Predicting ICD therapy and post-ablation ventricular tachycardia recurrence using cardiac MRI-based advanced computational reentrant pathway analysis

Abstract

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): Netherlands Heart Institute Fellowship, CVON PREDICT2 Young Talent Program Background MRI late gadolinium enhancement (LGE) images can provide novel insights about critical pathways through scar but does not assess the vulnerability of these pathways for sustaining scar-mediated ventricular tachycardia (VT). Computational modelling can augment the insights from imaging derived metrics by providing the functional implications of structural anatomy of the substrate. However, current (monodomain) approaches are computationally expensive and may not, by design, extract all critical pathways. Aim This study evaluated the performance of a novel, reaction-Eikonal based, automated reentrant pathway finding algorithm (VITA) to assess the functional viability of critical circuits identified on LGE and non-invasively predict arrhythmic risk in both an ICD and post-ablation cohort recurrence. Methods ADAS LV and custom-made software was used to generate 3D patient-specific ventricular models in a prospective cohort of post-infarct ICD patients (cohort 1, n=40) and a retrospective cohort of 20 post-infarct VT-ablation patients (cohort 2). Our Virtual Induction and Treatment of Arrhythmias (VITA) framework was then applied to comprehensively probe the viability of the scar substrate to sustaining reentrant circuits. VITA metrics, related to the numbers of induced VTs and their corresponding round trip times (RTTs), were compared with appropriate ICD therapy (cohort 1) and VT-recurrence (cohort 2) during follow-up. Results Patients in both cohorts with an event had higher VITA metrics. In cohort 1 (ICD), VITA demonstrated significantly more inducible VTs (6.6±4.2 vs. 4.1±3.4, p = .044), longer mean RTT (116.2±50.9 ms vs. 76.9±42.6 ms, p=.012) and max RTT (194.4±105.1 ms vs. 109.6±78.7, p =.009) in the event group. In addition, Cox-regression demonstrated a significant independent association with an event: induced VTs (HR 1.67; CI 1.04–2.68, p = .03), mean RTT (HR 2.14; CI 1.11–4.12, p = .02), maximum RTT (HR 2.13; CI 1.19–3.81, p = .01). In cohort 2 (VT-ablation), total induced VTs (85±43 vs. 42±27, p = .01) and unique VTs (9±4 vs. 5±4, p = .04) were significantly higher in patients with- compared to patients without recurrence, and were predictive of recurrence with AUC of .820 and .770, respectively. Max RTT demonstrated a trend towards significance 293 ± 90 ms vs. 200 ± 114 ms (p = .06) for recurrence and non-recurrence, respectively. No differences were observed in mean RTT between the two groups. Conclusion VITA enabled quantitative assessment of pro-arrhythmic vulnerability of the substrate which related directly to patient outcomes. The number of induced VTs were the most robust measure of appropriate ICD therapy and post-ablation arrhythmia recurrence. The RTT metrics, related to viable circuit lengths through scar, demonstrated a significant independent association with appropriate ICD therapy. Future studies should investigate the clinical utility of a VITA-guided selection and treatment approach.