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Radiology. 2014 Apr;271(1):239-47. doi: 10.1148/radiol.13131331. Epub 2013 Dec 3.

Cardiac arrythmias: multimodal assessment integrating body surface ECG mapping into cardiac imaging.

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From the Departments of Cardiovascular Imaging (H.C., M.M., F.L.) and Cardiac Pacing and Electrophysiology (F.S., N.D., M. Hocini, M. Haïssaguerre, P.J.), Centre Hospitalier Universitaire/Université de Bordeaux, Hopital Cardiologique Haut Lévêque, Avenue de Magellan, 33604 Pessac, France; L'Institut de Rythmologie et de Modélisation Cardiaque-Equipex Multimodal Platform for Specific Imaging in Cardiology, Centre Hospitalier Universitaire/Université de Bordeaux/Institut National de la Santé et de la Recherche Médicale U1045, Pessac, France (H.C., R.D., F.S., N.D., M.H., M.M., M.H., F.L., P.J.); and Institut National de Recherche en Informatique et Automatique Asclepios Research Team-Institut National de Recherche en Informatique et Automatique Sophia Antipolis, Sophia Antipolis, France (M.S.).



To demonstrate the feasibility of comprehensive assessment of cardiac arrhythmias by combining body surface electrocardiographic (ECG) mapping (BSM) and imaging.


This study was approved by the institutional review board, and all patients gave written informed consent. Twenty-seven patients referred for electrophysiologic procedures in the context of ventricular tachycardia (VT) (n = 9), Wolff-Parkinson-White (WPW) syndrome (n = 2), atrial fibrillation (AF) (n = 13), or scar-related ventricular fibrillation (VF) (n = 3) were examined. Patients underwent BSM and imaging with multidetector computed tomography (CT) (n = 12) and/or delayed enhanced magnetic resonance (MR) imaging (n = 23). BSM was performed by using a 252-electrode vest that enabled the computation of epicardial electrograms from body surface potentials. The epicardial geometry used for BSM was registered to the epicardial geometry segmented from imaging data by using an automatic algorithm. The output was a three-dimensional cardiac model that integrated cardiac anatomy, myocardial substrate, and epicardial activation.


Acquisition, segmentation, and registration were feasible in all patients. In VT, this enabled a noninvasive assessment of the arrhythmia mechanism and its location with respect to the myocardial substrate, coronary vessels, and phrenic nerve. In WPW syndrome, this enabled understanding of complex accessory pathways resistant to previous ablation. In AF and VF, this enabled the noninvasive assessment of arrhythmia mechanisms and the analysis of rotor trajectories with respect to the myocardial substrate. In all patients, models were successfully integrated in navigation systems and used to guide mapping and ablation.


By combining information on anatomy, substrate, and electrical activation, the fusion of BSM and imaging enables comprehensive noninvasive assessment of cardiac arrhythmias, with potential applications for diagnosis, prognosis, and ablation targeting. Online supplemental material is available for this article.

[Indexed for MEDLINE]

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