Interpretation Of Electrograms Research Articles

Image-Decomposition-Enhanced Deep Learning for Detection of Rotor Cores in Cardiac Fibrillation.

Rotors, regions of spiral wave reentry in cardiac tissues, are considered as the drivers of atrial fibrillation (AF), the most common arrhythmia. Whereas physics-based approaches have been widely deployed to detect the rotors, in-depth knowledge in cardiac physiology and electrogram interpretation skills are typically needed. The recent leap forward in smart sensing, data acquisition, and Artificial Intelligence (AI) has offered an unprecedented opportunity to transform diagnosis and treatment in cardiac ailment, including AF. This study aims to develop an image-decomposition-enhanced deep learning framework for automatic identification of rotor cores on both simulation and optical mapping data. We adopt the Ensemble Empirical Mode Decomposition algorithm (EEMD) to decompose the original image, and the most representative component is then fed into a You-Only-Look-Once (YOLO) object-detection architecture for rotor detection. Simulation data from a bi-domain simulation model and optical mapping acquired from isolated rabbit hearts are used for training and validation. This integrated EEMD-YOLO model achieves high accuracy on both simulation and optical mapping data (precision: 97.2%, 96.8%, recall: 93.8%, 92.2%, and F1 score: 95.5%, 94.4%, respectively). The proposed EEMD-YOLO yields comparable accuracy in rotor detection with the gold standard in literature.

Abstract 10532: Physician Interpretation and Characterization of Intracardiac Electrograms at the Time of Non-Cardiac Death

Introduction: Electrograms (EGMs) generated by implantable cardiac devices at the time of non-cardiac death may have artifact from non-arrhythmic sources, such as coagulated blood and air bubbles. While few studies have described the nature of terminal EGMs in non-cardiac death, it is clinically and medicolegally important to characterize these EGMs to elucidate events that may otherwise be misinterpreted as device failure. Here we investigated terminal EGM features that may aid clinicians in discerning cardiac from non-cardiac death. Methods: Terminal EGMs were analyzed by independent physician reviewers. Deaths were adjudicated as non-cardiac based on direct clinical data at the time of death using a modified Cardiac Arrhythmia Suppression Trial approach. In total, 16 non-cardiac terminal EGMs were identified and compared to a control cohort of true arrhythmic events. Using a subset of identified EGMs, an 8-question survey was administered to electrophysiologists blinded to cause of death. Several variables were identified as important for the correct classification of EGMs. The statistical performance of each variable for detecting non-cardiac death and true arrhythmias in our sample was evaluated. These results were shared, and the survey was readministered. Results: In our sample, absence of organized atrial activity had a sensitivity (SN) of 78.5%, specificity (SP) of 100%, and positive predictive value (PPV) of 100% for non-cardiac terminal EGMs. Cycle length <130 ms and absence of discernible deflections both had SPs and PPVs of 100% for non-cardiac death but were less sensitive (60% and 20%, respectively). An abrupt change following therapy and response to therapy both had SNs, SPs, and PPVs of 100% for true arrhythmias. Survey response rate was 68.8% and 62.5% for the pre- and post-survey, respectively. Pre-survey scores ranged from 50 – 87.5% correct with a mean of 72.7%. Post-survey scores ranged from 75 – 100% with a mean of 86.3% (p< 0.01). Conclusions: There is variability and inaccuracy among expert physicians' interpretation of EGMs during non-cardiac death. The variables identified in this study will aid in the development of a clinical risk score used to discern non-cardiac death and true device malfunction based on terminal EGMs.

Feasibility of near-infrared spectroscopy as a tool for anatomical mapping of the human epicardium.

Epicardial ablation is necessary for the treatment of ventricular tachycardias refractory to endocardial ablation due to arrhythmic substrates involving the epicardium. The human epicardium is composed of adipose tissue and coronary vasculature embedded on the surface and within the myocardium, which can complicate electroanatomical mapping, electrogram interpretation and ablation delivery. We propose using near-infrared spectroscopy (NIRS) to decipher adipose tissue from myocardial tissue within human hearts ex vivo. Histological measurement of epicardial adipose thickness direct correlated (R = 0.884) with the adipose contrast index. These results demonstrate the potential of NIRS integrated catheters for mapping the spatial distribution of epicardial substrates and could aid in improving guidance during epicardial ablation interventions.

Visualizing Localized Reentry With Ultra-High Density Mapping in Iatrogenic Atrial Tachycardia: Beware Pseudo-Reentry.

The activation pattern of localized reentry (LR) in atrial tachycardia remains incompletely understood. We used the ultra-high density Rhythmia mapping system to study activation patterns in LR. LR was suggested by small rotatory activations (carousels) containing the full spectrum of the color-coded map. Twenty-three left-sided atrial tachycardias were mapped in 15 patients (age: 64±11 years). 16 253±9192 points were displayed per map, collected over 26±14 minutes. A total of 50 carousels were identified (median 2; quartiles 1-3 per map), although this represented LR in only n=7 out of 50 (14%): here, rotation occurred around a small area of scar (<0.03 mV; 12±6 mm diameter). In LR, electrograms along the carousel encompassed the full tachycardia cycle length, and surrounding activation moved away from the carousel in all directions. Ablating fractionated electrograms (117±18 ms; 44±13% of tachycardia cycle length) within the carousel interrupted the tachycardia in every LR case. All remaining carousels were pseudo-reentrant (n=43/50 [86%]) occurring in areas of wavefront collision (n=21; median 0.5; quartiles 0-2 per map) or as artifact because of annotation of noise or interpolation in areas of incomplete mapping (n=22; median 1, quartiles 0-2 per map). Pseudo-reentrant carousels were incorrectly ablated in 5 cases having been misinterpreted as LR. The activation pattern of LR is of small stable rotational activations (carousels), and this drove 30% (7/23) of our postablation atrial tachycardias. However, this appearance is most often pseudo-reentrant and must be differentiated by interpretation of electrograms in the candidate circuit and activation in the wider surrounding region.

Measurement bias in activation-recovery intervals from unipolar electrograms.

The activation-recovery interval (ARI) calculated from unipolar electrograms is regularly used as a convenient surrogate measure of local cardiac action potential durations (APD). This method enables important research bridging between computational studies and in vitro and in vivo human studies. The Wyatt method is well established as a theoretically sound method for calculating ARIs; however, some studies have observed that it is prone to a bias error in measurement when applied to positive T waves. This article demonstrates that recent theoretical and computational studies supporting the use of the Wyatt method are likely to have underestimated the extent of this bias in many practical experimental recording scenarios. This work addresses these situations and explains the measurement bias by adapting existing theoretical expressions of the electrogram to represent practical experimental recording configurations. A new analytic expression for the electrogram's local component is derived, which identifies the source of measurement bias for positive T waves. A computer implementation of the new analytic model confirms our hypothesis that the bias is systematically dependent on the electrode configuration. These results provide an aid to electrogram interpretation in general, and this work's outcomes are used to make recommendations on how to minimize measurement error.

Serial Atrial Tachycardias

Complex serial type of atrial tachycardias could be encountered in the context of atrial fibrillation ablation. Careful conventional mapping and precise interpretation of electrograms are required for the diagnosis and treatment. Subtle changes in electrogram could be a sign of transition of atrial tachycardia. A conduction delay in left atrial appendage should be checked after extensive ablation and/or multiple procedures to avoid its electrical isolation.

A simple and definite proof of complete cavotricuspid isthmus block

Complete bidirectional block of the cavotricuspid isthmus (CTI) after radiofrequency ablation of typical atrial flutter is an established endpoint. Methods to determine completeness of block are subject to debate, 3‐6 since the ultimate electrophysiological proof does not seem to exist. Additionally, because of increasing economic constraints, the number of usable catheters and poles may become limited. The criterion for clockwise (CW) CTI block based on the anterior right atrium (RA) activation sequence during septal CTI pacing has been proposed to overcome the limitations of other criteria. 7 Pastor et al. elegantly and meticulously evaluate the clinical significance of this method, validating it as a powerful predictor of a freedom of recurrence after more than 3 years. Several issues are to be raised. First, in this retrospective series, three types of ablation catheters have been used which may partially affect the conclusion that can be drawn from this study: a solid 4 mm-tip catheter, a solid 8 mm-tip catheter, and an openirrigation 4 mm-tip catheter. It seems that the solid 4 mm-tip catheter was the least effective and accounted for the majority of recurrences. Secondly, the importance of obtaining non-ambiguous evidence of complete bidirectional CTI block is stressed again. Atrial flutter recurrence rate was only 3% in the presence of bidirectional block vs. 22% in the case of unidirectional block and 67% in the absence of block (P , 0.001 vs. bidirectional block). This is not a new observation but interestingly and, in our opinion, of major importance, CW CTI block, as demonstrated by completely descending anterior RA activation sequence during septal CTI pacing, was simultaneously proven by differential pacing in only 64% of these cases. The limited sensitivity of septal differential pacing was attributed to the unclear local CTI electrogram interpretation (due to the low voltage and fragmented potentials) and was observed in 36% of cases, which is similar to our experience. 5 Moreover, CTI anfractuous anatomy 8,9 makes detailed assessment of the ablation line difficult. We still think that accurate activation mapping of the anterior RA activation sequence during septal CTI pacing is of prime importance to clearly identify complete CTI block. The usefulness of a multipolar catheter is stressed out once more in this paper, with its distal poles placed along the antero-inferior RA wall but in the most immediate vicinity of the ablation line. Many cases of localized slow (yet persistent) conduction are then easily ruled out.

Standardization and validation of an automated algorithm to identify fractionation as a guide for atrial fibrillation ablation

Atrial fibrillation catheter ablation is frequently guided by identification of fractionated electrograms, which are thought to be critical for maintenance of the arrhythmia. Objective automated means for identifying fractionation independent of physician interpretation have not been standardized or validated. The purpose of this study was to standardize and validate an automated algorithm to rapidly identify fractionated electrograms for high-density atrial fibrillation fractionation mapping. Left and right atrial fractionation maps were generated by EnSite NavX 6.0 software, using standardized ablation catheters in eight patients with atrial fibrillation. Two blinded electrophysiologists interpreted all electrograms as either fractionated or not fractionated. A stepwise approach was used to optimize automated settings to accurately identify fractionation. High-density fractionation maps were generated with a 20-pole mapping catheter in eight other patients. Two blinded electrophysiologists interpreted all electrograms as near field or far field. The algorithm was refined to optimize settings to exclude far-field signals and retain near-field signals. The sampling segment length was adjusted to optimize recording time to ensure reproducibility. Using 1,514 points, the automated software achieved sensitivity of 0.75 and specificity of 0.80 for identification of fractionated electrograms. Using 725 points collected via multipole catheters with optimal automated settings, 94% of near-field fractionated electrograms were accurately identified. A 6-second sampling length was needed for reproducible fractionation measurements. Standardized settings of EnSite NavX 6.0 software with 6-second data collection per point can rapidly and accurately generate high-density fractionation maps independent of physician electrogram interpretation. This may allow for an automated, standardized approach to atrial fibrillation fractionated ablation.