Variant patterns of electrical activation and recovery in normal human hearts revealed by noninvasive electrocardiographic imaging.

AIMS: Although electrical activity of the normal human heart is well characterized by the electrocardiogram, detailed insights into within-subject and between-subject variations of ventricular activation and recovery by noninvasive electroanatomic mapping are lacking. We characterized human epicardial activation and recovery within and between normal subjects using non-invasive electrocardiographic imaging (ECGI) as a basis to better understand pathology. METHODS AND RESULTS: Epicardial activation and recovery were assessed by ECGI in 22 normal subjects, 4 subjects with bundle branch block (BBB) and 4 with long-QT syndrome (LQTS). We compared characteristics between the ventricles [left ventricle (LV) and right ventricle (RV)], sexes, and age groups (<50/≥50years). Pearson's correlation coefficient (CC) was used for within-subject and between-subject comparisons. Age of normal subjects averaged 49 ± 14 years, 6/22 were male, and no structural/electrical heart disease was present. The average activation time was longer in LV than in RV, but not different by sex or age. Electrical recovery was similar for the ventricles, but started earlier and was on average shorter in males. Median CCs of between-subject comparisons of the ECG signals, activation, and recovery patterns were 0.61, 0.32, and 0.19, respectively. Within-subject beat-to-beat comparisons yielded higher CCs (0.98, 0.89, and 0.82, respectively). Activation and/or recovery patterns of patients with BBB or LQTS contrasted significantly with those found in the normal population. CONCLUSION: Activation and recovery patterns vary profoundly between normal subjects, but are stable individually beat to beat, with a male preponderance to shorter recovery. Individual characterization by ECGI at baseline serves as reference to better understand the emergence, progression, and treatment of electrical heart disease.

Pilot study to evaluate left-to-right ventricular offset in biventricular pacing-comparison of electrocardiographic imaging and ECG.

INTRODUCTION: Biventricular pacing (BiVp) improves outcomes in systolic heart failure patients with electrical dyssynchrony. BiVp is delivered from epicardial left ventricular (LV) and endocardial right ventricular (RV) electrodes. Acute electrical activation changes with different LV-RV stimulation offsets can help guide individually optimized BiVp programming. We sought to study the BiVp ventricular activation with different LV-RV offsets and compare with 12-lead ECG. METHODS: In five patients with BiVp (63 ± 17-year-old, 80% male, LV ejection fraction 27 ± 6%), we evaluated acute ventricular epicardial activation, varying LV-RV offsets in 20 ms increments from -40 to 80 ms, using electrocardiographic imaging (ECGI) to obtain absolute ventricular electrical uncoupling (VEUabs, absolute difference in average LV and average RV activation time) and total activation time (TAT). For each patient, we calculated the correlation between ECGI and corresponding ECG (3D-QRS-area and QRS duration) with different LV-RV offsets. RESULTS: The LV-RV offset to attain minimum VEUabs in individual patients ranged 20-60 ms. In all patients, a larger LV-RV offset was required to achieve minimum VEUabs (36 ± 17 ms) or 3D-QRS-area (40 ± 14 ms) than that for minimum TAT (-4 ± 9 ms) or QRS duration (-8 ± 11 ms). In individual patients, 3D-QRS-area correlated with VEUabs (r 0.65 ± 0.24) and QRS duration correlated with TAT (r 0.95 ± 0.02). Minimum VEUabs and minimum 3D-QRS-area were obtained by LV-RV offset within 20 ms of each other in all five patients. CONCLUSIONS: LV-RV electrical uncoupling, as assessed by ECGI, can be minimized by optimizing LV-RV stimulation offset. 3D-QRS-area is a surrogate to identify LV-RV offset that minimizes LV-RV uncoupling.

Current Role of Electrocardiographic Imaging in Patient Selection for Cardiac Resynchronization Therapy.

Cardiac resynchronization therapy (CRT) is a recognized therapy for heart failure with altered ejection fraction and abnormal left ventricular activation time. Since the introduction of the therapy, a 30% rate of non-responders is observed and unchanged. The 12-lead ECG remains the only recommended tool for patient selection to CRT. The 12-lead ECG is, however, limited in its inability to provide a precise pattern of regional electrical activity. Electrocardiographic imaging (ECGi) provides a non-invasive detailed mapping of cardiac activation and therefore appears as a promising tool for CRT candidates. The non-invasive ventricular activation maps acquired by ECGi have been primarily explored for the diagnosis and guidance of therapy in patients with atrial or ventricular tachyarrhythmia. However, the accuracy of the system in this field is lacking and needs further improvement before considering a clinical application. On the other hand, its use for patient selection for CRT is encouraging. In this review, we introduce the technical considerations and we describe how ECGi can precisely characterize ventricular activation, especially in patients with left bundle branch block, thus identifying the electrical substrate responsive to CRT.

Basis and applicability of noninvasive inverse electrocardiography: a comparison between cardiac source models.

The body surface electrocardiogram (ECG) is a direct result of electrical activity generated by the myocardium. Using the body surface ECGs to reconstruct cardiac electrical activity is called the inverse problem of electrocardiography. The method to solve the inverse problem depends on the chosen cardiac source model to describe cardiac electrical activity. In this paper, we describe the theoretical basis of two inverse methods based on the most commonly used cardiac source models: the epicardial potential model and the equivalent dipole layer model. We discuss similarities and differences in applicability, strengths and weaknesses and sketch a road towards improved inverse solutions by targeted use, sequential application or a combination of the two methods.

ECGI targeted ablation for persistent AF not responding to pulmonary vein isolation: Results of a two-staged strategy (TARGET AF2).

Background: Mechanisms sustaining persistent atrial fibrillation (AF) remain unclear. Objectives: The study sought to evaluate both the clinical outcomes and response to ablation of potential drivers in patients with recurrent persistent AF recurrence following pulmonary vein isolation (PVI). Methods: A total of 100 patients with persistent AF of <2 years' duration underwent cryoballoon PVI (ECGI phenotyping of persistent AF based on driver burden and distribution to predict response to pulmonary vein isolation). Patients with documented recurrence of atrial arrhythmia within 12 months were recruited and underwent repeat PVI (if needed) followed by ablation of potential drivers (PDs) identified by electrocardiographic imaging (ECGI). PDs were defined as rotational activity >1.5 revolutions or focal activations. Cycle lengths were measured pre- and postablation. The primary outcome was freedom from atrial arrhythmia off antiarrhythmic drugs at 1 year as per guidelines. Results: Of 37 patients recruited, 26 had recurrent AF and underwent ECGI-guided ablation of PDs. An average of 6.4 ± 2.7 PDs were targeted per patient. The mean ablation time targeting PDs was 15.5 ± 6.9 minutes. An ablation response occurred in 20 patients (AF termination in 6, cycle length prolongation ≥10% in 14). At 1 year, 14 (54%) of 26 patients were free from arrhythmia, and 12 (46%) of 26 were off antiarrhythmic drugs. Considering the 96 patients who completed follow-up out of the original cohort of 100 patients undergoing cryoablation in this staged strategy, freedom from arrhythmia at 1 year following the last procedure was 72 (75%) of 96, or 70 (73%) of 96 off antiarrhythmic drugs. Conclusions: In patients with recurrent AF despite PVI, ECGI-guided ablation caused an acute response in a majority with reasonable long-term outcomes.

Quantifying and Visualizing Uncertainty for Source Localization in Electrocardiographic Imaging.

Electrocardiographic imaging (ECGI) presents a clinical opportunity to noninvasively understand the sources of arrhythmias for individual patients. To help increase the effectiveness of ECGI, we provide new ways to visualize associated measurement and modeling errors. In this paper, we study source localization uncertainty in two steps: First, we perform Monte Carlo simulations of a simple inverse ECGI source localization model with error sampling to understand the variations in ECGI solutions. Second, we present multiple visualization techniques, including confidence maps, level-sets, and topology-based visualizations, to better understand uncertainty in source localization. Our approach offers a new way to study uncertainty in the ECGI pipeline.

Electrocardiographic imaging to guide ablation of ventricular arrhythmias and agreement between two different systems.

BACKGROUND AND AIM: A recent study using an epicardial-only electrocardiographic imaging (ECGI), suggests that the agreement of ECGI activation mapping and that of the contact mapping for ventricular arrhythmias (VA) is poor. The aim of this study was to assess the diagnostic value of two endo-epicardial ECGI systems using different cardiac sources and the agreement between them. METHODS: We performed 69 ECGI procedures in 52 patients referred for ablation of VA at our center. One system based on the extracellular potentials was used in 26 patients, the other based on the equivalent double layer model in 9, and both in 17 patients. The first uses up to 224 leads and the second just the 12­lead ECG. The localization of the VA was done using a segmental model of the ventricles. A perfect match (PM) was defined as a predicted location within the same anatomic segment, whereas a near match (NM) as a predicted location within the same segment or a contiguous one. RESULTS: 44 patients underwent ablation, corresponding to 58 ECGI procedures (37 with the first and 21 with the second system). The percentage of PMs and NMs was not significantly different between the two systems, respectively 76% and 95%, p = 0.077, and 97% and 100%, p = 1.000. In 14 patients that underwent ablation and had the ECGI performed with both systems, raw agreement for PMs was 79%, p = 0.250 for disagreement. CONCLUSIONS: ECGI systems were useful to identify the origin of the VAs, and the results were reproducible regardless the cardiac source.

Comparison of dipole-based and potential-based ECGI methods for premature ventricular contraction beat localization with clinical data.

Introduction: Localization of premature ventricular contraction (PVC) origin to guide the radiofrequency ablation (RFA) procedure is one of the prominent clinical goals of non-invasive electrocardiographic imaging. However, the results reported in the literature vary significantly depending on the source model and the level of complexity in the forward model. This study aims to compare the paced and spontaneous PVC localization performances of dipole-based and potential-based source models and corresponding inverse methods using the same clinical data and to evaluate the effects of torso inhomogeneities on these performances. Methods: The publicly available EP solution data from the EDGAR data repository (BSPs from a maximum of 240 electrodes) with known pacing locations and the Bratislava data (BSPs in 128 leads) with spontaneous PVCs from patients who underwent successful RFA procedures were used. Homogeneous and inhomogeneous torso models and corresponding forward problem solutions were used to relate sources on the closed epicardial and epicardial-endocardial surfaces. The localization error (LE) between the true and estimated pacing site/PVC origin was evaluated. Results: For paced data, the median LE values were 25.2 and 13.9 mm for the dipole-based and potential-based models, respectively. These median LE values were higher for the spontaneous PVC data: 30.2-33.0 mm for the dipole-based model and 28.9-39.2 mm for the potential-based model. The assumption of inhomogeneities in the torso model did not change the dipole-based solutions much, but using an inhomogeneous model improved the potential-based solutions on the epicardial-endocardial ventricular surface. Conclusion: For the specific task of localization of pacing site/PVC origin, the dipole-based source model is more stable and robust than the potential-based source model. The torso inhomogeneities affect the performances of PVC origin localization in each source model differently. Hence, care must be taken in generating patient-specific geometric and forward models depending on the source model representation used in electrocardiographic imaging (ECGI).

Investigation into the importance of using natural PVCs and pathological models for potential-based ECGI validation.

Introduction: Premature ventricular contractions (PVCs) are one of the most commonly targeted pathologies for ECGI validation, often through ventricular stimulation to mimic the ectopic beat. However, it remains unclear if such stimulated beats faithfully reproduce spontaneously occurring PVCs, particularly in the case of the R-on-T phenomenon. The objective of this study was to determine the differences in ECGI accuracy when reconstructing spontaneous PVCs as compared to ventricular-stimulated beats and to explore the impact of pathophysiological perturbation on this reconstruction accuracy. Methods: Langendorff-perfused pig hearts (n = 3) were suspended in a human torso-shaped tank, and local hyperkalemia was induced through perfusion of a high-K+ solution (8 mM) into the LAD. Recordings were taken simultaneously from the heart and tank surfaces during ventricular pacing and during spontaneous PVCs (including R-on-T), both at baseline and high K+. Epicardial potentials were reconstructed from torso potentials using ECGI. Results: Spontaneously occurring PVCs were better reconstructed than stimulated beats at baseline in terms of electrogram morphology [correlation coefficient (CC) = 0.74 ± 0.05 vs. CC = 0.60 ± 0.10], potential maps (CC = 0.61 ± 0.06 vs. CC = 0.51 ± 0.12), and activation time maps (CC = 0.86 ± 0.07 vs. 0.76 ± 0.10), though there was no difference in the localization error (LE) of epicardial origin (LE = 14 ± 6 vs. 15 ± 11 mm). High K+ perfusion reduced the accuracy of ECGI reconstructions in terms of electrogram morphology (CC = 0.68 ± 0.10) and AT maps (CC = 0.70 ± 0.12 and 0.59 ± 0.23) for isolated PVCs and paced beats, respectively. LE trended worse, but the change was not significant (LE = 17 ± 9 and 20 ± 12 mm). Spontaneous PVCs were less well when the R-on-T phenomenon occurred and the activation wavefronts encountered a line of block. Conclusion: This study demonstrates the differences in ECGI accuracy between spontaneous PVCs and ventricular-paced beats. We also observed a reduction in this accuracy near regions of electrically inactive tissue. These results highlight the need for more physiologically realistic experimental models when evaluating the accuracy of ECGI methods. In particular, reconstruction accuracy needs to be further evaluated in the presence of R-on-T or isolated PVCs, particularly when encountering obstacles (functional or anatomical) which cause line of block and re-entry.

Understanding repolarization in the intracardiac unipolar electrogram: A long-lasting controversy revisited.

Background: The optimal way to determine repolarization time (RT) from the intracardiac unipolar electrogram (UEG) has been a topic of debate for decades. RT is typically determined by either the Wyatt method or the "alternative method," which both consider UEG T-wave slope, but differently. Objective: To determine the optimal method to measure RT on the UEG. Methods: Seven pig hearts surrounded by an epicardial sock with 100 electrodes were Langendorff-perfused with selective cannulation of the left anterior descending (LAD) coronary artery and submersed in a torso-shaped tank containing 256 electrodes on the torso surface. Repolarization was prolonged in the non-LAD-regions by infusing dofetilide and shortened in the LAD-region using pinacidil. RT was determined by the Wyatt (tWyatt) and alternative (tAlt) methods, in both invasive (recorded with epicardial electrodes) and in non-invasive UEGs (reconstructed with electrocardiographic imaging). tWyatt and tAlt were compared to local effective refractory period (ERP). Results: With contact mapping, mean absolute error (MAE) of tWyatt and tAlt vs. ERP were 21 ms and 71 ms, respectively. Positive T-waves typically had an earlier ERP than negative T-waves, in line with theory. tWyatt -but not tAlt-shortened by local infusion of pinacidil. Similar results were found for the non-invasive UEGs (MAE of tWyatt and tAlt vs. ERP were 30 ms and 92 ms, respectively). Conclusion: The Wyatt method is the most accurate to determine RT from (non) invasive UEGs, based on novel and historical analyses. Using it to determine RT could unify and facilitate repolarization assessment and amplify its role in cardiac electrophysiology.

High-resolution structural-functional substrate-trigger characterization: Future roadmap for catheter ablation of ventricular tachycardia.

Introduction: Patients with ventricular tachyarrhythmias (VT) are at high risk of sudden cardiac death. When appropriate, catheter ablation is modestly effective, with relatively high VT recurrence and complication rates. Personalized models that incorporate imaging and computational approaches have advanced VT management. However, 3D patient-specific functional electrical information is typically not considered. We hypothesize that incorporating non-invasive 3D electrical and structural characterization in a patient-specific model improves VT-substrate recognition and ablation targeting. Materials and methods: In a 53-year-old male with ischemic cardiomyopathy and recurrent monomorphic VT, we built a structural-functional model based on high-resolution 3D late-gadolinium enhancement (LGE) cardiac magnetic resonance imaging (3D-LGE CMR), multi-detector computed tomography (CT), and electrocardiographic imaging (ECGI). Invasive data from high-density contact and pace mapping obtained during endocardial VT-substrate modification were also incorporated. The integrated 3D electro-anatomic model was analyzed off-line. Results: Merging the invasive voltage maps and 3D-LGE CMR endocardial geometry led to a mean Euclidean node-to-node distance of 5 ± 2 mm. Inferolateral and apical areas of low bipolar voltage (<1.5 mV) were associated with high 3D-LGE CMR signal intensity (>0.4) and with higher transmurality of fibrosis. Areas of functional conduction delay or block (evoked delayed potentials, EDPs) were in close proximity to 3D-LGE CMR-derived heterogeneous tissue corridors. ECGI pinpointed the epicardial VT exit at ∼10 mm from the endocardial site of origin, both juxtaposed to the distal ends of two heterogeneous tissue corridors in the inferobasal left ventricle. Radiofrequency ablation at the entrances of these corridors, eliminating all EDPs, and at the VT site of origin rendered the patient non-inducible and arrhythmia-free until the present day (20 months follow-up). Off-line analysis in our model uncovered dynamic electrical instability of the LV inferolateral heterogeneous scar region which set the stage for an evolving VT circuit. Discussion and conclusion: We developed a personalized 3D model that integrates high-resolution structural and electrical information and allows the investigation of their dynamic interaction during arrhythmia formation. This model enhances our mechanistic understanding of scar-related VT and provides an advanced, non-invasive roadmap for catheter ablation.

Non-invasive three-dimensional electrical activation mapping to predict cardiac resynchronization therapy response: site of latest left ventricular activation relative to pacing site.

AIMS: Pacing remote from the latest electrically activated site (LEAS) in the left ventricle (LV) may diminish response to cardiac resynchronization therapy (CRT). We tested whether proximity of LV pacing site (LVPS) to LEAS, determined by non-invasive three-dimensional electrical activation mapping [electrocardiographic Imaging (ECGI)], increased likelihood of CRT response. METHODS AND RESULTS: Consecutive CRT patients underwent ECGI and chest/heart computed tomography 6-24 months of post-implant. Latest electrically activated site and the distance to LVPS (dp) were assessed. Left ventricular end-systolic volume (LVESV) reduction of ≥15% at clinical follow-up defined response. Logistic regression probabilistically modelled non-response; variables included demographics, heart failure classification, left bundle branch block (LBBB), ischaemic heart disease (IHD), atrial fibrillation, QRS duration, baseline ejection fraction (EF) and LVESV, comorbidities, use of CRT optimization algorithm, angiotensin-converting enzyme inhibitor(ACE)/angiotensin-receptor blocker (ARB), beta-blocker, diuretics, and dp. Of 111 studied patients [64 ± 11 years, EF 28 ± 6%, implant duration 12 ± 5 months (mean ± SD), 98% had LBBB, 38% IHD], 67% responded at 10 ± 3 months post CRT-implant. Latest electrically activated sites were outside the mid-to-basal lateral segments in 35% of the patients. dp was 42 ± 23 mm [31 ± 14 mm for responders vs. 63 ± 24 mm non-responders (P < 0.001)]. Longer dp and the lack of use of CRT optimization algorithm were the only independent predictors of non-response [area under the curve (AUC) 0.906]. dp of 47 mm delineated responders and non-responders (AUC 0.931). CONCLUSION: The distance between LV pacing site and latest electrical activation is a strong independent predictor for CRT response. Non-invasive electrical evaluation to characterize intrinsic activation and guide LV lead deployment may improve CRT efficacy.

AF driver detection in pulmonary vein area by electropcardiographic imaging: Relation with a favorable outcome of pulmonary vein isolation.

Pulmonary vein isolation (PVI) is the most successful treatment for atrial fibrillation (AF) nowadays. However, not all AF patients benefit from PVI. In this study, we evaluate the use of ECGI to identify reentries and relate rotor density in the pulmonary vein (PV) area as an indicator of PVI outcome. Rotor maps were computed in a set of 29 AF patients using a new rotor detection algorithm. The relationship between the distribution of reentrant activity and the clinical outcome after PVI was studied. The number of rotors and proportion of PSs in different atrial regions were computed and compared retrospectively in two groups of patients: patients that remained in sinus rhythm 6 months after PVI and patients with arrhythmia recurrence. The total number of rotors obtained was higher in patients returning to arrhythmia after the ablation (4.31 ± 2.77 vs. 3.58 ± 2.67%, p = 0.018). However, a significantly higher concentration of PSs in the pulmonary veins was found in patients that remained in sinus rhythm (10.20 ± 12.40% vs. 5.19 ± 9.13%, p = 0.011) 6 months after PVI. The results obtained show a direct relationship between the expected AF mechanism and the electrophysiological parameters provided by ECGI, suggesting that this technology offers relevant information to predict the clinical outcome after PVI in AF patients.

Tipping the scales of understanding: An engineering approach to design and implement whole-body cardiac electrophysiology experimental models.

The study of cardiac electrophysiology is built on experimental models that span all scales, from ion channels to whole-body preparations. Novel discoveries made at each scale have contributed to our fundamental understanding of human cardiac electrophysiology, which informs clinicians as they detect, diagnose, and treat complex cardiac pathologies. This expert review describes an engineering approach to developing experimental models that is applicable across scales. The review also outlines how we applied the approach to create a set of multiscale whole-body experimental models of cardiac electrophysiology, models that are driving new insights into the response of the myocardium to acute ischemia. Specifically, we propose that researchers must address three critical requirements to develop an effective experimental model: 1) how the experimental model replicates and maintains human physiological conditions, 2) how the interventions possible with the experimental model capture human pathophysiology, and 3) what signals need to be measured, at which levels of resolution and fidelity, and what are the resulting requirements of the measurement system and the access to the organs of interest. We will discuss these requirements in the context of two examples of whole-body experimental models, a closed chest in situ model of cardiac ischemia and an isolated-heart, torso-tank preparation, both of which we have developed over decades and used to gather valuable insights from hundreds of experiments.

Robustness of imageless electrocardiographic imaging against uncertainty in atrial morphology and location.

INTRODUCTION: Electrocardiographic Imaging is a non-invasive technique that requires cardiac Imaging for the reconstruction of cardiac electrical activity. In this study, we explored imageless ECGI by quantifying the errors of using heart meshes with either an inaccurate location inside the thorax or an inaccurate geometry. METHODS: Multiple­lead body surface recordings of 25 atrial fibrillation (AF) patients were recorded. Cardiac atrial meshes were obtained by segmentation of medical images obtained for each patient. ECGI was computed with each patient's segmented atrial mesh and compared with the ECGI obtained under errors in the atrial mesh used for ECGI estimation. We modeled both the uncertainty in the location of the atria inside the thorax by artificially translating the atria inside the thorax and the geometry of the atrial mesh by using an atrial mesh in a reference database. ECGI signals obtained with the actual meshes and the translated or estimated meshes were compared in terms of their correlation coefficients, relative difference measurement star, and errors in the dominant frequency (DF) estimation in epicardial nodes. RESULTS: CC between ECGI signals obtained after translating the actual atrial meshes from the original position by 1 cm was above 0.97. CC between ECGIs obtained with patient specific atrial geometry and estimated atrial geometries was 0.93 ± 0.11. Mean errors in DF estimation using an estimated atrial mesh were 7.6 ± 5.9%. CONCLUSION: Imageless ECGI can provide a robust estimation of cardiac electrophysiological parameters such as activation rates even during complex arrhythmias. Furthermore, it can allow more widespread use of ECGI in clinical practice.

Mechanisms of persistent atrial fibrillation and recurrences within 12 months post-ablation: Non-invasive mapping with electrocardiographic imaging.

Introduction: Catheter ablation of persistent AF has not been consistently successful in terminating AF or preventing arrhythmia recurrences. Non-invasive Electrocardiographic Imaging (ECGI) can help to understand recurrences by mapping the mechanisms of pre-ablation AF and comparing them with the patterns of recurrent arrhythmias in the same patient. Methods: Seventeen persistent AF patients underwent ECGI before their first catheter ablation. Time-domain activation maps and phase progression maps were obtained on the bi-atrial epicardium. Location of arrhythmogenic drivers were annotated on the bi-atrial anatomy. Activation and phase movies were examined to understand the wavefront dynamics during AF. Eight patients recurred within 12 months of ablation and underwent a follow-up ECGI. Driver locations and movies were compared for pre- and post-ablation AF. Results: A total of 243 focal drivers were mapped during pre-ablation AF. 62% of the drivers were mapped in the left atrium (LA). The pulmonary vein region harbored most of the drivers (43%). 35% of the drivers were mapped in the right atrium (RA). 59% (10/17) and 53% (9/17) of patients had repetitive sources in the left pulmonary veins (LPV) and left atrial appendage (LAA), and the lower half of RA, respectively. All patients had focal drivers. 29% (5/17) of patients had macro-reentry waves. 24% (4/17) of patients had rotors. Activation patterns during persistent AF varied from single macro-reentry to complex activity with multiple simultaneous wavefronts in both atria, resulting in frequent wave collisions. A total of 76 focal driver activities were mapped in 7/8 patients during recurrence. 59% of the post-ablation AF drivers were mapped in the LA. The pulmonary vein region harbored 50% of total drivers. 39% of sources were mapped in the RA. AF complexity remained similar post-ablation. 58% (44/76) of pre-ablation sources persisted during recurrence. 38% (3/8) of patients had macro-reentry and one patient had rotors. Conclusion: ECGI provides patient-specific information on mechanisms of persistent AF and recurrent arrhythmia. More than half pre-ablation sources repeated during post-ablation recurrence. This study provides direct evidence for drivers that persist days and months after the ablation procedure. Patient-tailored bi-atrial ablation is needed to successfully target persistent AF and prevent recurrence. ECGI can potentially predict recurrence and assist in choice of therapy.

ECG-I phenotyping of persistent AF based on driver burden and distribution to predict response to pulmonary vein isolation (PHENOTYPE-AF).

BACKGROUND: This prospective trial sought to phenotype persistent atrial fibrillation (AF) based on AF mechanisms using electrocardiographic imaging (ECGI) mapping to determine whether this would predict long-term freedom from arrhythmia after pulmonary vein isolation (PVI). METHODS: Patients with persistent AF of <2 years duration underwent cryoballoon PVI. ECGI mapping was performed before PVI to determine potential drivers (PDs) defined as rotational activations completing ≥1.5 revolutions or focal activations. The coprimary endpoint was the association between (1) PD burden (defined as the number of PD occurrences) and (2) PD distribution (defined as the number of segments on an 18-segment model of the atria harboring PDs) with freedom from arrhythmia at 1-year follow up. RESULTS: Of 100 patients, 97 completed follow up and 52 (53.6%) remained in sinus rhythm off antiarrhythmic drugs. Neither PD burden nor PD distribution predicted freedom from arrhythmia (hazard ratio [HR]: 1.01, 95% confidence interval [CI]: 0.99-1.03, p = .164; and HR: 1.04, 95% CI: 0.91-1.17, p = .591, respectively). Otherwise, the burden of rotational PDs, rotational stability, and the burden of PDs occurring at the pulmonary veins and posterior wall all failed to predict arrhythmia recurrence (all p > .10). CONCLUSIONS: AF mechanisms as determined using ECGI mapping do not predict outcomes after PVI for persistent AF. Further studies using different methodologies to characterize AF mechanisms are warranted (NCT03394404).

A fast algorithm for spatiotemporal signals recovery using arbitrary dictionaries with application to electrocardiographic imaging.

This paper presents a method to solve a linear regression problem subject to grouplassoand ridge penalisation when the model has a Kronecker structure. This model was developed to solve the inverse problem of electrocardiography using sparse signal representation over a redundant dictionary or frame. The optimisation algorithm was performed using the block coordinate descent and proximal gradient descent methods. The explicit computation of the underlying Kronecker structure in the regression was avoided, reducing space and temporal complexity. We developed an algorithm that supports the use of arbitrary dictionaries to obtain solutions and allows a flexible group distribution.

Assessment of wave front activation duration and speed across the right ventricular outflow tract using electrocardiographic imaging as predictors of the origin of the premature ventricular contractions: A validation study.

AIMS: Evaluate right ventricular outflow tract (RVOT) activation duration (AD) and speed, invasively and with the electrocardiographic imaging (ECGI), as predictors of the origin of the PVCs, validating the ECGI. METHODS: 18 consecutive patients, 8 males, median age 55 (35-63) years that underwent ablation of PVCs with inferior axis and had ECGI performed before ablation. Isochronal activation maps of the RVOT in PVC were obtained with the ECGI and invasively. Total RVOT AD was measured as the time between earliest and latest activated region, and propagation speed by measuring the area of the first 10 ms of activation. Cut-off values for AD, activation speed and number of 10 ms isochrones to predict the origin of the PVCs, were obtained with the ROC curve analysis. Agreement between methods was done with Pearson correlation test and Bland-Altman plot. RESULTS: PVCs originated from the RVOT in 11 (61%) patients. The stronger predictor of PVC origin was the AD. The median AD in PVCs from RVOT was significantly longer than from outside the RVOT, both with ECGI and invasively, respectively 62 (58-73) vs 37 (33-40) ms, p < 0.0001 and 68 (60-75) vs 35 (29-41) ms, p < 0.0001. Agreement between the two methods was good (r = 0.864, p < 0.0001). The cut-off value of 43 ms for AD measured with ECGI predicted the origin of the PVCs with a sensitivity and specificity of 100%. CONCLUSIONS: We found good agreement between ECGI and invasive map. The AD measured with ECGI was the best predictor of the origin of the PVCs.