The electrical arrhythmogenic substrate underlying the most common cardiac arrhythmia atrial fibrillation (AF) may consist of conduction disorders, low-voltage areas, or fractionated potentials. High-density and resolution epicardial mapping (HDREM) approaches have been introduced to quantify and visualize electrophysiological properties of the atria. These approaches are essential for obtaining innovative insights into arrhythmogenic substrates and identifying novel targets for therapy. The aim of this review is to summarize and discuss the (1) contribution of HDREM studies to the knowledge on atrial arrhythmogenesis and (2) future applications of HDREM of atria in daily clinical practice.

Background: Ablation strategies targeting fractionated or low-voltage potentials have been widely used in patients with persistent types of atrial fibrillation (AF). However, recent studies have questioned their role in effectively representing sites of conduction slowing, and thus arrhythmogenic substrates. Objectives: The authors studied the relationship between local conduction velocity (CV) and the occurrence of fractionated and/or low-voltage potentials in order to identify areas with critically slowing of conduction. Methods: Intraoperative epicardial mapping was performed during sinus rhythm. Unipolar potentials with an amplitude <1.0 mV were initially classified as low-voltage and potentials with ≥3 deflections as fractionation. A range of thresholds were also explored. Local CV was computed using discrete velocity vectors. Results: A total of 319 patients were included. Fractionated, low-voltage potentials were rare, accounting for only 0.36% (Q1-Q3: 0.15%-0.78%) of all atrial sites. Local CV at sites with fractionated, low-voltage potentials (46.0 cm/s [Q1-Q3: 22.6-72.7 cm/s]) was lowest compared with sites with either low-voltage, nonfractionated potentials (64.5 cm/s [Q1-Q3: 34.8-99.4 cm/s]) or fractionated, high-voltage potentials (65.9 cm/s [Q1-Q3: 41.7-92.8 cm/s]; P < 0.001). Slow conduction areas (CV <50 cm/s) could be most accurately identified by using a low voltage threshold (<1 mV) and a minimum of 3 deflections (positive predictive value: 54.2%-70.7%), although the overall sensitivity remained low (0.1%-1.9%). Conclusions: Sites with fractionated, low-voltage potentials have substantially slower local CV compared with sites with either low-voltage, nonfractionated potentials or fractionated, high-voltage potentials. However, the strong inverse relationship between the positive predictive value and sensitivity of a combined voltage and fractionation threshold for slowed conduction is likely to complicate the use of these signal-based ablation approaches in AF patients.

Objective: Patients with persistent atrial fibrillation (AF) have more electrical endo-epicardial asynchrony (EEA) during sinus rhythm (SR) than patients without AF. Prior mapping studies indicated that particularly unipolar, endo- and/or epicardial electrogram (EGM) morphology may be indicators of EEA. This study aim to develop a novel method for estimating the degree of EEA by using unipolar EGM characteristics recorded from either the endo- and/or epicardium. Methods: Simultaneous endo-epicardial mapping during sinus rhythm was performed in 86 patients. EGM characteristics, including unipolar voltages, low-voltage areas (LVAs), potential types (single, short/long double and fractionated potentials: SP, SDP, LDP and FP) and fractionation duration (FD) of double potentials (DP) and FP were compared between EEA and non-EEA areas. Asynchrony Fingerprinting Scores (AFS) containing quantified EGM characteristics were constructed to estimate the degree of EEA. Results: Endo- and epicardial sites of EEA areas are characterized by lower unipolar voltages, a higher number of LDPs and FPs and longer DP and FP durations. Patients with AF have lower potential voltages in EEA areas, along with alterations in the potential types. The EE-AFS, containing the proportion of endocardial LVAs and FD of epicardial DPs, had the highest predictive value for determining the degree of EEA (AUC: 0.913). Endo- and epi-AFS separately also showed good predictive values (AUC: 0.901 and 0.830 respectively). Conclusions: EGM characteristics can be used to identify EEA areas. AFS can be utilized as a novel diagnostic tool for accurately estimating the degree of EEA. These characteristics potentially indicate AF related arrhythmogenic substrates.