Dataset Information

An activation-repolarization time metric to predict localized regions of high susceptibility to reentry.

ABSTRACT: Initiation of reentrant ventricular tachycardia (VT) involves complex interactions between front and tail of the activation wave. Recent experimental work has identified the time interval between S2 repolarization proximal to a line of functional block and S2 activation at the adjacent distal side as a critical determinant of reentry.We hypothesized that (1) an algorithm could be developed to generate a spatial map of this interval ("reentry vulnerability index" [RVI]), (2) this would accurately identify a site of reentry without the need to actually induce the arrhythmia, and (3) it would be possible to generate an RVI map in patients during routine clinical procedures.An algorithm was developed that calculated RVI between all pairs of electrodes within a given radius.The algorithm successfully identified the region with increased susceptibility to reentry in an established Langendorff pig heart model and the site of reentry and rotor formation in an optically mapped sheep ventricular preparation and computational simulations. The feasibility of RVI mapping was evaluated during a clinical procedure by coregistering with cardiac anatomy and physiology of a patient undergoing VT ablation.We developed an algorithm to calculate a reentry vulnerability index from intervals between local repolarization and activation. The algorithm accurately identified the region of reentry in 2 animal models of functional reentry. The clinical application was demonstrated in a patient with VT and identified the area of reentry without the need of inducing the arrhythmia.

SUBMITTER: Child N

PROVIDER: S-EPMC4717521 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

An activation-repolarization time metric to predict localized regions of high susceptibility to reentry.

Child Nicholas N Bishop Martin J MJ Hanson Ben B Coronel Ruben R Opthof Tobias T Boukens Bastiaan J BJ Walton Richard D RD Efimov Igor R IR Bostock Julian J Hill Yolanda Y Rinaldi Christopher A CA Razavi Reza R Gill Jaswinder J Taggart Peter P

Heart rhythm 20150409 7

<h4>Background</h4>Initiation of reentrant ventricular tachycardia (VT) involves complex interactions between front and tail of the activation wave. Recent experimental work has identified the time interval between S2 repolarization proximal to a line of functional block and S2 activation at the adjacent distal side as a critical determinant of reentry.<h4>Objectives</h4>We hypothesized that (1) an algorithm could be developed to generate a spatial map of this interval ("reentry vulnerability in ...[more]

PMID: 25863160

Similar Datasets

Project description:Exit sites associated with scar-related reentrant arrhythmias represent important targets for catheter ablation therapy. However, their accurate location in a safe and robust manner remains a significant clinical challenge. We recently proposed a novel quantitative metric (termed the Reentry Vulnerability Index, RVI) to determine the difference between activation and repolarisation intervals measured from pairs of spatial locations during premature stimulation to accurately locate the critical site of reentry formation. In the clinic, the method showed potential to identify regions of low RVI corresponding to areas vulnerable to reentry, subsequently identified as ventricular tachycardia (VT) circuit exit sites. Here, we perform an in silico investigation of the RVI metric in order to aid the acquisition and interpretation of RVI maps and optimise its future usage within the clinic. Within idealised 2D sheet models we show that the RVI produces lower values under correspondingly more arrhythmogenic conditions, with even low resolution (8 mm electrode separation) recordings still able to locate vulnerable regions. When applied to models of infarct scars, the surface RVI maps successfully identified exit sites of the reentrant circuit, even in scenarios where the scar was wholly intramural. Within highly complex infarct scar anatomies with multiple reentrant pathways, the identified exit sites were dependent upon the specific pacing location used to compute the endocardial RVI maps. However, simulated ablation of these sites successfully prevented the reentry re-initiation. We conclude that endocardial surface RVI maps are able to successfully locate regions vulnerable to reentry corresponding to critical exit sites during sustained scar-related VT. The method is robust against highly complex and intramural scar anatomies and low resolution clinical data acquisition. Optimal location of all relevant sites requires RVI maps to be computed from multiple pacing locations.

Project description:Identification of targets for catheter ablation of ventricular tachycardias (VTs) remains a significant challenge. VTs are often driven by re-entrant circuits resulting from a complex interaction between the front (activation) and tail (repolarization) of the electrical wavefront. Most mapping techniques do not take into account the tissue repolarization which may hinder the detection of ablation targets. The re-entry vulnerability index (RVI), a recently proposed mapping procedure, incorporates both activation and repolarization times to uncover VT circuits. The method showed potential in a series of experiments, but it still requires further development to enable its incorporation into a clinical protocol. Here, in-silico experiments were conducted to thoroughly assess RVI maps constructed under clinically-relevant mapping conditions. Within idealized as well as anatomically realistic infarct models, we show that parameters of the algorithm such as the search radius can significantly alter the specificity and sensitivity of the RVI maps. When constructed on sparse grids obtained following various placements of clinical recording catheters, RVI maps can identify vulnerable regions as long as two electrodes were placed on both sides of the line of block. Moreover, maps computed during pacing without inducing VT can reveal areas of abnormal repolarization and slow conduction but not directly vulnerability. In conclusion, the RVI algorithm can detect re-entrant circuits during VT from low resolution mapping grids resembling the clinical setting. Furthermore, RVI maps may provide information about the underlying tissue electrophysiology to guide catheter ablation without the need of inducing potentially harmful VT during the clinical procedure. Finally, the ability of the RVI maps to identify vulnerable regions with specificity in high resolution computer models could potentially improve the prediction of optimal ablation targets of simulation-based strategies.

Dataset Information

An activation-repolarization time metric to predict localized regions of high susceptibility to reentry.

Publications

An activation-repolarization time metric to predict localized regions of high susceptibility to reentry.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets