Electrocardiographic imaging to guide VT ablation in structural heart disease

Abstract Introduction The efficacy of ventricular tachycardia (VT) ablation in patients (pts) with structural heart disease (SHD) remains sub-optimal, due to complex circuits and inability to map the clinical VT. Electrocardiographic imaging (ECGi) may allow to map the clinical VT, facilitating procedural planning. Its use in this specific setting has not been validated. Purpose To evaluate the accuracy of EGCi in predicting the area of interest for VT ablation, and to compare its accuracy with multidetector computed tomography (MDCT) and late gadolinium enhancement cardiac magnetic resonance (LE-CMR). Methods This prospective single-center study included pts with SHD referred for VT ablation. All pts underwent pre-procedural MDCT, and those without cardiac implanted devices also underwent LE-CMR (55%). The MDCT area of interest was defined as the region with a wall thickness ≤ 6mm. The LE-CMR area of interest was defined as the region with pixel signal intensity (PSI) ≥40±5%. Heterogeneous tissue corridors were predicted in PSI maps, and their areas were measured. Noninvasive programmed stimulation was performed using a 252-electrode noninvasive 3D mapping system (CardioInsight™) under mild sedation after a 72h anti-arrhythmic drug suspension. The ECGi area of interest was identified as the earliest activated area (initial 20±5ms since the first dV/dT). MDCT, LE-CMR, and ECGi maps were co-registered and integrated into the electroanatomical mapping (EAM) system for the VT ablation procedure. The area of interest predicted by each pre-procedural planning method was compared to the location of local abnormal ventricular activities (LAVA). In pts in whom the clinical VT was mapped, the VT exit site location was also analyzed. Results We studied 20 pts (67±14 years, 90% male, 50% ischemic SHD, LVEF 37±11%). At least 1 sustained VT was induced during the ECGi study in all patients. The median concordance between ECGi and EAM for the delineation of the area of interest for ablation was 61.6% [24.1-73.1], see Fig.1. ECGi correctly predicted the segments displaying LAVAs in 95% of pts, with a median discordance of 8mm in the remaining 5%. Among the various methods, ECGi was the most accurate in predicting the segment of interest for VT ablation, presenting a sensitivity of 92.5±24.5%, specificity of 98.7±2.7%, and accuracy of 98.2±2.8%, p<0.01 (see Fig.2). ECGi analysis resulted in a more restricted area of interest (11.6±6.9 cm²) compared to MDCT (67.5±53.3 cm²), LE-CMR (55.9±17.4 cm²), and LE-CMR corridors (20.5±10.4 cm²), p<0.01. During the ablation procedure, 17 VTs were mapped in 12 pts. We found an 88% overlap between the ECGi area of interest and the EAM-confirmed VT exit site. Conclusions ECGi is a valuable resource for pre-procedural planning in pts with SHD undergoing VT ablation, on top of advanced imaging modalities, accurately predicting the location of LAVAs and the VT exit site.