Description

Over the last decade, radiofrequency catheter ablation (RFCA) has become an established treatment for ventricular arrhythmias (VA). RFCA uses electromagnetic energy that transforms into heat upon delivery into the myocardium and irreversibly damages the viable myocytes, causing the loss of cellular excitability. Irreversible loss of cellular excitability generally occurs at temperatures exceeding 50°C, while at lower temperatures, the damage is not permanent and myocytes can recover excitability, leading to VA recurrences. Due to the challenging nature of visualizing lesion formation in real time and ensuring an effective transmural lesion, different surrogate measures of lesion quality have been used. The fall in local impedance during ablation has been considered as a first marker of the direct effect of ablation in cardiac tissue but the generator impedance drop does not correlate well with lesion size. First, large impedance drops can indicate impeding steam pop without effective lesion formation. Second scar tissue carries a lower impedance than healthy tissue due to their higher water/collagen content and make impedance drops less reliable.

One of the major determinants of lesion formation is an adequate contact between the tip of the catheter and the myocardial surface. A first major technological advancement in ablation catheters was the development of sensors at the distal tip capable of monitoring contact (contact force, CF). A recent ablation marker is the Force-Time-Integral (FTI), which multiplies CF by radiofrequency application duration. Limitations in this ablation parameter are the exclusion of maximal power settings being delivered and the assumption that a single target FTI is required in all myocardial segments with varying wall thickness and underlying substrate. Also for prolonged energy deliveries, the contribution of radiofrequency application duration is proportionally less important in lesion creation than CF. To overcome some of these limitations, the Ablation Index (AI) was introduced. This is a variable incorporating power delivery in its formula and combining it with CF and time in a weighted equation. It has shown to be a more precise estimation of lesion depth and quality in animal models and humans than FTI, time alone or impedance drop.

AI guidance has previously been shown to improve outcomes in atrial and ventricular ablation in patients with premature ventricular complexes (PVC). However research on outcomes following AI-guidance for VT ablation specifically in patients with structural disease and prior myocardial infarction remains sparse, with mainly research conducted in ex-vivo porcine or canine models. In theory, use of AI to guide ablation in this subpopulation of VT patients may shorten procedure time and possibly improve procedural safety in comparison to ablation guided by less reliable conventional parameters or fixed energy application durations. First pilot studies assessing AI-guided VT ablations in patients with structural heart disease provided some observational insights on procedural parameters but our study is the first randomized controlled trial testing for the superiority of an AI-guided approach regarding procedural duration.