Key result
Simulated ECG belt dyssynchrony metrics strongly correlate with ECGi for assessing left ventricular activation time.
Why the study?
The relationship between electrical dyssynchrony metrics derived from ECGi and the ECG belt in CRT patients is unknown.
Does a simulated ECG belt provide comparable electrical dyssynchrony metrics to electrocardiographic imaging (ECGi) in patients undergoing CRT?
Observational (n=17)
Does a simulated ECG belt provide comparable electrical dyssynchrony metrics to electrocardiographic imaging (ECGi) in patients undergoing CRT?
A simulated ECG belt provides electrical dyssynchrony metrics that strongly correlate with those from ECGi, potentially offering a simpler and more cost-effective assessment method.
ECG belt metrics may offer simpler dyssynchrony assessment than ECGi but should not yet change practice; leaves open prospective validation in CRT.
AIMS: Electrocardiographic imaging (ECGi) and the ECG belt are body surface potential mapping systems which can assess electrical dyssynchrony in patients undergoing cardiac resynchronization therapy (CRT). ECGi-derived dyssynchrony metrics are calculated from reconstructed epicardial potentials based on body surface potentials combined with a thoracic CT scan, while the ECG belt relies on body surface potentials alone. The relationship between dyssynchrony metrics from these two systems is unknown. In this study we aim to compare intra-ventricular and inter-ventricular dyssynchrony metrics between ECGi and the ECG belt. METHODS: Seventeen patients underwent ECGi after CRT. A subsample of 40 body surface potentials was used to simulate the ECG belt. ECGi dyssynchrony metrics, calculated from reconstructed epicardial potentials, and ECG belt dyssynchrony metrics, calculated from the sampled body surface potentials were compared. RESULTS: There was a strong positive correlation between ECGi left ventricular activation time (LVAT) and ECG belt left thorax activation time (LTAT) (R = 0.88 ; P < 0.001) and between ECGi standard deviation of activation times (SDAT) and ECG belt-SDAT (R = 0.76; P < 0.001) during intrinsic rhythm. The correlation for both pairs was also strong during biventricular pacing. Ventricular electrical uncoupling, a well validated ECGi inter-ventricular dyssynchrony metric, correlated strongly with ECG belt-SDAT during intrinsic rhythm (R = 0.76; P < 0.001) but not biventricular pacing (R = 0.29; P = 0.26). Cranial or caudal displacement of the simulated ECG belt did not affect LTAT or SDAT. CONCLUSION: ECGi- and ECG belt-derived intra-ventricular and inter-ventricular dyssynchrony metrics were strongly correlated. The ECG belt may offer comparable dyssynchrony assessment to ECGi, with associated practical and cost advantages.
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Elliott et al. (2021) conducted an observational in Patients undergoing cardiac resynchronization therapy (CRT) (n=17). Simulated ECG belt vs. Electrocardiographic imaging (ECGi) was evaluated on Correlation between ECGi left ventricular activation time (LVAT) and ECG belt left thorax activation time (LTAT) during intrinsic rhythm (R = 0.88, p=< 0.001). Simulated ECG belt-derived dyssynchrony metrics strongly correlated with ECGi metrics, including left ventricular activation time (R=0.88, P<0.001), offering comparable assessment.
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