Accuracy of standard bipolar amplitude voltage thresholds to identify late potential channels in ventricular tachycardia ablation

Autonomic neuro-cardiac profile of electrical, structural and neuronal remodeling in myocardial infarction-induced heart failure

Aims

Heart failure is a clinical syndrome typified by abnormal autonomic tone, impaired ventricular function, and increased arrhythmic vulnerability. This study aims to examine electrophysiological, structural and neuronal remodeling following myocardial infarction in a rabbit heart failure model to establish its neuro-cardiac profile.

Methods and results

Weight-matched adult male New Zealand White rabbits (3.2 ± 0.1 kg, n = 25) were randomized to have coronary ligation surgeries (HF group, n = 13) or sham procedures (SHM group, n = 12). Transthoracic echocardiography was performed six weeks post-operatively. On week 8, dual-innervated Langendorff-perfused heart preparations were set up for terminal experiments. Seventeen hearts (HF group, n = 10) underwent ex-vivo cardiac MRI. Twenty-two hearts (HF group, n = 7) were examined histologically. Electrical remodeling and abnormal autonomic profile were evident in HF rabbits with exaggerated sympathetic and attenuated vagal effect on ventricular fibrillation threshold, ventricular refractoriness and restitution curves, in addition to increased spatial restitution dispersion. Histologically, there was significant neuronal enlargement at the heart hila and conus arteriosus in HF. Structural remodeling was characterized by quantifiable myocardial scarring, enlarged left ventricles, altered ventricular geometry and impaired contractility.

Conclusion

In an infarct-induced rabbit heart failure model, extensive structural, neuronal and electrophysiological remodeling in conjunction with abnormal autonomic profile provide substrates for ventricular arrhythmias.

Computer-aided detection of arrhythmogenic sites in post-ischemic ventricular tachycardia

Nowadays, catheter-based ablation in patients with post-ischemic ventricular tachycardia (VT) is performed in arrhythmogenic sites identified by electrophysiologists by visual inspection during electroanatomic mapping. This work aims to present the development of machine learning tools aiming at supporting clinicians in the identification of arrhythmogenic sites by exploiting innovative features that belong to different domains. This study included 1584 bipolar electrograms from nine patients affected by post-ischemic VT. Different features were extracted in the time, time scale, frequency, and spatial domains and used to train different supervised classifiers. Classification results showed high performance, revealing robustness across the different classifiers in terms of accuracy, true positive, and false positive rates. The combination of multi-domain features with the ensemble tree is the most effective solution, exhibiting accuracies above 93% in the 10-time 10-fold cross-validation and 84% in the leave-one-subject-out validation. Results confirmed the effectiveness of the proposed features and their potential use in a computer-aided system for the detection of arrhythmogenic sites. This work demonstrates for the first time the usefulness of supervised machine learning for the detection of arrhythmogenic sites in post-ischemic VT patients, thus enabling the development of computer-aided systems to reduce operator dependence and errors, thereby possibly improving clinical outcomes.

Solving the Reach Problem: A Review of Present and Future Approaches for Addressing Ventricular Arrhythmias Arising from Deep Substrate

Ventricular tachycardia (VT) is a significant cause of morbidity and mortality in patients with ischaemic and non-ischaemic cardiomyopathies. In most patients, the primary strategy of VT catheter ablation is based on the identification of critical components of reentry circuits and modification of abnormal substrate which can initiate reentry. Despite technological advancements in catheter design and improved ability to localise abnormal substrates, putative circuits and site of origins of ventricular arrhythmias (VAs), current technologies remain inadequate and durable success may be elusive when the critical substrate is deep or near to critical structures that are at risk of collateral damage. In this article, we review the available and potential future non-surgical investigational approaches for treatment of VAs and discuss the viability of these modalities.

Ventricular Tachycardia Ablation Guided by Functional Substrate Mapping: Practices and Outcomes

Catheter ablation of ventricular tachycardia has demonstrated its important role in the treatment of ventricular tachycardia in patients with structural cardiomyopathy. Conventional mapping techniques used to define the critical isthmus, such as activation mapping and entrainment, are limited by the non-inducibility of the clinical tachycardia or its poor hemodynamic tolerance. To overcome these limitations, a voltage mapping strategy based on bipolar electrograms peak to peak analysis was developed, but a low specificity (30%) for VT isthmus has been described with this approach. Functional mapping strategy relies on the analysis of the characteristics of the electrograms but also their propagation patterns and their response to extra-stimulus or alternative pacing wavefronts to define the targets for ablation. With this review, we aim to summarize the different functional mapping strategies described to date to identify ventricular arrhythmic substrate in patients with structural heart disease.