Noninvasive assessment of the ventricular arrhythmogenic substrate using electrocardiographic imaging during sinus rhythm: The NIAVAS study

BACKGROUND: Late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) identifies structural properties associated with ventricular tachycardia (VT) but lacks functional information. Noninvasive identification of slow conduction regions using electrocardiographic imaging (ECGI) could complement LGE-CMR to aid VT risk stratification. OBJECTIVE: This study aimed to evaluate the relationship between ventricular arrhythmogenic substrate and regional ECGI markers during sinus rhythm in patients with ischemic cardiomyopathy (ICM). METHODS: Seventy-two patients were included: 29 with ICM evidenced by LGE-CMR referred for VT ablation, 17 with ICM with implantable cardioverter-defibrillator for primary prevention without documented VT, and 26 controls. ECGI-derived regional activation dispersion (rAD) and pseudo-regional conduction velocity (pseudo-rCV) were analyzed and compared between scarred and healthy regions based on LGE, and between patients with ICM with and without previous VT. In a subgroup with electroanatomic mapping (n = 16), deceleration zones were correlated with ECGI. RESULTS: Scarred regions showed higher rAD (46.3 ± 2.2 vs 30.1 ± 1.7 ms, P < .001) and reduced pseudo-rCV (149.9 ± 3.0 vs 165.7 ± 2.4 cm/s, P < .001) than healthy regions. In the subgroup with sinus rhythm electroanatomic mapping, regions containing deceleration zones showed increased rAD (64.9 ± 5.4 vs 43.1 ± 3.1 ms, P < .001), and ECGI identified 70.4% of those zones. At the patient level, the mean of the 3 regions with the highest activation dispersion differentiated patients with ICM with and without previous VT (rAD ≥60.0 ms, sensitivity 75.9%, area under the curve [AUC] 0.75, P = .005) and identified patients with ICM from controls (rAD ≥39.5 ms, AUC 0.93). CONCLUSION: This study introduces a novel regional ECGI methodology demonstrating that rAD identifies abnormalities linked to arrhythmogenic substrate and could help identify patients at risk of VT. These findings highlight ECGI's potential as a complementary tool to LGE-CMR.