The treatment of atrial fibrillation and other cardiac arrhythmias as a major cause of cardiovascular hospitalization has remained a challenge predominantly for patients with severely remodeled substrate. Individualized ablation strategies are extremely important both for pulmonary vein isolation and subsequent ablations. Current approaches to identifying arrhythmogenic regions rely on electrogram-based features such as activation time and voltage. Novel technologies now enable clinical assessment of the local impedance as tissue property. Previous studies demonstrated its use for ablation monitoring and indicated its potential to differentiate healthy substrate, scar, and pathological tissue. This study investigates the potential of local electrical impedance-based substrate mapping of the atria for human in-vivo data. The presented pipeline for impedance mapping particularly contains options for dealing with undesirable effects originating from cardiac motion, catheter motion, or proximity to other intracardiac devices. Bloodpool impedance was automatically determined as a patient-specific reference. Full-chamber, left atrial impedance maps were drawn up from interpolating the measured impedances to the atrial endocardium. Finally, the origin and magnitude of oscillations of the raw impedance recording were probed into. The most dominant reason for exclusion of impedance samples was the loss of endocardial contact. With median elevations above the bloodpool impedance between 29 and 46 Ω, the impedance within the pulmonary veins significantly exceeded the remaining atrial walls presenting median elevations above the bloodpool impedance between 16 and 20 Ω. Previous ablation lesions were distinguished from their surroundings by a significant drop in local impedance while the corresponding regions did not differ for the control group. The raw impedance was found to oscillate with median amplitudes between 6 and 17 Ω depending on the patient. Oscillations were traced back to an interplay of atrial, ventricular, and respiratory motion. In summary, local impedance measurements demonstrated their capability to distinguish pathological atrial tissue from physiological substrate. Methods to limit the influence of confounding factors that still hinder impedance mapping were presented. Measurements at different frequencies or the combination of multiple electrodes could lead to further improvement. The presented examples indicate that electrogram- and impedance-based substrate mapping have the potential to complement each other toward better patient outcomes in future.

The detailed characterization of complex forms of atrial flutter relies on the correct interpretation of intra-atrial electrograms. For this, the near field components, which represent the local electrical activity, are decisive. However, far field components arising from distant electrical sources in the atria can obscure the diagnosis. We developed a method to separate and characterize atrial near field and atrial far field components from bipolar intra-atrial electrograms. First, a set of bipolar electrograms was created by simulating different propagation scenarios representing common clinical depolarization patterns. Second, near and far fields were detected as active segments using a non-linear energy operator-based approach. Third, the maximum slope and the spectral power were extracted as features for all active segments. Active segments were grouped accounting for both the timing and the location of their occurrence. In a last step, the active segments were classified in near and far fields by comparing their feature values to a threshold. All active segments were detected correctly. On average, near fields showed 15.1x larger maximum slopes and 40.4x larger spectral powers above 100 Hz than far fields. For 135 active segments detected in 72 bipolar electrograms, 5.2% and 6.7% were misclassified using the maximum slope and the spectral power, respectively. All active segments were classified correctly if only one near field segment was assumed to occur per electrogram. The separation of atrial near and atrial far fields was successfully developed and applied to in silico electrograms. These investigations provide a promising basis for a future clinical study to ultimately facilitate the precise clinical diagnosis of atrial flutter.