Literature DB >> 33089458

Approaches for determining cardiac bidomain conductivity values: progress and challenges.

Barbara M Johnston1, Peter R Johnston2.   

Abstract

Modelling the electrical activity of the heart is an important tool for understanding electrical function in various diseases and conduction disorders. Clearly, for model results to be useful, it is necessary to have accurate inputs for the models, in particular the commonly used bidomain model. However, there are only three sets of four experimentally determined conductivity values for cardiac ventricular tissue and these are inconsistent, were measured around 40 years ago, often produce different results in simulations and do not fully represent the three-dimensional anisotropic nature of cardiac tissue. Despite efforts in the intervening years, difficulties associated with making the measurements and also determining the conductivities from the experimental data have not yet been overcome. In this review, we summarise what is known about the conductivity values, as well as progress to date in meeting the challenges associated with both the mathematical modelling and the experimental techniques. Graphical abstract Epicardial potential distributions, arising from a subendocardial ischaemic region, modelled using conductivity data from the indicated studies.

Entities:  

Keywords:  Bidomain model; Cardiac conductivity values; Electrophysiology; Heart; Review

Mesh:

Year:  2020        PMID: 33089458      PMCID: PMC7755382          DOI: 10.1007/s11517-020-02272-z

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  62 in total

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Authors:  Piero Colli-Franzone; Luciano Guerri; Bruno Taccardi
Journal:  Math Biosci       Date:  2004 Mar-Apr       Impact factor: 2.144

2.  Electrode systems for measuring cardiac impedances using optical transmembrane potential sensors and interstitial electrodes--theoretical design.

Authors:  Roger C Barr; Robert Plonsey
Journal:  IEEE Trans Biomed Eng       Date:  2003-08       Impact factor: 4.538

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Journal:  Prog Biophys Mol Biol       Date:  2010-05-27       Impact factor: 3.667

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Authors:  Leon S Graham; David Kilpatrick
Journal:  Ann Biomed Eng       Date:  2010-07-14       Impact factor: 3.934

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Authors:  K R Foster; H P Schwan
Journal:  Crit Rev Biomed Eng       Date:  1989

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Authors:  Travis M Austin; Mark L Trew; Andrew J Pullan
Journal:  IEEE Trans Biomed Eng       Date:  2006-07       Impact factor: 4.538

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Authors:  L Clerc
Journal:  J Physiol       Date:  1976-02       Impact factor: 5.182

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Authors:  Paul E Hand; Boyce E Griffith; Charles S Peskin
Journal:  Bull Math Biol       Date:  2009-05-02       Impact factor: 1.758

9.  Effect of inhomogeneities on the apparent location and magnitude of a cardiac current dipole source.

Authors:  R M Arthur; D B Geselowitz
Journal:  IEEE Trans Biomed Eng       Date:  1970-04       Impact factor: 4.538

10.  Electrical conductivity of skeletal muscle tissue: experimental results from different muscles in vivo.

Authors:  F L Gielen; W Wallinga-de Jonge; K L Boon
Journal:  Med Biol Eng Comput       Date:  1984-11       Impact factor: 2.602

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  1 in total

1.  Etiology-Specific Remodeling in Ventricular Tissue of Heart Failure Patients and Its Implications for Computational Modeling of Electrical Conduction.

Authors:  Aparna C Sankarankutty; Joachim Greiner; Jean Bragard; Joseph R Visker; Thirupura S Shankar; Christos P Kyriakopoulos; Stavros G Drakos; Frank B Sachse
Journal:  Front Physiol       Date:  2021-10-05       Impact factor: 4.566

  1 in total

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