Aims Accurate determination of intra-atrial conduction velocity (CV) is essential to identify arrhythmogenic areas. The most optimal, commonly used, estimation methodology to measure conduction heterogeneity, including finite differences (FiD), polynomial surface fitting (PSF), and a novel technique using discrete velocity vectors (DVV), has not been determined. We aim (i) to identify the most suitable methodology to unravel local areas of conduction heterogeneities using high-density CV estimation techniques, (ii) to quantify intra-atrial differences in CV, and (iii) to localize areas of CV slowing associated with paroxysmal atrial fibrillation (PAF). Methods and results Intra-operative epicardial mapping (>5000 sites, interelectrode distances 2 mm) of the right and left atrium and Bachmann’s bundle (BB) was performed during sinus rhythm (SR) in 412 patients with or without PAF. The median atrial CV estimated using the DVV, PSF, and FiD techniques was 90.0 (62.4–116.8), 92.0 (70.6–123.2), and 89.4 (62.5–126.5) cm/s, respectively. The largest difference in CV estimates was found between PSF and DVV which was caused by smaller CV magnitudes detected only by the DVV technique. Using DVV, a lower CV at BB was found in PAF patients compared with those without atrial fibrillation (AF) [79.1 (72.2–91.2) vs. 88.3 (79.3–97.2) cm/s; P < 0.001]. Conclusions Areas of local conduction heterogeneities were most accurately identified using the DVV technique, whereas PSF and FiD techniques smoothen wavefront propagation thereby masking local areas of conduction slowing. Comparing patients with and without AF, slower wavefront propagation during SR was found at BB in PAF patients, indicating structural remodelling.

Aims The morphology of unipolar single potentials (SPs) contains information on intra-atrial conduction disorders and possibly the substrate underlying atrial fibrillation (AF). This study examined the impact of AF episodes on features of SP morphology during sinus rhythm (SR) in patients with mitral valve disease. Methods and results Intraoperative epicardial mapping (interelectrode distance 2 mm) of the right and left atrium (RA, LA), Bachmann’s bundle (BB), and pulmonary vein area (PVA) was performed in 67 patients (27 male, 67 ± 11 years) with or without a history of paroxysmal AF (PAF). Unipolar SPs were classified according to their differences in relative R- and S-wave amplitude ratios. A clear predominance of S-waves was observed at BB and the RA in both the no AF and PAF groups (BB 88.8% vs. 85.9%, RA 92.1% vs. 85.1%, respectively). Potential voltages at the RA, BB, and PVA were significantly lower in the PAF group (P < 0.001 for each) and were mainly determined by the size of the S-waves amplitudes. The largest difference in S-wave amplitudes was found at BB; the S-wave amplitude was lower in the PAF group [4.08 (2.45–6.13) mV vs. 2.94 (1.40–4.75) mV; P < 0.001]. In addition, conduction velocity (CV) at BB was lower as well [0.97 (0.70–1.21) m/s vs. 0.89 (0.62–1.16) m/s, P < 0.001]. Conclusion Though excitation of the atria during SR is heterogeneously disrupted, a history of AF is characterized by decreased SP amplitudes at BB due to loss of S-wave amplitudes and decreased CV. This suggests that SP morphology could provide additional information on wavefront propagation.

Background: The current paradigm is that fibrosis promotes electrophysiological disorders and drives atrial fibrillation (AF). In this current study, we investigated the relation between the degree of fibrosis in human atrial tissue samples of controls and patients in various stages of AF and the degree of electrophysiological abnormalities. Methods: The degree of fibrosis was measured in the atrial tissue and serum of patients in various stages of AF and the controls. Hereto, picrosirius and H&E staining were performed to quantify degree of total, endo-perimysial fibrosis, and cardiomyocyte diameter. Western blot quantified fibrosis markers: neural cell adhesion molecule, tissue inhibitor of metalloproteinase, lysyl oxidase, and α-smooth muscle actin. In serum, the ratio carboxyl-terminal telopeptide of collagen/matrix-metalloproteinase1 was determined. High-resolution epicardial mapping evaluated low-voltage areas and conduction abnormalities. Results: No significant differences were observed in the degree of fibrosis between the groups. Finally, no significant correlation—absolute nor spatial—was observed between all electrophysiological parameters and histological fibrosis markers. Conclusions: No differences in the degree of fibrosis were observed in patients from various stages of AF compared to the controls. Moreover, electrophysiological abnormalities did not correlate with any of the fibrosis markers. The findings indicate that fibrosis is not the hallmark of structural remodeling in AF.

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Background - Low-voltage areas (LVA) are commonly considered surrogate markers for an arrhythmogenic substrate underlying tachyarrhythmias. It remains challenging to define a proper threshold to classify LVA and it is unknown whether unipolar, bipolar and the recently introduced omnipolar voltage mapping techniques are complementary or contradictory in classifying LVAs. Therefore, this study examined similarities and dissimilarities in unipolar, bipolar and omnipolar voltage mapping and explored the relation between various types of voltages and conduction velocity (CV). Methods - Intra-operative epicardial mapping (interelectrode distance 2mm, ±1900 sites) was performed during sinus rhythm in 21 patients (48±13 years, 9 male) with atrial volume overload. Cliques of 4 electrodes (2x2 mm) were used to calculate the maximal unipolar (V uni,max ), bipolar (V bi,max ) and omnipolar (V omni,max ) voltages and mean CV. Areas with V bi,max or V omni,max ≤0.5 mV were defined as LVA. Results - V uni,max was not only larger than V bi,max but also larger than V omni,max (7.08 [4.22-10.59] mV vs. 5.27 [2.39-9.56] mV and 5.77 [2.58-10.52] mV respectively, P<0.001). In addition, the largest bipolar clique voltage was on average 1.66 (range: 1.0 - 59.0) times larger to the corresponding perpendicular bipolar voltage pair. LVAs identified by a bipolar or omnipolar threshold corresponded to a broad spectrum of unipolar voltages and, even though CV was generally decreased, still high CVs and large unipolar voltages were found in these LVAs. Conclusions - In patients with atrial volume overload, there were considerable discrepancies in the different types of LVAs. Additionally, identification of LVAs was hampered by considerable directional differences in bipolar voltages. Even using directional independent omnipolar voltage to identify LVAs, high CVs and large unipolar voltages are present within these areas. Therefore, a combination of low unipolar and low omnipolar voltage may be more indicative of 'true' LVAs.