Three‐dimensional morphological characterization of colorectal pits from label‐free microscopy images
The prognosis of colorectal cancer (CRC), one of the most prevalent pathologies worldwide, is linked to early detection. Kudo's pit pattern classification states morphological pit patterns of the Lieberkühn crypts by analyzing the superficial mucosa, predicting the histology of colorectal lesio...
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creator | Erbes, Luciana A. Izaguirre, María F. Casco, Víctor H. Adur, Javier |
description | The prognosis of colorectal cancer (CRC), one of the most prevalent pathologies worldwide, is linked to early detection. Kudo's pit pattern classification states morphological pit patterns of the Lieberkühn crypts by analyzing the superficial mucosa, predicting the histology of colorectal lesions. Its use as a highly accurate two‐dimensional diagnostic criterion has increased, mostly involving expert endoscopists’ judgment. The processing of autofluorescence images could allow the diagnostic, bypassing staining techniques and decreasing the biopsies, resources and times involved in the inspection. That criterion could be extended by data of the pit three‐dimensional (3D) morphology. Thus, this work was aimed at obtaining 3D morphological information by quantifying geometrical and shape descriptors through software processing and analysis of widefield autofluorescence microscopy image stacks acquired by fresh colon tissue samples from a murine model of CRC. Statistical analyses included pits from control mice and from the second (2nd), fourth (4th), and eighth (8th) weeks of treatment. Statistically significant differences were found for almost all parameters between the pits from control and from the 4th treated week, stating that the major morphological changes begin after the 2nd week. In particular, pits from control or initial treatment time points were more tubular, straighter and less rough than the ones from later treatment points. Therefore, they may be more associated to normal or non‐neoplastic crypt lumens than linked to adenomas or even cancer crypts. These preliminary outcomes could be considered an advance in 3D pit morphology characterization.
3D representations of around 50 μm of the colorectal pits, from the outer mucosal layer to the inside, exemplifying the morphologies found in control and AOM/DSS treated time points. |
doi_str_mv | 10.1002/jemt.24055 |
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3D representations of around 50 μm of the colorectal pits, from the outer mucosal layer to the inside, exemplifying the morphologies found in control and AOM/DSS treated time points.</description><identifier>ISSN: 1059-910X</identifier><identifier>EISSN: 1097-0029</identifier><identifier>DOI: 10.1002/jemt.24055</identifier><identifier>PMID: 35072317</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley & Sons, Inc</publisher><subject>Adenoma - diagnostic imaging ; Adenoma - pathology ; Animal models ; Animals ; autofluorescence ; Biopsy ; Cancer ; Colon ; Colonoscopy - methods ; Colorectal cancer ; Colorectal carcinoma ; Colorectal Neoplasms - diagnostic imaging ; Colorectal Neoplasms - pathology ; Criteria ; crypt ; Crypts ; Histology ; Image acquisition ; Inspection ; Lumens ; Mathematical models ; Medical imaging ; Mice ; Microscopy ; Morphology ; Mucosa ; pit ; Pits ; Statistical analysis ; Statistical methods ; three‐dimensional morphology</subject><ispartof>Microscopy research and technique, 2022-05, Vol.85 (5), p.1937-1948</ispartof><rights>2022 Wiley Periodicals LLC.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c3165-840851ea8e71af27d56ed55acbc0899cfa257d52b44818beba080c1eb780c3bd3</cites><orcidid>0000-0003-3632-136X ; 0000-0002-3737-479X ; 0000-0003-2176-2226 ; 0000-0001-6799-583X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjemt.24055$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjemt.24055$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35072317$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Erbes, Luciana A.</creatorcontrib><creatorcontrib>Izaguirre, María F.</creatorcontrib><creatorcontrib>Casco, Víctor H.</creatorcontrib><creatorcontrib>Adur, Javier</creatorcontrib><title>Three‐dimensional morphological characterization of colorectal pits from label‐free microscopy images</title><title>Microscopy research and technique</title><addtitle>Microsc Res Tech</addtitle><description>The prognosis of colorectal cancer (CRC), one of the most prevalent pathologies worldwide, is linked to early detection. Kudo's pit pattern classification states morphological pit patterns of the Lieberkühn crypts by analyzing the superficial mucosa, predicting the histology of colorectal lesions. Its use as a highly accurate two‐dimensional diagnostic criterion has increased, mostly involving expert endoscopists’ judgment. The processing of autofluorescence images could allow the diagnostic, bypassing staining techniques and decreasing the biopsies, resources and times involved in the inspection. That criterion could be extended by data of the pit three‐dimensional (3D) morphology. Thus, this work was aimed at obtaining 3D morphological information by quantifying geometrical and shape descriptors through software processing and analysis of widefield autofluorescence microscopy image stacks acquired by fresh colon tissue samples from a murine model of CRC. Statistical analyses included pits from control mice and from the second (2nd), fourth (4th), and eighth (8th) weeks of treatment. Statistically significant differences were found for almost all parameters between the pits from control and from the 4th treated week, stating that the major morphological changes begin after the 2nd week. In particular, pits from control or initial treatment time points were more tubular, straighter and less rough than the ones from later treatment points. Therefore, they may be more associated to normal or non‐neoplastic crypt lumens than linked to adenomas or even cancer crypts. These preliminary outcomes could be considered an advance in 3D pit morphology characterization.
3D representations of around 50 μm of the colorectal pits, from the outer mucosal layer to the inside, exemplifying the morphologies found in control and AOM/DSS treated time points.</description><subject>Adenoma - diagnostic imaging</subject><subject>Adenoma - pathology</subject><subject>Animal models</subject><subject>Animals</subject><subject>autofluorescence</subject><subject>Biopsy</subject><subject>Cancer</subject><subject>Colon</subject><subject>Colonoscopy - methods</subject><subject>Colorectal cancer</subject><subject>Colorectal carcinoma</subject><subject>Colorectal Neoplasms - diagnostic imaging</subject><subject>Colorectal Neoplasms - pathology</subject><subject>Criteria</subject><subject>crypt</subject><subject>Crypts</subject><subject>Histology</subject><subject>Image acquisition</subject><subject>Inspection</subject><subject>Lumens</subject><subject>Mathematical models</subject><subject>Medical imaging</subject><subject>Mice</subject><subject>Microscopy</subject><subject>Morphology</subject><subject>Mucosa</subject><subject>pit</subject><subject>Pits</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><subject>three‐dimensional morphology</subject><issn>1059-910X</issn><issn>1097-0029</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kb9OwzAQhy0EoqWw8AAoEgtCCthO3Dgjqso_FbEUiS1ynEvryqmDnQiViUfgGXkSHFIYGJjOvvv0Sfc7hI4JviAY08sVVM0FjTFjO2hIcJqEvpvudm-WhinBzwN04NwKY0IYiffRIGI4oRFJhkjNlxbg8_2jUBWsnTJroYPK2HpptFko6X9yKayQDVj1JhoPBKYMpJ9akI0f16pxQWlNFWiRg_aq0huDSklrnDT1JlCVWIA7RHul0A6OtnWEnq6n88ltOHu8uZtczUIZkTELeYw5IyA4JESUNCnYGArGhMwl5mkqS0GZb9I8jjnhOeQCcywJ5IkvUV5EI3TWe2trXlpwTVYpJ0FrsQbTuoyOKY05TmLi0dM_6Mq01ifQUYyl2EeUeOq8p7qFnIUyq61fyW4ygrPuAFl3gOz7AB4-2SrbvILiF_1J3AOkB16Vhs0_qux--jDvpV91apRU</recordid><startdate>202205</startdate><enddate>202205</enddate><creator>Erbes, Luciana A.</creator><creator>Izaguirre, María F.</creator><creator>Casco, Víctor H.</creator><creator>Adur, Javier</creator><general>John Wiley & Sons, Inc</general><general>Wiley Subscription Services, Inc</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>7QF</scope><scope>7QO</scope><scope>7QP</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7SS</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>7U7</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>JG9</scope><scope>JQ2</scope><scope>K9.</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-3632-136X</orcidid><orcidid>https://orcid.org/0000-0002-3737-479X</orcidid><orcidid>https://orcid.org/0000-0003-2176-2226</orcidid><orcidid>https://orcid.org/0000-0001-6799-583X</orcidid></search><sort><creationdate>202205</creationdate><title>Three‐dimensional morphological characterization of colorectal pits from label‐free microscopy images</title><author>Erbes, Luciana A. ; Izaguirre, María F. ; Casco, Víctor H. ; Adur, Javier</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3165-840851ea8e71af27d56ed55acbc0899cfa257d52b44818beba080c1eb780c3bd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Adenoma - diagnostic imaging</topic><topic>Adenoma - pathology</topic><topic>Animal models</topic><topic>Animals</topic><topic>autofluorescence</topic><topic>Biopsy</topic><topic>Cancer</topic><topic>Colon</topic><topic>Colonoscopy - methods</topic><topic>Colorectal cancer</topic><topic>Colorectal carcinoma</topic><topic>Colorectal Neoplasms - diagnostic imaging</topic><topic>Colorectal Neoplasms - pathology</topic><topic>Criteria</topic><topic>crypt</topic><topic>Crypts</topic><topic>Histology</topic><topic>Image acquisition</topic><topic>Inspection</topic><topic>Lumens</topic><topic>Mathematical models</topic><topic>Medical imaging</topic><topic>Mice</topic><topic>Microscopy</topic><topic>Morphology</topic><topic>Mucosa</topic><topic>pit</topic><topic>Pits</topic><topic>Statistical analysis</topic><topic>Statistical methods</topic><topic>three‐dimensional morphology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Erbes, Luciana A.</creatorcontrib><creatorcontrib>Izaguirre, María F.</creatorcontrib><creatorcontrib>Casco, Víctor H.</creatorcontrib><creatorcontrib>Adur, Javier</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Toxicology Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Microscopy research and technique</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Erbes, Luciana A.</au><au>Izaguirre, María F.</au><au>Casco, Víctor H.</au><au>Adur, Javier</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Three‐dimensional morphological characterization of colorectal pits from label‐free microscopy images</atitle><jtitle>Microscopy research and technique</jtitle><addtitle>Microsc Res Tech</addtitle><date>2022-05</date><risdate>2022</risdate><volume>85</volume><issue>5</issue><spage>1937</spage><epage>1948</epage><pages>1937-1948</pages><issn>1059-910X</issn><eissn>1097-0029</eissn><abstract>The prognosis of colorectal cancer (CRC), one of the most prevalent pathologies worldwide, is linked to early detection. Kudo's pit pattern classification states morphological pit patterns of the Lieberkühn crypts by analyzing the superficial mucosa, predicting the histology of colorectal lesions. Its use as a highly accurate two‐dimensional diagnostic criterion has increased, mostly involving expert endoscopists’ judgment. The processing of autofluorescence images could allow the diagnostic, bypassing staining techniques and decreasing the biopsies, resources and times involved in the inspection. That criterion could be extended by data of the pit three‐dimensional (3D) morphology. Thus, this work was aimed at obtaining 3D morphological information by quantifying geometrical and shape descriptors through software processing and analysis of widefield autofluorescence microscopy image stacks acquired by fresh colon tissue samples from a murine model of CRC. Statistical analyses included pits from control mice and from the second (2nd), fourth (4th), and eighth (8th) weeks of treatment. Statistically significant differences were found for almost all parameters between the pits from control and from the 4th treated week, stating that the major morphological changes begin after the 2nd week. In particular, pits from control or initial treatment time points were more tubular, straighter and less rough than the ones from later treatment points. Therefore, they may be more associated to normal or non‐neoplastic crypt lumens than linked to adenomas or even cancer crypts. These preliminary outcomes could be considered an advance in 3D pit morphology characterization.
3D representations of around 50 μm of the colorectal pits, from the outer mucosal layer to the inside, exemplifying the morphologies found in control and AOM/DSS treated time points.</abstract><cop>Hoboken, USA</cop><pub>John Wiley & Sons, Inc</pub><pmid>35072317</pmid><doi>10.1002/jemt.24055</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0003-3632-136X</orcidid><orcidid>https://orcid.org/0000-0002-3737-479X</orcidid><orcidid>https://orcid.org/0000-0003-2176-2226</orcidid><orcidid>https://orcid.org/0000-0001-6799-583X</orcidid></addata></record> |
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subjects | Adenoma - diagnostic imaging Adenoma - pathology Animal models Animals autofluorescence Biopsy Cancer Colon Colonoscopy - methods Colorectal cancer Colorectal carcinoma Colorectal Neoplasms - diagnostic imaging Colorectal Neoplasms - pathology Criteria crypt Crypts Histology Image acquisition Inspection Lumens Mathematical models Medical imaging Mice Microscopy Morphology Mucosa pit Pits Statistical analysis Statistical methods three‐dimensional morphology |
title | Three‐dimensional morphological characterization of colorectal pits from label‐free microscopy images |
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