Non-invasive identification of ventricular deceleration zones using electrocardiographic imaging

EP Europace Journal

23 May 2025
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ESC Journals

Abstract

AbstractBackground

Catheter ablation is the most effective technique for treating ventricular tachycardia (VT). However, accurately identifying target regions is challenging. The gold standard relies on finding deceleration zones (DZs) through invasive isochronal late activation mapping (ILAM), a complex, time-consuming process. Using simultaneous, non-invasive electrocardiographic imaging (ECGI) could aid in pre-procedural planning and accelerate DZ identification.

Purpose

To analyse the correlation between non-invasive conduction deceleration markers and DZs assessed during VT catheter ablation.

Methods

Seventy-one consecutive patients (63±12 years, 89% male, left ventricular ejection fraction: 32±10%, non-ischemic: 35%) referred for VT ablation were included in the study. Simultaneous electroanatomical mapping (EAM) and ECGI were performed throughout the procedure for both techniques during SR (n=38), RV pacing at CL 600ms (S1 protocol, n=70), and VT (n=65). Ventricles were segmented into 15 regions (6 in the right and 9 in the left), identifying those containing DZs (based on ILAM) and VT origins (based on earliest activation/pacemap). Presence of non-invasive DZ was assessed by calculating the regional total activation time (rTAT)—time span between the earliest and latest activations—using ECGI activation maps from a single QRS complex.

Results

Our results indicate that regions identified by the endocardial map as having DZs, the non-invasive map demonstrated a longer duration between the earliest and latest activation (rTAT) compared to regions without DZs. Specifically, non-invasive rTAT values were significantly higher in DZs than in healthy regions during both SR (66.3±4.3ms vs. 43.2±2.9ms, p < 0.001) and S1 (115.0±4.6ms vs. 71.3±3.5ms, p<0.001, see Figure 1 for population differences). ROC analysis identified optimal rTAT thresholds of 60ms (sensitivity: 70%, specificity: 80%) for SR and 82ms (sensitivity: 80%, specificity: 70%) for S1, effectively distinguishing regions containing DZs from those without. Figure 2 illustrates the correlation between EAM and ECGI activation maps for a representative ischemic case.

Conclusion

Non-invasive assessment of regional total activation time using ECGI shows a good correlation with DZs identified through electroanatomical mapping, enabling identification of pro-arrhythmogenic regions during basal rhythm in patients with VT. Such an approach could aid in guiding treatment planning both before and during ablation procedures