Atrial Tachycardias After Atrial Fibrillation Ablation Manifest Different Waveform Characteristics: Implications for Characterizing Tachycardias

SuperMap algorithm: an efficient, safe and accurate modality for mapping and eliminating challenging cardiac arrhythmias

Even with the development of advanced catheter-based mapping systems, there remain several challenges in the electrophysiological evaluation and elimination of atrial arrhythmias. For instance, atrial tachycardias with irregular rates cannot be reliably mapped by systems that require stability in order to sequentially gather data points to be organized thereafter. Separately, these arrhythmias often arise following initial ablation for atrial fibrillation, posing logistic challenges. Here, we present the available literature summarizing the use of a non-contact mapping catheter, the AcQMap catheter, in conjunction with SuperMap, an algorithm that compiles a large number of non-contact data points from multiple catheter positions within the atria. These studies demonstrate the efficiency, safety and accuracy of this technology.

Novel noncontact charge density map in the setting of post-atrial fibrillation atrial tachycardias: first experience with the Acutus SuperMap Algorithm

PURPOSE

The purpose of this study was to evaluate the safety and feasibility of the new high-resolution mapping algorithm SuperMap (Acutus Medical, CA, USA) in identifying and guiding ablation in the setting of regular atrial tachycardias following index atrial fibrillation (AF) ablation.

METHODS

Seven consecutive patients who underwent a radiofrequency catheter ablation guided by the novel noncontact charge density (CD) SuperMap for atrial tachycardia were prospectively enrolled in our study.

RESULTS

Arrhythmogenic substrate was identified in all seven patients. Mean number of EGM per map was 5859.7 ± 4348.5 points. Three patients (43%) exhibited focal tachycardia mechanisms in the left atrium, alternating from anteroseptal right superior pulmonary vein (RSPV), posterior in proximity of left inferior pulmonary vein (LIPV), and interarial septum in proximity of fossa ovalis, respectively. Four patients exhibited macroreentrant mechanism. In 3 of these patients, SuperMap detected mitral isthmus-dependent flutters with tachycardia cycle lengths of 240, 270 and 420 ms, respectively. In one patient, the mechanism was a macroreentrant tachycardia with the critical isthmus located between the crista terminalis and atriotomy. The mean ablation time (min) was 18.2 ± 12.5 and the mean procedural duration time was 56.4 ± 12.1 min. No minor or major complications occurred.

CONCLUSION

The novel high-resolution mapping algorithm SuperMap proved to be safe, fast, and feasible in identifying and guiding ablation in the setting of regular atrial tachycardias following index AF ablation.

Increased body mass index, age, and left atrial size are associated with altered intracardiac atrial electrograms in persistent atrial fibrillation patients

BACKGROUND

There are limited studies evaluating whether atrial fibrillation (AF) patients with increased BMI, age, and left atrial (LA) size have altered intracardiac electrogram (EGM) morphology.

METHODS

We analyzed left atrial intracardiac EGMs acquired during invasive electrophysiology study in 54 patients with AF. EGM correlations were assessed among AF risk factors including age, left atrial size, and BMI.

RESULTS

BMI correlated positively with DF (r² = 0.17, p = 0.009) and MP (r² = 0.16, p = 0.01) with dominant frequency (DF) and mean spectral profile (MP) greater among obese individuals. Age was negatively associated with mean amplitude (r² = 0.42, p < 0.001) and width (r² = 0.32, p < 0.001); age was positively correlated with MP (r² = 0.24, p < 0.001). LA size was negatively correlated with mean amplitude (r² = 0.18, p = 0.03) and width (r² = 0.23, p = 0.01); LA size was positively correlated with DF (r² = 0.22, p = 0.01) and MP (r² = 0.23, p = 0.01). Mean amplitude and width were decreased among subjects with a severely enlarged LA; DF and MP were increased in those with severely enlarged LA. The associations with BMI and LA size remained significant in multiple regression models that included age, male gender, time since AF diagnosis, and LVEF.

CONCLUSIONS

EGM morphology of AF patients with increased BMI, older age, and an enlarged LA possessed decreased amplitude and decreased width and increased DF and MP. These findings suggest that atrial remodeling due to increased age, LA size, and BMI is associated with differences in local atrial activation, decreased refractoriness, and more heterogeneous activation. These novel findings point out clinical risk factors for atrial fibrillation that may affect electrogram characteristics.

Patient-Specific Identification of Atrial Flutter Vulnerability-A Computational Approach to Reveal Latent Reentry Pathways

Atypical atrial flutter (AFlut) is a reentrant arrhythmia which patients frequently develop after ablation for atrial fibrillation (AF). Indeed, substrate modifications during AF ablation can increase the likelihood to develop AFlut and it is clinically not feasible to reliably and sensitively test if a patient is vulnerable to AFlut. Here, we present a novel method based on personalized computational models to identify pathways along which AFlut can be sustained in an individual patient. We build a personalized model of atrial excitation propagation considering the anatomy as well as the spatial distribution of anisotropic conduction velocity and repolarization characteristics based on a combination of a priori knowledge on the population level and information derived from measurements performed in the individual patient. The fast marching scheme is employed to compute activation times for stimuli from all parts of the atria. Potential flutter pathways are then identified by tracing loops from wave front collision sites and constricting them using a geometric snake approach under consideration of the heterogeneous wavelength condition. In this way, all pathways along which AFlut can be sustained are identified. Flutter pathways can be instantiated by using an eikonal-diffusion phase extrapolation approach and a dynamic multifront fast marching simulation. In these dynamic simulations, the initial pattern eventually turns into the one driven by the dominant pathway, which is the only pathway that can be observed clinically. We assessed the sensitivity of the flutter pathway maps with respect to conduction velocity and its anisotropy. Moreover, we demonstrate the application of tailored models considering disease-specific repolarization properties (healthy, AF-remodeled, potassium channel mutations) as well as applicabiltiy on a clinical dataset. Finally, we tested how AFlut vulnerability of these substrates is modulated by exemplary antiarrhythmic drugs (amiodarone, dronedarone). Our novel method allows to assess the vulnerability of an individual patient to develop AFlut based on the personal anatomical, electrophysiological, and pharmacological characteristics. In contrast to clinical electrophysiological studies, our computational approach provides the means to identify all possible AFlut pathways and not just the currently dominant one. This allows to consider all relevant AFlut pathways when tailoring clinical ablation therapy in order to reduce the development and recurrence of AFlut.