Quantitative analysis of electro-anatomical maps: application to an experimental model of LBBB/CRT

Abstract : Electroanatomical maps (EAMs) are commonly acquired in clinical routine for guiding ablation therapies. They provide voltage and activation time information on a 3D anatomical mesh representation, making them useful for analyzing the electrical activation patterns in specific pathologies. However, they are extremely acquisition dependent and complex, and therefore difficult to quantify and compare with other EAMs acquired at different times or from different patients. In this paper, we introduce a set of tools for the quantitative analysis of EAMs, going beyond the methods currently used in clinical practice. They are based on the quantitative estimation of simple biomarkers relevant to disease and therapies. Notably, we develop global indices (total activation time), local indices (local activation time, surrogates of conduction velocity, inter-ventricular and transmural delays), and therapy-based indices (lead position) to better characterize EAM data. Furthermore we propose 2D and 3D representations of the activation patterns –for their enhanced visualization and comparison in a common reference system. After verification and validation experiments on synthetically generated data, the proposed analysis tools are applied to EAM data obtained in an experimental swine model of induced Left Bundle Branch Block (LBBB) with an implanted Cardiac Resynchronization (CRT) device. Specifically, we have analyzed and compared electrical activation patterns at baseline, LBBB and CRT stages in 4 animals: two without any structural disease; and two with an induced infarction. The proposed tools automatically relate the ventricular lead location with electrical dyssynchrony, which allows evaluating the current hypothesis about lead placement in CRT.
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IEEE Journal of Translational Engineering in Health and Medicine, IEEE, 2017, 5, pp.1900215. 〈10.1109/JTEHM.2016.2634006〉
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David Soto-Iglesias, Nicolas Duchateau, Constantine Butakoff, David Andreu, Juan Fernández-Armenta, et al.. Quantitative analysis of electro-anatomical maps: application to an experimental model of LBBB/CRT. IEEE Journal of Translational Engineering in Health and Medicine, IEEE, 2017, 5, pp.1900215. 〈10.1109/JTEHM.2016.2634006〉. 〈hal-01398828〉

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