Contact

All Publications

  • Machine Learning-Enabled Multimodal Fusion of Intra-Atrial and Body Surface Signals in Prediction of Atrial Fibrillation Ablation Outcomes. Circulation. Arrhythmia and electrophysiology Tang, S., Razeghi, O., Kapoor, R., Alhusseini, M. I., Fazal, M., Rogers, A. J., Rodrigo Bort, M., Clopton, P., Wang, P., Rubin, D., Narayan, S. M., Baykaner, T. 2022: 101161CIRCEP122010850

    Abstract

    BACKGROUND: Machine learning is a promising approach to personalize atrial fibrillation management strategies for patients after catheter ablation. Prior atrial fibrillation ablation outcome prediction studies applied classical machine learning methods to hand-crafted clinical scores, and none have leveraged intracardiac electrograms or 12-lead surface electrocardiograms for outcome prediction. We hypothesized that (1) machine learning models trained on electrograms or ECG signals can perform better at predicting patient outcomes after atrial fibrillation ablation than existing clinical scores and (2) multimodal fusion of electrogram, ECG, and clinical features can further improve the prediction of patient outcomes.METHODS: Consecutive patients who underwent catheter ablation between 2015 and 2017 with panoramic left atrial electrogram before ablation and clinical follow-up for at least 1 year following ablation were included. Convolutional neural network and a novel multimodal fusion framework were developed for predicting 1-year atrial fibrillation recurrence after catheter ablation from electrogram, ECG signals, and clinical features. The models were trained and validated using 10-fold cross-validation on patient-level splits.RESULTS: One hundred fifty-six patients (64.5±10.5 years, 74% male, 42% paroxysmal) were analyzed. Using electrogram signals alone, the convolutional neural network achieved an area under the receiver operating characteristics curve of 0.731, outperforming the existing APPLE scores (area under the receiver operating characteristics curve=0.644) and CHA2DS2-VASc scores (area under the receiver operating characteristics curve=0.650). Similarly using 12-lead ECG alone, the convolutional neural network achieved an AUROC of 0.767. Combining electrogram, ECG, and clinical features, the fusion model achieved an AUROC of 0.859, outperforming single and dual modality models.CONCLUSIONS: Deep neural networks trained on electrogram or ECG signals improved the prediction of catheter ablation outcome compared with existing clinical scores, and fusion of electrogram, ECG, and clinical features further improved the prediction. This suggests the promise of using machine learning to help treatment planning for patients after catheter ablation.

    View details for DOI 10.1161/CIRCEP.122.010850

    View details for PubMedID 35867397

  • Atrial fibrillation signatures on intracardiac electrograms identified by deep learning. Computers in biology and medicine Rodrigo, M., Alhusseini, M. I., Rogers, A. J., Krittanawong, C., Thakur, S., Feng, R., Ganesan, P., Narayan, S. M. 2022; 145: 105451

    Abstract

    BACKGROUND: Automatic detection of atrial fibrillation (AF) by cardiac devices is increasingly common yet suboptimally groups AF, flutter or tachycardia (AT) together as 'high rate events'. This may delay or misdirect therapy.OBJECTIVE: We hypothesized that deep learning (DL) can accurately classify AF from AT by revealing electrogram (EGM) signatures.METHODS: We studied 86 patients in whom the diagnosis of AF or AT was established at electrophysiological study (25 female, 65±11 years). Custom DL architectures were trained to identify AF using N=29,340 unipolar and N=23,760 bipolar EGM segments. We compared DL to traditional classifiers based on rate or regularity. We explained DL using computer models to assess the impact of controlled variations in shape, rate and timing on AF/AT classification in 246,067 EGMs reconstructed from clinical data.RESULTS: DL identified AF with AUC of 0.97±0.04 (unipolar) and 0.92±0.09 (bipolar). Rule-based classifiers misclassified 10-12% of cases. DL classification was explained by regularity in EGM shape (13%) or timing (26%), and rate (60%; p<0.001), and also by a set of unipolar EGM shapes that classified as AF independent of rate or regularity. Overall, the optimal AF 'fingerprint' comprised these specific EGM shapes, >15% timing variation, <0.48 correlation in beat-to-beat EGM shapes and CL<190ms (p<0.001).CONCLUSIONS: Deep learning of intracardiac EGMs can identify AF or AT via signatures of rate, regularity in timing or shape, and specific EGM shapes. Future work should examine if these signatures differ between different clinical subpopulations with AF.

    View details for DOI 10.1016/j.compbiomed.2022.105451

    View details for PubMedID 35429831

  • VALIDATING NON-INVASIVE INDICES OF AF COMPLEXITY AGAINST INTRACARDIAC MEASUREMENTS Rodrigo, M., Alhusseini, M., Rogers, A., Narayan, S. ELSEVIER SCIENCE INC. 2021: 1354

    View details for Web of Science ID 000647487501362

  • CLASSIFICATION OF INDIVIDUAL ATRIAL INTRACARDIAC ELECTROGRAMS BY DEEP LEARNING Rodrigo, M., Rogers, A., Ganesan, P., Krittanawong, C., Alhusseini, M., Narayan, S. ELSEVIER SCIENCE INC. 2021: 3217

    View details for Web of Science ID 000647487503241

  • PROBING MACHINE LEARNING TO SEPARATE ATRIAL FIBRILLATION FROM OTHER ARRHYTHMIAS Rodrigo, M., Rogers, A., Ganesan, P., Alhusseini, M., Krittanawong, C., Narayan, S. ELSEVIER SCIENCE INC. 2021: 3410

    View details for Web of Science ID 000647487503431

  • MACHINE LEARNING CLASSIFIES INTRACARDIAC ELECTROGRAMS OF ATRIAL FIBRILLATION FROM OTHER ARRHYTHMIAS Rodrigo, M., Rogers, A., Ganesan, P., Krittanawong, C., Alhusseini, M., Narayan, S. ELSEVIER SCIENCE INC. 2021: 279

    View details for Web of Science ID 000647487500279

  • Non-invasive Spatial Mapping of Frequencies in Atrial Fibrillation: Correlation With Contact Mapping FRONTIERS IN PHYSIOLOGY Rodrigo, M., Waddell, K., Magee, S., Rogers, A. J., Alhusseini, M., Hernandez-Romero, I., Costoya-Sanchez, A., Liberos, A., Narayan, S. M. 2021; 11

    View details for DOI 10.3389/fphys.2020.611266

    View details for Web of Science ID 000608806200001

  • Three dimensional reconstruction to visualize atrial fibrillation activation patterns on curved atrial geometry. PloS one Abad, R., Collart, O., Ganesan, P., Rogers, A. J., Alhusseini, M. I., Rodrigo, M., Narayan, S. M., Rappel, W. 2021; 16 (4): e0249873

    Abstract

    BACKGROUND: The rotational activation created by spiral waves may be a mechanism for atrial fibrillation (AF), yet it is unclear how activation patterns obtained from endocardial baskets are influenced by the 3D geometric curvature of the atrium or 'unfolding' into 2D maps. We develop algorithms that can visualize spiral waves and their tip locations on curved atrial geometries. We use these algorithms to quantify differences in AF maps and spiral tip locations between 3D basket reconstructions, projection onto 3D anatomical shells and unfolded 2D surfaces.METHODS: We tested our algorithms in N = 20 patients in whom AF was recorded from 64-pole baskets (Abbott, CA). Phase maps were generated by non-proprietary software to identify the tips of spiral waves, indicated by phase singularities. The number and density of spiral tips were compared in patient-specific 3D shells constructed from the basket, as well as 3D maps from clinical electroanatomic mapping systems and 2D maps.RESULTS: Patients (59.4±12.7 yrs, 60% M) showed 1.7±0.8 phase singularities/patient, in whom ablation terminated AF in 11/20 patients (55%). There was no difference in the location of phase singularities, between 3D curved surfaces and 2D unfolded surfaces, with a median correlation coefficient between phase singularity density maps of 0.985 (0.978-0.990). No significant impact was noted by phase singularities location in more curved regions or relative to the basket location (p>0.1).CONCLUSIONS: AF maps and phase singularities mapped by endocardial baskets are qualitatively and quantitatively similar whether calculated by 3D phase maps on patient-specific curved atrial geometries or in 2D. Phase maps on patient-specific geometries may be easier to interpret relative to critical structures for ablation planning.

    View details for DOI 10.1371/journal.pone.0249873

    View details for PubMedID 33836026

  • Deep Neural Network Trained on Surface ECG Improves Diagnostic Accuracy of Prior Myocardial Infarction Over Q Wave Analysis Yildirim, O., Baloglu, U. B., Talo, M., Ganesan, P., Tung, J. S., Kang, G., Tooley, J., Alhusseini, M., Baykaner, T., Wang, P. J., Perez, M., Tereshchenko, L., Narayan, S. M., Rogers, A. J., IEEE IEEE. 2021

    View details for DOI 10.22489/CinC.2021.010

    View details for Web of Science ID 000821955000130

  • Machine Learned Cellular Phenotypes Predict Outcome in Ischemic Cardiomyopathy. Circulation research Rogers, A. J., Selvalingam, A., Alhusseini, M. I., Krummen, D. E., Corrado, C., Abuzaid, F., Baykaner, T., Meyer, C., Clopton, P., Giles, W. R., Bailis, P., Niederer, S. A., Wang, P. J., Rappel, W., Zaharia, M., Narayan, S. M. 2020

    Abstract

    RATIONALE: Susceptibility to ventricular arrhythmias (VT/VF) is difficult to predict in patients with ischemic cardiomyopathy either by clinical tools or by attempting to translate cellular mechanisms to the bedside.OBJECTIVE: To develop computational phenotypes of patients with ischemic cardiomyopathy, by training then interpreting machine learning (ML) of ventricular monophasic action potentials (MAPs) to reveal phenotypes that predict long-term outcomes.METHODS AND RESULTS: We recorded 5706 ventricular MAPs in 42 patients with coronary disease (CAD) and left ventricular ejection fraction (LVEF) {less than or equal to}40% during steady-state pacing. Patients were randomly allocated to independent training and testing cohorts in a 70:30 ratio, repeated K=10 fold. Support vector machines (SVM) and convolutional neural networks (CNN) were trained to 2 endpoints: (i) sustained VT/VF or (ii) mortality at 3 years. SVM provided superior classification. For patient-level predictions, we computed personalized MAP scores as the proportion of MAP beats predicting each endpoint. Patient-level predictions in independent test cohorts yielded c-statistics of 0.90 for sustained VT/VF (95% CI: 0.76-1.00) and 0.91 for mortality (95% CI: 0.83-1.00) and were the most significant multivariate predictors. Interpreting trained SVM revealed MAP morphologies that, using in silico modeling, revealed higher L-type calcium current or sodium calcium exchanger as predominant phenotypes for VT/VF.CONCLUSIONS: Machine learning of action potential recordings in patients revealed novel phenotypes for long-term outcomes in ischemic cardiomyopathy. Such computational phenotypes provide an approach which may reveal cellular mechanisms for clinical outcomes and could be applied to other conditions.

    View details for DOI 10.1161/CIRCRESAHA.120.317345

    View details for PubMedID 33167779

  • Machine Learning to Classify Intracardiac Electrical Patterns during Atrial Fibrillation. Circulation. Arrhythmia and electrophysiology Alhusseini, M. I., Abuzaid, F., Rogers, A. J., Zaman, J. A., Baykaner, T., Clopton, P., Bailis, P., Zaharia, M., Wang, P. J., Rappel, W., Narayan, S. M. 2020

    Abstract

    Background - Advances in ablation for atrial fibrillation (AF) continue to be hindered by ambiguities in mapping, even between experts. We hypothesized that convolutional neural networks (CNN) may enable objective analysis of intracardiac activation in AF, which could be applied clinically if CNN classifications could also be explained. Methods - We performed panoramic recording of bi-atrial electrical signals in AF. We used the Hilbert-transform to produce 175,000 image grids in 35 patients, labeled for rotational activation by experts who showed consistency but with variability (kappa=0.79). In each patient, ablation terminated AF. A CNN was developed and trained on 100,000 AF image grids, validated on 25,000 grids, then tested on a separate 50,000 grids. Results - In the separate test cohort (50,000 grids), CNN reproducibly classified AF image grids into those with/without rotational sites with 95.0% accuracy (CI 94.8-95.2%). This accuracy exceeded that of support vector machines, traditional linear discriminant and k-nearest neighbor statistical analyses. To probe the CNN, we applied Gradient-weighted Class Activation Mapping which revealed that the decision logic closely mimicked rules used by experts (C-statistic 0.96). Conclusions - Convolutional neural networks improved the classification of intracardiac AF maps compared to other analyses, and agreed with expert evaluation. Novel explainability analyses revealed that the CNN operated using a decision logic similar to rules used by experts, even though these rules were not provided in training. We thus describe a scaleable platform for robust comparisons of complex AF data from multiple systems, which may provide immediate clinical utility to guide ablation.

    View details for DOI 10.1161/CIRCEP.119.008160

    View details for PubMedID 32631100

  • PREDICTING SUDDEN CARDIAC DEATH BY MACHINE LEARNING OF VENTRICULAR ACTION POTENTIALS Selvalingam, A., Alhusseini, M., Rogers, A. J., Krummen, D., Abuzaid, F. M., Baykaner, T., Clopton, P., Bailis, P., Zaharia, M., Wang, P., Narayan, S. ELSEVIER SCIENCE INC. 2020: 427

    View details for Web of Science ID 000522979100416

  • LARGER ORGANIZED AREAS IN PERSISTENT ATRIAL FIBRILLATION PREDICTS TERMINATION DURING ABLATION Ravi, N., Rogers, A. J., Bhatia, N., Tung, J. S., Krummen, D., Sauer, W., Alhusseini, M., Baykaner, T., Wang, P., Rappel, W., Narayan, S. ELSEVIER SCIENCE INC. 2020: 279

    View details for Web of Science ID 000522979100273

  • Non-invasive Spatial Mapping of Frequencies in Atrial Fibrillation: Correlation With Contact Mapping. Frontiers in physiology Rodrigo, M., Waddell, K., Magee, S., Rogers, A. J., Alhusseini, M., Hernandez-Romero, I., Costoya-Sánchez, A., Liberos, A., Narayan, S. M. 2020; 11: 611266

    Abstract

    Introduction: Regional differences in activation rates may contribute to the electrical substrates that maintain atrial fibrillation (AF), and estimating them non-invasively may help guide ablation or select anti-arrhythmic medications. We tested whether non-invasive assessment of regional AF rate accurately represents intracardiac recordings. Methods: In 47 patients with AF (27 persistent, age 63 ± 13 years) we performed 57-lead non-invasive Electrocardiographic Imaging (ECGI) in AF, simultaneously with 64-pole intracardiac signals of both atria. ECGI was reconstructed by Tikhonov regularization. We constructed personalized 3D AF rate distribution maps by Dominant Frequency (DF) analysis from intracardiac and non-invasive recordings. Results: Raw intracardiac and non-invasive DF differed substantially, by 0.54 Hz [0.13 - 1.37] across bi-atrial regions (R2 = 0.11). Filtering by high spectral organization reduced this difference to 0.10 Hz (cycle length difference of 1 - 11 ms) [0.03 - 0.42] for patient-level comparisons (R2 = 0.62), and 0.19 Hz [0.03 - 0.59] and 0.20 Hz [0.04 - 0.61] for median and highest DF, respectively. Non-invasive and highest DF predicted acute ablation success (p = 0.04). Conclusion: Non-invasive estimation of atrial activation rates is feasible and, when filtered by high spectral organization, provide a moderate estimate of intracardiac recording rates in AF. Non-invasive technology could be an effective tool to identify patients who may respond to AF ablation for personalized therapy.

    View details for DOI 10.3389/fphys.2020.611266

    View details for PubMedID 33584334

    View details for PubMedCentralID PMC7873897

  • Termination of persistent atrial fibrillation by ablating sites that control large atrial areas. Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology Bhatia, N. K., Rogers, A. J., Krummen, D. E., Hossainy, S. n., Sauer, W. n., Miller, J. M., Alhusseini, M. I., Peszek, A. n., Armenia, E. n., Baykaner, T. n., Brachmann, J. n., Turakhia, M. P., Clopton, P. n., Wang, P. J., Rappel, W. J., Narayan, S. M. 2020

    Abstract

    Persistent atrial fibrillation (AF) has been explained by multiple mechanisms which, while they conflict, all agree that more disorganized AF is more difficult to treat than organized AF. We hypothesized that persistent AF consists of interacting organized areas which may enlarge, shrink or coalesce, and that patients whose AF areas enlarge by ablation are more likely to respond to therapy.We mapped vectorial propagation in persistent AF using wavefront fields (WFF), constructed from raw unipolar electrograms at 64-pole basket catheters, during ablation until termination (Group 1, N = 20 patients) or cardioversion (Group 2, N = 20 patients). Wavefront field mapping of patients (age 61.1 ± 13.2 years, left atrium 47.1 ± 6.9 mm) at baseline showed 4.6 ± 1.0 organized areas, each separated by disorganization. Ablation of sites that led to termination controlled larger organized area than competing sites (44.1 ± 11.1% vs. 22.4 ± 7.0%, P < 0.001). In Group 1, ablation progressively enlarged unablated areas (rising from 32.2 ± 15.7% to 44.1 ± 11.1% of mapped atrium, P < 0.0001). In Group 2, organized areas did not enlarge but contracted during ablation (23.6 ± 6.3% to 15.2 ± 5.6%, P < 0.0001).Mapping wavefront vectors in persistent AF revealed competing organized areas. Ablation that progressively enlarged remaining areas was acutely successful, and sites where ablation terminated AF were surrounded by large organized areas. Patients in whom large organized areas did not emerge during ablation did not exhibit AF termination. Further studies should define how fibrillatory activity is organized within such areas and whether this approach can guide ablation.

    View details for DOI 10.1093/europace/euaa018

    View details for PubMedID 32243508

  • Non-Invasive Assessment of Complexity of Atrial Fibrillation: Correlation with Contact Mapping and Impact of Ablation. Circulation. Arrhythmia and electrophysiology Rodrigo, M. n., Climent, A. M., Hernández-Romero, I. n., Liberos, A. n., Baykaner, T. n., Rogers, A. J., Alhusseini, M. n., Wang, P. J., Fernández-Avilés, F. n., Guillem, M. S., Narayan, S. M., Atienza, F. n. 2020

    Abstract

    Background - It is difficult to non-invasively phenotype atrial fibrillation (AF) in a way that reflects clinical endpoints such as response to therapy. We set out to map electrical patterns of disorganization and regions of reentrant activity in AF from the body surface using electrocardiographic imaging (ECGI), calibrated to panoramic intracardiac recordings and referenced to AF termination by ablation. Methods - Bi-atrial intracardiac electrograms of 47 AF patients at ablation (30 persistent, 29 male, 63±9 years) were recorded with 64-pole basket catheters and simultaneous 57-lead body surface ECGs. Atrial epicardial electrical activity was reconstructed and organized sites were invasively and non-invasively tracked in 3D using phase singularity (PS). In a subset of 17 patients, sites of AF organization were targeted for ablation. Results - Body surface mapping showed greater AF organization near intracardially-detected drivers than elsewhere, both in PS density (2.3±2.1 vs 1.9±1.6, p=0.02) and number of drivers (3.2±2.3 vs 2.7±1.7, p=0.02). Complexity, defined as the number of stable AF reentrant sites, was concordant between non-invasive and invasive methods (r2 =0.5, CC=0.71). In the subset receiving targeted ablation, AF complexity showed lower values in those in whom AF terminated than those in whom AF did not terminate (p<0.01). Conclusions - AF complexity tracked non-invasively correlates well with organized and disorganized regions detected by panoramic intracardiac mapping, and correlates with the acute outcome by ablation. This approach may assist in bedside monitoring of therapy or in improving the efficacy of ongoing ablation procedures.

    View details for DOI 10.1161/CIRCEP.119.007700

    View details for PubMedID 32078374

  • Electrographic flow mapping in persistent atrial fibrillation Baykaner, T., Alhusseini, M., Rogers, A., Sauer, W., Ruppersberg, P., Narayan, S. WILEY. 2019: 1745–46

    View details for Web of Science ID 000485280500073

  • Wavefront Field Mapping Reveals a Physiologic Network Between Drivers Where Ablation Terminates Atrial Fibrillation. Circulation. Arrhythmia and electrophysiology Leef, G., Shenasa, F., Bhatia, N. K., Rogers, A. J., Sauer, W., Miller, J. M., Swerdlow, M., Tamboli, M., Alhusseini, M. I., Armenia, E., Baykaner, T., Brachmann, J., Turakhia, M. P., Atienza, F., Rappel, W., Wang, P. J., Narayan, S. M. 2019; 12 (8): e006835

    Abstract

    BACKGROUND: Localized drivers are proposed mechanisms for persistent atrial fibrillation (AF) from optical mapping of human atria and clinical studies of AF, yet are controversial because drivers fluctuate and ablating them may not terminate AF. We used wavefront field mapping to test the hypothesis that AF drivers, if concurrent, may interact to produce fluctuating areas of control to explain their appearance/disappearance and acute impact of ablation.METHODS: We recruited 54 patients from an international registry in whom persistent AF terminated by targeted ablation. Unipolar AF electrograms were analyzed from 64-pole baskets to reconstruct activation times, map propagation vectors each 20 ms, and create nonproprietary phase maps.RESULTS: Each patient (63.6±8.5 years, 29.6% women) showed 4.0±2.1 spatially anchored rotational or focal sites in AF in 3 patterns. First, a single (type I; n=7) or, second, paired chiral-antichiral (type II; n=5) rotational drivers controlled most of the atrial area. Ablation of 1 to 2 large drivers terminated all cases of types I or II AF. Third, interaction of 3 to 5 drivers (type III; n=42) with changing areas of control. Targeted ablation at driver centers terminated AF and required more ablation in types III versus I (P=0.02 in left atrium).CONCLUSIONS: Wavefront field mapping of persistent AF reveals a pathophysiologic network of a small number of spatially anchored rotational and focal sites, which interact, fluctuate, and control varying areas. Future work should define whether AF drivers that control larger atrial areas are attractive targets for ablation.

    View details for DOI 10.1161/CIRCEP.118.006835

    View details for PubMedID 31352796

  • MACHINE LEARNING IDENTIFIES SITES WHERE ABLATION TERMINATES PERSISTENT ATRIAL FIBRILLATION Alhusseini, M., Abuzaid, F., Clopton, P., Rogers, A., Rodrigo, M., Baykaner, T., Wang, P., Rappel, W., Narayan, S. ELSEVIER SCIENCE INC. 2019: 301

    View details for Web of Science ID 000460565900301

  • SITES THAT CONTROL LARGER AREAS DURING ATRIAL FIBRILLATION MAY DETERMINE TERMINATION DURING ABLATION Bhatia, N. K., Hossainy, S., Rogers, A., Alhusseini, M., Brodt, C., Moosvi, N., Baykaner, T., Wang, P., Rappel, W., Narayan, S. ELSEVIER SCIENCE INC. 2019: 400

    View details for Web of Science ID 000460565900400

  • INTRACLASS CORRELATIONS OF VOLTAGE, FRACTIONATED ELECTROGRAMS, AND DOMINANT FREQUENCY IN PATIENTS WHERE LOCALIZED ABLATION TERMINATED PERSISTENT ATRIAL FIBRILLATION Rogers, A. J., Moosvi, N., Singh, A., Alhusseini, M., Baykaner, T., Clopton, P., Rappel, W., Wang, P., Narayan, S. ELSEVIER SCIENCE INC. 2019: 521

    View details for Web of Science ID 000460565900521

  • Online webinar training to analyse complex atrial fibrillation maps: A randomized trial. PloS one Mesquita, J. n., Maniar, N. n., Baykaner, T. n., Rogers, A. J., Swerdlow, M. n., Alhusseini, M. I., Shenasa, F. n., Brizido, C. n., Matos, D. n., Freitas, P. n., Santos, A. R., Rodrigues, G. n., Silva, C. n., Rodrigo, M. n., Dong, Y. n., Clopton, P. n., Ferreira, A. M., Narayan, S. M. 2019; 14 (7): e0217988

    Abstract

    Specific tools have been recently developed to map atrial fibrillation (AF) and help guide ablation. However, when used in clinical practice, panoramic AF maps generated from multipolar intracardiac electrograms have yielded conflicting results between centers, likely due to their complexity and steep learning curve, thus limiting the proper assessment of its clinical impact.The main purpose of this trial was to assess the impact of online training on the identification of AF driver sites where ablation terminated persistent AF, through a standardized training program. Extending this concept to mobile health was defined as a secondary objective.An online database of panoramic AF movies was generated from a multicenter registry of patients in whom targeted ablation terminated non-paroxysmal AF, using a freely available method (Kuklik et al-method A) and a commercial one (RhythmView-method B). Cardiology Fellows naive to AF mapping were enrolled and randomized to training vs no training (control). All participants evaluated an initial set of movies to identify sites of AF termination. Participants randomized to training evaluated a second set of movies in which they received feedback on their answers. Both groups re-evaluated the initial set to assess the impact of training. This concept was then migrated to a smartphone application (App).12 individuals (median age of 30 years (IQR 28-32), 6 females) read 480 AF maps. Baseline identification of AF termination sites by ablation was poor (40%±12% vs 42%±11%, P = 0.78), but similar for both mapping methods (P = 0.68). Training improved accuracy for both methods A (P = 0.001) and B (p = 0.012); whereas controls showed no change in accuracy (P = NS). The Smartphone App accessed AF maps from multiple systems on the cloud to recreate this training environment.Digital online training improved interpretation of panoramic AF maps in previously inexperienced clinicians. Combining online clinical data, smartphone apps and other digital resources provides a powerful, scalable approach for training in novel techniques in electrophysiology.

    View details for DOI 10.1371/journal.pone.0217988

    View details for PubMedID 31269029

  • AF Drivers Where Ablation Terminates Persistent AF Fluctuate Due to Competing Drivers but Remain Anchored in Specific Locations Meckler, G. L., Kowalewski, C. A., Rogers, A. J., Rodrigo, M., Clopton, P., Shenasa, F., Alhusseini, M., Swerdlow, M., Joshi, V., Hossainy, S., Zaman, J., Baykaner, T., Brachmann, J., Miller, J., Krummen, D. E., Sauer, W., Viswanathan, M., Wang, P., Narayan, S. M. LIPPINCOTT WILLIAMS & WILKINS. 2018

    View details for Web of Science ID 000528619407352

  • Electrode Density is Greater at Sites Where Ablation Acutely Terminates Atrial Fibrillation Rogers, A. J., Juan, R. C., Collart, O., Swerdlow, M., Alhusseini, M., Rodrigo, M., Kowalewski, C., Baykaner, T., Zaman, J., Wang, P. J., Rappel, W., Narayan, S. M. LIPPINCOTT WILLIAMS & WILKINS. 2018

    View details for Web of Science ID 000528619405137

  • Comparing Multiple Mapping Methods at Sites of AF Termination: The COMPARE-AF Registry. Zaman, J. A., Baykaner, T., Meckler, G., Clopton, P., Alhusseini, M., Shenasa, F., Kowalewski, C., Rogers, A., Vidmar, D., Krummen, D., Viswanathan, M., Rappel, W., Brachmann, J., Peters, N., Miller, J., Wang, P., Sauer, W., Atienza, F., Narayan, S. LIPPINCOTT WILLIAMS & WILKINS. 2018

    View details for Web of Science ID 000528619405012

  • Sites Where Ablation Terminated Atrial Fibrillation Identified by Machine Learning Models Alhusseini, M., Abuzaid, F., Swerdlow, M., Meckler, G., Clopton, P., Rogers, A., Rodrigo, M., Baykaner, T., Zaman, J., Kowalewski, C., Shenasa, F., Atienza, F., Mohan, N., Wang, P. J., Rappel, W. J., Bailis, P., Zaharia, M., Narayan, S. LIPPINCOTT WILLIAMS & WILKINS. 2018

    View details for Web of Science ID 000528619403044

  • Machine Learning Reveals That Drivers for Persistent Atrial Fibrillation at Termination Sites Show Irregular Rotational Cycles and Domain Size Alhusseini, M., Abuzaid, F., Swerdlow, M., Clopton, P., Meckler, G. L., Maniar, N. M., Rogers, A., Rodrigo, M., Baykaner, T., Zaman, J., Kowalewski, C., Shenasa, F., Tamboli, M., Viswanathan, M., Wang, P., Atienza, F., Rappel, W. J., Bailis, P., Zaharia, M., Narayan, S. M. LIPPINCOTT WILLIAMS & WILKINS. 2018

    View details for Web of Science ID 000528619404020

  • Procedural and Clinical Determinants of Acute Success of Driver Ablation for Persistent Atrial Fibrillation Baykaner, T., Rogers, A. J., Rodrigo, M., Alhusseini, M., Zaman, J. A., Wang, P. J., Narayan, S. M., Spitzer, S., Szili-Torok, T. LIPPINCOTT WILLIAMS & WILKINS. 2018

    View details for Web of Science ID 000528619404248

  • Localized Driver Regions That Control Larger Regions of the Atria May Be Critical to Sustaining Atrial Fibrillation: Analyses From Novel Vector Mapping Leef, G., Shenasa, F., Sauer, W., Miller, J. M., Vidmar, D., Swerdlow, M. A., Tomboli, M., Rogers, A. J., Alhusseini, M., Armenia, E., Baykaner, T., Brachmann, J., Atienza, F., Wang, P. J., Rappel, W., Narayan, S. M. LIPPINCOTT WILLIAMS & WILKINS. 2018

    View details for Web of Science ID 000528619402146

  • Characterizing Electrogram Signal Fidelity and the Effects of Signal Contamination on Mapping Human Persistent Atrial Fibrillation FRONTIERS IN PHYSIOLOGY Vidmar, D., Alhusseini, M., Narayan, S. M., Rappel, W. 2018; 9

    View details for DOI 10.3389/fphys.2018.01232

    View details for Web of Science ID 000443769500001

  • Characterizing Electrogram Signal Fidelity and the Effects of Signal Contamination on Mapping Human Persistent Atrial Fibrillation. Frontiers in physiology Vidmar, D., Alhusseini, M. I., Narayan, S. M., Rappel, W. J. 2018; 9: 1232

    Abstract

    Objective: Determining accurate intracardiac maps of atrial fibrillation (AF) in humans can be difficult, owing primarily to various sources of contamination in electrogram signals. The goal of this study is to develop a measure for signal fidelity and to develop methods to quantify robustness of observed rotational activity in phase maps subject to signal contamination. Methods: We identified rotational activity in phase maps of human persistent AF using the Hilbert transform of sinusoidally recomposed signals, where localized ablation at rotational sites terminated fibrillation. A novel measure of signal fidelity was developed to quantify signal quality. Contamination is then introduced to the underlying electrograms by removing signals at random, adding noise to computations of cycle length, and adding realistic far-field signals. Mean tip number N and tip density δ, defined as the proportion of time a region contains a tip, at the termination site are computed to compare the effects of contamination. Results: Domains of low signal fidelity correspond to the location of rotational cores. Removing signals and altering cycle length accounted for minor changes in tip density, while targeted removal of low fidelity electrograms can result in a significant increase in tip density and stability. Far-field contamination was found to obscure rotation at the termination site. Conclusion: Rotational activity in clinical AF can produce domains of low fidelity electrogram recordings at rotational cores. Observed rotational patterns in phase maps appear most sensitive to far-field activation. These results may inform novel methods to map AF in humans which can be tested directly in patients at electrophysiological study and ablation.

    View details for DOI 10.3389/fphys.2018.01232

    View details for PubMedID 30237766

    View details for PubMedCentralID PMC6135945

  • Interaction of Localized Drivers and Disorganized Activation in Persistent Atrial Fibrillation: Reconciling Putative Mechanisms Using Multiple Mapping Techniques CIRCULATION-ARRHYTHMIA AND ELECTROPHYSIOLOGY Kowalewski, C. A. B., Shenasa, F., Rodrigo, M., Clopton, P., Meckler, G., Alhusseini, M. I., Swerdlow, M. A., Joshi, V., Hossainy, S., Zaman, J. A. B., Baykaner, T., Rogers, A. J., Brachmann, J., Miller, J. M., Krummen, D. E., Sauer, W. H., Peters, N. S., Wang, P. J., Narayan, S. M. 2018; 11 (6): e005846

    Abstract

    Mechanisms for persistent atrial fibrillation (AF) are unclear. We hypothesized that putative AF drivers and disorganized zones may interact dynamically over short time scales. We studied this interaction over prolonged durations, focusing on regions where ablation terminates persistent AF using 2 mapping methods.We recruited 55 patients with persistent AF in whom ablation terminated AF prior to pulmonary vein isolation from a multicenter registry. AF was mapped globally using electrograms for 360±45 cycles using (1) a published phase method and (2) a commercial activation/phase method.Patients were 62.2±9.7 years, 76% male. Sites of AF termination showed rotational/focal patterns by methods 1 and 2 (51/55 vs 55/55; P=0.13) in spatially conserved regions, yet fluctuated over time. Time points with no AF driver showed competing drivers elsewhere or disordered waves. Organized regions were detected for 61.6±23.9% and 70.6±20.6% of 1 minute per method (P=nonsignificant), confirmed by automatic phase tracking (P<0.05). To detect AF drivers with >90% sensitivity, 8 to 32 s of AF recordings were required depending on driver definition.Sites at which persistent AF terminated by ablation show organized activation that fluctuate over time, because of collision from concurrent organized zones or fibrillatory waves, yet recur in conserved spatial regions. Results were similar by 2 mapping methods. This network of competing mechanisms should be reconciled with existing disorganized or driver mechanisms for AF, to improve clinical mapping and ablation of persistent AF.URL: http://www.clinicaltrials.gov. Unique identifier: NCT02997254.

    View details for PubMedID 29884620

  • Clinical Implications of Ablation of Drivers for Atrial Fibrillation A Systematic Review and Meta-Analysis CIRCULATION-ARRHYTHMIA AND ELECTROPHYSIOLOGY Baykaner, T., Rogers, A. J., Meckler, G. L., Zaman, J., Navara, R., Rodrigo, M., Alhusseini, M., Kowalewski, C. A. B., Viswanathan, M. N., Narayan, S. M., Clopton, P., Wang, P. J., Heidenreich, P. A. 2018; 11 (5)

    View details for DOI 10.1161/CIRCEP.117.006119

    View details for Web of Science ID 000439150300011

  • Clinical Implications of Ablation of Drivers for Atrial Fibrillation: A Systematic Review and Meta-Analysis. Circulation. Arrhythmia and electrophysiology Baykaner, T. n., Rogers, A. J., Meckler, G. L., Zaman, J. n., Navara, R. n., Rodrigo, M. n., Alhusseini, M. n., Kowalewski, C. A., Viswanathan, M. N., Narayan, S. M., Clopton, P. n., Wang, P. J., Heidenreich, P. A. 2018; 11 (5): e006119

    Abstract

    The outcomes from pulmonary vein isolation (PVI) for atrial fibrillation (AF) are suboptimal, but the benefits of additional lesion sets remain unproven. Recent studies propose ablation of AF drivers improves outcomes over PVI, yet with conflicting reports in the literature. We undertook a systematic literature review and meta-analysis to determine outcomes from ablation of AF drivers in addition to PVI or as a stand-alone procedure.Database search was done using the terms atrial fibrillation and ablation or catheter ablation and driver or rotor or focal impulse or FIRM (Focal Impulse and Rotor Modulation). We pooled data using random effects model and assessed heterogeneity with I2 statistic.Seventeen studies met inclusion criteria, in a cohort size of 3294 patients. Adding AF driver ablation to PVI reported freedom from AF of 72.5% (confidence interval [CI], 62.1%-81.8%; P<0.01) and from all arrhythmias of 57.8% (CI, 47.5%-67.7%; P<0.01). AF driver ablation when added to PVI or as stand-alone procedure compared with controls produced an odds ratio of 3.1 (CI, 1.3-7.7; P=0.02) for freedom from AF and an odds ratio of 1.8 (CI, 1.2-2.7; P<0.01) for freedom from all arrhythmias in 4 controlled studies. AF termination rate was 40.5% (CI, 30.6%-50.9%) and predicted favorable outcome from ablation(P<0.05).In controlled studies, the addition of AF driver ablation to PVI supports the possible benefit of a combined approach of AF driver ablation and PVI in improving single-procedure freedom from all arrhythmias. However, most studies are uncontrolled and are limited by substantial heterogeneity in outcomes. Large multicenter randomized trials are needed to precisely define the benefits of adding driver ablation to PVI.

    View details for PubMedID 29743170

  • Identification and Characterization of Sites Where Persistent Atrial Fibrillation Is Terminated by Localized Ablation CIRCULATION-ARRHYTHMIA AND ELECTROPHYSIOLOGY Zaman, J. A. B., Sauer, W. H., Alhusseini, M. I., Baykaner, T., Borne, R. T., Kowalewski, C. A. B., Busch, S., Zei, P. C., Park, S., Viswanathan, M. N., Wang, P. J., Brachmann, J., Krummen, D. E., Miller, J. M., Rappel, W., Narayan, S. M., Peters, N. S. 2018; 11 (1): e005258

    Abstract

    The mechanisms by which persistent atrial fibrillation (AF) terminates via localized ablation are not well understood. To address the hypothesis that sites where localized ablation terminates persistent AF have characteristics identifiable with activation mapping during AF, we systematically examined activation patterns acquired only in cases of unequivocal termination by ablation.We recruited 57 patients with persistent AF undergoing ablation, in whom localized ablation terminated AF to sinus rhythm or organized tachycardia. For each site, we performed an offline analysis of unprocessed unipolar electrograms collected during AF from multipolar basket catheters using the maximum -dV/dt assignment to construct isochronal activation maps for multiple cycles. Additional computational modeling and phase analysis were used to study mechanisms of map variability. At all sites of AF termination, localized repetitive activation patterns were observed. Partial rotational circuits were observed in 26 of 57 (46%) cases, focal patterns in 19 of 57 (33%), and complete rotational activity in 12 of 57 (21%) cases. In computer simulations, incomplete segments of partial rotations coincided with areas of slow conduction characterized by complex, multicomponent electrograms, and variations in assigning activation times at such sites substantially altered mapped mechanisms.Local activation mapping at sites of termination of persistent AF showed repetitive patterns of rotational or focal activity. In computer simulations, complete rotational activation sequence was observed but was sensitive to assignment of activation timing particularly in segments of slow conduction. The observed phenomena of repetitive localized activation and the mechanism by which local ablation terminates putative AF drivers require further investigation.

    View details for PubMedID 29330332

    View details for PubMedCentralID PMC5769709

  • Spatial relationship of organized rotational and focal sources in human atrial fibrillation to autonomic ganglionated plexi. International journal of cardiology Baykaner, T., Zografos, T. A., Zaman, J. A., Pantos, I., Alhusseini, M., Navara, R., Krummen, D. E., Narayan, S. M., Katritsis, D. G. 2017

    Abstract

    One approach to improve ablation for atrial fibrillation (AF) is to focus on physiological targets including focal or rotational sources or ganglionic plexi (GP). However, the spatial relationship between these potential mechanisms has never been studied. We tested the hypothesis that rotors and focal sources for AF may co-localize with ganglionated plexi (GP).We prospectively identified locations of AF rotors and focal sources, and correlated these to GP sites in 97 consecutive patients (age 59.9±11.4, 73% persistent AF). AF was recorded with 64-pole catheters with activation/phase mapping, and related to anatomic GP sites on electroanatomic maps.AF sources arose in 96/97 (99%) patients for 2.6±1.4 sources per patient (left atrium: 1.7±0.9 right atrium: 1.1±0.8), each with an area of 2-3cm(2). On area analyses, the probability of an AF source randomly overlapping a GP area was 26%. Left atrial sources were seen in 94 (97%) patients, in whom ≥1 source co-localized with GP in 75 patients (80%; p<0.05). AF sources were more likely to colocalize with left vs right GPs (p<0.05), and colocalization was more likely in patients with higher CHADS2VASc scores (age>65, diabetes; p<0.05).This is the first study to demonstrate that clinically detected AF focal and rotational sources in the left atrium often colocalize with regions of autonomic innervation. Studies should define if the role of AF sources differs by their anatomical location.

    View details for DOI 10.1016/j.ijcard.2017.02.152

    View details for PubMedID 28433558

  • Two Independent Mapping Techniques Identify Rotational Activity Patterns at Sites of Local Termination during Persistent Atrial Fibrillation. Journal of cardiovascular electrophysiology Alhusseini, M., Vidmar, D., Meckler, G. L., Kowalewski, C., Shenasa, F., Wang, P. J., Narayan, S. M., Rappel, W. 2017

    Abstract

    The mechanisms for atrial fibrillation (AF) are unclear in part because diverse mapping techniques yield diverse maps, ranging from stable organized sources to highly disordered waves. We hypothesized that AF mechanisms may be clarified if mapping techniques were compared in the same patients, and referenced to a clinical endpoint. We compared two independent AF mapping techniques in patients in whom ablation terminated persistent AF before pulmonary vein isolation (PVI).We identified 12 patients with persistent AF (61.2 ± 10.8 years, four female) in whom mapping with 64 pole baskets and technique 1 (activation/phase mapping, FIRM) identified rotational activation patterns during at least 50% of the 4-second mapping interval and targeted ablation at these rotational sites terminated AF to sinus rhythm (n = 10) or atrial tachycardia. We analyzed the unipolar electrograms of these patients to determine phase maps of activation by an independent technique 2 (Kuklik, Schotten et al., IEEE Trans Biomed Eng 2015). Compared to technique 1, technique 2 revealed a source in 12 of 12 (100%) cases with spatial concordance in all cases (P <0.05) and similar rotational characteristics.At sites where ablation terminated persistent AF, two independent mapping techniques identified stable rotational activation for multiple cycles that drove peripheral disorder. Future comparative studies referenced to a clinical endpoint may help reconcile if discrepancies between AF mapping studies reports represent techniques, patient populations or models of AF, and improve mapping to better guide ablation.

    View details for DOI 10.1111/jce.13177

    View details for PubMedID 28185348

  • Spatial relationship of sites for atrial fibrillation drivers and atrial tachycardia in patients with both arrhythmias. International journal of cardiology Baykaner, T. n., Zaman, J. A., Rogers, A. J., Navara, R. n., AlHusseini, M. n., Borne, R. T., Park, S. n., Wang, P. J., Krummen, D. E., Sauer, W. H., Narayan, S. M. 2017; 248: 188–95

    Abstract

    Atrial fibrillation (AF) often converts to and from atrial tachycardia (AT), but it is undefined if these rhythms are mechanistically related in such patients. We tested the hypothesis that critical sites for AT may be related to regional AF sources in patients with both rhythms, by mapping their locations and response to ablation on transitions to and from AF.From 219 patients undergoing spatial mapping of AF prior to ablation at 3 centers, we enrolled 26 patients in whom AF converted to AT by ablation (n=19) or spontaneously (n=7; left atrial size 42±6cm, 38% persistent AF). Both atria were mapped in both rhythms by 64-electrode baskets, traditional activation maps and entrainment.Each patient had a single mapped AT (17 reentrant, 9 focal) and 3.7±1.7 AF sources. The mapped AT spatially overlapped one AF source in 88% (23/26) of patients, in left (15/23) or right (8/23) atria. AF transitioned to AT by 3 mechanisms: (a) ablation anchoring AF rotor to AT (n=13); (b) residual, unablated AF source producing AT (n=6); (c) spontaneous slowing of AF rotor leaving reentrant AT at this site without any ablation (n=7). Electrogram analysis revealed a lower peak-to-peak voltage at overlapping sites (0.36±0.2mV vs 0.49±0.2mV p=0.03).Mechanisms responsible for AT and AF may arise in overlapping atrial regions. This mechanistic inter-relationship may reflect structural and/or functional properties in either atrium. Future work should delineate how acceleration of an organized AT may produce AF, and whether such regions can be targeted a priori to prevent AT recurrence post AF ablation.

    View details for PubMedID 28733070