The relative role of patient physiology and device optimisation in cardiac resynchronisation therapy: A computational modelling study
Abstract Cardiac resynchronisation therapy (CRT) is an established treatment for heart failure, however the effective selection of patients and optimisation of therapy remain controversial. While extensive research is ongoing, it remains unclear whether improvements in patient selection or therapy p...
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Veröffentlicht in: | Journal of molecular and cellular cardiology 2016-07, Vol.96, p.93-100 |
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creator | Crozier, Andrew Blazevic, Bojan Lamata, Pablo Plank, Gernot Ginks, Matthew Duckett, Simon Sohal, Manav Shetty, Anoop Rinaldi, Christopher A Razavi, Reza Smith, Nicolas P Niederer, Steven A |
description | Abstract Cardiac resynchronisation therapy (CRT) is an established treatment for heart failure, however the effective selection of patients and optimisation of therapy remain controversial. While extensive research is ongoing, it remains unclear whether improvements in patient selection or therapy planning offers a greater opportunity for the improvement of clinical outcomes. This computational study investigates the impact of both physiological conditions that guide patient selection and the optimisation of pacing lead placement on CRT outcomes. A multi-scale biophysical model of cardiac electromechanics was developed and personalised to patient data in three patients. These models were separated into components representing cardiac anatomy, pacing lead location, myocardial conductivity and stiffness, afterload, active contraction and conduction block for each individual, and recombined to generate a cohort of 648 virtual patients. The effect of these components on the change in total activation time of the ventricles (ΔTAT) and acute haemodynamic response (AHR) was analysed. The pacing site location was found to have the largest effect on ΔTAT and AHR. Secondary effects on ΔTAT and AHR were found for functional conduction block and cardiac anatomy. The simulation results highlight a need for a greater emphasis on therapy optimisation in order to achieve the best outcomes for patients. |
doi_str_mv | 10.1016/j.yjmcc.2015.10.026 |
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While extensive research is ongoing, it remains unclear whether improvements in patient selection or therapy planning offers a greater opportunity for the improvement of clinical outcomes. This computational study investigates the impact of both physiological conditions that guide patient selection and the optimisation of pacing lead placement on CRT outcomes. A multi-scale biophysical model of cardiac electromechanics was developed and personalised to patient data in three patients. These models were separated into components representing cardiac anatomy, pacing lead location, myocardial conductivity and stiffness, afterload, active contraction and conduction block for each individual, and recombined to generate a cohort of 648 virtual patients. The effect of these components on the change in total activation time of the ventricles (ΔTAT) and acute haemodynamic response (AHR) was analysed. The pacing site location was found to have the largest effect on ΔTAT and AHR. Secondary effects on ΔTAT and AHR were found for functional conduction block and cardiac anatomy. The simulation results highlight a need for a greater emphasis on therapy optimisation in order to achieve the best outcomes for patients.</description><identifier>ISSN: 0022-2828</identifier><identifier>EISSN: 1095-8584</identifier><identifier>DOI: 10.1016/j.yjmcc.2015.10.026</identifier><identifier>PMID: 26546827</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Aged ; Aged, 80 and over ; Cardiac resynchronisation therapy ; Cardiac Resynchronization Therapy ; Cardiovascular ; Computational modelling ; Computer Simulation ; Dyssynchronous heart failure ; Female ; Heart failure ; Heart Failure - diagnosis ; Heart Failure - physiopathology ; Heart Failure - therapy ; Hemodynamics ; Humans ; Magnetic Resonance Imaging ; Male ; Middle Aged ; Models, Cardiovascular ; Myocardium - metabolism ; Patient-specific modelling ; Review ; Ventricular Dysfunction</subject><ispartof>Journal of molecular and cellular cardiology, 2016-07, Vol.96, p.93-100</ispartof><rights>Elsevier Ltd</rights><rights>2015 The Authors</rights><rights>Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.</rights><rights>2015 The Authors 2015</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c481t-1c1e3b6bac233e47d03e4266267597a961b1ecbbe531f0da816d0ca86fa9abe73</citedby><cites>FETCH-LOGICAL-c481t-1c1e3b6bac233e47d03e4266267597a961b1ecbbe531f0da816d0ca86fa9abe73</cites><orcidid>0000-0002-7380-6908 ; 0000-0002-3097-4928 ; 0000-0002-5081-784X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.yjmcc.2015.10.026$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,3549,27923,27924,45994</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26546827$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Crozier, Andrew</creatorcontrib><creatorcontrib>Blazevic, Bojan</creatorcontrib><creatorcontrib>Lamata, Pablo</creatorcontrib><creatorcontrib>Plank, Gernot</creatorcontrib><creatorcontrib>Ginks, Matthew</creatorcontrib><creatorcontrib>Duckett, Simon</creatorcontrib><creatorcontrib>Sohal, Manav</creatorcontrib><creatorcontrib>Shetty, Anoop</creatorcontrib><creatorcontrib>Rinaldi, Christopher A</creatorcontrib><creatorcontrib>Razavi, Reza</creatorcontrib><creatorcontrib>Smith, Nicolas P</creatorcontrib><creatorcontrib>Niederer, Steven A</creatorcontrib><title>The relative role of patient physiology and device optimisation in cardiac resynchronisation therapy: A computational modelling study</title><title>Journal of molecular and cellular cardiology</title><addtitle>J Mol Cell Cardiol</addtitle><description>Abstract Cardiac resynchronisation therapy (CRT) is an established treatment for heart failure, however the effective selection of patients and optimisation of therapy remain controversial. While extensive research is ongoing, it remains unclear whether improvements in patient selection or therapy planning offers a greater opportunity for the improvement of clinical outcomes. This computational study investigates the impact of both physiological conditions that guide patient selection and the optimisation of pacing lead placement on CRT outcomes. A multi-scale biophysical model of cardiac electromechanics was developed and personalised to patient data in three patients. These models were separated into components representing cardiac anatomy, pacing lead location, myocardial conductivity and stiffness, afterload, active contraction and conduction block for each individual, and recombined to generate a cohort of 648 virtual patients. The effect of these components on the change in total activation time of the ventricles (ΔTAT) and acute haemodynamic response (AHR) was analysed. The pacing site location was found to have the largest effect on ΔTAT and AHR. Secondary effects on ΔTAT and AHR were found for functional conduction block and cardiac anatomy. The simulation results highlight a need for a greater emphasis on therapy optimisation in order to achieve the best outcomes for patients.</description><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Cardiac resynchronisation therapy</subject><subject>Cardiac Resynchronization Therapy</subject><subject>Cardiovascular</subject><subject>Computational modelling</subject><subject>Computer Simulation</subject><subject>Dyssynchronous heart failure</subject><subject>Female</subject><subject>Heart failure</subject><subject>Heart Failure - diagnosis</subject><subject>Heart Failure - physiopathology</subject><subject>Heart Failure - therapy</subject><subject>Hemodynamics</subject><subject>Humans</subject><subject>Magnetic Resonance Imaging</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Models, Cardiovascular</subject><subject>Myocardium - metabolism</subject><subject>Patient-specific modelling</subject><subject>Review</subject><subject>Ventricular Dysfunction</subject><issn>0022-2828</issn><issn>1095-8584</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFUttu1DAQtRCILoUvQEL-gSy-JE6CRKWq4iZV4oHybDnjycYhiSM7u1I-gP_G6dIKeOHFl5lzzmjmDCGvOdtzxtXbfr_2I8BeMF6kyJ4J9YTsOKuLrCqq_CnZMSZEJipRXZAXMfaMsTqX8jm5EKrIVSXKHfl51yENOJjFndLDD0h9S-f0xWmhc7dG5wd_WKmZLLV4cpAA8-JGFxPGT9RNFEywzkCSiesEXfDTQ3LpMJh5fUevKfhxPi73YTPQ0VscBjcdaFyOdn1JnrVmiPjq931Jvn_8cHfzObv9-unLzfVtBnnFl4wDR9moxoCQEvPSsnQKpYQqi7o0teINR2gaLCRvmTUVV5aBqVRratNgKS_J1Vl3PjYjWkg9BjPoObjRhFV74_Tfmcl1-uBPOq95kdSSgDwLQPAxBmwfuZzpzRXd63tX9ObKFkyuJNabP8s-ch5sSID3ZwCm5k8Og46QDAC0LiAs2nr3nwJX__AhDdeBGX7girH3x5CmHjXXUWimv22Lse0FL2TaCcXlL2Ytuc4</recordid><startdate>20160701</startdate><enddate>20160701</enddate><creator>Crozier, Andrew</creator><creator>Blazevic, Bojan</creator><creator>Lamata, Pablo</creator><creator>Plank, Gernot</creator><creator>Ginks, Matthew</creator><creator>Duckett, Simon</creator><creator>Sohal, Manav</creator><creator>Shetty, Anoop</creator><creator>Rinaldi, Christopher A</creator><creator>Razavi, Reza</creator><creator>Smith, Nicolas P</creator><creator>Niederer, Steven A</creator><general>Elsevier Ltd</general><general>Academic Press</general><scope>6I.</scope><scope>AAFTH</scope><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>5PM</scope><orcidid>https://orcid.org/0000-0002-7380-6908</orcidid><orcidid>https://orcid.org/0000-0002-3097-4928</orcidid><orcidid>https://orcid.org/0000-0002-5081-784X</orcidid></search><sort><creationdate>20160701</creationdate><title>The relative role of patient physiology and device optimisation in cardiac resynchronisation therapy: A computational modelling study</title><author>Crozier, Andrew ; Blazevic, Bojan ; Lamata, Pablo ; Plank, Gernot ; Ginks, Matthew ; Duckett, Simon ; Sohal, Manav ; Shetty, Anoop ; Rinaldi, Christopher A ; Razavi, Reza ; Smith, Nicolas P ; Niederer, Steven A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c481t-1c1e3b6bac233e47d03e4266267597a961b1ecbbe531f0da816d0ca86fa9abe73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Cardiac resynchronisation therapy</topic><topic>Cardiac Resynchronization Therapy</topic><topic>Cardiovascular</topic><topic>Computational modelling</topic><topic>Computer Simulation</topic><topic>Dyssynchronous heart failure</topic><topic>Female</topic><topic>Heart failure</topic><topic>Heart Failure - diagnosis</topic><topic>Heart Failure - physiopathology</topic><topic>Heart Failure - therapy</topic><topic>Hemodynamics</topic><topic>Humans</topic><topic>Magnetic Resonance Imaging</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Models, Cardiovascular</topic><topic>Myocardium - metabolism</topic><topic>Patient-specific modelling</topic><topic>Review</topic><topic>Ventricular Dysfunction</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Crozier, Andrew</creatorcontrib><creatorcontrib>Blazevic, Bojan</creatorcontrib><creatorcontrib>Lamata, Pablo</creatorcontrib><creatorcontrib>Plank, Gernot</creatorcontrib><creatorcontrib>Ginks, Matthew</creatorcontrib><creatorcontrib>Duckett, Simon</creatorcontrib><creatorcontrib>Sohal, Manav</creatorcontrib><creatorcontrib>Shetty, Anoop</creatorcontrib><creatorcontrib>Rinaldi, Christopher A</creatorcontrib><creatorcontrib>Razavi, Reza</creatorcontrib><creatorcontrib>Smith, Nicolas P</creatorcontrib><creatorcontrib>Niederer, Steven A</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of molecular and cellular cardiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Crozier, Andrew</au><au>Blazevic, Bojan</au><au>Lamata, Pablo</au><au>Plank, Gernot</au><au>Ginks, Matthew</au><au>Duckett, Simon</au><au>Sohal, Manav</au><au>Shetty, Anoop</au><au>Rinaldi, Christopher A</au><au>Razavi, Reza</au><au>Smith, Nicolas P</au><au>Niederer, Steven A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The relative role of patient physiology and device optimisation in cardiac resynchronisation therapy: A computational modelling study</atitle><jtitle>Journal of molecular and cellular cardiology</jtitle><addtitle>J Mol Cell Cardiol</addtitle><date>2016-07-01</date><risdate>2016</risdate><volume>96</volume><spage>93</spage><epage>100</epage><pages>93-100</pages><issn>0022-2828</issn><eissn>1095-8584</eissn><abstract>Abstract Cardiac resynchronisation therapy (CRT) is an established treatment for heart failure, however the effective selection of patients and optimisation of therapy remain controversial. While extensive research is ongoing, it remains unclear whether improvements in patient selection or therapy planning offers a greater opportunity for the improvement of clinical outcomes. This computational study investigates the impact of both physiological conditions that guide patient selection and the optimisation of pacing lead placement on CRT outcomes. A multi-scale biophysical model of cardiac electromechanics was developed and personalised to patient data in three patients. These models were separated into components representing cardiac anatomy, pacing lead location, myocardial conductivity and stiffness, afterload, active contraction and conduction block for each individual, and recombined to generate a cohort of 648 virtual patients. The effect of these components on the change in total activation time of the ventricles (ΔTAT) and acute haemodynamic response (AHR) was analysed. The pacing site location was found to have the largest effect on ΔTAT and AHR. Secondary effects on ΔTAT and AHR were found for functional conduction block and cardiac anatomy. The simulation results highlight a need for a greater emphasis on therapy optimisation in order to achieve the best outcomes for patients.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>26546827</pmid><doi>10.1016/j.yjmcc.2015.10.026</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-7380-6908</orcidid><orcidid>https://orcid.org/0000-0002-3097-4928</orcidid><orcidid>https://orcid.org/0000-0002-5081-784X</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Aged Aged, 80 and over Cardiac resynchronisation therapy Cardiac Resynchronization Therapy Cardiovascular Computational modelling Computer Simulation Dyssynchronous heart failure Female Heart failure Heart Failure - diagnosis Heart Failure - physiopathology Heart Failure - therapy Hemodynamics Humans Magnetic Resonance Imaging Male Middle Aged Models, Cardiovascular Myocardium - metabolism Patient-specific modelling Review Ventricular Dysfunction |
title | The relative role of patient physiology and device optimisation in cardiac resynchronisation therapy: A computational modelling study |
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