Characterizing Conduction Channels in Postinfarction Patients Using a Personalized Virtual Heart.

Autor:	Deng D; School of Biomedical Engineering, Dalian University of Technology, Dalian, Liaoning, China; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland., Prakosa A; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland., Shade J; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland., Nikolov P; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland., Trayanova NA; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland. Electronic address: ntrayanova@jhu.edu.
Jazyk:	angličtina
Zdroj:	Biophysical journal [Biophys J] 2019 Dec 17; Vol. 117 (12), pp. 2287-2294. Date of Electronic Publication: 2019 Jul 22.
DOI:	10.1016/j.bpj.2019.07.024
Abstrakt:	Patients with myocardial infarction have an abundance of conduction channels (CC); however, only a small subset of these CCs sustain ventricular tachycardia (VT). Identifying these critical CCs (CCCs) in the clinic so that they can be targeted by ablation remains a significant challenge. The objective of this study is to use a personalized virtual-heart approach to conduct a three-dimensional (3D) assessment of CCCs sustaining VTs of different morphologies in these patients, to investigate their 3D structural features, and to determine the optimal ablation strategy for each VT. To achieve these goals, ventricular models were constructed from contrast enhanced magnetic resonance imagings of six postinfarction patients. Rapid pacing induced VTs in each model. CCCs that sustained different VT morphologies were identified. CCCs' 3D structure and type and the resulting rotational electrical activity were examined. Ablation was performed at the optimal part of each CCC, aiming to terminate each VT with a minimal lesion size. Predicted ablation locations were compared to clinical. Analyzing the simulation results, we found that the observed VTs in each patient model were sustained by a limited number (2.7 ± 1.2) of CCCs. Further, we identified three types of CCCs sustaining VTs: I-type and T-type channels, with all channel branches bounded by scar, and functional reentry channels, which were fully or partially bounded by conduction block surfaces. The different types of CCCs accounted for 43.8, 18.8, and 37.4% of all CCCs, respectively. The mean narrowest width of CCCs or a branch of CCC was 9.7 ± 3.6 mm. Ablation of the narrowest part of each CCC was sufficient to terminate VT. Our results demonstrate that a personalized virtual-heart approach can determine the possible VT morphologies in each patient and identify the CCCs that sustain reentry. The approach can aid clinicians in identifying accurately the optimal VT ablation targets in postinfarction patients. (Copyright © 2019 Biophysical Society. Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu