Key result
Electrocardiographic imaging accurately detects electrical dyssynchrony and identifies the latest activation site within ~9 mm.
Why the study?
Does electrocardiographic imaging accurately detect electrical dyssynchrony compared to direct epicardial recordings in a pig heart model?
Does electrocardiographic imaging accurately detect electrical dyssynchrony compared to direct epicardial recordings in a pig heart model?
Electrocardiographic imaging accurately detects electrical dyssynchrony and the site of latest activation, providing superior information compared to standard body surface potentials.
ECGi accurately maps activation in porcine models; leaves open translation to human CRT optimization.
BACKGROUND: Poor identification of electrical dyssynchrony is postulated to be a major factor contributing to the low success rate for cardiac resynchronization therapy. OBJECTIVE: The purpose of this study was to evaluate the sensitivity of body surface mapping and electrocardiographic imaging (ECGi) to detect electrical dyssynchrony noninvasively. METHODS: Langendorff-perfused pig hearts (n = 11) were suspended in a human torso-shaped tank, with left bundle branch block (LBBB) induced through ablation. Recordings were taken simultaneously from a 108-electrode epicardial sock and 128 electrodes embedded in the tank surface during sinus rhythm and ventricular pacing. Computed tomography provided electrode and heart positions in the tank. Epicardial unipolar electrograms were reconstructed from torso potentials using ECGi. Dyssynchrony markers from torso potentials (eg, QRS duration) or ECGi (total activation time, interventricular delay [D-LR], and intraventricular markers) were correlated with those recorded from the sock. RESULTS: LBBB was induced (n = 8), and sock-derived activation maps demonstrated interventricular dyssynchrony (D-LR and total activation time) in all cases (P < .05) and intraventricular dyssynchrony for complete LBBB (P < .05) compared to normal sinus rhythm. Only D-LR returned to normal with biventricular pacing (P = .1). Torso markers increased with large degrees of dyssynchrony, and no reduction was seen during biventricular pacing (P > .05). Although ECGi-derived markers were significantly lower than recorded (P < .05), there was a significant strong linear relationship between ECGi and recorded values. ECGi correctly diagnosed electrical dyssynchrony and interventricular resynchronization in all cases. The latest site of activation was identified to 9.1 ± 0.6 mm by ECGi. CONCLUSION: ECGi reliably and accurately detects electrical dyssynchrony, resynchronization by biventricular pacing, and the site of latest activation, providing more information than do body surface potentials.
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Bear et al. (2018) studied Electrical dyssynchrony (n=11). Electrocardiographic imaging (ECGi) vs. Body surface mapping and epicardial sock recordings was evaluated on Detection of electrical dyssynchrony and site of latest activation. Electrocardiographic imaging accurately detected electrical dyssynchrony and resynchronization, identifying the latest site of activation to 9.1 ± 0.6 mm compared to epicardial recordings.
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