Prediction of the Exit Site of Ventricular Tachycardia Based on Different ECG Lead Systems

Michał Kania 1 Yves Coudière 2 Hubert Cochet 2 Michel Haïssaguerre 2 Pierre Jaïs 2 Mark Potse 2
1 CARMEN - Modélisation et calculs pour l'électrophysiologie cardiaque
IHU-LIRYC, IMB - Institut de Mathématiques de Bordeaux, Inria Bordeaux - Sud-Ouest
Abstract : The effectiveness of a computer-based method for localization of arrhythmia exit sites was studied. The proposed algorithm works on any set of 3 or more ECG leads. The QRS complex integral of an ectopic beat is reduced to principal components treated as coordinates of the exit site in ECG space and then projected to real space by a linear transformation. The accuracy of the method was tested on 5 patient-tailored models of human heart and torso. For each model ~500 simulations were run, each for different stimulus location. All locations were then estimated from simulated surface ECGs and method accuracy was investigated. The algorithm performed better for the left ventricle than for the right ventricle. The group mean absolute and relative (to a neighboring stimulation site) localization errors in millimeters were: 11.5 (SD=2.5), 2.6 (SD=0.5) for the 252-lead ECG; 12.2 (SD=2.7), 2.7 (SD=0.5) for the 12-lead ECG; and 11.7 (SD=2.4), 2.7 (SD=0.5) for the Frank VCG. This study suggest that the proposed method can predict exit sites with a precision in the order of a centimeter. Low values of error for neighbouring activation sites suggest opportunity for algorithm improvement. The use of vectorcardiographic leads is enough to obtain a precision comparable to a 252-lead ECG.
Type de document :
Communication dans un congrès
Computing in Cardiology, Sep 2017, Rennes, France. 〈http://www.cinc.org/〉
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Soumis le : mardi 3 octobre 2017 - 17:18:45
Dernière modification le : jeudi 15 mars 2018 - 22:16:03

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Michał Kania, Yves Coudière, Hubert Cochet, Michel Haïssaguerre, Pierre Jaïs, et al.. Prediction of the Exit Site of Ventricular Tachycardia Based on Different ECG Lead Systems. Computing in Cardiology, Sep 2017, Rennes, France. 〈http://www.cinc.org/〉. 〈hal-01567961〉

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