An Advanced Histologic Method for Evaluation of Intestinal Adenomas in Mice Using Digital Slides

Mice are used for modelling the biology of many human diseases, including colorectal cancer (CRC). Mouse models recapitulate many aspects of human disease and are invaluable tools for studying the biology, treatment and prevention of CRC. Unlike humans, many mouse models develop lesions primarily in...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:PloS one 2016-03, Vol.11 (3), p.e0151463-e0151463
Hauptverfasser: Davis, Jennifer S, Gupta, Vineet, Gagea, Mihai, Wu, Xiangwei
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page e0151463
container_issue 3
container_start_page e0151463
container_title PloS one
container_volume 11
creator Davis, Jennifer S
Gupta, Vineet
Gagea, Mihai
Wu, Xiangwei
description Mice are used for modelling the biology of many human diseases, including colorectal cancer (CRC). Mouse models recapitulate many aspects of human disease and are invaluable tools for studying the biology, treatment and prevention of CRC. Unlike humans, many mouse models develop lesions primarily in the small intestine, which necessitates removal and examination of this organ in order to evaluate treatment efficacy. Commonly, the small intestine is visually examined for gross lesions and then selectively embedded in paraffin blocks for further microscopic analysis. Unfortunately, this method suffers from inherent bias toward counting large lesions and simultaneously missing smaller lesions. Even more, this method leaves no permanent record of diagnosed and measured lesions. We evaluated inter-observer variability in a mouse model of CRC using visual examination, and directly compared the visual, gross examination with a histologic analytic method using digital slides of hematoxylin and eosin stained tissue sections. Using visual examination, there was a high degree of inter-observer variability. As this method does not provide a permanent record of measurements, there is no capability to arbitrate between differing observations. In contrast, histologic analysis allowed for the creation of a permanent record of lesion measurements taken. When compared directly, histologic analysis of annotated digital images has significantly improved accuracy. Using this method we were able to distinguish mutant mice from wild type littermates even at a very young age. With gross visual examination, this distinction was not possible. Histologic analysis of digital images of murine intestinal tissue provides a vital improvement over the commonly used visual, gross examination method. Unlike visual gross examination, histologic analysis is not biased by the size of intestinal adenoma, misdiagnosis of another lesion type, or presence of a Peyer's patch. It also provides accountability in the form of a permanent record of lesions counted. Histologic analysis using digital slides represents a critical improvement over the current, widely used method of visual gross examination and should be considered for future studies using mouse models of CRC.
doi_str_mv 10.1371/journal.pone.0151463
format Article
fullrecord <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_1773262897</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A453471388</galeid><doaj_id>oai_doaj_org_article_84831d12192d4affafa3e2bc3c3695a0</doaj_id><sourcerecordid>A453471388</sourcerecordid><originalsourceid>FETCH-LOGICAL-c692t-a130d2fffa20c42ef2cf4080f48d22d557a031beff0b8a4114b1ecb103f411c03</originalsourceid><addsrcrecordid>eNqNk9tu1DAQhiMEoqXwBggiISG42MWnnG6QVqXQlVpVopRbM_Eh68prL7GzgrfHy6bVBvUC5SKx_f3_eCYzWfYSozmmFf5w64fegZ1vvFNzhAvMSvooO8YNJbOSIPr44PsoexbCLUIFrcvyaXZEyqZilJTH2Y-FyxdyC04omZ-bEL31nRH5pYorL3Pt-_xsC3aAaLzLvc6XLqoQTYqcdMr5NYTcuPzSCJXfBOO6_JPpTEzH19ZIFZ5nTzTYoF6M75Ps5vPZt9Pz2cXVl-Xp4mImyobEGWCKJNFaA0GCEaWJ0AzVSLNaEiKLogJEcau0Rm0NDGPWYiVajKhOC4HoSfZ677uxPvCxOIHjqkp5krqpErHcE9LDLd_0Zg39b-7B8L8bvu849NEIq3jNaoolJrghkkG6lAaqSCuooGVTwC7axzHa0K6VFMrFHuzEdHrizIp3fstZ1aAG42TwbjTo_c8hVZSvTRDKWnDKD_t71xiVjCX0zT_ow9mNVAcpAeO0T3HFzpQvWEFZhWldJ2r-AJUeqdZGpE7SJu1PBO8ngsRE9St2MITAl9df_5-9-j5l3x6wKwU2roK3w67NwhRke1D0PoRe6fsiY8R3g3BXDb4bBD4OQpK9OvxB96K7zqd_ACZUAns</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1773262897</pqid></control><display><type>article</type><title>An Advanced Histologic Method for Evaluation of Intestinal Adenomas in Mice Using Digital Slides</title><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>Public Library of Science (PLoS)</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><creator>Davis, Jennifer S ; Gupta, Vineet ; Gagea, Mihai ; Wu, Xiangwei</creator><contributor>Fornace, Albert J.</contributor><creatorcontrib>Davis, Jennifer S ; Gupta, Vineet ; Gagea, Mihai ; Wu, Xiangwei ; Fornace, Albert J.</creatorcontrib><description>Mice are used for modelling the biology of many human diseases, including colorectal cancer (CRC). Mouse models recapitulate many aspects of human disease and are invaluable tools for studying the biology, treatment and prevention of CRC. Unlike humans, many mouse models develop lesions primarily in the small intestine, which necessitates removal and examination of this organ in order to evaluate treatment efficacy. Commonly, the small intestine is visually examined for gross lesions and then selectively embedded in paraffin blocks for further microscopic analysis. Unfortunately, this method suffers from inherent bias toward counting large lesions and simultaneously missing smaller lesions. Even more, this method leaves no permanent record of diagnosed and measured lesions. We evaluated inter-observer variability in a mouse model of CRC using visual examination, and directly compared the visual, gross examination with a histologic analytic method using digital slides of hematoxylin and eosin stained tissue sections. Using visual examination, there was a high degree of inter-observer variability. As this method does not provide a permanent record of measurements, there is no capability to arbitrate between differing observations. In contrast, histologic analysis allowed for the creation of a permanent record of lesion measurements taken. When compared directly, histologic analysis of annotated digital images has significantly improved accuracy. Using this method we were able to distinguish mutant mice from wild type littermates even at a very young age. With gross visual examination, this distinction was not possible. Histologic analysis of digital images of murine intestinal tissue provides a vital improvement over the commonly used visual, gross examination method. Unlike visual gross examination, histologic analysis is not biased by the size of intestinal adenoma, misdiagnosis of another lesion type, or presence of a Peyer's patch. It also provides accountability in the form of a permanent record of lesions counted. Histologic analysis using digital slides represents a critical improvement over the current, widely used method of visual gross examination and should be considered for future studies using mouse models of CRC.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0151463</identifier><identifier>PMID: 26974326</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Accountability ; Accuracy ; Adenoma ; Adenoma - pathology ; Animal models ; Animals ; Annotations ; Arbitration ; Biology ; Biology and Life Sciences ; Cancer ; Colon cancer ; Colorectal cancer ; Colorectal carcinoma ; Counting ; Diagnosis ; Digital imaging ; Disease prevention ; Engineering and Technology ; Experiments ; Gagea ; Histological Techniques - methods ; Intestinal Neoplasms - pathology ; Intestines - pathology ; Laboratory animals ; Lesions ; Medicine and Health Sciences ; Mice, Inbred C57BL ; Microscopic analysis ; Mutation ; Paraffin ; Prevention ; Research and Analysis Methods ; Small intestine ; Studies ; Tumors ; Variability ; Veterinary medicine ; Visual observation</subject><ispartof>PloS one, 2016-03, Vol.11 (3), p.e0151463-e0151463</ispartof><rights>COPYRIGHT 2016 Public Library of Science</rights><rights>2016 Davis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2016 Davis et al 2016 Davis et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-a130d2fffa20c42ef2cf4080f48d22d557a031beff0b8a4114b1ecb103f411c03</citedby><cites>FETCH-LOGICAL-c692t-a130d2fffa20c42ef2cf4080f48d22d557a031beff0b8a4114b1ecb103f411c03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4790911/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4790911/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2100,2926,23864,27922,27923,53789,53791,79370,79371</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26974326$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Fornace, Albert J.</contributor><creatorcontrib>Davis, Jennifer S</creatorcontrib><creatorcontrib>Gupta, Vineet</creatorcontrib><creatorcontrib>Gagea, Mihai</creatorcontrib><creatorcontrib>Wu, Xiangwei</creatorcontrib><title>An Advanced Histologic Method for Evaluation of Intestinal Adenomas in Mice Using Digital Slides</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Mice are used for modelling the biology of many human diseases, including colorectal cancer (CRC). Mouse models recapitulate many aspects of human disease and are invaluable tools for studying the biology, treatment and prevention of CRC. Unlike humans, many mouse models develop lesions primarily in the small intestine, which necessitates removal and examination of this organ in order to evaluate treatment efficacy. Commonly, the small intestine is visually examined for gross lesions and then selectively embedded in paraffin blocks for further microscopic analysis. Unfortunately, this method suffers from inherent bias toward counting large lesions and simultaneously missing smaller lesions. Even more, this method leaves no permanent record of diagnosed and measured lesions. We evaluated inter-observer variability in a mouse model of CRC using visual examination, and directly compared the visual, gross examination with a histologic analytic method using digital slides of hematoxylin and eosin stained tissue sections. Using visual examination, there was a high degree of inter-observer variability. As this method does not provide a permanent record of measurements, there is no capability to arbitrate between differing observations. In contrast, histologic analysis allowed for the creation of a permanent record of lesion measurements taken. When compared directly, histologic analysis of annotated digital images has significantly improved accuracy. Using this method we were able to distinguish mutant mice from wild type littermates even at a very young age. With gross visual examination, this distinction was not possible. Histologic analysis of digital images of murine intestinal tissue provides a vital improvement over the commonly used visual, gross examination method. Unlike visual gross examination, histologic analysis is not biased by the size of intestinal adenoma, misdiagnosis of another lesion type, or presence of a Peyer's patch. It also provides accountability in the form of a permanent record of lesions counted. Histologic analysis using digital slides represents a critical improvement over the current, widely used method of visual gross examination and should be considered for future studies using mouse models of CRC.</description><subject>Accountability</subject><subject>Accuracy</subject><subject>Adenoma</subject><subject>Adenoma - pathology</subject><subject>Animal models</subject><subject>Animals</subject><subject>Annotations</subject><subject>Arbitration</subject><subject>Biology</subject><subject>Biology and Life Sciences</subject><subject>Cancer</subject><subject>Colon cancer</subject><subject>Colorectal cancer</subject><subject>Colorectal carcinoma</subject><subject>Counting</subject><subject>Diagnosis</subject><subject>Digital imaging</subject><subject>Disease prevention</subject><subject>Engineering and Technology</subject><subject>Experiments</subject><subject>Gagea</subject><subject>Histological Techniques - methods</subject><subject>Intestinal Neoplasms - pathology</subject><subject>Intestines - pathology</subject><subject>Laboratory animals</subject><subject>Lesions</subject><subject>Medicine and Health Sciences</subject><subject>Mice, Inbred C57BL</subject><subject>Microscopic analysis</subject><subject>Mutation</subject><subject>Paraffin</subject><subject>Prevention</subject><subject>Research and Analysis Methods</subject><subject>Small intestine</subject><subject>Studies</subject><subject>Tumors</subject><subject>Variability</subject><subject>Veterinary medicine</subject><subject>Visual observation</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNk9tu1DAQhiMEoqXwBggiISG42MWnnG6QVqXQlVpVopRbM_Eh68prL7GzgrfHy6bVBvUC5SKx_f3_eCYzWfYSozmmFf5w64fegZ1vvFNzhAvMSvooO8YNJbOSIPr44PsoexbCLUIFrcvyaXZEyqZilJTH2Y-FyxdyC04omZ-bEL31nRH5pYorL3Pt-_xsC3aAaLzLvc6XLqoQTYqcdMr5NYTcuPzSCJXfBOO6_JPpTEzH19ZIFZ5nTzTYoF6M75Ps5vPZt9Pz2cXVl-Xp4mImyobEGWCKJNFaA0GCEaWJ0AzVSLNaEiKLogJEcau0Rm0NDGPWYiVajKhOC4HoSfZ677uxPvCxOIHjqkp5krqpErHcE9LDLd_0Zg39b-7B8L8bvu849NEIq3jNaoolJrghkkG6lAaqSCuooGVTwC7axzHa0K6VFMrFHuzEdHrizIp3fstZ1aAG42TwbjTo_c8hVZSvTRDKWnDKD_t71xiVjCX0zT_ow9mNVAcpAeO0T3HFzpQvWEFZhWldJ2r-AJUeqdZGpE7SJu1PBO8ngsRE9St2MITAl9df_5-9-j5l3x6wKwU2roK3w67NwhRke1D0PoRe6fsiY8R3g3BXDb4bBD4OQpK9OvxB96K7zqd_ACZUAns</recordid><startdate>20160314</startdate><enddate>20160314</enddate><creator>Davis, Jennifer S</creator><creator>Gupta, Vineet</creator><creator>Gagea, Mihai</creator><creator>Wu, Xiangwei</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20160314</creationdate><title>An Advanced Histologic Method for Evaluation of Intestinal Adenomas in Mice Using Digital Slides</title><author>Davis, Jennifer S ; Gupta, Vineet ; Gagea, Mihai ; Wu, Xiangwei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-a130d2fffa20c42ef2cf4080f48d22d557a031beff0b8a4114b1ecb103f411c03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Accountability</topic><topic>Accuracy</topic><topic>Adenoma</topic><topic>Adenoma - pathology</topic><topic>Animal models</topic><topic>Animals</topic><topic>Annotations</topic><topic>Arbitration</topic><topic>Biology</topic><topic>Biology and Life Sciences</topic><topic>Cancer</topic><topic>Colon cancer</topic><topic>Colorectal cancer</topic><topic>Colorectal carcinoma</topic><topic>Counting</topic><topic>Diagnosis</topic><topic>Digital imaging</topic><topic>Disease prevention</topic><topic>Engineering and Technology</topic><topic>Experiments</topic><topic>Gagea</topic><topic>Histological Techniques - methods</topic><topic>Intestinal Neoplasms - pathology</topic><topic>Intestines - pathology</topic><topic>Laboratory animals</topic><topic>Lesions</topic><topic>Medicine and Health Sciences</topic><topic>Mice, Inbred C57BL</topic><topic>Microscopic analysis</topic><topic>Mutation</topic><topic>Paraffin</topic><topic>Prevention</topic><topic>Research and Analysis Methods</topic><topic>Small intestine</topic><topic>Studies</topic><topic>Tumors</topic><topic>Variability</topic><topic>Veterinary medicine</topic><topic>Visual observation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Davis, Jennifer S</creatorcontrib><creatorcontrib>Gupta, Vineet</creatorcontrib><creatorcontrib>Gagea, Mihai</creatorcontrib><creatorcontrib>Wu, Xiangwei</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing &amp; Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological &amp; Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>Agricultural &amp; Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection (ProQuest)</collection><collection>Natural Science Collection (ProQuest)</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing &amp; Allied Health Database (Alumni Edition)</collection><collection>Meteorological &amp; Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Davis, Jennifer S</au><au>Gupta, Vineet</au><au>Gagea, Mihai</au><au>Wu, Xiangwei</au><au>Fornace, Albert J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Advanced Histologic Method for Evaluation of Intestinal Adenomas in Mice Using Digital Slides</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2016-03-14</date><risdate>2016</risdate><volume>11</volume><issue>3</issue><spage>e0151463</spage><epage>e0151463</epage><pages>e0151463-e0151463</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Mice are used for modelling the biology of many human diseases, including colorectal cancer (CRC). Mouse models recapitulate many aspects of human disease and are invaluable tools for studying the biology, treatment and prevention of CRC. Unlike humans, many mouse models develop lesions primarily in the small intestine, which necessitates removal and examination of this organ in order to evaluate treatment efficacy. Commonly, the small intestine is visually examined for gross lesions and then selectively embedded in paraffin blocks for further microscopic analysis. Unfortunately, this method suffers from inherent bias toward counting large lesions and simultaneously missing smaller lesions. Even more, this method leaves no permanent record of diagnosed and measured lesions. We evaluated inter-observer variability in a mouse model of CRC using visual examination, and directly compared the visual, gross examination with a histologic analytic method using digital slides of hematoxylin and eosin stained tissue sections. Using visual examination, there was a high degree of inter-observer variability. As this method does not provide a permanent record of measurements, there is no capability to arbitrate between differing observations. In contrast, histologic analysis allowed for the creation of a permanent record of lesion measurements taken. When compared directly, histologic analysis of annotated digital images has significantly improved accuracy. Using this method we were able to distinguish mutant mice from wild type littermates even at a very young age. With gross visual examination, this distinction was not possible. Histologic analysis of digital images of murine intestinal tissue provides a vital improvement over the commonly used visual, gross examination method. Unlike visual gross examination, histologic analysis is not biased by the size of intestinal adenoma, misdiagnosis of another lesion type, or presence of a Peyer's patch. It also provides accountability in the form of a permanent record of lesions counted. Histologic analysis using digital slides represents a critical improvement over the current, widely used method of visual gross examination and should be considered for future studies using mouse models of CRC.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>26974326</pmid><doi>10.1371/journal.pone.0151463</doi><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1932-6203
ispartof PloS one, 2016-03, Vol.11 (3), p.e0151463-e0151463
issn 1932-6203
1932-6203
language eng
recordid cdi_plos_journals_1773262897
source MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS); EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry
subjects Accountability
Accuracy
Adenoma
Adenoma - pathology
Animal models
Animals
Annotations
Arbitration
Biology
Biology and Life Sciences
Cancer
Colon cancer
Colorectal cancer
Colorectal carcinoma
Counting
Diagnosis
Digital imaging
Disease prevention
Engineering and Technology
Experiments
Gagea
Histological Techniques - methods
Intestinal Neoplasms - pathology
Intestines - pathology
Laboratory animals
Lesions
Medicine and Health Sciences
Mice, Inbred C57BL
Microscopic analysis
Mutation
Paraffin
Prevention
Research and Analysis Methods
Small intestine
Studies
Tumors
Variability
Veterinary medicine
Visual observation
title An Advanced Histologic Method for Evaluation of Intestinal Adenomas in Mice Using Digital Slides
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-09T16%3A33%3A10IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=An%20Advanced%20Histologic%20Method%20for%20Evaluation%20of%20Intestinal%20Adenomas%20in%20Mice%20Using%20Digital%20Slides&rft.jtitle=PloS%20one&rft.au=Davis,%20Jennifer%20S&rft.date=2016-03-14&rft.volume=11&rft.issue=3&rft.spage=e0151463&rft.epage=e0151463&rft.pages=e0151463-e0151463&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0151463&rft_dat=%3Cgale_plos_%3EA453471388%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1773262897&rft_id=info:pmid/26974326&rft_galeid=A453471388&rft_doaj_id=oai_doaj_org_article_84831d12192d4affafa3e2bc3c3695a0&rfr_iscdi=true