Abstract:

Cardiac arrhythmias are a widely spread disease in industrialized countries. A common clinical treatment for this disease is radiofrequency ablation (RFA), in which high frequency alternating current creates a lesion on the myocardium. However, the formation of the lesion is not entirely understood. To obtain more information about ablation lesions (ALs) and their electrophysiological properties, we established an in-vitro setup to record electrical activity of rat myocardium. Electrical activity is measured by a circular shaped multielectrode array. This work was focused to gain more information by developing algorithms to process the measured electrical signals to collect different features, which may allow us to characterize an AL. First, pacing artefacts were detected and blanked. Subsequently, data were filtered. Afterwards, activations in atrial signals were detected using a non-linear energy operator (NLEO) and templates of these activations were generated. Finally, we determined different features on each activation in order to evaluate changes of unipolar as well as bipolar electrograms and considered these features before and after ablation. In conclusion, the majority of the signal features delivered significant differences between normal tissue and lesion. Among others, a reduction in peak to peak amplitude and a diminished spectral power in the band 0 to 100 Hz may be useful indicators for AL. These criteria should be verified in future studies with the aim of estimating indirectly the formation of a lesion.

Abstract:

Cardiac arrhythmias are a widely spread disease in industrialized countries. A common clinical treatment for this disease is radio frequency ablation (RFA), in which high frequency alternating current creates a lesion on the myocardium. However, the formation of the lesion is not entirely understood and non-transmural or incomplete lesions lead to high recurrence rates. To obtain more information about ablation lesions (ALs) and their electrophysiological properties, we established an in-vitro setup to record electrical activity of rat myocardium under well-defined conditions. Electrical activity is measured by a circular shaped multielec- trode array.This work was focused to obtain more information by developing an algorithm to process the measured electrical signals to collect different features, which may allow us to characterize an AL. The algorithm was separated in different parts and designed to process unipolar and bipolar data simultaneously. First, pacing artifacts were detected and blanked. Subsequently, the recorded data were processed by a filtering algorithm created to match the power density spectrum of the recorded signal. Afterwards, activations in atrial signals were detected using the nonlinear energy operator (NLEO) or the negative slope (NS) method and templates of these activations were generated. Finally, we determined different features on each activation in order to evaluate changes of unipolar as well as bipolar electrograms and considered these features before and after ablation. For further investigation local activation time (LAT) maps as well as conduction velocity (CV) were determined. In conclusion, some of the signal features delivered significant differences between healthy tissue and lesion. Among others, a reduction in peak to peak amplitude (P2P) and a shift of the bandwidth towards lower frequencies may be useful indicators for AL. Also, a reduction of the maximum of the NS was a significant indicator for an AL. These criteria should be verified in future studies with the aim of estimating indirectly the formation of a lesion. The results of this work could help to improve the success rates currently achieved by RFA.