Epicardial substrate mapping for ventricular tachycardia ablation in patients with non-ischaemic cardiomyopathy: a new algorithm to differentiate between scar and viable myocardium developed by simultaneous integration of computed tomography and contrast-enhanced magnetic resonance imaging.

AIMS

During epicardial electroanatomical mapping (EAM), it is difficult to differentiate between fibrosis and fat, as both exhibit attenuated bipolar voltage (BV). The purpose of this study was to assess whether unipolar voltage (UV), BV, and electrogram characteristics (EC) can distinguish fibrosis from viable myocardium and fat during epicardial EAM for ventricular tachycardia (VT) ablation in non-ischaemic cardiomyopathy (NICM).

METHODS AND RESULTS

Ten NICM patients (7 males, 56 ± 13 years) with VT underwent epicardial EAM with real-time integration of computed tomography-derived epicardial fat and contrast-enhanced MRI-derived scar. Bipolar voltage (filtered 30-400 Hz), UV (filtered 1-240 Hz), and EC (duration and morphology) were correlated with the presence of fat and scar. At sites devoid of fat, the optimal cutoff values to differentiate between scar and myocardium were 1.81 mV for BV and 7.95 mV for UV. Bipolar voltage, UV, and electrogram duration >50 ms distinguished scar from myocardium in areas covered with <2.8 mm fat (all P < 0.001), but not ≥ 2.8 mm fat. In contrast, electrogram morphology-characteristics could also detect scar covered with ≥ 2.8 mm fat (P = 0.001). A newly developed three-step algorithm combining electrogram morphology, duration, and UV could correctly identify scar with a sensitivity of 75%. Unipolar voltage but not BV could detect intramural scar in the absence of fat.

CONCLUSIONS

Both BV ≤ 1.81 mV and UV ≤ 7.95 mV are useful for detection of scar during epicardial EAM, in the absence of ≥ 2.8 mm fat. However, EC can be used to detect scar covered with fat. A newly developed algorithm combining UV and EC can differentiate between scar and viable myocardium. Unipolar voltage but not BV could detect intramural scar.