qFibrosis: A fully-quantitative innovative method incorporating histological features to facilitate accurate fibrosis scoring in animal model and chronic hepatitis B patients
There is increasing need for accurate assessment of liver fibrosis/cirrhosis. We aimed to develop qFibrosis, a fully-automated assessment method combining quantification of histopathological architectural features, to address unmet needs in core biopsy evaluation of fibrosis in chronic hepatitis B (...
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| Published in | Journal of hepatology Vol. 61; no. 2; pp. 260 - 269 |
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| Main Authors | , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Netherlands
Elsevier B.V
01.08.2014
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| Subjects | |
| Online Access | Get full text |
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| Abstract | There is increasing need for accurate assessment of liver fibrosis/cirrhosis. We aimed to develop qFibrosis, a fully-automated assessment method combining quantification of histopathological architectural features, to address unmet needs in core biopsy evaluation of fibrosis in chronic hepatitis B (CHB) patients.
qFibrosis was established as a combined index based on 87 parameters of architectural features. Images acquired from 25 Thioacetamide-treated rat samples and 162 CHB core biopsies were used to train and test qFibrosis and to demonstrate its reproducibility. qFibrosis scoring was analyzed employing Metavir and Ishak fibrosis staging as standard references, and collagen proportionate area (CPA) measurement for comparison.
qFibrosis faithfully and reliably recapitulates Metavir fibrosis scores, as it can identify differences between all stages in both animal samples (p<0.001) and human biopsies (p<0.05). It is robust to sampling size, allowing for discrimination of different stages in samples of different sizes (area under the curve (AUC): 0.93–0.99 for animal samples: 1–16mm2; AUC: 0.84–0.97 for biopsies: 10–44mm in length). qFibrosis can significantly predict staging underestimation in suboptimal biopsies (<15mm) and under- and over-scoring by different pathologists (p<0.001). qFibrosis can also differentiate between Ishak stages 5 and 6 (AUC: 0.73, p=0.008), suggesting the possibility of monitoring intra-stage cirrhosis changes. Best of all, qFibrosis demonstrates superior performance to CPA on all counts.
qFibrosis can improve fibrosis scoring accuracy and throughput, thus allowing for reproducible and reliable analysis of efficacies of anti-fibrotic therapies in clinical research and practice. |
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| AbstractList | There is increasing need for accurate assessment of liver fibrosis/cirrhosis. We aimed to develop qFibrosis, a fully-automated assessment method combining quantification of histopathological architectural features, to address unmet needs in core biopsy evaluation of fibrosis in chronic hepatitis B (CHB) patients.
qFibrosis was established as a combined index based on 87 parameters of architectural features. Images acquired from 25 Thioacetamide-treated rat samples and 162 CHB core biopsies were used to train and test qFibrosis and to demonstrate its reproducibility. qFibrosis scoring was analyzed employing Metavir and Ishak fibrosis staging as standard references, and collagen proportionate area (CPA) measurement for comparison.
qFibrosis faithfully and reliably recapitulates Metavir fibrosis scores, as it can identify differences between all stages in both animal samples (p<0.001) and human biopsies (p<0.05). It is robust to sampling size, allowing for discrimination of different stages in samples of different sizes (area under the curve (AUC): 0.93-0.99 for animal samples: 1-16 mm(2); AUC: 0.84-0.97 for biopsies: 10-44 mm in length). qFibrosis can significantly predict staging underestimation in suboptimal biopsies (<15 mm) and under- and over-scoring by different pathologists (p<0.001). qFibrosis can also differentiate between Ishak stages 5 and 6 (AUC: 0.73, p=0.008), suggesting the possibility of monitoring intra-stage cirrhosis changes. Best of all, qFibrosis demonstrates superior performance to CPA on all counts.
qFibrosis can improve fibrosis scoring accuracy and throughput, thus allowing for reproducible and reliable analysis of efficacies of anti-fibrotic therapies in clinical research and practice. There is increasing need for accurate assessment of liver fibrosis/cirrhosis. We aimed to develop qFibrosis, a fully-automated assessment method combining quantification of histopathological architectural features, to address unmet needs in core biopsy evaluation of fibrosis in chronic hepatitis B (CHB) patients. qFibrosis was established as a combined index based on 87 parameters of architectural features. Images acquired from 25 Thioacetamide-treated rat samples and 162 CHB core biopsies were used to train and test qFibrosis and to demonstrate its reproducibility. qFibrosis scoring was analyzed employing Metavir and Ishak fibrosis staging as standard references, and collagen proportionate area (CPA) measurement for comparison. qFibrosis faithfully and reliably recapitulates Metavir fibrosis scores, as it can identify differences between all stages in both animal samples (p<0.001) and human biopsies (p<0.05). It is robust to sampling size, allowing for discrimination of different stages in samples of different sizes (area under the curve (AUC): 0.93–0.99 for animal samples: 1–16mm2; AUC: 0.84–0.97 for biopsies: 10–44mm in length). qFibrosis can significantly predict staging underestimation in suboptimal biopsies (<15mm) and under- and over-scoring by different pathologists (p<0.001). qFibrosis can also differentiate between Ishak stages 5 and 6 (AUC: 0.73, p=0.008), suggesting the possibility of monitoring intra-stage cirrhosis changes. Best of all, qFibrosis demonstrates superior performance to CPA on all counts. qFibrosis can improve fibrosis scoring accuracy and throughput, thus allowing for reproducible and reliable analysis of efficacies of anti-fibrotic therapies in clinical research and practice. There is increasing need for accurate assessment of liver fibrosis/cirrhosis. We aimed to develop qFibrosis, a fully-automated assessment method combining quantification of histopathological architectural features, to address unmet needs in core biopsy evaluation of fibrosis in chronic hepatitis B (CHB) patients.BACKGROUND & AIMSThere is increasing need for accurate assessment of liver fibrosis/cirrhosis. We aimed to develop qFibrosis, a fully-automated assessment method combining quantification of histopathological architectural features, to address unmet needs in core biopsy evaluation of fibrosis in chronic hepatitis B (CHB) patients.qFibrosis was established as a combined index based on 87 parameters of architectural features. Images acquired from 25 Thioacetamide-treated rat samples and 162 CHB core biopsies were used to train and test qFibrosis and to demonstrate its reproducibility. qFibrosis scoring was analyzed employing Metavir and Ishak fibrosis staging as standard references, and collagen proportionate area (CPA) measurement for comparison.METHODSqFibrosis was established as a combined index based on 87 parameters of architectural features. Images acquired from 25 Thioacetamide-treated rat samples and 162 CHB core biopsies were used to train and test qFibrosis and to demonstrate its reproducibility. qFibrosis scoring was analyzed employing Metavir and Ishak fibrosis staging as standard references, and collagen proportionate area (CPA) measurement for comparison.qFibrosis faithfully and reliably recapitulates Metavir fibrosis scores, as it can identify differences between all stages in both animal samples (p<0.001) and human biopsies (p<0.05). It is robust to sampling size, allowing for discrimination of different stages in samples of different sizes (area under the curve (AUC): 0.93-0.99 for animal samples: 1-16 mm(2); AUC: 0.84-0.97 for biopsies: 10-44 mm in length). qFibrosis can significantly predict staging underestimation in suboptimal biopsies (<15 mm) and under- and over-scoring by different pathologists (p<0.001). qFibrosis can also differentiate between Ishak stages 5 and 6 (AUC: 0.73, p=0.008), suggesting the possibility of monitoring intra-stage cirrhosis changes. Best of all, qFibrosis demonstrates superior performance to CPA on all counts.RESULTSqFibrosis faithfully and reliably recapitulates Metavir fibrosis scores, as it can identify differences between all stages in both animal samples (p<0.001) and human biopsies (p<0.05). It is robust to sampling size, allowing for discrimination of different stages in samples of different sizes (area under the curve (AUC): 0.93-0.99 for animal samples: 1-16 mm(2); AUC: 0.84-0.97 for biopsies: 10-44 mm in length). qFibrosis can significantly predict staging underestimation in suboptimal biopsies (<15 mm) and under- and over-scoring by different pathologists (p<0.001). qFibrosis can also differentiate between Ishak stages 5 and 6 (AUC: 0.73, p=0.008), suggesting the possibility of monitoring intra-stage cirrhosis changes. Best of all, qFibrosis demonstrates superior performance to CPA on all counts.qFibrosis can improve fibrosis scoring accuracy and throughput, thus allowing for reproducible and reliable analysis of efficacies of anti-fibrotic therapies in clinical research and practice.CONCLUSIONSqFibrosis can improve fibrosis scoring accuracy and throughput, thus allowing for reproducible and reliable analysis of efficacies of anti-fibrotic therapies in clinical research and practice. |
| Author | Peng, Qiwen Zhu, Youfu Liang, Xieer Wee, Aileen Yu, Hanry Hou, Jinlin Sun, Jian Xu, Shuoyu Wang, Yan So, Peter T.C. Welsch, Roy E. Tai, Dean C.S. Cheng, Chee Leong Yan, Jie Rajapakse, Jagath C. Wang, Shi Chen, Yongpeng |
| AuthorAffiliation | 6 Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, 2 Medical Drive, MD9 #04-01, Singapore 117597, Singapore 2 Computation and System Biology Program, Singapore-MIT Alliance, 4 Engineering Drive 3, E4-04-10, Singapore 117576, Singapore 9 Sloan School of Management, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA 11 Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA 10 Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA 7 Department of Pathology, National University Hospital, 5 Lower Kent Ridge Road, Singapore 119074, Singapore 8 Bioinformatics Research Center, School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore 3 Biosystems and Micromechanics IRG, Singapore-MIT Alliance for Research and Technology, 1 C |
| AuthorAffiliation_xml | – name: 8 Bioinformatics Research Center, School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore – name: 9 Sloan School of Management, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA – name: 6 Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, 2 Medical Drive, MD9 #04-01, Singapore 117597, Singapore – name: 3 Biosystems and Micromechanics IRG, Singapore-MIT Alliance for Research and Technology, 1 CREATE Way, #04-13/14 Enterprise Wing, Singapore 138602, Singapore – name: 11 Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA – name: 7 Department of Pathology, National University Hospital, 5 Lower Kent Ridge Road, Singapore 119074, Singapore – name: 1 Institute of Bioengineering and Nanotechnology, 31 Biopolis Way, #04-01, Singapore 138669, Singapore – name: 5 Departments of Hepatobiliary Surgery and Pathology, Zhujiang Hospital, Southern Medical University, 253 Gongye Dadao Avenue, Guangzhou 510280, China – name: 10 Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA – name: 4 Institute of Hepatology, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, 1838 North Guangzhou Avenue, Guangzhou 510515, China – name: 2 Computation and System Biology Program, Singapore-MIT Alliance, 4 Engineering Drive 3, E4-04-10, Singapore 117576, Singapore – name: 12 Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, 5 Lower Kent Ridge Road, Singapore 119074, Singapore – name: 13 The Mechanobiology Institute, 5A Engineering Drive 1, T-Lab #05-01, Singapore 117411, Singapore |
| Author_xml | – sequence: 1 givenname: Shuoyu surname: Xu fullname: Xu, Shuoyu organization: Institute of Bioengineering and Nanotechnology, 31 Biopolis Way, #04-01, Singapore 138669, Singapore – sequence: 2 givenname: Yan surname: Wang fullname: Wang, Yan organization: Institute of Hepatology, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, 1838 North Guangzhou Avenue, Guangzhou 510515, China – sequence: 3 givenname: Dean C.S. surname: Tai fullname: Tai, Dean C.S. organization: Institute of Bioengineering and Nanotechnology, 31 Biopolis Way, #04-01, Singapore 138669, Singapore – sequence: 4 givenname: Shi surname: Wang fullname: Wang, Shi organization: Department of Pathology, National University Hospital, 5 Lower Kent Ridge Road, Singapore 119074, Singapore – sequence: 5 givenname: Chee Leong surname: Cheng fullname: Cheng, Chee Leong organization: Department of Pathology, National University Hospital, 5 Lower Kent Ridge Road, Singapore 119074, Singapore – sequence: 6 givenname: Qiwen surname: Peng fullname: Peng, Qiwen organization: Institute of Bioengineering and Nanotechnology, 31 Biopolis Way, #04-01, Singapore 138669, Singapore – sequence: 7 givenname: Jie surname: Yan fullname: Yan, Jie organization: Institute of Bioengineering and Nanotechnology, 31 Biopolis Way, #04-01, Singapore 138669, Singapore – sequence: 8 givenname: Yongpeng surname: Chen fullname: Chen, Yongpeng organization: Institute of Hepatology, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, 1838 North Guangzhou Avenue, Guangzhou 510515, China – sequence: 9 givenname: Jian surname: Sun fullname: Sun, Jian organization: Institute of Hepatology, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, 1838 North Guangzhou Avenue, Guangzhou 510515, China – sequence: 10 givenname: Xieer surname: Liang fullname: Liang, Xieer organization: Institute of Hepatology, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, 1838 North Guangzhou Avenue, Guangzhou 510515, China – sequence: 11 givenname: Youfu surname: Zhu fullname: Zhu, Youfu organization: Institute of Hepatology, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, 1838 North Guangzhou Avenue, Guangzhou 510515, China – sequence: 12 givenname: Jagath C. surname: Rajapakse fullname: Rajapakse, Jagath C. organization: Computation and System Biology Program, Singapore-MIT Alliance, 4 Engineering Drive 3, E4-04-10, Singapore 117576, Singapore – sequence: 13 givenname: Roy E. surname: Welsch fullname: Welsch, Roy E. organization: Computation and System Biology Program, Singapore-MIT Alliance, 4 Engineering Drive 3, E4-04-10, Singapore 117576, Singapore – sequence: 14 givenname: Peter T.C. surname: So fullname: So, Peter T.C. organization: Computation and System Biology Program, Singapore-MIT Alliance, 4 Engineering Drive 3, E4-04-10, Singapore 117576, Singapore – sequence: 15 givenname: Aileen surname: Wee fullname: Wee, Aileen email: aileen_wee@nuhs.edu.sg organization: Department of Pathology, National University Hospital, 5 Lower Kent Ridge Road, Singapore 119074, Singapore – sequence: 16 givenname: Jinlin surname: Hou fullname: Hou, Jinlin email: jlhou@smu.edu.cn organization: Institute of Hepatology, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, 1838 North Guangzhou Avenue, Guangzhou 510515, China – sequence: 17 givenname: Hanry surname: Yu fullname: Yu, Hanry organization: Institute of Bioengineering and Nanotechnology, 31 Biopolis Way, #04-01, Singapore 138669, Singapore |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/24583249$$D View this record in MEDLINE/PubMed |
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| Copyright | 2014 European Association for the Study of the Liver Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved. 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved. 2014 |
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| Keywords | Liver biopsy AST PT CI ROC ALT INR ECM AUC Image analysis SHG CV Chronic hepatitis B TAA CPA TBIL ALB APRI Liver fibrosis assessment PLT qFibrosis CLD TPEF CHB |
| Language | English |
| License | This is an open access article under the CC BY-NC-ND license. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved. |
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| OpenAccessLink | https://www.sciencedirect.com/science/article/pii/S0168827814001214 |
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| PublicationDate | 2014-08-01 |
| PublicationDateYYYYMMDD | 2014-08-01 |
| PublicationDate_xml | – month: 08 year: 2014 text: 2014-08-01 day: 01 |
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| PublicationPlace | Netherlands |
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| PublicationTitle | Journal of hepatology |
| PublicationTitleAlternate | J Hepatol |
| PublicationYear | 2014 |
| Publisher | Elsevier B.V |
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| SubjectTerms | Animals Biopsy Chronic hepatitis B Collagen - analysis Disease Models, Animal Hepatitis B, Chronic - complications Humans Image analysis Liver - pathology Liver biopsy Liver Cirrhosis, Experimental - diagnosis Liver Cirrhosis, Experimental - pathology Liver fibrosis assessment qFibrosis Rats |
| Title | qFibrosis: A fully-quantitative innovative method incorporating histological features to facilitate accurate fibrosis scoring in animal model and chronic hepatitis B patients |
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