A realistic, accurate and fast source modeling approach for the EEG forward problem.

The aim of this paper is to advance electroencephalography (EEG) source analysis using finite element method (FEM) head volume conductor models that go beyond the standard three compartment (skin, skull, brain) approach and take brain tissue inhomogeneity (gray and white matter and cerebrospinal fluid) into account. The new approach should enable accurate EEG forward modeling in the thin human cortical structures and, more specifically, in the especially thin cortices in children brain research or in pathological applications. The source model should thus be focal enough to be usable in the thin cortices, but should on the other side be more realistic than the current standard mathematical point dipole. Furthermore, it should be numerically accurate and computationally fast. We propose to achieve the best balance between these demands with a current preserving (divergence conforming) dipolar source model. We develop and investigate a varying number of current preserving source basis elements n (n=1,…,n=5). For validation, we conducted numerical experiments within a multi-layered spherical domain, where an analytical solution exists. We show that the accuracy increases along with the number of basis elements, while focality decreases. The results suggest that the best balance between accuracy and focality in thin cortices is achieved with n=4 (or in extreme cases even n=3) basis functions, while in thicker cortices n=5 is recommended to obtain the highest accuracy. We also compare the current preserving approach to two further FEM source modeling techniques, namely partial integration and St. Venant, and show that the best current preserving source model outperforms the competing methods with regard to overall balance. For all tested approaches, FEM transfer matrices enable high computational speed. We implemented the new EEG forward modeling approaches into the open source duneuro library for forward modeling in bioelectromagnetism to enable its broader use by the brain research community. This library is build upon the DUNE framework for parallel finite elements simulations and integrates with high-level toolboxes like FieldTrip. Additionally, an inversion test has been implemented using the realistic head model to demonstrate and compare the differences between the aforementioned source models.

Ultra-rapid high-density mapping system with the phase singularity technique is feasible in identifying rotors and focal sources and predicting AF termination.

INTRODUCTION: Phase singularity (PS) mapping provides additional insight into the AF mechanism and is accurate in identifying rotors. The study aimed to evaluate the feasibility of PS mapping in identifying AF rotors using data obtained from an automatic ultra-rapid high-resolution mapping system with a high-density mini-basket catheter. METHODS: Twenty-three pigs underwent rapid right atrial (RA) pacing (RAP 480 bpm) for 5 weeks before the experiment. During AF, RA endocardial automatic continuous mappings with a mini-basket catheter were generated using an automatic ultra-rapid mapping system. Both fractionation mapping and waveform similarity measurements using a PS mapping algorithm were applied on the same recording signals to localize substrates maintaining AF. RESULTS: Seventeen (74%) pigs developed sustained AF after RAP. Three were excluded because of periprocedural ventricular arrhythmia and corrupted digital data. RA fractionation maps were acquired with 6.17 ± 4.29 minutes mean acquisition time, 13768 ± 12698 acquisition points mapped during AF from 581 ± 387 beats. Fractionation mapping identified extensively distributed (66.7%) RA complex fractionated atrial electrogram (CFAE), whereas the nonlinear analysis identified high similarity index (SI > 0.7) parts in limited areas (23.7%). There was an average of 1.67 ± 0.87 SI sites with 0.43 ± 0.76 rotor/focal source/chamber. AF termination occurred in 11/16 (68.75%) AF events in 14 pigs during ablation targeting max CFAE. There was a higher incidence of rotor/focal source at AF termination sites compared with non-AF termination sites (54.5% vs 0%, P = 0.011). CONCLUSIONS: The data obtained from ultra-rapid high-density automatic mapping is feasible and effective in identifying AF rotors/focal sources using PS technique, and those critical substrates were closely related to AF procedural termination.

Efficacy of catheter ablation of focal sources in persistent atrial fibrillation.

INTRODUCTION: Recent studies suggest that atrial fibrillation (AF) is maintained by electrical activity arising from focal sources. We sought to test whether catheter ablation that targets focal sources can improve on current ablation protocols for persistent AF. METHODS AND RESULTS: In patients with persistent AF whose AF did not terminate with pulmonary vein (PV) isolation, the left atrium was mapped with a 20-pole high-density mapping catheter using CARTO® 3 navigation. If a site demonstrated centrifugal activation over at least three consecutive cycles, it was deemed a focal source and ablated. If AF remained, defragmentation was performed until AF was terminated. Freedom from atrial tachyarrhythmia was compared between the study patients and propensity score matched historical controls who had undergone conventional stepwise ablation. Of the 68 study patients, 2.9 ± 1.9 focal sources were identified in 60 patients. Focal sources displayed transient centrifugal activation patterns for a median of six consecutive cycles. Total radiofrequency duration was shorter in the study group (62 ± 16 minutes vs. 75 ± 24 minutes, P = 0.0003). During a 1-year follow-up period, 39 (57%) and 26 (38%) patients were free from atrial tachyarrhythmias in the absence of antiarrhythmic drugs in the study and control groups, respectively (hazard ratio: 1.85, 95% confidence interval: 1.17-2.96, P = 0.009). Improvement of clinical outcome was mainly driven by a decrease in recurrence of atrial tachycardia in the study patients (22% vs. 40%, P = 0.047). CONCLUSION: The results of this study suggest that focal sources are appropriate ablation targets in addition to the PVs in persistent AF.

Organized Sources Are Spatially Conserved in Recurrent Compared to Pre-Ablation Atrial Fibrillation: Further Evidence for Non-Random Electrical Substrates.

INTRODUCTION: Recurrent atrial fibrillation (AF) after ablation is associated with reconnection of initially isolated pulmonary vein (PV) trigger sites. Substrates are often targeted in addition to PVI, but it is unclear how substrates progress over time. We studied if substrates in recurrent AF are conserved or have developed de novo from pre-ablation AF. METHODS AND RESULTS: Of 137 patients undergoing Focal Impulse and Rotor Mapping (FIRM) at their index procedure for AF, 29 consecutive patients (60 ± 8 years, 79% persistent) recurred and were also mapped at repeat procedure (21 ± 20 months later) using carefully placed 64-pole baskets and RhythmView(TM) (Topera, Menlo Park, CA, USA) to identify AF sources and disorganized zones. Compared to index AF, recurrent AF had a longer cycle length (177 ± 21 vs. 167 ± 19 milliseconds, P = 0.01). All patients (100%) had 1 or more conserved AF rotors between procedures with surrounding disorganization. The number of sources was similar for recurrent AF post-PVI versus index AF (3.2 ± 1.4 vs. 3.1 ± 1.0, P = 0.79), but was lower for recurrent AF after FIRM+PVI versus index AF (4.4 ± 1.4 vs. 2.9 ± 1.7, P = 0.03). Overall, 81% (61/75) of AF sources lay in conserved regions, while 19% (14/75) were detected de novo. CONCLUSION: Electrical propagation patterns for recurrent AF after unsuccessful ablation are similar in individual patients to their index AF. These data support temporospatial stability of AF substrates over 1-2 years. Trials should determine the relative benefit of adding substrate mapping and ablation to PVI for recurrent AF.

Directed graph mapping shows rotors maintain non-terminating and focal sources maintain self-terminating Torsade de Pointes in canine model.

Torsade de Pointes is a polymorphic ventricular tachycardia which is as yet incompletely understood. While the onset of a TdP episode is generally accepted to be caused by triggered activity, the mechanisms for the perpetuation is still under debate. In this study, we analysed data from 54 TdP episodes divided over 5 dogs (4 female, 1 male) with chronic atrioventricular block. Previous research on this dataset showed both reentry and triggered activity to perpetuate the arrhythmia. 13 of those TdP episodes showed reentry as part of the driving mechanism of perpetuating the episode. The remaining 41 episodes were purely ectopic. Reentry was the main mechanism in long-lasting episodes (>14 beats), while focal sources were responsible for maintaining shorter episodes. Building on these results, we re-analysed the data using directed graph mapping This program uses principles from network theory and a combination of positional data and local activation times to identify reentry loops and focal sources within the data. The results of this study are twofold. First, concerning reentry loops, we found that on average non-terminating (NT) episodes (≥10 s) show significantly more simultaneous reentry loops than self-terminating (ST) TdP (<10 s). Non-terminating episodes have on average 2.72 ± 1.48 simultaneous loops, compared to an average of 1.33 ± 0.66 for self-terminating episodes. In addition, each NT episode showed a presence of (bi-)ventricular loops between 10.10% and 69.62% of their total reentry duration. Compared to the ST episodes, only 1 in 4 episodes (25%) showed (bi-)ventricular reentry, lasting only 7.12% of its total reentry duration. This suggests that while focal beats trigger TdP, macro-reentry and multiple simultaneous localized reentries are the major drivers of long-lasting episodes. Second, using heatmaps, we found focal sources to occur in preferred locations, instead of being distributed randomly. This may have implications on treatment if such focal origins can be disabled reliably.

Non-invasive localization of the ventricular excitation origin without patient-specific geometries using deep learning.

Cardiovascular diseases account for 17 million deaths per year worldwide. Of these, 25% are categorized as sudden cardiac death, which can be related to ventricular tachycardia (VT). This type of arrhythmia can be caused by focal activation sources outside the sinus node. Catheter ablation of these foci is a curative treatment in order to inactivate the abnormal triggering activity. However, the localization procedure is usually time-consuming and requires an invasive procedure in the catheter lab. To facilitate and expedite the treatment, we present two novel localization support techniques based on convolutional neural networks (CNNs) that address these clinical needs. In contrast to existing methods, our approaches were designed to be independent of the patient-specific geometry and directly applicable to surface ECG signals, while also delivering a binary transmural position. Moreover, one of the method's outputs can be interpreted as several ranked solutions. The CNNs were trained on a dataset containing only simulated data and evaluated both on simulated test data and clinical data. On a novel large and open simulated dataset, the median test error was below 3 mm. The median localization error on the unseen clinical data ranged from 32 mm to 41 mm without optimizing the pre-processing and CNN to the clinical data. Interpreting the output of one of the approaches as ranked solutions, the best median error of the top-3 solutions decreased to 20 mm on the clinical data. The transmural position was correctly detected in up to 82% of all clinical cases. These results demonstrate a proof of principle to utilize CNNs to localize the activation source without the intrinsic need for patient-specific geometrical information. Furthermore, providing multiple solutions can assist physicians in identifying the true activation source amongst more than one possible location. With further optimization to clinical data, these methods have high potential to accelerate clinical interventions, replace certain steps within these procedures and consequently reduce procedural risk and improve VT patient outcomes.

DG-Mapping: a novel software package for the analysis of any type of reentry and focal activation of simulated, experimental or clinical data of cardiac arrhythmia.

In this work, we present the release of a novel easy to use software package called DGM or Directed-Graph-Mapping. DGM can automatically analyze any type of arrhythmia to find reentry or focal sources if the measurements are synchronized in time. Currently, DGM requires the local activation times (LAT) and the spatial coordinates of the measured electrodes. However, there is no requirement for any spatial organization of the electrodes, allowing to analyze clinical, experimental or computational data. DGM creates directed networks of the activation, which are analyzed with fast algorithms to search for reentry (cycles in the network) and focal sources (nodes with outgoing arrows). DGM has been mainly optimized to analyze atrial tachycardia, but we also discuss other applications of DGM demonstrating its wide applicability. The goal is to release a free software package which can allow researchers to save time in the analysis of cardiac data. An academic license is attached to the software, allowing only non-commercial use of the software. All updates of the software, user and installation guide will be published on a dedicated website www.dgmapping.com . Graphical Abstract Direct-Graph-Mapping is a method to automatically analyze a given arrhythmia by converting measured data of the electrodes in a directed network. DGM requires the local activation times (LAT) and the spatial coordinates of the measured electrodes. There is no requirement for any spatial organization of the electrodes, allowing to analyze clinical, experimental or computational data (see left). An example could be the LATs and coordinates from a CARTO file. DGM creates a directed network of the activation by (1) determining the neighbors of each node, 2 (2) allowing a directed arrow between two neighbors if propagation of the electrical wave is possible, (3) repeating this process for all nodes, (4) if necessary, redistributing the nodes more uniformly and repeating step (1)-(3). Two possible steps are (5) to visualize the wavefront by creating an average graph or (6) find the cycles in the network which represent the reentry loops. Focal sources are nodes with only outgoing arrows.

New Insights Into Understanding Rotor Versus Focal Activation in Patients With Persistent Atrial Fibrillation.

OBJECTIVES: This study was to test the hypotheses that: 1) when using phase analysis, repetitive Wannabe re-entry produces a phase singularity point (i.e., a rotor); and 2) the location of the stable rotor is close to the focal source. BACKGROUND: Recent contact mapping studies in patients with persistent atrial fibrillation (AF) demonstrated that phase analysis produced a different mechanistic result than classical activation sequence analysis. Our studies in patients with persistent AF showed that focal sources sometimes produced repetitive Wannabe re-entry, that is, incomplete re-entry. METHODS: During open heart surgery, we recorded activation from both atria simultaneously using 510 to 512 electrodes in 12 patients with persistent AF. We performed activation sequence mapping and phase analyses on 4 s of mapped data. For each detected stable rotor (>2 full rotations [720°] recurring at the same site), the corresponding activation patterns were examined from the activation sequence maps. RESULTS: During AF, phase singularity points (rotors) were identified in both atria in all patients. However, stable phase singularity points were only present in 6 of 12 patients. The range of stable phase singularity points per patient was 0 to 6 (total 14). Stable phase singularity points were produced due to repetitive Wannabe re-entry generated from a focal source or by passive activation. A conduction block sometimes created a stable phase singularity point (n = 2). The average distance between a focal source and a stable rotor was 0.9 ± 0.3 cm. CONCLUSIONS: Repetitive Wannabe re-entry generated stable rotors adjacent to a focal source. No true re-entry occurred.

Deep Learning Classification of Unipolar Electrograms in Human Atrial Fibrillation: Application in Focal Source Mapping.

Focal sources are potential targets for atrial fibrillation (AF) catheter ablation, but they can be time-consuming and challenging to identify when unipolar electrograms (EGM) are numerous and complex. Our aim was to apply deep learning (DL) to raw unipolar EGMs in order to automate putative focal sources detection. We included 78 patients from the Focal Source and Trigger (FaST) randomized controlled trial that evaluated the efficacy of adjunctive FaST ablation compared to pulmonary vein isolation alone in reducing AF recurrence. FaST sites were identified based on manual classification of sustained periodic unipolar QS EGMs over 5-s. All periodic unipolar EGMs were divided into training (n = 10,004) and testing cohorts (n = 3,180). DL was developed using residual convolutional neural network to discriminate between FaST and non-FaST. A gradient-based method was applied to interpret the DL model. DL classified FaST with a receiver operator characteristic area under curve of 0.904 ± 0.010 (cross-validation) and 0.923 ± 0.003 (testing). At a prespecified sensitivity of 90%, the specificity and accuracy were 81.9 and 82.5%, respectively, in detecting FaST. DL had similar performance (sensitivity 78%, specificity 89%) to that of FaST re-classification by cardiologists (sensitivity 78%, specificity 79%). The gradient-based interpretation demonstrated accurate tracking of unipolar QS complexes by select DL convolutional layers. In conclusion, our novel DL model trained on raw unipolar EGMs allowed automated and accurate classification of FaST sites. Performance was similar to FaST re-classification by cardiologists. Future application of DL to classify FaST may improve the efficiency of real-time focal source detection for targeted AF ablation therapy.

Focal source and trigger mapping in atrial fibrillation: Randomized controlled trial evaluating a novel adjunctive ablation strategy.

BACKGROUND: Intraoperative mapping has demonstrated focal activations during human atrial fibrillation (AF). These putative AF sources can manifest sustained periodic bipolar and unipolar QS electrograms (EGMs). We have automated the detection of these EGM features using our validated Focal Source and Trigger (FaST) computational algorithm. OBJECTIVE: The purpose of this study was to conduct a randomized controlled pilot evaluating the feasibility and efficacy of FaST mapping/ablation as an adjunct to pulmonary vein isolation (PVI) in reducing AF recurrence. METHODS: We randomized 80 patients with high-burden paroxysmal or persistent AF (age 61 ± 10 years; 75% male) to PVI alone (n = 41) or PVI+FaST mapping/ablation (n = 39). The primary endpoint was time to AF recurrence >30 seconds between 3 and 12 months after 1 procedure. RESULTS: FaST sites were identified in all but 1 patient and were localized to pulmonary vein (PV) (2.1 ± 1.1 per patient) and extra-PV regions (2.8 ± 1.4 per patient). FaST mapping and ablation times were 27 ± 9 minutes and 8.5 ± 5 minutes, respectively. Patients with AF termination during ablation had greater AF cycle length prolongation with PVI+FaST than PVI (Δ20 ± 14 ms vs Δ5 ± 17 ms; P = .046). Freedom from AF recurrence at 12 months was higher in PVI+FaST vs PVI for patients off antiarrhythmic drugs (74% vs 51%; hazard ratio 0.48; 95% confidence interval 0.21-1.08; P = .064) but did not quite reach statistical significance. Major adverse events were similar between the 2 groups. CONCLUSION: In this randomized controlled pilot, real-time FaST mapping provided an intuitive, automated approach for localizing focal AF sources. FaST ablation as an adjunct to PVI may reduce AF recurrence, which requires verification with a larger multicenter trial.

Linking Electrical Drivers With Atrial Cardiomyopathy for the Targeted Treatment of Atrial Fibrillation.

The relationship between atrial fibrillation (AF) and underlying functional and structural abnormalities has received substantial attention in the research literature over the past decade. Significant progress has been made in identifying these changes using non-invasive imaging, voltage mapping, and electrical recordings. Advances in computed tomography and cardiac magnetic resonance imaging can now provide insight regarding the presence and extent of cardiac fibrosis. Additionally, multiple technologies able to identify electrical targets during AF have emerged. However, an organized strategy to employ these resources in the targeted treatment of AF remains elusive. In this work, we will discuss the basis for mechanistic importance of atrial fibrosis and scar as potential sites promoting AF and emerging technologies to identify and target these structural and functional substrates in the electrophysiology laboratory. We also propose an approach to the use of such technologies to serve as a basis for ongoing work in the field.

Simulation of Spiral Waves and Point Sources in Atrial Fibrillation with Application to Rotor Localization.

Cardiac simulations play an important role in studies involving understanding and investigating the mechanisms of cardiac arrhythmias. Today, studies of arrhythmogenesis and maintenance are largely being performed by creating simulations of a particular arrhythmia with high accuracy comparable to the results of clinical experiments. Atrial fibrillation (AF), the most common arrhythmia in the United States and many other parts of the world, is one of the major field where simulation and modeling is largely used. AF simulations not only assist in understanding its mechanisms but also help to develop, evaluate and improve the computer algorithms used in electrophysiology (EP) systems for ablation therapies. In this paper, we begin with a brief overeview of some common techniques used in simulations to simulate two major AF mechanisms - spiral waves (or rotors) and point (or focal) sources. We particularly focus on 2D simulations using Nygren et al.'s mathematical model of human atrial cell. Then, we elucidate an application of the developed AF simulation to an algorithm designed for localizing AF rotors for improving current AF ablation therapies. Our simulation methods and results, along with the other discussions presented in this paper is aimed to provide engineers and professionals with a working-knowledge of application-specific simulations of spirals and foci.

Ventricular fibrillation: triggers, mechanisms and therapies.

Ventricular fibrillation (VF) is a common, life-threatening arrhythmia responsible for significant morbidity and mortality. Due to challenges in safely mapping VF, a comprehensive understanding of its mechanisms remains elusive. Recent findings have provided new insights into mechanisms that sustain early VF. Notably, the central role of electrical rotors and catheter-based ablation of VF rotor substrate have been recently reported. In this article, we will review data regarding four stages of VF: initiation, transition, maintenance and evolution. We will discuss the particular mechanisms for each stage and therapies targeting these mechanisms. We also examine inherited arrhythmia syndromes, including the mechanisms and therapies specific to each. We hope that the overview of VF outlined in this work will assist other investigators in designing future therapies to interrupt this life-threatening arrhythmia.

Role of Rotors in the Ablative Therapy of Persistent Atrial Fibrillation.

Atrial fibrillation (AF) ablation is increasingly used to maintain sinus rhythm yet its results are sub-optimal, especially in patients with persistent AF or prior unsuccessful procedures. Attempts at improvement have often targeted substrates that sustain AF after it is triggered, yet those mechanisms are debated. Many studies now challenge the concept that AF is driven by self-sustaining disordered wavelets, showing instead that localised drivers (rotors) may drive disorder via a process known as fibrillatory conduction. Novel mapping using wide-area recordings, physiological filtering and phase analysis demonstrates rotors in human AF. Contact mapping with focal impulse and rotor modulation (FIRM) shows that localised ablation at sources can improve procedural success in many populations on long-term follow up and some newer approaches to rotor mapping are qualitatively similar. This review critically evaluates the data on rotor mapping and ablation, which advances our conceptual understanding of AF and holds the promise of substantially improving ablative outcomes in patients with persistent AF.