Spectral characterisation of ventricular intracardiac potentials in human post-ischaemic bipolar electrograms

Abstract

Abnormal ventricular potentials (AVPs) are frequently referred to as high-frequency deflections in intracardiac electrograms (EGMs). However, no scientific study performed a deep spectral characterisation of AVPs and physiological potentials in real bipolar intracardiac recordings across the entire frequency range imposed by their sampling frequency. In this work, the power contributions of post-ischaemic physiological potentials and AVPs, along with some spectral features, were evaluated in the frequency domain and then statistically compared to highlight specific spectral signatures for these signals. To this end, 450 bipolar EGMs from seven patients affected by post-ischaemic ventricular tachycardia were retrospectively annotated by an experienced cardiologist. Given the high variability of the morphologies observed, three different sub-classes of AVPs and two sub-categories of post-ischaemic physiological potentials were considered. All signals were acquired by the CARTO^® 3 system during substrate-guided catheter ablation procedures. Our findings indicated that the main frequency contributions of physiological and pathological post-ischaemic EGMs are found below 320 Hz. Statistical analyses showed that, when biases due to the signal amplitude influence are eliminated, not only physiological potentials show greater contributions below 20 Hz whereas AVPs demonstrate higher spectral contributions above ~ 40 Hz, but several finer differences may be observed between the different AVP types.

Figure 1

Prototypical examples for each EGM type. Two examples are represented on top and bottom rows for each EGM type. Specifically, from left to right, border-zone potentials, scar potentials, LP1 EGMs, LP2 EGMs and EP EGMs are depicted.

Figure 2

Distribution of the frequency values f_H including 95% of the total PSD power for each EGM type. Distributions of frequency limits f_H are reported as medians (squares) and 5th and 95th percentiles.

Figure 3

Median relative power contents in the different sub-bands for each EGM type. Median values of relative power contents obtained in the different spectral ranges are reported for Border (black bars), Scar (darker grey bars), LP1 (middle grey bars), LP2 (lighter grey bars) and EP (white bars) EGMs. A zoom on the upper sub-bands (i.e., from 80 to 320 Hz) is also provided to allow for a better visualization of the relative power contributions at the higher frequencies. The legend graphically details the association between colours and the different EGM types.

Figure 4

Spectral features estimated for all EGM types. Spectral feature results are reported as medians (black squares) and 5th and 95th percentiles. Specifically, in (a) the distributions of mean frequency (MF) values are represented for all EGM types, whereas in (b–d) those referred to the mean spectral power (MP), the maximum or peak frequency (PKF) and the power spectrum ratio (PSR), respectively.

Figure 5

Absolute and normalised PSDs for all EGM types. Representative PSDs for both physiological and pathological signals in terms of medians (black solid line) and 5th and 95th percentiles (grey zones). From top to bottom: PSDs for border, scar, LP1, LP2 and EP EGMs. The left column illustrates standard PSD curves, whilst the right column depicts the same PSD curves after normalisation so that the area under each curve is unitary, thus allowing for a comparative overview of both absolute and relative power contents for all EGM types in different sub-bands.