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Impact of Intracardiac Neurons on Cardiac Electrophysiology and Arrhythmogenesis in an Ex Vivo Langendorff System
Published on: May 22, 2018
Investigating a Novel Activation-Repolarisation Time Metric to Predict Localised Vulnerability to Reentry Using
Yolanda R Hill1, Nick Child1, Ben Hanson2
1Department of Biomedical Engineering, Division of Imaging Sciences & Biomedical Engineering, King's College London, London, United Kingdom.
Locating critical reentry sites for ventricular tachycardia (VT) ablation is challenging. The Reentry Vulnerability Index (RVI) metric effectively identifies these vulnerable areas, even in complex scar models, improving ablation targeting.
Area of Science:
- Electrophysiology
- Computational Cardiology
- Medical Device Technology
Background:
- Scar-related reentrant arrhythmias, particularly ventricular tachycardia (VT), pose significant clinical challenges for catheter ablation.
- Accurate and robust localization of reentry circuit exit sites is crucial for successful ablation therapy but remains difficult.
- A novel quantitative metric, the Reentry Vulnerability Index (RVI), was previously proposed to identify reentry formation sites.
Purpose of the Study:
- To perform an in silico investigation of the RVI metric to aid in the acquisition and interpretation of RVI maps.
- To optimize the future clinical usage of the RVI metric for locating critical reentry sites.
- To validate the RVI metric's efficacy in diverse and complex cardiac scar models.
Main Methods:
- Simulations were conducted using idealised 2D sheet models and models of infarct scars.
- The RVI was calculated based on the difference between activation and repolarisation intervals during premature stimulation.
- RVI maps were generated and analyzed under various conditions, including different scar complexities and electrode resolutions.
Main Results:
- The RVI metric demonstrated lower values under more arrhythmogenic conditions in 2D models.
- Low-resolution recordings (8 mm electrode separation) were sufficient to identify vulnerable regions.
- In infarct scar models, surface RVI maps accurately identified reentrant circuit exit sites, even in intramural scars, and simulated ablation prevented reentry re-initiation.
Conclusions:
- Endocardial surface RVI maps successfully locate reentry-vulnerable regions corresponding to critical exit sites during scar-related VT.
- The RVI method is robust against complex and intramural scar anatomies and low-resolution data acquisition.
- Optimal identification of all critical sites necessitates computing RVI maps from multiple pacing locations.
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