Deciphering microvascular changes after myocardial infarction through 3D fully automated image analysis
The microvasculature continuously adapts in response to pathophysiological conditions to meet tissue demands. Quantitative assessment of the dynamic changes in the coronary microvasculature is therefore crucial in enhancing our knowledge regarding the impact of cardiovascular diseases in tissue perf...
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creator | Gkontra, Polyxeni Norton, Kerri-Ann Żak, Magdalena M. Clemente, Cristina Agüero, Jaume Ibáñez, Borja Santos, Andrés Popel, Aleksander S. Arroyo, Alicia G. |
description | The microvasculature continuously adapts in response to pathophysiological conditions to meet tissue demands. Quantitative assessment of the dynamic changes in the coronary microvasculature is therefore crucial in enhancing our knowledge regarding the impact of cardiovascular diseases in tissue perfusion and in developing efficient angiotherapies. Using confocal microscopy and thick tissue sections, we developed a 3D fully automated pipeline that allows to precisely reconstruct the microvasculature and to extract parameters that quantify all its major features, its relation to smooth muscle actin positive cells and capillary diffusion regions. The novel pipeline was applied in the analysis of the coronary microvasculature from healthy tissue and tissue at various stages after myocardial infarction (MI) in the pig model, whose coronary vasculature closely resembles that of human tissue. We unravelled alterations in the microvasculature, particularly structural changes and angioadaptation in the aftermath of MI. In addition, we evaluated the extracted knowledge’s potential for the prediction of pathophysiological conditions in tissue, using different classification schemes. The high accuracy achieved in this respect, demonstrates the ability of our approach not only to quantify and identify pathology-related changes of microvascular beds, but also to predict complex and dynamic microvascular patterns. |
doi_str_mv | 10.1038/s41598-018-19758-4 |
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Quantitative assessment of the dynamic changes in the coronary microvasculature is therefore crucial in enhancing our knowledge regarding the impact of cardiovascular diseases in tissue perfusion and in developing efficient angiotherapies. Using confocal microscopy and thick tissue sections, we developed a 3D fully automated pipeline that allows to precisely reconstruct the microvasculature and to extract parameters that quantify all its major features, its relation to smooth muscle actin positive cells and capillary diffusion regions. The novel pipeline was applied in the analysis of the coronary microvasculature from healthy tissue and tissue at various stages after myocardial infarction (MI) in the pig model, whose coronary vasculature closely resembles that of human tissue. We unravelled alterations in the microvasculature, particularly structural changes and angioadaptation in the aftermath of MI. In addition, we evaluated the extracted knowledge’s potential for the prediction of pathophysiological conditions in tissue, using different classification schemes. The high accuracy achieved in this respect, demonstrates the ability of our approach not only to quantify and identify pathology-related changes of microvascular beds, but also to predict complex and dynamic microvascular patterns.</description><identifier>ISSN: 2045-2322</identifier><identifier>EISSN: 2045-2322</identifier><identifier>DOI: 10.1038/s41598-018-19758-4</identifier><identifier>PMID: 29382844</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>14/19 ; 631/114/1305 ; 631/114/1564 ; 631/1647/245/2221 ; 631/1647/245/2225 ; Actin ; Animals ; Automation ; Cardiovascular diseases ; Confocal microscopy ; Heart attacks ; Humanities and Social Sciences ; Image processing ; Image Processing, Computer-Assisted - methods ; Imaging, Three-Dimensional - methods ; Male ; Microcirculation ; Microvasculature ; Microvessels - diagnostic imaging ; Microvessels - physiopathology ; multidisciplinary ; Myocardial infarction ; Myocardial Infarction - diagnostic imaging ; Myocardial Infarction - physiopathology ; Perfusion ; Science ; Science (multidisciplinary) ; Smooth muscle ; Swine ; Tissues</subject><ispartof>Scientific reports, 2018-01, Vol.8 (1), p.1854-19, Article 1854</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-b074b5b93c7eabee306a255e697198ae0b48fcfb06892f3154d4d6709d09e9a3</citedby><cites>FETCH-LOGICAL-c474t-b074b5b93c7eabee306a255e697198ae0b48fcfb06892f3154d4d6709d09e9a3</cites><orcidid>0000-0003-1002-9467</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/PMC5789835/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5789835/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,27903,27904,41099,42168,51555,53770,53772</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29382844$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gkontra, Polyxeni</creatorcontrib><creatorcontrib>Norton, Kerri-Ann</creatorcontrib><creatorcontrib>Żak, Magdalena M.</creatorcontrib><creatorcontrib>Clemente, Cristina</creatorcontrib><creatorcontrib>Agüero, Jaume</creatorcontrib><creatorcontrib>Ibáñez, Borja</creatorcontrib><creatorcontrib>Santos, Andrés</creatorcontrib><creatorcontrib>Popel, Aleksander S.</creatorcontrib><creatorcontrib>Arroyo, Alicia G.</creatorcontrib><title>Deciphering microvascular changes after myocardial infarction through 3D fully automated image analysis</title><title>Scientific reports</title><addtitle>Sci Rep</addtitle><addtitle>Sci Rep</addtitle><description>The microvasculature continuously adapts in response to pathophysiological conditions to meet tissue demands. Quantitative assessment of the dynamic changes in the coronary microvasculature is therefore crucial in enhancing our knowledge regarding the impact of cardiovascular diseases in tissue perfusion and in developing efficient angiotherapies. Using confocal microscopy and thick tissue sections, we developed a 3D fully automated pipeline that allows to precisely reconstruct the microvasculature and to extract parameters that quantify all its major features, its relation to smooth muscle actin positive cells and capillary diffusion regions. The novel pipeline was applied in the analysis of the coronary microvasculature from healthy tissue and tissue at various stages after myocardial infarction (MI) in the pig model, whose coronary vasculature closely resembles that of human tissue. We unravelled alterations in the microvasculature, particularly structural changes and angioadaptation in the aftermath of MI. In addition, we evaluated the extracted knowledge’s potential for the prediction of pathophysiological conditions in tissue, using different classification schemes. The high accuracy achieved in this respect, demonstrates the ability of our approach not only to quantify and identify pathology-related changes of microvascular beds, but also to predict complex and dynamic microvascular patterns.</description><subject>14/19</subject><subject>631/114/1305</subject><subject>631/114/1564</subject><subject>631/1647/245/2221</subject><subject>631/1647/245/2225</subject><subject>Actin</subject><subject>Animals</subject><subject>Automation</subject><subject>Cardiovascular diseases</subject><subject>Confocal microscopy</subject><subject>Heart attacks</subject><subject>Humanities and Social Sciences</subject><subject>Image processing</subject><subject>Image Processing, Computer-Assisted - methods</subject><subject>Imaging, Three-Dimensional - methods</subject><subject>Male</subject><subject>Microcirculation</subject><subject>Microvasculature</subject><subject>Microvessels - diagnostic imaging</subject><subject>Microvessels - physiopathology</subject><subject>multidisciplinary</subject><subject>Myocardial infarction</subject><subject>Myocardial Infarction - 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methods</topic><topic>Imaging, Three-Dimensional - methods</topic><topic>Male</topic><topic>Microcirculation</topic><topic>Microvasculature</topic><topic>Microvessels - diagnostic imaging</topic><topic>Microvessels - physiopathology</topic><topic>multidisciplinary</topic><topic>Myocardial infarction</topic><topic>Myocardial Infarction - diagnostic imaging</topic><topic>Myocardial Infarction - physiopathology</topic><topic>Perfusion</topic><topic>Science</topic><topic>Science (multidisciplinary)</topic><topic>Smooth muscle</topic><topic>Swine</topic><topic>Tissues</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gkontra, Polyxeni</creatorcontrib><creatorcontrib>Norton, Kerri-Ann</creatorcontrib><creatorcontrib>Żak, Magdalena M.</creatorcontrib><creatorcontrib>Clemente, Cristina</creatorcontrib><creatorcontrib>Agüero, Jaume</creatorcontrib><creatorcontrib>Ibáñez, Borja</creatorcontrib><creatorcontrib>Santos, Andrés</creatorcontrib><creatorcontrib>Popel, Aleksander S.</creatorcontrib><creatorcontrib>Arroyo, Alicia G.</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech 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>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database</collection><collection>Biological Science Database</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>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Scientific reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gkontra, Polyxeni</au><au>Norton, Kerri-Ann</au><au>Żak, Magdalena M.</au><au>Clemente, Cristina</au><au>Agüero, Jaume</au><au>Ibáñez, Borja</au><au>Santos, Andrés</au><au>Popel, Aleksander S.</au><au>Arroyo, Alicia G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Deciphering microvascular changes after myocardial infarction through 3D fully automated image analysis</atitle><jtitle>Scientific reports</jtitle><stitle>Sci Rep</stitle><addtitle>Sci Rep</addtitle><date>2018-01-30</date><risdate>2018</risdate><volume>8</volume><issue>1</issue><spage>1854</spage><epage>19</epage><pages>1854-19</pages><artnum>1854</artnum><issn>2045-2322</issn><eissn>2045-2322</eissn><abstract>The microvasculature continuously adapts in response to pathophysiological conditions to meet tissue demands. Quantitative assessment of the dynamic changes in the coronary microvasculature is therefore crucial in enhancing our knowledge regarding the impact of cardiovascular diseases in tissue perfusion and in developing efficient angiotherapies. Using confocal microscopy and thick tissue sections, we developed a 3D fully automated pipeline that allows to precisely reconstruct the microvasculature and to extract parameters that quantify all its major features, its relation to smooth muscle actin positive cells and capillary diffusion regions. The novel pipeline was applied in the analysis of the coronary microvasculature from healthy tissue and tissue at various stages after myocardial infarction (MI) in the pig model, whose coronary vasculature closely resembles that of human tissue. We unravelled alterations in the microvasculature, particularly structural changes and angioadaptation in the aftermath of MI. In addition, we evaluated the extracted knowledge’s potential for the prediction of pathophysiological conditions in tissue, using different classification schemes. The high accuracy achieved in this respect, demonstrates the ability of our approach not only to quantify and identify pathology-related changes of microvascular beds, but also to predict complex and dynamic microvascular patterns.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>29382844</pmid><doi>10.1038/s41598-018-19758-4</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0003-1002-9467</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | 14/19 631/114/1305 631/114/1564 631/1647/245/2221 631/1647/245/2225 Actin Animals Automation Cardiovascular diseases Confocal microscopy Heart attacks Humanities and Social Sciences Image processing Image Processing, Computer-Assisted - methods Imaging, Three-Dimensional - methods Male Microcirculation Microvasculature Microvessels - diagnostic imaging Microvessels - physiopathology multidisciplinary Myocardial infarction Myocardial Infarction - diagnostic imaging Myocardial Infarction - physiopathology Perfusion Science Science (multidisciplinary) Smooth muscle Swine Tissues |
title | Deciphering microvascular changes after myocardial infarction through 3D fully automated image analysis |
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