Background Conduction blocks (CBs) play an important role in the initiation and perpetuation of atrial fibrillation and may be masked because of its direction- or rate dependency. Objective We aim to investigate how the highest amount and most severe CB at the right atrium (RA) can be unmasked by delivering programmed electrical stimulation (PES) from various directions and at different frequencies. Methods High-resolution epicardial mapping was performed at the middle of the RA on 40 patients during sinus rhythm (SR) and PES from the 4 sides of the mapping array at the average SR cycle length minus 50 ms (SR ₅₀) and 3 different S1S2 trains (S1 ₄₀₀, S2 ₃₀₀, S2 ₂₅₀ or S2 ₂₀₀). CB area percentage (CBA%) was defined as the proportion of electrodes with a local conduction time ≥12 ms. CB severity was defined as the 95th percentile of the conduction times over the lines of CB. Results CBA% increased from 0.6 [0-7.0]% during SR to 15.4 [12.3-19.2]% during S2 ₂₀₀ (P <.001). CB severity increased from 18 [14-29] ms during SR to 46 [29-53] ms during S2 ₂₀₀ (P <.001). PES increased CBA% over SR from 58% of patients during SR ₅₀ to 100% during S2 ₂₀₀. The largest increase in CBA% occurred during S2 ₂₅₀ during pacing from perpendicular (+7.3 [0.5-10.8]%) and opposite (+7.4 [3.5-15.5]%) to the direction of SR. Conclusion Perpendicular pacing opposite to the direction of SR using premature stimuli is optimal for unmasking CB. PES may also reduce CB in patients who already exhibit complex activation patterns during SR.

Background: Bachmann's bundle (BB) may potentially play a role in the earlier onset and faster progression of atrial fibrillation in adult patients with congenital heart disease (CHD). It is unknown whether electrophysiological alterations already exist at BB in pediatric patients with CHD and whether they are related to aging. Objective: This study aimed to investigate BB electrophysiology in pediatric patients with CHD and assess the impact of age on BB electrophysiology. Methods: BB mapping was conducted in 55 patients (0.2–17.5 years). Activation patterns, potential voltages, low-voltage areas (LVAs), potential morphology, and conduction disorders of BB were analyzed and correlated with age. Results: Right-to-left activation across BB occurred in 96.4% of patients. Potential voltage was on average 7.2 ± 3.0 mV, and LVAs occurred in 85.4% of patients. Median local conduction velocity was 96.6 (72.9–121.0) cm/s, and conduction block occurred in 56.4% of patients. Most potentials were single and short-double potentials; long-double and fractionated potentials were recorded in 49.1% and 72.7% of patients, respectively. Age was weakly correlated with potential voltages (r = 0.312, P = .020) and moderately with local conduction velocity (r = 0.439, P < .001), but not with potential morphology or conduction block. Conclusion: In pediatric patients with CHD, BB already contains a considerable amount of conduction disorders, LVAs, and potentials with complex morphology. The prevalence of these early electrophysiological alterations is not age related and does not differ among the right, left, and middle parts of BB.

Background: Areas of conduction disorders play an important role in both initiation and perpetuation of AF and can be recognized by specific changes in unipolar potential morphology. For example, EGM fractionation may be caused by asynchronous activation of adjacent cardiomyocytes because of structural barriers such as fibrotic strands. However, it is unknown whether there are sex differences in unipolar potential morphology. Therefore, atrial potential morphologies during sinus rhythm (SR) were compared between male and female patients. Methods: Based on propensity score matching, 62 male and female patients in whom high-resolution mapping of the right atrium (RA), left atrium (LA), and pulmonary vein area (PVA) including Bachmann's bundle (BB) was performed during coronary bypass grafting surgery and/or valvular heart surgery. Unipolar potentials were classified as single potentials (SPs), short double potentials (SDPs), long double potentials (LDP), fractionated potentials (FPs) and fraction duration (FD). The proportion of conduction block lines was also determined. Results: Female patients had a higher proportion of SDPs, LDPs and FPs at the RA, and SDPs at BB. At the PVA, there were less SPs and more SDPs and FPs. In females, FDs were longer at the RA and PVA, and potential voltages of only SPs were lower at the RA (all P < 0.05). Females also had more CB at the RA and at PVA (P < 0.05). Conclusion: In females, the proportion of single unipolar potentials indicative of smooth conduction, was lower compared to males, at the RA and PVA and to a lesser degree at BB. Females also had more CB at RA and PVA. Hence, these results may reflect sex-differences in the degree of electrical remodeling.

Background: Atrial fibrillation (AF) persistence is associated with molecular remodeling that fuels electrical conduction abnormalities in atrial tissue. Previous research revealed DNA damage as a molecular driver of AF. Objectives: This study sought to explore the diagnostic value of DNA damage in atrial tissue and blood samples as an indicator of the prevalence of electrical conduction abnormalities and stage of AF. Methods: High-sensitivity long-run real-time PCR was performed on mitochondrial (ND1) and nuclear (P53) DNA from atrial tissue samples from paroxysmal (PAF), persistent (PeAF), and longstanding persistent (LS-PeAF) AF, and sinus rhythm (SR) patients (n = 83). PicoGreen assay and quantitative polymerase chain reaction were used on circulating free DNA (cfDNA) markers (total cfDNA, β-globin, ND1, and P53) in blood samples of 70 patients with AF or SR. High-resolution epicardial mapping of the atria (n = 48) was conducted to quantify electrical conduction abnormalities. Results: The number of DNA lesions gradually and significantly increased in PAF and PeAF and in patients with <3 years of AF compared with SR. In SR, the quantity of nuclear DNA damage significantly correlated with the proportion of fractionated potentials. Mitochondrial DNA lesions correlated with slower conduction velocity and lower potential amplitudes in AF samples. Also, mitochondrial cfDNA levels decreased in patients with >3 years of AF compared with <3 years of AF (P = 0.004). Conclusions: The quantity of DNA lesions in atrial tissue samples is associated with atrial conduction abnormalities and stage of AF. Serum DNA damage markers discriminate short- from long-term AF. Therefore, the quantity of DNA damage may have diagnostic value in clinical AF management.

Background: Aging induces structural remodeling, altering atrial electrogram morphology. Over time, structural and consequently electrical remodeling creates a substrate for atrial fibrillation. In structural heart disease, age-induced remodeling comes on top of a pre-existing degree of structural remodeling due to pressure or volume overload. Objective: Investigate the severity of age-related electrical remodeling in patients undergoing surgery for structural heart disease by utilizing a high resolution epicardial mapping approach. Methods: Five seconds of sinus rhythm were recorded intraoperatively at the right atrium (RA), Bachmann's bundle (BB), the left atrium, and the pulmonary vein area. Potential voltage, low-voltage area (LVA) and conduction velocity (CV) were assessed in all regions. Results: 104 patients were included (62,5 % male, age: 26–84 years) and categorized in three age groups: young-age (age <60 years, n = 40), middle-age (age 60–71 years, n = 33), or old-age (age ≥72 years, n = 31) group. Compared to the young-age group, the old-age group had 1) lower median potential voltages at RA (4.65 [3.53–5.62]mV versus 5.94 [4.86–6.79]mV, p = 0.001) and 2) lower CV at RA (87.86 [82.53–96.67]cm/s versus 94.81 [90.14–98.59]cm/s, p = 0.016) and BB (83.38 [67.72–94.96]cm/s versus 98.84 [86.58–102.90]cm/s, p = 0.005). Conclusions: Age-related electrophysiological changes in patients with structural heart disease include reduction in atrial potential voltages and slowing of CV. These changes were less pronounced in the middle-age group. This indicates that electrical remodeling is a combination of both the underlying heart disease and the aging process. However, the less pronounced changes in the middle-age group may reflect a more gradual progression of age-related remodeling.

Objective: The severity of atrial fibrillation (AF) can be assessed from intra-operative epicardial measurements (high-resolution electrograms), using metrics such as conduction block (CB) and continuous conduction delay and block (cCDCB). These features capture differences in conduction velocity and wavefront propagation, but ignore complementary properties such as the morphology of the action potentials. In this work, we focus on such complementary properties, and derive features to detect variations in the atrial potential waveforms. Methods: We show that the spatial variation of atrial potential morphology during a single beat may be described by changes in the singular values of the epicardial measurement matrix. The method is non-parametric and requires little preprocessing. A corresponding singular value map points at areas subject to fractionation and block. Further, we developed an experiment where we simultaneously measure electrograms (EGMs) and a multi-lead ECG. Results: The captured data showed that the normalized singular values of the heartbeats during AF are higher than during SR, and that this difference is more pronounced for the (non-invasive) ECG data than for the EGM data, if the electrodes are positioned at favorable locations. Conclusion: Overall, the singular value-based features are a useful indicator to detect and evaluate AF. Significance: The proposed method might be beneficial for identifying electropathological regions in the tissue without estimating the local activation time.

(1) Background: Structural remodeling plays an important role in the pathophysiology of atrial fibrillation (AF). It is likely that structural remodeling occurs transmurally, giving rise to electrical endo-epicardial asynchrony (EEA). Recent studies have suggested that areas of EEA may be suitable targets for ablation therapy of AF. We hypothesized that the degree of EEA is more pronounced in areas of transmural conduction block (T-CB) than single-sided CB (SS-CB). This study examined the degree to which SS-CB and T-CB enhance EEA and which specific unipolar potential morphology parameters are predictive for SS-CB or T-CB. (2) Methods: Simultaneous endo-epicardial mapping in the human right atrium was performed in 86 patients. Potential morphology parameters included unipolar potential voltages, low-voltage areas, potential complexity (long double and fractionated potentials: LDPs and FPs), and the duration of fractionation. (3) Results: EEA was mostly affected by the presence of T-CB areas. Lower potential voltages and more LDPs and FPs were observed in T-CB areas compared to SS-CB areas. (4) Conclusion: Areas of T-CB could be most accurately predicted by combining epicardial unipolar potential morphology parameters, including voltages, fractionation, and fractionation duration (AUC = 0.91). If transmural areas of CB indeed play a pivotal role in the pathophysiology of AF, they could theoretically be used as target sites for ablation.

Normothermic ex-situ heart perfusion (ESHP) enables assessment of hearts donated after circulatory death (DCD) prior to transplantation. However, sensitive parameters of cardiac function of DCD hearts on ESHP are needed. This study proposes a novel approach using electrophysiological (EP) parameters derived from electrical mapping as biomarkers of post-ischemic cardiac performance. Porcine slaughterhouse hearts (PSH) were divided in two groups based on the type of warm ischemia (Group 1: 10 ± 1 min with animal depilation vs. Group 2: ≤5 min without depilation). Electrical mapping of the right (RV) and left ventricle (LV) was performed on ESHP. Potential voltages, slopes and conduction velocities were computed from unipolar electrograms and compared between groups. Voltages were lower in Group 1 compared to Group 2 (RV: 3.6 vs. 15.3 mV, p = 0.057; LV: 10.8 vs. 23.6 mV, p = 0.029). In addition, the percentage of low-voltage potentials was higher and potential slopes were flatter in Group 1. Voltages and slopes strongly correlated with the visual contractile performance of PSH, but showed weaker correlation with lactate profiles. In conclusion, unipolar potential voltages and potential slopes were decreased in hearts with severe warm ischemia. As such, EP parameters could aid transplantation teams in decision-making on transplantability of DCD hearts.

Background: Quantified features of local conduction heterogeneity due to pathological alterations of myocardial tissue could serve as a marker for the degree of electrical remodeling and hence be used to determine the stage of atrial fibrillation (AF). Objectives: In this study, the authors investigated whether local directional heterogeneity (LDH) and anisotropy ratio, derived from estimated local conduction velocities (CVs) during AF, are suitable electrical parameters to stage AF. Methods: Epicardial mapping (244-electrode array, interelectrode distance 2.25 mm) of the right atrium was performed during acute atrial fibrillation (AAF) (n = 25, 32 ± 11 years of age) and during long-standing persistent atrial fibrillation (LSPAF) (n = 23, 64 ± 9 years of age). Episodes of 9 ± 4 seconds of AF were analyzed. Local CV vectors were constructed to assess the degree of anisotropy. Directions and magnitudes of individual vectors were compared with surrounding vectors to identify LDH. Results: Compared with the entire AAF group, LSPAF was characterized by slower conduction (71.5 ± 6.8 cm/s vs 67.6 ± 5.6 cm/s; P = 0.037) with a larger dispersion (1.59 ± 0.21 vs 1.95 ± 0.17; P < 0.001) and temporal variability (32.0 ± 4.7 cm/s vs 38.5 ± 3.3 cm/s; P < 0.001). Also, LSPAF was characterized by more LDH (19.6% ± 4.4% vs 26.0% ± 3.4%; P < 0.001) and a higher degree of anisotropy (1.38 ± 0.07 vs 1.51 ± 0.14; P < 0.001). Compared with the most complex type of AAF (type III), LSPAF was still associated with a larger CV dispersion, higher temporal variability of CV, and larger amount of LDH. Conclusions: Increasing AF complexity was associated with increased spatiotemporal variability of local CV vectors, local conduction heterogeneity, and anisotropy ratio. By using these novel parameters, LSPAF could potentially be discriminated from the most complex type of AAF. These observations may indicate pathological alterations of myocardial tissue underlying progression of AF.

BACKGROUND AND AIMS: Atrial extrasystoles (AES) provoke conduction disorders and may trigger episodes of atrial fibrillation (AF). However, the direction- and rate-dependency of electrophysiological tissue properties on epicardial unipolar electrogram (EGM) morphology is unknown. Therefore, this study examined the impact of spontaneous AES on potential amplitude, -fractionation, -duration, and low-voltage areas (LVAs), and correlated these differences with various degrees of prematurity and aberrancy. METHODS AND RESULTS: Intra-operative high-resolution epicardial mapping of the right and left atrium, Bachmann's Bundle, and pulmonary vein area was performed during sinus rhythm (SR) in 287 patients (60 with AF). AES were categorized according to their prematurity index (>25% shortening) and degree of aberrancy (none, mild/opposite, moderate and severe). In total, 837 unique AES (457 premature; 58 mild/opposite, 355 moderate, and 154 severe aberrant) were included. The average prematurity index was 28% [12-45]. Comparing SR and AES, average voltage decreased (-1.1 [-1.2, -0.9] mV, P < 0.001) at all atrial regions, whereas the amount of LVAs and fractionation increased (respectively, +3.4 [2.7, 4.1] % and +3.2 [2.6, 3.7] %, P < 0.001). Only weak or moderate correlations were found between EGM morphology parameters and prematurity indices (R2 < 0.299, P < 0.001). All parameters were, however, most severely affected by either mild/opposite or severely aberrant AES, in which the effect was more pronounced in AF patients. Also, there were considerable regional differences in effects provoked by AES. CONCLUSION: Unipolar EGM characteristics during spontaneous AES are mainly directional-dependent and not rate-dependent. AF patients have more direction-dependent conduction disorders, indicating enhanced non-uniform anisotropy that is uncovered by spontaneous AES.

Aims: Areas of conduction inhomogeneity (CI) during sinus rhythm may facilitate the initiation and perpetuation of atrial fibrillation (AF). Currently, no tool is available to quantify the severity of CI. Our aim is to develop and validate a novel tool using unipolar electrograms (EGMs) only to quantify the severity of CI in the atria. Methods and results: Epicardial mapping of the right atrium (RA) and left atrium, including Bachmann's bundle, was performed in 235 patients undergoing coronary artery bypass grafting surgery. Conduction inhomogeneity was defined as the amount of conduction block. Electrograms were classified as single, short, long double (LDP), and fractionated potentials (FPs), and the fractionation duration of non-single potentials was measured. The proportion of low-voltage areas (LVAs, <1mV) was calculated. Increased CI was associated with decreased potential voltages and increased LVAs, LDPs, and FPs. The Electrical Fingerprint Score consisting of RA EGM features, including LVAs and LDPs, was most accurate in predicting CI severity. The RA Electrical Fingerprint Score demonstrated the highest correlation with the amount of CI in both atria (r = 0.70, P < 0.001). Conclusion: The Electrical Fingerprint Score is a novel tool to quantify the severity of CI using only unipolar EGM characteristics recorded. This tool can be used to stage the degree of conduction abnormalities without constructing spatial activation patterns, potentially enabling early identification of patients at high risk of post-operative AF or selection of the appropriate ablation approach in addition to pulmonary vein isolation at the electrophysiology laboratory.

Background: An increasing number of wearables are capable of measuring electrocardiograms (ECGs), which may help in early detection of atrial fibrillation (AF). Therefore, many studies focus on automated detection of AF in ECGs. A major obstacle is the required amount of manually labelled data. This study aimed to provide an efficient and reliable method to train a classifier for AF detection using large datasets of real-life ECGs. Method: Human-controlled semi-supervised learning was applied, consisting of two phases: the pre-training phase and the semi-automated training phase. During pre-training, an initial classifier was trained, which was used to predict the classes of new ECG segments in the semi-automated training phase. Based on the degree of certainty, segments were added to the training dataset automatically or after human validation. Thereafter, the classifier was retrained and this procedure was repeated. To test the model performance, a real-life telemetry dataset containing 3,846,564 30-s ECG segments of hospitalized patients (n = 476) and the CinC Challenge 2017 database were used. Results: After pre-training, the average F1-score on a hidden testing dataset was 89.0%. Furthermore, after the pre-training phase 68.0% of all segments in the hidden test set could be classified with an estimated probability of successful classification of 99%, providing an F1-score of 97.9% for these segments. During the semi-automated training phase, this F1-score showed little variation (97.3%–97.9% in the hidden test set), whilst the number of segments which could be automatically classified increased from 68.0% to 75.8% due to the enhanced training dataset. At the same time, the overall F1-score increased from 89.0% to 91.4%. Conclusions: Human-validated semi-supervised learning makes training a classifier more time efficient without compromising on accuracy, hence this method might be valuable in the automated detection of AF in real-life ECGs.

Aims: Automated detection of atrial fibrillation (AF) in continuous rhythm registrations is essential in order to prevent complications and optimize treatment of AF. Many algorithms have been developed to detect AF in surface electrocardiograms (ECGs) during the past few years. The aim of this systematic review is to gain more insight into these available classification methods by discussing previously used digital biomarkers and algorithms and make recommendations for future research. Methods: On the 14^th of September 2020, the PubMed database was searched for articles focusing on algorithms for AF detection in ECGs using the MeSH terms Atrial Fibrillation, Electrocardiography and Algorithms. Articles which solely focused on differentiation of types of rhythm disorders or prediction of AF termination were excluded. Results: The search resulted in 451 articles, of which 130 remained after full-text screening. Not only did the amount of research on methods for AF detection increase over the past years, but a trend towards more complex classification methods is observed. Furthermore, three different types of features can be distinguished: atrial features, ventricular features, and signal features. Although AF is an atrial disease, only 22% of the described methods use atrial features. Conclusion: More and more studies focus on improving accuracy of classification methods for AF in ECGs. As a result, algorithms become increasingly complex and less well interpretable. Only a few studies focus on detecting atrial activity in the ECG. Developing innovative methods focusing on detection of atrial activity might provide accurate classifiers without compromising on transparency.