The Dutch Idiopathic Ventricular Fibrillation Registry: progress report on the quest to identify the unidentifiable.

BACKGROUND: Idiopathic ventricular fibrillation (iVF) is a rare cause of sudden cardiac arrest and, by definition, a diagnosis of exclusion. Due to the rarity of the disease, previous and current studies are limited by their retrospective design and small patient numbers. Even though the incidence of iVF has declined owing to the identification of new disease entities, an important subgroup of patients remains. AIM: To expand the existing Dutch iVF Registry into a large nationwide cohort of patients initially diagnosed with iVF, to reveal the underlying cause of iVF in these patients, and to improve arrhythmia management. METHODS: The Dutch iVF Registry includes sudden cardiac arrest survivors with an initial diagnosis of iVF. Clinical data and outcomes are collected. Outcomes include subsequent detection of a diagnosis other than 'idiopathic', arrhythmia recurrence and death. Non-invasive electrocardiographic imaging is used to investigate electropathological substrates and triggers of VF. RESULTS: To date, 432 patients have been included in the registry (median age at event 40 years (interquartile range 28-52)), 61% male. During a median follow-up of 6 (2-12) years, 38 patients (9%) received a diagnosis other than 'idiopathic'. Eleven iVF patients were characterised with electrocardiographic imaging. CONCLUSION: The Dutch iVF Registry is currently the largest of its kind worldwide. In this heterogeneous population of index patients, we aim to identify common functional denominators associated with iVF. With the implementation of non-invasive electrocardiographic imaging and other diagnostic modalities (e.g. echocardiographic deformation, cardiac magnetic resonance), we advance the possibilities to reveal pro-fibrillatory substrates.

Support vector machine-based assessment of the T-wave morphology improves long QT syndrome diagnosis.

AIMS: Diagnosing long QT syndrome (LQTS) is challenging due to a considerable overlap of the QTc-interval between LQTS patients and healthy controls. The aim of this study was to investigate the added value of T-wave morphology markers obtained from 12-lead electrocardiograms (ECGs) in diagnosing LQTS in a large cohort of gene-positive LQTS patients and gene-negative family members using a support vector machine. METHODS AND RESULTS: A retrospective study was performed including 688 digital 12-lead ECGs recorded from genotype-positive LQTS patients and genotype-negative relatives at their first visit. Two models were trained and tested equally: a baseline model with age, gender, RR-interval, QT-interval, and QTc-intervals as inputs and an extended model including morphology features as well. The best performing baseline model showed an area under the receiver-operating characteristic curve (AUC) of 0.821, whereas the extended model showed an AUC of 0.901. Sensitivity and specificity at the maximal Youden's indexes changed from 0.694 and 0.829 with the baseline model to 0.820 and 0.861 with the extended model. Compared with clinically used QTc-interval cut-off values (>480 ms), the extended model showed a major drop in false negative classifications of LQTS patients. CONCLUSION: The support vector machine-based extended model with T-wave morphology markers resulted in a major rise in sensitivity and specificity at the maximal Youden's index. From this, it can be concluded that T-wave morphology assessment has an added value in the diagnosis of LQTS.

Bariatric surgery partially reverses subclinical proarrhythmic structural, electrophysiological, and autonomic changes in obesity.

BACKGROUND: Obesity confers higher risks of cardiac arrhythmias. The extent to which weight loss reverses subclinical proarrhythmic adaptations in arrhythmia-free obese individuals is unknown. OBJECTIVE: The purpose of this study was to study structural, electrophysiological, and autonomic remodeling in arrhythmia-free obese patients and their reversibility with bariatric surgery using electrocardiographic imaging (ECGi). METHODS: Sixteen arrhythmia-free obese patients (mean age 43 ± 12 years; 13 females; BMI 46.7 ± 5.5 kg/m2) had ECGi pre-bariatric surgery, of whom 12 had ECGi postsurgery (BMI 36.8 ± 6.5 kg/m2). Sixteen age- and sex-matched lean healthy individuals (mean age 42 ± 11 years; BMI 22.8 ± 2.6 kg/m2) acted as controls and had ECGi only once. RESULTS: Obesity was associated with structural (increased epicardial fat volumes and left ventricular mass), autonomic (blunted heart rate variability), and electrophysiological (slower atrial conduction and steeper ventricular repolarization gradients) remodeling. After bariatric surgery, there was partial structural reverse remodeling, with a reduction in epicardial fat volumes (68.7 cm3 vs 64.5 cm3; P = .0010) and left ventricular mass (33 g/m2.7 vs 25 g/m2.7; P < .0005). There was also partial electrophysiological reverse remodeling with a reduction in mean spatial ventricular repolarization gradients (26 mm/ms vs 19 mm/ms; P = .0009), although atrial activation remained prolonged. Heart rate variability, quantified by standard deviation of successive differences in R-R intervals, was also partially improved after bariatric surgery (18.7 ms vs 25.9 ms; P = .017). Computational modeling showed that presurgery obese hearts had a larger window of vulnerability to unidirectional block and had an earlier spiral-wave breakup with more complex reentry patterns than did postsurgery counterparts. CONCLUSION: Obesity is associated with adverse electrophysiological, structural, and autonomic remodeling that is partially reversed after bariatric surgery. These data have important implications for bariatric surgery weight thresholds and weight loss strategies.

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.

The effect of interpolating low amplitude leads on the inverse reconstruction of cardiac electrical activity.

Electrocardiographic imaging is an imaging modality that has been introduced recently to help in visualizing the electrical activity of the heart and consequently guide the ablation therapy for ventricular arrhythmias. One of the main challenges of this modality is that the electrocardiographic signals recorded at the torso surface are contaminated with noise from different sources. Low amplitude leads are more affected by noise due to their low peak-to-peak amplitude. In this paper, we have studied 6 datasets from two torso tank experiments (Bordeaux and Utah experiments) to investigate the impact of removing or interpolating these low amplitude leads on the inverse reconstruction of cardiac electrical activity. Body surface potential maps used were calculated by using the full set of recorded leads, removing 1, 6, 11, 16, or 21 low amplitude leads, or interpolating 1, 6, 11, 16, or 21 low amplitude leads using one of the three interpolation methods - Laplacian interpolation, hybrid interpolation, or the inverse-forward interpolation. The epicardial potential maps and activation time maps were computed from these body surface potential maps and compared with those recorded directly from the heart surface in the torso tank experiments. There was no significant change in the potential maps and activation time maps after the removal of up to 11 low amplitude leads. Laplacian interpolation and hybrid interpolation improved the inverse reconstruction in some datasets and worsened it in the rest. The inverse forward interpolation of low amplitude leads improved it in two out of 6 datasets and at least remained the same in the other datasets. It was noticed that after doing the inverse-forward interpolation, the selected lambda value was closer to the optimum lambda value that gives the inverse solution best correlated with the recorded one.

Noninvasive detection of spatiotemporal activation-repolarization interactions that prime idiopathic ventricular fibrillation.

A comprehensive understanding of the interaction between triggers and electrical substrates leading to ventricular fibrillation (VF) and sudden cardiac arrest is lacking, and electrical substrates are difficult to detect and localize with current clinical tools. Here, we created repolarization time (RT) dispersion by regional drug infusion in perfused explanted human (n = 1) and porcine (n = 6) hearts and in a computational model of the human ventricle. Arrhythmia induction was tested with a single ventricular extrastimulus applied at the early or late RT region. Arrhythmias could only be induced from early RT regions. Vulnerability to VF increased with RT gradient steepness and with larger areas of early RT, but not with markers on the body-surface electrocardiogram. Noninvasive electrocardiographic imaging was performed in survivors of idiopathic VF (n = 11), patients with frequent premature ventricular complexes (PVCs) but no history of sudden cardiac arrest (n = 7), and controls (n = 10). In survivors of idiopathic VF, RT gradients were steeper than in controls, without differences in the clinical electrocardiogram, consistent with the ex vivo results. Patients with idiopathic VF also showed local myocardial regions with distinctly early-versus-late RT that were more balanced in size than in controls. Premature beats originated more often from the early RT regions in idiopathic VF survivors than in patients with frequent PVCs only. Thus, idiopathic VF emerges from the spatiotemporal interaction of a premature beat from an early-repolarization region with critical repolarization dispersion in that region. Electrocardiographic imaging can uncover the co-occurrence of these abnormalities.