Automatic identification of VT substrate in the era of ultrahigh‐density mapping: Do humans or machines emerge victoriously?

The legendary story of John Henry is the classic human versus machine tale set in 1800s in West Virginia, United States. John Henry worked on the railroad construction for the Westward expansion of America. He was of legendary size and strength, over 6‐feet tall, and able to drive a rail spike with a single swing of his 20‐pound hammer. As the legend goes, John Henry's prowess was measured in a race against the newly developed steam‐powered rock drilling machine. The race was set to see whether human or machine made the most progress in drilling. On that day, John Henry emerged victorious over the machine only to die in victory with hammer in hand. This epic story, although not quite the same, carries some parallels to the contemporary challenges that face ventricular tachycardia (VT) ablation in the setting of structural heart disease (SHD)—a disease which poses one of the greatest challenges in electrophysiology, where the comparison is now made between automatic versus manual annotation during substrate mapping. SHD‐related VT is predominantly re‐entrant in mechanism, in or around ischemic or nonischemic scar. Catheter ablation (CA) is a Class I recommendation for the drug‐refractory treatment. Identification of VT isthmii is critical for the efficacy of CA. Historically, activation mapping, followed by entrainment and termination of VT with ablation has allowed identification of VT isthmii and formed the basis for SHD‐related VT ablation. However, unreliable inducibility, conversion of VT to another, nonsustainability of VT to permit activation/entrainment mapping and the hemodynamic instability during VT, meant that alternative mapping strategies were desirable. This formed the basis for the evolution of substrate mapping. Substrate mapping allows identification of putative VT isthmii by using surrogate markers in stable sinus or paced rhythm representing slow, discontinuous conduction in and around scar. Substrate mapping has improved the feasibility of VT ablation by avoiding the deleterious consequences of prolonged episodes of sustained VT to permit activation/entrainment mapping. One such surrogate marker, termed local abnormal ventricular activities (LAVAs), represent regions of delayed conduction and are defined as sharp, high‐frequency ventricular potentials, which are distinct from the far‐field electrogram and often display fractionated, double or multiple components, separated by low‐amplitude signals or an isoelectric interval. Typically, these signals have been annotated and tagged on the electroanatomic map manually, because automated algorithms are generally limited in their ability to differentiate the delayed multiple component signals within the scar from the initial far‐ field component of the electrogram. Advances in multielectrode mapping catheters and electroanatomic mapping systems now allow rapid collection of a large volume of intracardiac electrograms, which poses a significant challenge to this real‐time manual electrogram annotation. The Lumipoint algorithm (Boston Scientific) can annotate signals throughout the entire mapping window, as opposed to a peak signal and is therefore able to identify LAVAs rapidly. It is plausible to suggest that the automated annotation of LAVAs may improve procedural efficiency and potentially, the consistency of point annotation and rapid delineation of VT isthmii. In this study, Nakatani et al. describe 100 patients with SHD (ischemic [n = 75] and nonischemic [n = 25]) related VT undergoing electroanatomic mapping and CA, using the ultrahigh‐ density Rhythmia system (Boston Scientific). The study aimed to determine if the Lumipoint algorithm is accurate in detecting LAVAs. The automatic identification of LAVAs was performed retrospectively using the algorithm features to detect late potentials (LP), fragmented potentials (FP), and double potentials (DP), this was directly compared to the real‐time manual electrogram annotation of LAVAs and sites of ablation, performed during each procedure. Mapping was performed using the Intellamap Orion catheter (Boston Scientific) in the left ventricle (83%), right ventricle (8%), and epicardium (9%). The average number of points collected per map were 9976 ± 7477 over 31 ± 11 min. Overall, the three Lumipoint features complemented each other and correctly identified LAVAs equally or better than manual annotation in 79% of patients (64% equally and 15% better). Conversely, there were 18% of patients in whom LAVAs were missed by Lumipoint but identified by manual annotation. These discrepancies were predominantly due to Lumipoint detecting very low amplitude LAVAs better than manual annotation but missing fragmented signals with few activation components