Assessment of the equivalent dipole layer source model in the reconstruction of cardiac activation times on the basis of BSPMs ... View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-06

AUTHORS

Arno M. Janssen, Danila Potyagaylo, Olaf Dössel, Thom F. Oostendorp

ABSTRACT

Promising results have been reported in noninvasive estimation of cardiac activation times (AT) using the equivalent dipole layer (EDL) source model in combination with the boundary element method (BEM). However, the assumption of equal anisotropy ratios in the heart that underlies the EDL model does not reflect reality. In the present study, we quantify the errors of the nonlinear AT imaging based on the EDL approximation. Nine different excitation patterns (sinus rhythm and eight ectopic beats) were simulated with the monodomain model. Based on the bidomain theory, the body surface potential maps (BSPMs) were calculated for a realistic finite element volume conductor with an anisotropic heart model. For the forward calculations, three cases of bidomain conductivity tensors in the heart were considered: isotropic, equal, and unequal anisotropy ratios in the intra- and extracellular spaces. In all inverse reconstructions, the EDL model with BEM was employed: AT were estimated by solving the nonlinear optimization problem with the initial guess provided by the fastest route algorithm. Expectedly, the case of unequal anisotropy ratios resulted in larger localization errors for almost all considered activation patterns. For the sinus rhythm, all sites of early activation were correctly estimated with an optimal regularization parameter being used. For the ectopic beats, all but one foci were correctly classified to have either endo- or epicardial origin with an average localization error of 20.4 mm for unequal anisotropy ratio. The obtained results confirm validation studies and suggest that cardiac anisotropy might be neglected in clinical applications of the considered EDL-based inverse procedure. More... »

PAGES

1013-1025

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s11517-017-1715-x

    DOI

    http://dx.doi.org/10.1007/s11517-017-1715-x

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1092657164

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/29130137


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