Substrate-based approach for ventricular tachycardia in structural heart disease: Tips for mapping and ablation

Catheter ablation of ventricular tachycardia: strategies to improve outcomes

Catheter ablation of ventricular arrhythmias has evolved considerably since it was first described more than 3 decades ago. Advancements in understanding the underlying substrate, utilizing pre-procedural imaging, and evolving ablation techniques have improved the outcomes of catheter ablation. Ensuring safety and efficacy during catheter ablation requires adequate planning, including analysis of the 12 lead ECG and appropriate pre-procedural imaging. Defining the underlying arrhythmogenic substrate and disease eitology allow for the developed of tailored ablation strategies, especially for patients with non-ischemic cardiomyopathies. During ablation, the type of anesthesia can affect VT induction, the quality of the electro-anatomic map, and the stability of the catheter during ablation. For high risk patients, appropriate selection of hemodynamic support can increase the success of VT ablation. For patients in whom VT is hemodynamically unstable or difficult to induce, substrate modification strategies can aid in safe and successful ablation. Recently, there has been an several advancements in substrate mapping strategies that can be used to identify and differentiate local late potentials. The incorporation of high-definition mapping and contact-sense technologies have both had incremental benefits on the success of ablation procedures. It is crucial to harness newer technology and ablation strategies with the highest level of peri-procedural safety to achieve optimal long-term outcomes in patients undergoing VT ablation.

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.

Spectral characterisation of ventricular intracardiac potentials in human post-ischaemic bipolar electrograms

Abnormal ventricular potentials (AVPs) are frequently referred to as high-frequency deflections in intracardiac electrograms (EGMs). However, no scientific study performed a deep spectral characterisation of AVPs and physiological potentials in real bipolar intracardiac recordings across the entire frequency range imposed by their sampling frequency. In this work, the power contributions of post-ischaemic physiological potentials and AVPs, along with some spectral features, were evaluated in the frequency domain and then statistically compared to highlight specific spectral signatures for these signals. To this end, 450 bipolar EGMs from seven patients affected by post-ischaemic ventricular tachycardia were retrospectively annotated by an experienced cardiologist. Given the high variability of the morphologies observed, three different sub-classes of AVPs and two sub-categories of post-ischaemic physiological potentials were considered. All signals were acquired by the CARTO® 3 system during substrate-guided catheter ablation procedures. Our findings indicated that the main frequency contributions of physiological and pathological post-ischaemic EGMs are found below 320 Hz. Statistical analyses showed that, when biases due to the signal amplitude influence are eliminated, not only physiological potentials show greater contributions below 20 Hz whereas AVPs demonstrate higher spectral contributions above ~ 40 Hz, but several finer differences may be observed between the different AVP types.

Use of the inverse solution guidance algorithm method for RF ablation catheter guidance

INTRODUCTION

We previously introduced the inverse solution guidance algorithm (ISGA) methodology using a Single Equivalent Moving Dipole model of cardiac electrical activity to localize both the exit site of a re-entrant circuit and the tip of a radiofrequency (RF) ablation catheter. The purpose of this study was to investigate the use of ISGA for ablation catheter guidance in an animal model.

METHODS

Ventricular tachycardia (VT) was simulated by rapid ventricular pacing at a target site in eleven Yorkshire swine. The ablation target was established using three different techniques: a pacing lead placed into the ventricular wall at the mid-myocardial level (Type-1), an intracardiac mapping catheter (Type-2), and an RF ablation catheter placed at a random position on the endocardial surface (Type-3). In each experiment, one operator placed the catheter/pacing lead at the target location, while another used the ISGA system to manipulate the RF ablation catheter starting from a random ventricular location to locate the target.

RESULTS

The average localization error of the RF ablation catheter tip was 0.31 ± 0.08 cm. After analyzing approximately 35 cardiac cycles of simulated VT, the ISGA system's accuracy in locating the target was 0.4 cm after four catheter movements in the Type-1 experiment, 0.48 cm after six movements in the Type-2 experiment, and 0.67 cm after seven movements in the Type-3 experiment.

CONCLUSION

We demonstrated the feasibility of using the ISGA method to guide an ablation catheter to the origin of a VT focus by analyzing a few beats of body surface potentials without electro-anatomic mapping.