Virtual cardiac electrophysiologic testing for sudden death risk stratification

描述(申请人提供)：在美国，心脏性猝死是主要的死亡原因。虽然植入型心律转复除颤器(ICD)已被证明能有效预防室性心律失常患者的心脏性猝死，但目前确定谁将受益于ICD的风险分层方法并不理想。在这项应用中，提出了一种新的危险分层工具的开发和评估，以预测有心肌梗死(即心脏病发作)患者的心脏性猝死。这种方法基于电生理测试；风险分层方法是通过放置在脑室的导管进行程序化刺激，以测试潜在威胁生命的室性快速性心律失常的诱发性。我们假设计算机模拟可以用来无创地测试这些室性快速性心律失常的诱发性。已有研究表明，由梗塞引起的疤痕和部分存活组织为这些室性心律失常的发生提供了底物。对比增强磁共振成像(MRI)可以有效地区分存活心肌、部分存活心肌和梗死瘢痕。通过将真实的电生理特征和传导特性分配给输入到工作站的三维MRI图像，假设使用该模型的模拟程序刺激将识别具有诱导性室性快速性心律失常的患者，从而受益于ICD。除了猝死风险分层，电生理学计算机建模和心脏MRI的集成可能还有其他潜在的临床应用，包括评估双室起搏治疗候选者的电不同步，为有病例室性心动过速的患者进行导管消融的术前计划，以及作为培训医生和医疗专业人员的教育软件工具。在这项研究的第一阶段，我们计划开发和实施该工具，使用来自健康志愿者和接受电生理测试的患者的MRI数据来调整模型参数。在第二阶段，我们将重点比较“虚拟”电生理测试的结果和在更大的患者队列中进行的实际电生理测试，并评估其预测室性心律失常风险的能力。公共卫生相关性心脏性猝死的有效危险分层对于及时和适当的治疗是必要的。一种非侵入性的方法来检测患者是否有必要的心律失常底物，可以显著改善对心脏性猝死的预防，这在美国是导致死亡的主要原因。

DESCRIPTION (provided by applicant): Sudden cardiac death is a leading cause of death in the United States. Although implanted cardioverter defibrillators (ICD) have been shown to be effective in preventing sudden cardiac death in patients who experience ventricular arrhythmias, current risk stratification methods in determining who will or will not benefit from an ICD have been suboptimal. In this application, the development and evaluation of a novel risk stratification tool to predict sudden cardiac death in patients who have had a myocardial infarction (i.e. heart attack) is proposed. This method is based on electrophysiologic testing; a risk stratification approach in which programmed stimulation via catheters placed in the ventricle is used to test for inducibility of potentially life threatening ventricular tachyarrhythmias. We hypothesize that computer simulations could be used to non- invasively test for inducibility of these ventricular tachyarrhythmias. It has been shown that the scars and partially viable tissue resulting from an infarction provide the substrate for these ventricular arrhythmias to occur. Contrast-enhanced magnetic resonance imaging (MRI) can effectively differentiate between viable myocardium, partially viable myocardium, and infarction scar. By assigning realistic electrophysiologic characteristics and conduction properties to the three-dimensional MRI image that is imported to the workstation, it is hypothesized that simulated programmed stimulation using this model will identify the patients who have inducible ventricular tachyarrhythmias and thus would benefit from an ICD. The integration of electrophysiologic computer modeling and cardiac MRI may have other potential clinical applications beyond sudden death risk stratification, including the evaluation of electrical dyssynchrony in candidates for bi- ventricular pacing therapy, pre-procedure planning for catheter ablation of patients with documented ventricular tachycardias, and as an educational software tool for training doctors and medical professionals. In the first stage of this study we plan to develop and implement of the tool using MRI data from healthy volunteers and patients undergoing electrophysiology testing to adjust model parameters. In the second stage, we will focus on comparing the results of "virtual" electrophysiologic testing to actual electrophysiologic testing in a larger cohort of patients and evaluating its ability to predict risk for ventricular arrhythmias. PUBLIC HEALTH RELEVANCE Effective risk stratification for sudden cardiac death is necessary for timely and appropriate therapy. A non- invasive approach to detect whether a patient has the necessary substrate for arrhythmias could significantly improve the prevention of sudden cardiac death, a leading cause of mortality in the United States.