We previously reported the feasibility and efficacy of a simulation-guided clinical catheter ablation of atrial fibrillation (AF) in an in-silico AF model. We developed a highly efficient realistic AF model reflecting the patient endocardial voltage and local conduction and tested its clinical feasibility. We acquired > 500 endocardial bipolar electrograms during right atrial pacing at the beginning of the AF ablation procedures. Based on the clinical bipolar electrograms, we generated simulated voltage maps by applying fibrosis and local activation maps adjusted for the fiber orientation. The software’s accuracy (CUVIA2.5) was retrospectively tested in 17 patients and feasibility prospectively in 10 during clinical AF ablation. Results: We found excellent correlations between the clinical and simulated voltage maps (R = 0.933, p < 0.001) and clinical and virtual local conduction (R = 0.958, p < 0.001). The proportion of virtual local fibrosis was 15.4, 22.2, and 36.9% in the paroxysmal AF, persistent AF, and post-pulmonary vein isolation (PVI) states, respectively. The reconstructed virtual bipolar electrogram exhibited a relatively good similarities of morphology to the local clinical bipolar electrogram (R = 0.60 ± 0.08, p < 0.001). Feasibility testing revealed an in situ procedural computing time from the clinical data acquisition to wave-dynamics analyses of 48.2 ± 4.9 min. All virtual analyses were successfully achieved during clinical PVI procedures. We developed a highly efficient, realistic, in situ procedural simulation model reflective of individual anatomy, fiber orientation, fibrosis, and electrophysiology that can be applied during AF ablation.
Bibliographical noteFunding Information:
This work was supported by a grant [HI18C0070] and [HI19C0114] from the Korea Health 21 R&D Project, Ministry of Health and Welfare, and a grant [NRF-2017R1A2B4003983] and [NRF-2019R1C1C1009075] from the Basic Science Research Program run by the National Research Foundation of Korea (NRF), which is funded by the Ministry of Science, ICT, & Future Planning (MSIP). We thank Mr. Dong-Su Jang for providing excellent support with medical illustration, and Mr. John Martin for his linguistic assistance.
© 2020, The Author(s).
All Science Journal Classification (ASJC) codes