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Bridging the gap between computation and clinical biology: validation of cable theory in humans
Introduction: Computerized simulations of cardiac activity have significantly contributed to our understanding of cardiac electrophysiology, but techniques of simulations based on patient-acquired data remain in their infancy. We sought to integrate data acquired from human electrophysiological stud...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3761165/ https://www.ncbi.nlm.nih.gov/pubmed/24027527 http://dx.doi.org/10.3389/fphys.2013.00213 |
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author | Finlay, Malcolm C. Xu, Lei Taggart, Peter Hanson, Ben Lambiase, Pier D. |
author_facet | Finlay, Malcolm C. Xu, Lei Taggart, Peter Hanson, Ben Lambiase, Pier D. |
author_sort | Finlay, Malcolm C. |
collection | PubMed |
description | Introduction: Computerized simulations of cardiac activity have significantly contributed to our understanding of cardiac electrophysiology, but techniques of simulations based on patient-acquired data remain in their infancy. We sought to integrate data acquired from human electrophysiological studies into patient-specific models, and validated this approach by testing whether electrophysiological responses to sequential premature stimuli could be predicted in a quantitatively accurate manner. Methods: Eleven patients with structurally normal hearts underwent electrophysiological studies. Semi-automated analysis was used to reconstruct activation and repolarization dynamics for each electrode. This S(2) extrastimuli data was used to inform individualized models of cardiac conduction, including a novel derivation of conduction velocity restitution. Activation dynamics of multiple premature extrastimuli were then predicted from this model and compared against measured patient data as well as data derived from the ten-Tusscher cell-ionic model. Results: Activation dynamics following a premature S(3) were significantly different from those after an S(2). Patient specific models demonstrated accurate prediction of the S(3) activation wave, (Pearson's R(2) = 0.90, median error 4%). Examination of the modeled conduction dynamics allowed inferences into the spatial dispersion of activation delay. Further validation was performed against data from the ten-Tusscher cell-ionic model, with our model accurately recapitulating predictions of repolarization times (R(2) = 0.99). Conclusions: Simulations based on clinically acquired data can be used to successfully predict complex activation patterns following sequential extrastimuli. Such modeling techniques may be useful as a method of incorporation of clinical data into predictive models. |
format | Online Article Text |
id | pubmed-3761165 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-37611652013-09-11 Bridging the gap between computation and clinical biology: validation of cable theory in humans Finlay, Malcolm C. Xu, Lei Taggart, Peter Hanson, Ben Lambiase, Pier D. Front Physiol Physiology Introduction: Computerized simulations of cardiac activity have significantly contributed to our understanding of cardiac electrophysiology, but techniques of simulations based on patient-acquired data remain in their infancy. We sought to integrate data acquired from human electrophysiological studies into patient-specific models, and validated this approach by testing whether electrophysiological responses to sequential premature stimuli could be predicted in a quantitatively accurate manner. Methods: Eleven patients with structurally normal hearts underwent electrophysiological studies. Semi-automated analysis was used to reconstruct activation and repolarization dynamics for each electrode. This S(2) extrastimuli data was used to inform individualized models of cardiac conduction, including a novel derivation of conduction velocity restitution. Activation dynamics of multiple premature extrastimuli were then predicted from this model and compared against measured patient data as well as data derived from the ten-Tusscher cell-ionic model. Results: Activation dynamics following a premature S(3) were significantly different from those after an S(2). Patient specific models demonstrated accurate prediction of the S(3) activation wave, (Pearson's R(2) = 0.90, median error 4%). Examination of the modeled conduction dynamics allowed inferences into the spatial dispersion of activation delay. Further validation was performed against data from the ten-Tusscher cell-ionic model, with our model accurately recapitulating predictions of repolarization times (R(2) = 0.99). Conclusions: Simulations based on clinically acquired data can be used to successfully predict complex activation patterns following sequential extrastimuli. Such modeling techniques may be useful as a method of incorporation of clinical data into predictive models. Frontiers Media S.A. 2013-09-04 /pmc/articles/PMC3761165/ /pubmed/24027527 http://dx.doi.org/10.3389/fphys.2013.00213 Text en Copyright © 2013 Finlay, Xu, Taggart, Hanson and Lambiase. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Physiology Finlay, Malcolm C. Xu, Lei Taggart, Peter Hanson, Ben Lambiase, Pier D. Bridging the gap between computation and clinical biology: validation of cable theory in humans |
title | Bridging the gap between computation and clinical biology: validation of cable theory in humans |
title_full | Bridging the gap between computation and clinical biology: validation of cable theory in humans |
title_fullStr | Bridging the gap between computation and clinical biology: validation of cable theory in humans |
title_full_unstemmed | Bridging the gap between computation and clinical biology: validation of cable theory in humans |
title_short | Bridging the gap between computation and clinical biology: validation of cable theory in humans |
title_sort | bridging the gap between computation and clinical biology: validation of cable theory in humans |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3761165/ https://www.ncbi.nlm.nih.gov/pubmed/24027527 http://dx.doi.org/10.3389/fphys.2013.00213 |
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