Document Detail

Inter-model consistency and complementarity: learning from ex-vivo imaging and electrophysiological data towards an integrated understanding of cardiac physiology.
MedLine Citation:
PMID:  21791225     Owner:  NLM     Status:  MEDLINE    
Computational models of the heart at various scales and levels of complexity have been independently developed, parameterised and validated using a wide range of experimental data for over four decades. However, despite remarkable progress, the lack of coordinated efforts to compare and combine these computational models has limited their impact on the numerous open questions in cardiac physiology. To address this issue, a comprehensive dataset has previously been made available to the community that contains the cardiac anatomy and fibre orientations from magnetic resonance imaging as well as epicardial transmembrane potentials from optical mapping measured on a perfused ex-vivo porcine heart. This data was used to develop and customize four models of cardiac electrophysiology with different level of details, including a personalized fast conduction Purkinje system, a maximum a posteriori estimation of the 3D distribution of transmembrane potential, the personalization of a simplified reaction-diffusion model, and a detailed biophysical model with generic conduction parameters. This study proposes the integration of these four models into a single modelling and simulation pipeline, after analyzing their common features and discrepancies. The proposed integrated pipeline demonstrates an increase prediction power of depolarization isochrones in different pacing conditions.
O Camara; M Sermesant; P Lamata; L Wang; M Pop; J Relan; M De Craene; H Delingette; H Liu; S Niederer; A Pashaei; G Plank; D Romero; R Sebastian; K C L Wong; H Zhang; N Ayache; A F Frangi; P Shi; N P Smith; G A Wright
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Publication Detail:
Type:  In Vitro; Journal Article; Research Support, Non-U.S. Gov't     Date:  2011-07-20
Journal Detail:
Title:  Progress in biophysics and molecular biology     Volume:  107     ISSN:  1873-1732     ISO Abbreviation:  Prog. Biophys. Mol. Biol.     Publication Date:  2011 Oct 
Date Detail:
Created Date:  2011-10-10     Completed Date:  2012-01-30     Revised Date:  2014-03-27    
Medline Journal Info:
Nlm Unique ID:  0401233     Medline TA:  Prog Biophys Mol Biol     Country:  England    
Other Details:
Languages:  eng     Pagination:  122-33     Citation Subset:  IM    
Copyright Information:
Copyright © 2011 Elsevier Ltd. All rights reserved.
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MeSH Terms
Biophysical Processes
Electrophysiological Processes*
Heart / anatomy & histology,  physiology*
Magnetic Resonance Imaging*
Membrane Potentials
Models, Biological*
Pericardium / anatomy & histology,  cytology,  physiology
Purkinje Fibers / anatomy & histology,  cytology,  physiology
Reproducibility of Results
Systems Integration
Time Factors
Grant Support
MOP93531//Canadian Institutes of Health Research

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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