Imaging-Based Simulations for Predicting Sudden Death and Guiding Ventricular Tachycardia Ablation
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- arrhythmias, cardiac
- cardiac ablations
- defibrillators, implantable
- image-based simulations
- myocardial infarction
- risk assessment
- tachycardia, ventricular
Simulation-driven engineering has put rockets in space, airplanes in the sky, and self-driving cars on the road. Computational approaches have also contributed to advancements in clinical medicine and human health.1–3 In the arena of cardiac care, the recent emphasis on personalized medicine has provided a significant impetus for the development of predictive approaches combining imaging and computational modeling that can be applied to the diagnosis and treatment of heart rhythm disorders. A major advance in this direction is the creation and translation into clinical practice of novel imaging- and simulation-based strategies for predicting an individual’s risk of sudden cardiac death (SCD) and for the noninvasive planning of optimal personalized antiarrhythmia therapies. Clinical decisions about the stratification of patients for SCD risk resulting from arrhythmia and for determining the optimal targets for antiarrhythmia ablation therapies could greatly benefit from such targeted developments because current approaches, although life saving, remain suboptimal, often increase the burden on the healthcare system, and could lead to increased patient morbidity.
SCD resulting from ventricular arrhythmias is a leading cause of death in the industrialized world, particularly among patients with prior myocardial infarction (MI).4 For patients at high risk of SCD, mortality is reduced by the prophylactic insertion of implantable cardioverter defibrillators (ICDs).5 To determine the level of SCD risk, clinical cardiology practice still relies on the one-size- fits-all metric of left ventricular ejection fraction (LVEF) <35% to identify high-risk patients. Mechanistically, in hearts with structural disease, arrhythmia results from the heterogeneously distributed remodeled tissue, which can promote the initiation and maintenance of electric instability. Global LVEF poorly reflects these mechanistic factors and, hence, its use to determine the level of SCD risk and stratify patients for ICD implantation results in a low rate of appropriate ICD device therapy, only 5% per …