Accuracy of endocardial abnormal electrogram characterization using a 17-AHA-segmental late boundary and voltage-dependent sensitivity annotation for ventricular tachycardia ablation

Abstract Background Substrate-based catheter ablation of ventricular tachycardia (VT) has become the mainstay therapy for patients with scar-related VT. Correct identification and timing of abnormal near-field EGMs and discerning it from far-field EGMs, is key for procedural success. The novel CARTO™ Late Activation Mapping (LAM) module provides fast and accurate annotation of near-field EGMs including late abnormal ventricular activation. For the algorithm to succeed, a late boundary (LB) annotation line should be positioned immediately behind the normal near-field EGM, however, since the timing of normal local near-field activation varies greatly throughout the endocardium, there is currently no consensus for the optimal LB positioning. We hypothesized that 17-AHA segmental annotation of the endocardial LB followed by scar-dependent sensitivity settings, will improve the accuracy of the near-field EGM characterization. Purpose To evaluate the accuracy of endocardial abnormal EGM characterization using a 17-AHA-segmental late boundary and voltage-dependent sensitivity annotation as compared to conventional mid-QRS LB positioning. Methods Five high-resolution substrate voltage maps were obtained from 5 patients (80% male, 68±7 years old, 80% ischemic cardiomyopathy) that underwent a catheter-based ablation for scar-related VT. A personalized CT-derived anatomical reconstruction of the 17-segment AHA model was co-registered offline with the electroanatomic voltage map, using ADAS3D software. Per segment, individual LB timings were set at the highest sensitivity. A gold standard annotation map was created by two independent experts after manual scrutiny of individual EGMs. Next, the expert map was compared to automatic maps created from segmental LB and mid-QRS LB positions at normal, high, highest or mixed (normal/high or normal/highest) sensitivities, focusing on EGM voltage and activation accuracy. Results A mean of 2041±1028 points per map were analyzed. Correct correlation of EGM annotation was found on average in 91% (activation) and 81% (voltage) for all segmental LB positioned maps (segLB), and in 83% (activation) and 77% (voltage) for all mid-QRS LB positioned maps (mid-QRSLB). The highest correlation with expert map for both activation and voltage annotation was found in the mixed sensitivity normal/highest map with segmental LB positioning (activation 98%, voltage 88%). The correlation on activation was significantly superior in the segLB map when compared to the normal sensitivity maps (p=0.0008 for mid-QRSLB and p=0.02 for segLB). For correlation on voltage, the segLBmap with mixed sensitivity was significantly superior compared to three mid-QRSLB maps at normal (p=0.04), high and highest (p=0.01) sensitivity. Conclusion Individualized, 17-AHA-segmental late boundary and voltage-dependent sensitivity annotation provides a possible accurate and clinically-relevant framework for substrate assessment. Prospective validation is needed.