Literature DB >> 22402335

Individualized model of torso surface for the inverse problem of electrocardiology.

Jana Lenkova1, Jana Svehlikova, Milan Tysler.   

Abstract

PURPOSE: We studied the implementation of a patient-specific torso model created without the use of magnetic resonance imaging in the inverse problem of electrocardiology.
METHOD: Three types of inhomogeneous numerical torso models were created, with different degrees of adjustment of the outer surface to patients, whereas the heart and lung models remained unchanged. The torso models were used in the inverse localization of small areas with repolarization changes from simulated difference integral QRST maps. The localization error (LE) was evaluated as the distance between the centers of the modeled and the inversely found area with repolarization changes.
RESULTS: The mean LE was 1.88 cm with the standard torso model. After adapting the torso shape, the mean LE was 1.83 cm, whereas after adapting both, the shape and electrode positions, the mean LE was 1.02 cm.
CONCLUSION: If torso imaging is not available, a torso model with adapted shape and electrode positions gives only slightly less accurate results.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22402335     DOI: 10.1016/j.jelectrocard.2012.01.006

Source DB:  PubMed          Journal:  J Electrocardiol        ISSN: 0022-0736            Impact factor:   1.438


  2 in total

1.  Effects of torso mesh density and electrode distribution on the accuracy of electrocardiographic imaging during atrial fibrillation.

Authors:  Rubén Molero; Ana González-Ascaso; Ismael Hernández-Romero; David Lundback-Mompó; Andreu M Climent; María S Guillem
Journal:  Front Physiol       Date:  2022-08-29       Impact factor: 4.755

2.  Detailed Anatomical and Electrophysiological Models of Human Atria and Torso for the Simulation of Atrial Activation.

Authors:  Ana Ferrer; Rafael Sebastián; Damián Sánchez-Quintana; José F Rodríguez; Eduardo J Godoy; Laura Martínez; Javier Saiz
Journal:  PLoS One       Date:  2015-11-02       Impact factor: 3.240

  2 in total

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