Key result
Multichannel ECG signal processing using morphological, frequency, and spectrogram features correctly classified premature ventricular contraction foci into five groups in 88.4% of patients.
Observational (n=87)
No
Multichannel ECG signal processing using morphological, frequency, and spectrogram features can accurately localize PVC foci in 88.4% of patients without structural heart disease, potentially aiding pre-procedural planning for ablation.
May aid PVC ablation planning; hypothesis-generating and requires prospective validation.
A premature ventricular contraction (PVC) is relatively a common event where the heartbeat is initiated by the other pathway rather than by the Sinoatrial node, the normal heartbeat initiator. Determining PVC foci is important for ablation procedure and it can help in pre-procedural planning and potentially may improve ablation outcome. In this study, 12-lead Electrocardiogram (ECG) of 87 patients without structural cardiac diseases, who had experienced PVC, were obtained. Initially, PVC foci were labeled based on Electrophysiology study (EPS) reports. PVC beats were detected by wavelet method and their foci were classified using Mahalanobis distance and One-way ANOVA. Using morphological, frequency and spectrogram features, these foci in the heart were classified into five groups: Left Ventricular Outflow Tract (LVOT), Right Ventricular Outflow Tract (RVOT) septum, basal Right Ventricular (RV), RVOT free-wall, and Aortic Cusp (AC). The results showed that 88.4% of patients are classified correctly.
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Soheilykhah et al. (2013) conducted an observational in Premature ventricular contraction (n=87). Multichannel ECG signal processing vs. Electrophysiology study (EPS) reports was evaluated on Correct classification of PVC foci. Multichannel ECG signal processing using morphological, frequency, and spectrogram features correctly classified premature ventricular contraction foci into five groups in 88.4% of patients.
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