PRIMARY ECG - MRI RISK STRATIFICATION

主要心电图 - MRI 风险分层

• 批准号: 8136440
• 负责人: Joao A C Lima
• 金额: $ 8.95万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-04-01 至 2012-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8136440
• 关键词: Address; Algorithms; Cardiac; Cardiology; Cardiovascular system; Caring; Cicatrix; Computer Systems; Data; Detection; Development; Devices; Diagnostic; Electrocardiogram; Evaluation; Event; Functional disorder; Genetic; Goals; Heart failure; Heterogeneity; Incidence; Individual; Infarction; Institution; Instruction; Magnetic Resonance Imaging; Methods; Metric; Modality; Myocardial; Outcome; Patients; Pharmaceutical Preparations; Phase; Predisposition; Prevention; Public Health; Research; Resolution; Resources; Risk; Risk Assessment; Sensitivity and Specificity; Stratification; Structure; United States National Institutes of Health; base; high risk; improved; mortality; novel; prognostic; sudden cardiac death

DESCRIPTION (provided by applicant): The goal of this proposal is to implement new strategies in personalized risk assessment for heart failure progression and sudden cardiac death (SCD) using a sequential algorithm involving ECG and cardiac MRI analyses in combination with conventional and newly emerging risk-stratification methods. While prevention of heart failure progression and SCD in patients of indeterminate risk represents one of the most challenging issues in contemporary cardiology, there has been little progress in reducing the incidence of heart failure and SCD mortality. Furthermore, current risk-stratification methods that focus on LV dysfunction and electrophysiological metrics lack the sensitivity and specificity needed for individualized care. Here we assess myocardial damage by applying novel automated ECG based QRS scoring combined with the detection of heterogeneity in myocardial structure and viability with contrast-enhanced MRI. We have validated the ECG QRS-scoring algorithm against high resolution scar quantification by MRI, thus demonstrating its potential utility in identifying individuals who should undergo detailed infarct heterogeneity studies by MRI for further risk stratification. Thus, in Phase I we apply the two modalities sequentially in combination with existing markers to refine development of an algorithm that will then be used to address feasibility and accuracy of the approach in a large (n>2,000) multi-center analysis during Phase II, where technological, logistical and intellectual advances refined in Phase I will be implemented at 4 additional institutions. Marker associations, cardiac events and statistical outcomes will be analyzed via the centralized computer system provided by the NIH Cardiovascular Research GRID resource (CVRG) at our institution. Based on preliminary data, we anticipate that this new combined diagnostic approach will discriminate patients who harbor previously undetected high risk for heart failure progression as well as SCD mortality susceptibility that is not detectable using current strategies. Evaluation of ancillary genetic- and bio-markers during Phase II will provide additional prognostic information useful for individualized risk assessment. RELEVANCE (See instructions): This proposal addresses two major public health challenges in cardiology: improved identification and risk stratification of patients for 1) sudden cardiac death and 2) heart failure progression and mortality. Focus is placed on non-invasive approaches relevant to evaluation of specific individuals to improve drug and device targeting using new and existing therapies.

描述（由申请人提供）： 该提案的目标是使用涉及心电图和心脏 MRI 分析的序贯算法，并结合传统和新兴的风险分层方法，对心力衰竭进展和心源性猝死 (SCD) 的个性化风险评估实施新策略。虽然预防不确定风险患者的心力衰竭进展和 SCD 是当代心脏病学中最具挑战性的问题之一，但在降低心力衰竭发生率和 SCD 死亡率方面进展甚微。此外，目前关注左心室功能障碍和电生理指标的风险分层方法缺乏个体化护理所需的敏感性和特异性。在这里，我们通过应用基于 QRS 评分的新型自动心电图并结合对比增强 MRI 检测心肌结构和活力的异质性来评估心肌损伤。我们已经针对 MRI 高分辨率疤痕量化验证了心电图 QRS 评分算法，从而证明了其在识别应通过 MRI 进行详细梗塞异质性研究以进行进一步风险分层的个体方面的潜在实用性。因此，在第一阶段，我们依次应用这两种模式并结合现有标记来改进算法的开发，然后将该算法用于在第二阶段的大型（n> 2,000）多中心分析中解决该方法的可行性和准确性，第一阶段完善的技术、后勤和智力进步将在另外 4 个机构实施。标记物关联、心脏事件和统计结果将通过我们机构的 NIH 心血管研究网格资源 (CVRG) 提供的中央计算机系统进行分析。根据初步数据，我们预计这种新的联合诊断方法将区分那些以前未检测到的心力衰竭进展高风险以及使用当前策略无法检测到的 SCD 死亡率易感性的患者。第二阶段期间辅助遗传和生物标志物的评估将为个体化风险评估提供有用的额外预后信息。相关性（参见说明）：该提案解决了心脏病学领域的两个主要公共卫生挑战：改进患者的识别和风险分层：1) 心源性猝死和 2) 心力衰竭进展和死亡率。重点放在与特定个体评估相关的非侵入性方法上，以使用新的和现有的疗法改善药物和设备的靶向性。