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Next-generation In Silico Cardiac Electrophysiology Through Immersed Grid Meshfree Modeling: Application To Simulation Of Myocardial Infarction
State-of-art simulators of cardiac tissue electrophysiology are commonly based on the Finite Element Method (FEM). FEM is known to be a robust and accurate numerical method, but its accuracy highly depends on the quality of the mesh. Generating a good-quality mesh may be cumbersome and time consumin...
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description | State-of-art simulators of cardiac tissue electrophysiology are commonly based on the Finite Element Method (FEM). FEM is known to be a robust and accurate numerical method, but its accuracy highly depends on the quality of the mesh. Generating a good-quality mesh may be cumbersome and time consuming for models with complex geometries, such as those representing the anatomy of human organs. This limitation restricts the clinical application of FEM. To overcome this challenge, we propose the use of a meshfree method, the Moving Kriging Mixed Collocation (MKMC) method for in silico cardiac electrophysiology. MKMC is a purely meshfree method requiring the definition of a point cloud rather than a mesh. We propose the construction of the point cloud as an immersed grid of points generated automatically from image data. In simulations on a swine biventricular model, both under baseline and myocardial infarction conditions, we demonstrate the capability of the MKMC method to generate results in very good agreement with FEM while alleviating the mesh requirement. Differences in local activation time and action potential duration between MKMC and FEM are in mean below 3%. The proposed MKMC method represents a promising alternative to FEM for cardiac in silico investigations with the potential to be integrated in the clinic. |
doi_str_mv | 10.22489/CinC.2020.254 |
format | conference_proceeding |
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FEM is known to be a robust and accurate numerical method, but its accuracy highly depends on the quality of the mesh. Generating a good-quality mesh may be cumbersome and time consuming for models with complex geometries, such as those representing the anatomy of human organs. This limitation restricts the clinical application of FEM. To overcome this challenge, we propose the use of a meshfree method, the Moving Kriging Mixed Collocation (MKMC) method for in silico cardiac electrophysiology. MKMC is a purely meshfree method requiring the definition of a point cloud rather than a mesh. We propose the construction of the point cloud as an immersed grid of points generated automatically from image data. In simulations on a swine biventricular model, both under baseline and myocardial infarction conditions, we demonstrate the capability of the MKMC method to generate results in very good agreement with FEM while alleviating the mesh requirement. Differences in local activation time and action potential duration between MKMC and FEM are in mean below 3%. The proposed MKMC method represents a promising alternative to FEM for cardiac in silico investigations with the potential to be integrated in the clinic.</description><identifier>EISSN: 2325-887X</identifier><identifier>EISBN: 9781728173825</identifier><identifier>EISBN: 1728173825</identifier><identifier>DOI: 10.22489/CinC.2020.254</identifier><language>eng</language><publisher>Creative Commons; the authors hold their copyright</publisher><subject>Computational modeling ; Finite element analysis ; Myocardium ; Next generation networking ; Silicon compounds ; Solid modeling ; Three-dimensional displays</subject><ispartof>2020 Computing in Cardiology, 2020, p.1-4</ispartof><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9344286$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,27904,54533,54910</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9344286$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Mountris, Konstantinos A</creatorcontrib><creatorcontrib>Pueyo, Esther</creatorcontrib><title>Next-generation In Silico Cardiac Electrophysiology Through Immersed Grid Meshfree Modeling: Application To Simulation Of Myocardial Infarction</title><title>2020 Computing in Cardiology</title><addtitle>CinC</addtitle><description>State-of-art simulators of cardiac tissue electrophysiology are commonly based on the Finite Element Method (FEM). 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Differences in local activation time and action potential duration between MKMC and FEM are in mean below 3%. The proposed MKMC method represents a promising alternative to FEM for cardiac in silico investigations with the potential to be integrated in the clinic.</description><subject>Computational modeling</subject><subject>Finite element analysis</subject><subject>Myocardium</subject><subject>Next generation networking</subject><subject>Silicon compounds</subject><subject>Solid modeling</subject><subject>Three-dimensional displays</subject><issn>2325-887X</issn><isbn>9781728173825</isbn><isbn>1728173825</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2020</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotjUFLw0AQhVdBsNRevXjZP5CazG6SjbcSai209mAFb2WzmU1WkmzYpGB-hX_Z1TowM7z34HuE3EfhEoCL7DE3Xb6EELyO-RVZZKmIUvDLBMTXZAYM4kCI9OOWLIbhM_QTpyJLxIx8v-LXGFTYoZOjsR3ddvTNNEZZmktXGqnoukE1OtvX02BsY6uJHmtnz1VNt22LbsCSbpwp6R6HWjtEurclNqarnuiq7z3qAj5aD27PzUUdNN1PVv1VNL5US6d-gztyo2Uz4OL_z8n78_qYvwS7w2abr3aBAc7GICtYqAoBUVLwKIwKDFEwSHWoFYciBalRK38wycpUMYi8ySMpGAOeFKjZnDxcuAYRT70zrXTTKWOcg0jYD-3YZ8I</recordid><startdate>20200913</startdate><enddate>20200913</enddate><creator>Mountris, Konstantinos A</creator><creator>Pueyo, Esther</creator><general>Creative Commons; the authors hold their copyright</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>20200913</creationdate><title>Next-generation In Silico Cardiac Electrophysiology Through Immersed Grid Meshfree Modeling: Application To Simulation Of Myocardial Infarction</title><author>Mountris, Konstantinos A ; Pueyo, Esther</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i243t-9b30cb8216b4101be0e8327f0fc42b72afefcafee69d7c3212b741a833246bef3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Computational modeling</topic><topic>Finite element analysis</topic><topic>Myocardium</topic><topic>Next generation networking</topic><topic>Silicon compounds</topic><topic>Solid modeling</topic><topic>Three-dimensional displays</topic><toplevel>online_resources</toplevel><creatorcontrib>Mountris, Konstantinos A</creatorcontrib><creatorcontrib>Pueyo, Esther</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Mountris, Konstantinos A</au><au>Pueyo, Esther</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Next-generation In Silico Cardiac Electrophysiology Through Immersed Grid Meshfree Modeling: Application To Simulation Of Myocardial Infarction</atitle><btitle>2020 Computing in Cardiology</btitle><stitle>CinC</stitle><date>2020-09-13</date><risdate>2020</risdate><spage>1</spage><epage>4</epage><pages>1-4</pages><eissn>2325-887X</eissn><eisbn>9781728173825</eisbn><eisbn>1728173825</eisbn><abstract>State-of-art simulators of cardiac tissue electrophysiology are commonly based on the Finite Element Method (FEM). FEM is known to be a robust and accurate numerical method, but its accuracy highly depends on the quality of the mesh. Generating a good-quality mesh may be cumbersome and time consuming for models with complex geometries, such as those representing the anatomy of human organs. This limitation restricts the clinical application of FEM. To overcome this challenge, we propose the use of a meshfree method, the Moving Kriging Mixed Collocation (MKMC) method for in silico cardiac electrophysiology. MKMC is a purely meshfree method requiring the definition of a point cloud rather than a mesh. We propose the construction of the point cloud as an immersed grid of points generated automatically from image data. In simulations on a swine biventricular model, both under baseline and myocardial infarction conditions, we demonstrate the capability of the MKMC method to generate results in very good agreement with FEM while alleviating the mesh requirement. 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subjects | Computational modeling Finite element analysis Myocardium Next generation networking Silicon compounds Solid modeling Three-dimensional displays |
title | Next-generation In Silico Cardiac Electrophysiology Through Immersed Grid Meshfree Modeling: Application To Simulation Of Myocardial Infarction |
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