Key result
In-silico pace-mapping with stored electrograms identifies exit sites and isthmuses across 6 simulated VT episodes.
Why the study?
Long procedure durations and the need for VT induction make conventional pace-mapping non-optimal, creating a need to evaluate in-silico pace-mapping using stored implanted device electrograms for pre-procedural ablation planning.
Does in-silico pace-mapping using implanted device EGMs accurately localize VT exit sites and isthmuses in a 3D torso model?
Does in-silico pace-mapping using implanted device EGMs accurately localize VT exit sites and isthmuses in a 3D torso model?
In-silico pace-mapping using implanted device electrograms can successfully localize VT exit sites and isthmuses, offering a potential tool for pre-procedural ablation planning.
May support pre-procedural VT mapping with implanted devices; leaves open prospective clinical validation.
BACKGROUND: Pace-mapping is a commonly used electrophysiological (EP) procedure which aims to identify exit sites of ventricular tachycardia (VT) by matching ventricular activation patterns (assessed by QRS morphology) at specific pacing locations with activation during VT. However, long procedure durations and the need for VT induction render this technique non-optimal. To demonstrate the potential of in-silico pace-mapping, using stored electrogram (EGM) recordings of clinical VT from implanted devices to guide pre-procedural ablation planning. METHOD: Six scar-related VT episodes were simulated in a 3D torso model reconstructed from computed tomography (CT) imaging data, including three different infarct anatomies mapped from infarcted porcine imaging data. In-silico pace-mapping was performed to localise VT exit sites and isthmuses by using 12-lead electrocardiogram (ECG) signals and different combinations of EGM sensing vectors from implanted devices, through the creation of conventional correlation maps and reference-less maps. RESULTS: Our in-silico platform was successful in identifying VT exit sites for a variety of different VT morphologies from both ECG correlation maps and corresponding EGM maps, with the latter dependent upon the number of sensing vectors used. We also showed the added utility of both ECG and EGM reference-less pace-mapping for the identification of slow-conducting isthmuses, uncovering the optimal algorithm parameters. Finally, EGM-based pace-mapping was shown to be more dependent upon the mapped surface (epicardial/endocardial), relative to the VT origin. CONCLUSIONS: In-silico pace-mapping can be used along with EGMs from implanted devices to localise VT ablation targets in pre-procedural planning.
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Monaci et al. (2020) studied Ventricular tachycardia (n=6). In-silico pace-mapping was evaluated on Localization of VT exit sites and isthmuses. In-silico pace-mapping using stored electrograms successfully identified exit sites and slow-conducting isthmuses across 6 simulated scar-related ventricular tachycardia episodes.
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