Whole-heart computational modelling provides further mechanistic insights into ST-elevation in Brugada syndrome

Wülfers, Eike M.; Moss, Robin; Lehrmann, Heiko; Arentz, Thomas; Westermann, Dirk; Seemann, Gunnar; Odening, Katja E.; Steinfurt, Johannes

doi:10.1016/j.ijcha.2024.101373

Cited by 2 publications

(1 citation statement)

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“…As an example, we know that the degree of ST elevation in the type 1 ECG is related to the area of abnormal electrophysiological substrate, however, it is not possible to establish how, or how much abnormality or substrate area are needed to generate a surface signal, or how the substrate area affects arrhythmogenesis. In this direction, a recent computational study 93 has explored the effect of conduction slowing and early repolarization on the surface ECG, confirming that the presence of the ECG pattern is related to the abnormal substrate in the epicardial RVOT. As noted in several studies, 89…”

Section: Translational Outlookmentioning

confidence: 83%

Electrophysiological patterns and structural substrates of Brugada syndrome: Critical appraisal and computational analyses

Seghetti,

Latrofa,

Biasi

et al. 2024

Cardiovasc electrophysiol

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Brugada syndrome (BrS) is a cardiac electrophysiological disease with unknown etiology, associated with sudden cardiac death. Symptomatic patients are treated with implanted cardiac defibrillator, but no risk stratification strategy is effective in patients that are at low to medium arrhythmic risk. Cardiac computational modeling is an emerging tool that can be used to verify the hypotheses of pathogenesis and inspire new risk stratification strategies. However, to obtain reliable results computational models must be validated with consistent experimental data. We reviewed the main electrophysiological and structural variables from BrS clinical studies to assess which data could be used to validate a computational approach. Activation delay in the epicardial right ventricular outflow tract is a consistent finding, as well as increased fibrosis and subclinical alterations of right ventricular functional and morphological parameters. The comparison between other electrophysiological variables is hindered by methodological differences between studies, which we commented. We conclude by presenting a recent theory unifying electrophysiological and structural substrate in BrS and illustrate how computational modeling could help translation to risk stratification.

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Section: Translational Outlookmentioning

confidence: 83%