high impact peer review journals from 1980 to 2014. STUDY SELECTION: Key articles were selected mainly according to their levels of relevance to this topic and citations. RESULTS: With the recently mounting progress in chronic liver disease therapeutics, comes by a pressing need for precise, accurate, and dynamic assessment of hepatic fibrosis and cirrhosis in individual patients. Histopathological information is recognized as the most valuable data for fibrosis assessment. Conventional histology categorical systems describe the changes of fibrosis patterns in liver tissue; but the simplified ordinal digits assigned by these systems cannot reflect the fibrosis dynamics with sufficient precision and reproducibility. Morphometric assessment by computer assist digital image analysis, such as collagen proportionate area (CPA), detects change of fibrosis amount in tissue section in a continuous variable, and has shown its independent diagnostic value for assessment of advanced or late-stage of fibrosis. Due to its evident sensitivity to sampling variances, morphometric measurement is feasible to be taken as a reliable statistical parameter for the study of a large cohort. Combining state-of-art imaging technology and fundamental principle in Tissue Engineering, structure-based quantitation was recently initiated with a novel proof-of-concept tool, qFibrosis. qFibrosis showed not only the superior performance to CPA in accurately and reproducibly differentiating adjacent stages of fibrosis, but also the possibility for facilitating analysis of fibrotic regression and cirrhosis sub-staging. CONCLUSIONS: With input from multidisciplinary innovation, liver biopsy assessment as a new “gold standard” is anticipated to substantially support the accelerated progress of Hepatology medicine.
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spelling pubmed-48378472016-05-02 Current Strategies for Quantitating Fibrosis in Liver Biopsy Wang, Yan Hou, Jin-Lin Chin Med J (Engl) Review Article OBJECTIVE: The present mini-review updated the progress in methodologies based on using liver biopsy. DATA SOURCES: Articles for study of liver fibrosis, liver biopsy or fibrosis assessment published on high impact peer review journals from 1980 to 2014. STUDY SELECTION: Key articles were selected mainly according to their levels of relevance to this topic and citations. RESULTS: With the recently mounting progress in chronic liver disease therapeutics, comes by a pressing need for precise, accurate, and dynamic assessment of hepatic fibrosis and cirrhosis in individual patients. Histopathological information is recognized as the most valuable data for fibrosis assessment. Conventional histology categorical systems describe the changes of fibrosis patterns in liver tissue; but the simplified ordinal digits assigned by these systems cannot reflect the fibrosis dynamics with sufficient precision and reproducibility. Morphometric assessment by computer assist digital image analysis, such as collagen proportionate area (CPA), detects change of fibrosis amount in tissue section in a continuous variable, and has shown its independent diagnostic value for assessment of advanced or late-stage of fibrosis. Due to its evident sensitivity to sampling variances, morphometric measurement is feasible to be taken as a reliable statistical parameter for the study of a large cohort. Combining state-of-art imaging technology and fundamental principle in Tissue Engineering, structure-based quantitation was recently initiated with a novel proof-of-concept tool, qFibrosis. qFibrosis showed not only the superior performance to CPA in accurately and reproducibly differentiating adjacent stages of fibrosis, but also the possibility for facilitating analysis of fibrotic regression and cirrhosis sub-staging. CONCLUSIONS: With input from multidisciplinary innovation, liver biopsy assessment as a new “gold standard” is anticipated to substantially support the accelerated progress of Hepatology medicine. Medknow Publications & Media Pvt Ltd 2015-01-20 /pmc/articles/PMC4837847/ /pubmed/25591571 http://dx.doi.org/10.4103/0366-6999.149223 Text en Copyright: © 2015 Chinese Medical Journal http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.
spellingShingle Review Article
Wang, Yan
Hou, Jin-Lin
Current Strategies for Quantitating Fibrosis in Liver Biopsy
title Current Strategies for Quantitating Fibrosis in Liver Biopsy
title_full Current Strategies for Quantitating Fibrosis in Liver Biopsy
title_fullStr Current Strategies for Quantitating Fibrosis in Liver Biopsy
title_full_unstemmed Current Strategies for Quantitating Fibrosis in Liver Biopsy
title_short Current Strategies for Quantitating Fibrosis in Liver Biopsy
title_sort current strategies for quantitating fibrosis in liver biopsy
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4837847/
https://www.ncbi.nlm.nih.gov/pubmed/25591571
http://dx.doi.org/10.4103/0366-6999.149223
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