REGIONAL VENTRICULAR STRAIN METRICS TO PREDICT NEW-ONSET HEART FAILURE COURSE
预测新发心力衰竭病程的区域心室应变指标
基本信息
- 批准号:8629626
- 负责人:
- 金额:$ 37.24万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2012
- 资助国家:美国
- 起止时间:2012-04-15 至 2017-02-28
- 项目状态:已结题
- 来源:
- 关键词:Adverse eventCardiovascular DiseasesClinicalClinical ManagementCoronary arteryCritical IllnessDataDatabasesDefibrillatorsDeteriorationDevicesDilated CardiomyopathyDiseaseEFRACEchocardiographyEmergency SituationFoundationsGuidelinesHealthcareHeartHeart failureHeterogeneityHumanImplantable DefibrillatorsIncidenceIndividualInjuryLaboratoriesLeftLeft ventricular structureLifeMagnetic Resonance ImagingMedicalMetricMorbidity - disease rateNatureOperative Surgical ProceduresOrgan failureOutcomePacemakersPatientsPatternPopulation StudyPrimary idiopathic dilated cardiomyopathyRecoveryRegimenRiskSentinelSentinel SurveillanceSeptal RegionSeveritiesStagingStratificationSudden DeathTestingTimeVentricularbaseclinically significantdirect applicationhigh riskindexinginjuredminimally invasivemortalitynovelresponseventricular assist device
项目摘要
DESCRIPTION (provided by applicant): Patients with clinically significant heart failure comprise the largest and most rapidly growing subset of patients with cardiovascular disease in the U.S. The burden in regard to morbidity, mortality, and health care expense is staggering. In the clinical management of critically ill new-onset heart failure patients, the inability to immediately differentiate those who will respond to medical therapy from those who will not results in the inappropriate application of high-risk heart failure surgery in patients who do not need it, while also denying surgery to those who have the most to benefit from it. MRI-based multi-parametric strain analysis generates a patient-specific, "normalized," and highly accurate description of micro-regional left ventricular (LV) contractile function by comparing three patient
specific raw strain parameter values from each of 15,300 grid points (a total of 45,900 database comparisons per patient) to the respective normal average +/- standard deviation (from our laboratory's normal human strain database; n>70). This "normalization" of multiple different patient- specific strain parameter values allows their combination into novel and powerful multi-parametric strain indices that have proven more powerful than any individual strain metric. By applying MRI-based multi-parametric strain analysis in new-onset heart failure (dilated cardiomyopathy) patients, we have discovered marked heterogeneity in the LV regional distribution of contractile injury. This unexpected heterogeneity of contractile injury in dilated cardiomyopathy patients occurs in a consistent pattern that has allowed us to identify "sentinel" LV regions (basilar-septal and mid-septal) that are more sensitive to early injury and that serve as harbingers of irreversible contractile injury in new-onset heart failure patients. We hypothesize that the surveillance of these sentinel LV regions by MRI-based multi-parametric strain analysis allows the risk stratification of new onset heart failure patients in regard to eary response to medical therapy and the subsequent occurrence of heart failure adverse events. New-onset heart failure patients who 1) do not yet have a cardioverter/defibrillator or biventricular pacemaker, 2) have an ejection fraction <30%, and 3) have idiopathic dilated cardiomyopathy (no coronary artery or valvular disease) will undergo MRI-based multi- parametric strain analysis to produce average Z-scores for 72 LV micro-regions. After stabilization on heart failure medical therapy (ACC/AHA Clinical Guidelines), they will be restudied 3 months later. We will statistically characterize the ability of baseline basilar-septal
and mid-septal sentinel regional average multi- parametric strain Z-scores to predict both contractile recovery on medical therapy and the occurrence of heart failure adverse events. We will statistically optimize the micro-regional makeup of our sentinel surveillance region and compare our results to the predictive capabilities of the current standard, echocardiographic ejection fraction. A metric of micro-regional LV contractile function that predicts early recovery on heart failure medical therapy would more accurately direct the application of high-risk surgical therapy for heart failure.
描述(由申请人提供):临床显著性心力衰竭患者构成了美国心血管疾病患者中最大且增长最快的一个子集。在发病率、死亡率和医疗费用方面的负担是惊人的。在危重新发心力衰竭患者的临床管理中,由于无法立即区分哪些患者对药物治疗有反应,哪些患者对药物治疗没有反应,导致对不需要的患者不适当地应用高危心力衰竭手术,同时也拒绝对最有可能受益的患者进行手术。通过比较三位患者,基于mri的多参数应变分析生成了患者特异性的、“规范化”的、高度准确的微区域左心室(LV)收缩功能描述
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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MICHAEL K PASQUE其他文献
MICHAEL K PASQUE的其他文献
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{{ truncateString('MICHAEL K PASQUE', 18)}}的其他基金
Left Ventricular Distribution Patterns of the Regionally varying Ischemic Myocardial Contractile Substrates Associated with Ischemic Mitral Regurgitation
与缺血性二尖瓣反流相关的局部缺血性心肌收缩基质的左心室分布模式
- 批准号:
9769299 - 财政年份:2018
- 资助金额:
$ 37.24万 - 项目类别:
REGIONAL VENTRICULAR STRAIN METRICS TO PREDICT NEW-ONSET HEART FAILURE COURSE
预测新发心力衰竭病程的区域心室应变指标
- 批准号:
8271119 - 财政年份:2012
- 资助金额:
$ 37.24万 - 项目类别:
REGIONAL VENTRICULAR STRAIN METRICS TO PREDICT NEW-ONSET HEART FAILURE COURSE
预测新发心力衰竭病程的区域心室应变指标
- 批准号:
8800569 - 财政年份:2012
- 资助金额:
$ 37.24万 - 项目类别:
REGIONAL VENTRICULAR STRAIN METRICS TO PREDICT NEW-ONSET HEART FAILURE COURSE
预测新发心力衰竭病程的区域心室应变指标
- 批准号:
8457103 - 财政年份:2012
- 资助金额:
$ 37.24万 - 项目类别:
Left Ventricular Remodeling in Aortic Insufficiency
主动脉瓣关闭不全的左心室重构
- 批准号:
7169865 - 财政年份:2000
- 资助金额:
$ 37.24万 - 项目类别:
Left Ventricular Remodeling in Aortic Insufficiency
主动脉瓣关闭不全的左心室重构
- 批准号:
7348393 - 财政年份:2000
- 资助金额:
$ 37.24万 - 项目类别:
LEFT VENTRICULAR REMODELING IN AORTIC INSUFFICIENCY
主动脉瓣关闭不全的左心室重构
- 批准号:
6091867 - 财政年份:2000
- 资助金额:
$ 37.24万 - 项目类别:
LEFT VENTRICULAR REMODELING IN AORTEC INSUFFICIENCY
主动脉瓣功能不全的左心室重构
- 批准号:
6390731 - 财政年份:2000
- 资助金额:
$ 37.24万 - 项目类别:
LEFT VENTRICULAR REMODELING IN AORTEC INSUFFICIENCY
主动脉瓣功能不全的左心室重构
- 批准号:
6537813 - 财政年份:2000
- 资助金额:
$ 37.24万 - 项目类别:
Left Ventricular Remodeling in Aortic Insufficiency
主动脉瓣关闭不全的左心室重构
- 批准号:
7010745 - 财政年份:2000
- 资助金额:
$ 37.24万 - 项目类别:
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