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...
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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. |
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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 & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & 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 & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & 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 & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - 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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> |
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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 |
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