InForm software: a semi-automated research tool to identify presumptive human hepatic progenitor cells, and other histological features of pathological significance
Hepatic progenitor cells (HPCs) play an important regenerative role in acute and chronic liver pathologies. Liver disease research often necessitates the grading of disease severity, and pathologists’ reports are the current gold-standard for assessment. However, it is often impractical to recruit p...
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| Veröffentlicht in: | Scientific reports 2018-02, Vol.8 (1), p.3418-10, Article 3418 |
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| description | Hepatic progenitor cells (HPCs) play an important regenerative role in acute and chronic liver pathologies. Liver disease research often necessitates the grading of disease severity, and pathologists’ reports are the current gold-standard for assessment. However, it is often impractical to recruit pathologists in large cohort studies. In this study we utilise PerkinElmer’s “InForm” software package to semi-automate the scoring of patient liver biopsies, and compare outputs to a pathologist’s assessment. We examined a cohort of eleven acute hepatitis samples and three non-alcoholic fatty liver disease (NAFLD) samples, stained with HPC markers (GCTM-5 and Pan Cytokeratin), an inflammatory marker (CD45), Sirius Red to detect collagen and haematoxylin/eosin for general histology. InForm was configured to identify presumptive HPCs, CD45
+ve
inflammatory cells, areas of necrosis, fat and collagen deposition (p |
| doi_str_mv | 10.1038/s41598-018-21757-4 |
| format | Article |
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+ve
inflammatory cells, areas of necrosis, fat and collagen deposition (p < 0.0001). Hepatitis samples were then evaluated both by a pathologist using the Ishak-Knodell scoring system, and by InForm through customised algorithms. Necroinflammation as evaluated by a pathologist, correlated with InForm outputs (r
2
= 0.8192, p < 0.05). This study demonstrates that the InForm software package provides a useful tool for liver disease research, allowing rapid, and objective quantification of the presumptive HPCs and identifies histological features that assist with assessing liver disease severity, and potentially can facilitate diagnosis.</description><identifier>ISSN: 2045-2322</identifier><identifier>EISSN: 2045-2322</identifier><identifier>DOI: 10.1038/s41598-018-21757-4</identifier><identifier>PMID: 29467378</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>14 ; 14/34 ; 14/56 ; 14/63 ; 631/532/71 ; 692/308/2171 ; Automation ; CD45 antigen ; Collagen ; Computer programs ; Cytokeratin ; Fatty liver ; Hepatitis ; Histology ; Humanities and Social Sciences ; Inflammation ; Liver ; Liver diseases ; multidisciplinary ; Progenitor cells ; Science ; Science (multidisciplinary) ; Software ; Software packages ; Stem cells</subject><ispartof>Scientific reports, 2018-02, Vol.8 (1), p.3418-10, Article 3418</ispartof><rights>The Author(s) 2018</rights><rights>2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c474t-899dbb93cb757c221ce2c774cdeaa97564a5bbdafd0805e0529f846fd8cdfd853</citedby><cites>FETCH-LOGICAL-c474t-899dbb93cb757c221ce2c774cdeaa97564a5bbdafd0805e0529f846fd8cdfd853</cites><orcidid>0000-0002-8752-037X ; 0000-0002-4740-4702</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5821869/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5821869/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,27901,27902,41096,42165,51551,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29467378$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kramer, Anne S.</creatorcontrib><creatorcontrib>Latham, Bruce</creatorcontrib><creatorcontrib>Diepeveen, Luke A.</creatorcontrib><creatorcontrib>Mou, Lingjun</creatorcontrib><creatorcontrib>Laurent, Geoffrey J.</creatorcontrib><creatorcontrib>Elsegood, Caryn</creatorcontrib><creatorcontrib>Ochoa-Callejero, Laura</creatorcontrib><creatorcontrib>Yeoh, George C.</creatorcontrib><title>InForm software: a semi-automated research tool to identify presumptive human hepatic progenitor cells, and other histological features of pathological significance</title><title>Scientific reports</title><addtitle>Sci Rep</addtitle><addtitle>Sci Rep</addtitle><description>Hepatic progenitor cells (HPCs) play an important regenerative role in acute and chronic liver pathologies. Liver disease research often necessitates the grading of disease severity, and pathologists’ reports are the current gold-standard for assessment. However, it is often impractical to recruit pathologists in large cohort studies. In this study we utilise PerkinElmer’s “InForm” software package to semi-automate the scoring of patient liver biopsies, and compare outputs to a pathologist’s assessment. We examined a cohort of eleven acute hepatitis samples and three non-alcoholic fatty liver disease (NAFLD) samples, stained with HPC markers (GCTM-5 and Pan Cytokeratin), an inflammatory marker (CD45), Sirius Red to detect collagen and haematoxylin/eosin for general histology. InForm was configured to identify presumptive HPCs, CD45
+ve
inflammatory cells, areas of necrosis, fat and collagen deposition (p < 0.0001). Hepatitis samples were then evaluated both by a pathologist using the Ishak-Knodell scoring system, and by InForm through customised algorithms. Necroinflammation as evaluated by a pathologist, correlated with InForm outputs (r
2
= 0.8192, p < 0.05). This study demonstrates that the InForm software package provides a useful tool for liver disease research, allowing rapid, and objective quantification of the presumptive HPCs and identifies histological features that assist with assessing liver disease severity, and potentially can facilitate diagnosis.</description><subject>14</subject><subject>14/34</subject><subject>14/56</subject><subject>14/63</subject><subject>631/532/71</subject><subject>692/308/2171</subject><subject>Automation</subject><subject>CD45 antigen</subject><subject>Collagen</subject><subject>Computer programs</subject><subject>Cytokeratin</subject><subject>Fatty liver</subject><subject>Hepatitis</subject><subject>Histology</subject><subject>Humanities and Social Sciences</subject><subject>Inflammation</subject><subject>Liver</subject><subject>Liver diseases</subject><subject>multidisciplinary</subject><subject>Progenitor cells</subject><subject>Science</subject><subject>Science (multidisciplinary)</subject><subject>Software</subject><subject>Software packages</subject><subject>Stem cells</subject><issn>2045-2322</issn><issn>2045-2322</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>BENPR</sourceid><recordid>eNp9UsFu1TAQjBCIVqU_wAFZ4sKBFMexY4cDEqooVKrEBc6WY68TV4kdbKeo_8OH4tdXXgsHfFivNLNj7-5U1csGnzW4Fe8SbVgvatyImjSc8Zo-qY4JpqwmLSFPH-VH1WlK17gcRnra9M-ro3J3vOXiuPp16S9CXFAKNv9UEd4jhRIsrlZbDovKYFCEBCrqCeUQ5hKQM-Czs7doLdC2rNndAJq2RXk0waqy0wUJI3iXQ0Qa5jm9RcobFPIEEU0u5TCH0Wk1Iwsqb0UGBYtK6XQAkhu9syX1Gl5Uz6yaE5ze3yfV94tP386_1FdfP1-ef7yqNeU016LvzTD0rR7KPDQhjQaiOafagFI9Zx1VbBiMsgYLzGA3DitoZ43QpgTWnlQf9rrrNixgdGkzqlmu0S0q3sqgnPwb8W6SY7iRTJBGdH0ReHMvEMOPDVKWi0u7ASgPYUuSYMzLBnjbFerrf6jXYYu-tHfHwn3HBC4ssmfpGFKKYA-fabDc-UDufSCLD-SdDyQtRa8et3Eo-bP1Qmj3hFQgP0J8ePs_sr8B4f_D_g</recordid><startdate>20180221</startdate><enddate>20180221</enddate><creator>Kramer, Anne S.</creator><creator>Latham, Bruce</creator><creator>Diepeveen, Luke A.</creator><creator>Mou, Lingjun</creator><creator>Laurent, Geoffrey J.</creator><creator>Elsegood, Caryn</creator><creator>Ochoa-Callejero, Laura</creator><creator>Yeoh, George C.</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>C6C</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-8752-037X</orcidid><orcidid>https://orcid.org/0000-0002-4740-4702</orcidid></search><sort><creationdate>20180221</creationdate><title>InForm software: a semi-automated research tool to identify presumptive human hepatic progenitor cells, and other histological features of pathological significance</title><author>Kramer, Anne S. ; 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Liver disease research often necessitates the grading of disease severity, and pathologists’ reports are the current gold-standard for assessment. However, it is often impractical to recruit pathologists in large cohort studies. In this study we utilise PerkinElmer’s “InForm” software package to semi-automate the scoring of patient liver biopsies, and compare outputs to a pathologist’s assessment. We examined a cohort of eleven acute hepatitis samples and three non-alcoholic fatty liver disease (NAFLD) samples, stained with HPC markers (GCTM-5 and Pan Cytokeratin), an inflammatory marker (CD45), Sirius Red to detect collagen and haematoxylin/eosin for general histology. InForm was configured to identify presumptive HPCs, CD45
+ve
inflammatory cells, areas of necrosis, fat and collagen deposition (p < 0.0001). Hepatitis samples were then evaluated both by a pathologist using the Ishak-Knodell scoring system, and by InForm through customised algorithms. Necroinflammation as evaluated by a pathologist, correlated with InForm outputs (r
2
= 0.8192, p < 0.05). This study demonstrates that the InForm software package provides a useful tool for liver disease research, allowing rapid, and objective quantification of the presumptive HPCs and identifies histological features that assist with assessing liver disease severity, and potentially can facilitate diagnosis.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>29467378</pmid><doi>10.1038/s41598-018-21757-4</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-8752-037X</orcidid><orcidid>https://orcid.org/0000-0002-4740-4702</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | 14 14/34 14/56 14/63 631/532/71 692/308/2171 Automation CD45 antigen Collagen Computer programs Cytokeratin Fatty liver Hepatitis Histology Humanities and Social Sciences Inflammation Liver Liver diseases multidisciplinary Progenitor cells Science Science (multidisciplinary) Software Software packages Stem cells |
| title | InForm software: a semi-automated research tool to identify presumptive human hepatic progenitor cells, and other histological features of pathological significance |
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