Cardiac mapping techniques, in which an electrode-array is placed directly on the surface of the heart, were developed to gain a better insight in the underlying electropathology of cardiac arrhythmias. This procedure is performed in patients undergoing cardiac surgery, but here not all relevant cardiac structures and conduction inquiries can be tested due to possible complications. Hence, to fulfill this gap, an ex vivo Langendorff perfused heart model was designed in this study. Porcine hearts were collected at an abattoir and resuscitated on this setup, after which cardiac mapping was performed. The presented method is the first to perform epicardial mapping on an isolated beating porcine slaughterhouse heart and can be used for a large variety of electrophysiology studies.

Introduction: Potentials measured at the epicardial surface contain information regarding the conductive properties of the atrial tissue. The current lack of morphological categorization during atrial fibrillation (AF) provokes the usage of unsupervised learning methods to evaluate time series electrograms across the atrial surface. Analysis of regional potential morphology increases insight in individual tissue characteristics, possibly aiding in future selection of patients with AF benefitting from additional treatment with. Methods: single potentials (SP) are extracted from four defined regions: right atrium (RA), left atrium (LA), pulmonary veins (PV) and Bachmann’s bundle (BB). The methods are divided in two parts. In part one, the clusters are determined. Choice of algorithm, evaluation of distance metrics and evaluation in reduced dimensionality are performed sequentially to determine the eventual clustering setup. The clustering setup is repeated for different types of input data, originating from different regional structures (all four regions, solely LA and solely the RA) to avoid deterioration of cluster formation from single region(s). In the second part, the clusters are adapted to evaluate morphological characteristics in the included regions. Results: Data from a total of 23 patients was used, containing 128 files and 468588 SPs. K-means using the first 8 principal components was deemed the most suitable clustering method with the current data, identifying a total of five clusters. The clusters showed evident different morphology, mostly distinguishable by RS-ratio and potential duration. RA showed a predominant S to an RS-wave pattern, comparable to PV. Both showed similar contribution of fast and slow S-wave morphology. LA showed a RS to R-wave morphology. The cluster showing a slow S-wave morphology was substantially increased across BB compared to other regions but also when compared to other clusters in BB. Conclusion: Looking at spatial cluster occurrence through an RS-ratio perspective, the beforehand expected deviation from AF compared to sinus rhythm (SR) was not observed. The observed pattern during AF suggests more elaborate contribution of atrial tissue than often targeted in current daily practice. The methodology and defined groups of potentials facilitate evaluation of potential morphology at an individual level. Translation to an endocardial perspective could assist in selecting patients eligible for additional treatment when technologically feasible. Future research should be focused on including potentials containing multiple deflections and estimation of progression state of the atrial tissue.

Introduction: Currently, there is no method available for intra-operative evaluation of the completeness (transmurality and continuity) of surgical ablation lesions. This study aimed to investigate the changes in electrogram characteristics and activation patterns caused by different (non)transmural and (dis)continuous ablation lesions in ex vivo perfused porcine hearts. Methods: Donation after circulatory death porcine hearts ex vivo perfused in Langendorff mode were used to perform ablation experiments in a controlled setting. Three subsequent radiofrequency ablation lesions – with different degrees of transmurality and continuity - were created on the right ventricle using AtriCure’s Isolator Synergy Bipolar clamp. Electrograms of the lesion and surrounding tissue were recorded by unipolar high-resolution mapping. These measurements were executed during pacing perpendicular to the ablation lesion from two sides and during intrinsic cardiac rhythm. Electrograms were processed using custom-made software. The inter-electrode conduction time, potential voltage, potential slope, and R-to-S-amplitude ratio were analyzed. Results: The first radiofrequency application significantly affected all parameters in the lesion area. Conduction times increased, the potential voltage and slope decreased, and there was a loss of S-wave amplitude. The increase in conduction time and the decrease in voltage were less steep when there was a conduction gap in the ablation line. However, conduction time was less sensitive to lesion transmurality because it remained stable even when the lesion became more transmural. The potential voltage on the other hand, became significantly lower in transmural lesions, showing an overall decrease of 84% from baseline to the third (complete) lesion. The potential slope showed similar trends as the voltage, although it was less discriminative for (non)transmurality and (dis)continuity. The loss of the S-wave became significantly more pronounced with more radiofrequency delivery. Conclusions: Complete ablation lesions are characterized by a stable conduction time when applying subsequent ablation, a decrease in potential voltage of 84% on the lesion and its border zone, and loss of the contribution of S-wave amplitude. The combination of these parameters in one tool could help to detect incomplete surgical ablation lesions in the individual patient during Maze surgery. This could potentially reduce post-maze gap-related atrial tachyarrhythmias and thus improve long-term success rates.