Comprehensive CT Guided Coronary Artery Bypass Graft Surgery
Comprehensive CT Guided Coronary Artery Bypass Graft Surgery
批准号:
10333312
负责人:
Koen Nieman
金额:
$72.5万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-02-15 至 2024-01-31
关键词:
AlgorithmsAnatomyAngiographyAtherosclerosisBehaviorBlindedBlood VesselsBlood flowCardiacCaringCatheterizationCharacteristicsChest PainCicatrixClinicalCoronaryCoronary ArteriosclerosisCoronary Artery BypassCoronary OcclusionsCoronary VesselsCoronary heart diseaseDataDecision MakingDevelopmentDiagnosticDiffuseDiseaseDistalEffectivenessEvaluationFunctional ImagingFutureGoalsHealthImageImaging DeviceImaging TechniquesIndividualInfarctionIntuitionIschemiaKnowledgeLesionLifeLiquid substanceMachine LearningManualsMeasuresMissionModelingMorbidity - disease rateMyocardialMyocardial IschemiaMyocardial perfusionNatureOperative Surgical ProceduresOrganismOutcomePatientsPerformancePerfusionPhysiologyProceduresPublic HealthReportingReproducibilityResearchResidual stateResolutionSafetySeveritiesStenosisStressSurgical complicationSymptomsTechniquesTestingThromboplastinTimeTissuesUnited States National Institutes of HealthX-Ray Computed Tomographybaseblood flow measurementclinical applicationclinical decision-makingclinical implementationclinical practicecohortcostdisabilityfunctional outcomeshemodynamicsimage guidedimprovedimproved outcomeinnovationmortalitynovel therapeuticsperfusion imagingpredictive modelingprospectiverestorationsimulationstandard caresurgery outcometoolvirtual
中文摘要
项目摘要
冠状动脉旁路移植术(CABG)改善了冠心病(CAD)患者的生活,
但20%的患者在手术后一年仍有症状。在临床实践中,CABG决策主要是
由侵入性血管造影确定的狭窄严重度驱动,尽管已知功能相关性
CAD参数。 如果没有临床可用的高分辨率,
定量功能成像,并更好地了解与解剖相关的临床结局
(血管造影)和功能(缺血、瘢痕组织)因素。 长期目标是改善
通过个性化成像进行CABG-远程指导护理。 本建议的总体目标是确定
心肌血流恢复(缺血减少)的决定因素,并开发用于
个体化的、病变特异性的CABG决策制定,以及基于
患者的解剖结构和功能来预测血流动力学结果。 支持使用侵入性
血流储备分数-冠脉搭桥术,拟议研究的基本原理是解剖(血管造影)
和功能信息(缺血、瘢痕组织)将识别将受益于
血运重建和通过流动模拟进行的外科手术的个体优化将最大限度地提高临床
CABG对CAD患者的益处。 在有希望的初步数据的支持下,三个具体目标是
建议:1)预先确定结果的血管造影、功能和临床基线决定因素
CABG后,定义为心肌灌注改善(缺血减少)和心绞痛症状; 1992)
开发并验证综合成像策略和临床适用工具,
每支血管/病变的血管造影和定量功能信息(缺血、存活)分辨率
再血管化决策; 103)开发和验证新的多参数计算流模拟,
结合功能成像数据,可预测个体血流动力学结果
并最终基于虚拟血液动力学结果进行手术优化。 这种做法是创新的
因为新的成像技术将促进该领域对CABG生理学的理解,
将开发临床适用的工具,用于全面的临床决策和优化手术
规划所获得的知识和开发的工具适用于其他血管背景,并且可以
也有助于新的治疗创新。 这项研究意义重大,因为
冠状动脉旁路移植术结果决定因素的识别,以及综合决策制定的新解决方案,
程序指导,有可能提高有效性(通过完整的功能
再血管化)和CABG的效率(通过避免无效移植物)。 对于一大群患者来说,
创新将改善患者对CABG的益处(并发症,症状),
提高护理效率。
英文摘要
Project Summary
Coronary bypass graft surgery (CABG) improves the lives of patients with coronary disease (CAD) as a group,
but 20% of patients remain symptomatic one year after surgery. In clinical practice CABG decisions are largely
driven by stenosis severity determined from invasive angiography despite the known relevance of functional
CAD parameters. This practical impasse will continue to exist without clinically available, high-resolution,
quantitative functional imaging, and a better understanding of the clinical outcomes in relation to anatomical
(angiography) and functional (ischemia, scar tissue) factors. The long-term goal is to improve outcome of
CABG through personalized imaging-guided care. The overall objective of this proposal is to identify
determinants of myocardial flow restoration (ischemia reduction), and develop integrated imaging tools for
individualized, lesion-specific CABG decision-making, and computational flow simulations based on the
patient’s anatomy and function to predict the hemodynamic outcome. Supported by studies using invasive
FFR-guided CABG, the rationale for the proposed research is that integration of anatomical (angiography)
and functional information (ischemia, scar tissue) will identify individual coronary vessels that will benefit from
revascularization, and individual optimization of surgical procedures by flow simulations will maximize clinical
benefit of CABG for patients with CAD. Supported by promising preliminary data, three specific aims are
proposed: 1) Prospectively identify angiographic, functional and clinical baseline determinants of outcome
after CABG, defined as improvement of myocardial perfusion (ischemia reduction) and angina symptoms;; 2)
Develop and validate a comprehensive imaging strategy and clinically applicable tool that integrate high-
resolution angiographic and quantitative functional information (ischemia, viability) for per-vessel/lesion
revascularization decisions;; 3) Develop and validate new multi-parametric computational flow simulations,
with incorporation of functional imaging data, which allows for prediction of individual hemodynamic outcome
and ultimately surgical optimization based on virtual hemodynamic results. This approach is innovative
because new imaging techniques will advance the field’s understanding of CABG physiology, and new
clinically applicable tools will be developed for comprehensive clinical decision-making and optimized surgical
planning. The acquired knowledge and developed tools are applicable to other vascular contexts, and may
also be instrumental for new therapeutic innovations. The proposed research is significant because
identification of CABG outcome determinants, and new solutions for comprehensive decision-making and
procedural guidance, have the potential to improve the effectiveness (by complete functional
revascularization) and efficiency of CABG (by avoiding futile grafts). For a large group of patients, these
innovations will improve the patient-valued benefit of CABG (complications, symptoms), and also decrease
cost by improved efficiency of care.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
International Consortium for Multimodality Phenotyping in Adults with Non-compaction
-
批准号:10452602
-
项目类别:
-
资助金额:$72.35万
-
财政年份:2020
-
负责人:Koen Nieman
-
依托单位:
International Consortium for Multimodality Phenotyping in Adults with Non-compaction
-
批准号:10218265
-
项目类别:
-
资助金额:$73.33万
-
财政年份:2020
-
负责人:Koen Nieman
-
依托单位:
International Consortium for Multimodality Phenotyping in Adults with Non-compaction
-
批准号:9977674
-
项目类别:
-
资助金额:$80.58万
-
财政年份:2020
-
负责人:Koen Nieman
-
依托单位:
International Consortium for Multimodality Phenotyping in Adults with Non-compaction
-
批准号:10674511
-
项目类别:
-
资助金额:$71.26万
-
财政年份:2020
-
负责人:Koen Nieman
-
依托单位:
Comprehensive CT Guided Coronary Artery Bypass Graft Surgery
-
批准号:10599842
-
项目类别:
-
资助金额:$56.73万
-
财政年份:2019
-
负责人:Koen Nieman
-
依托单位:
Comprehensive CT Guided Coronary Artery Bypass Graft Surgery
-
批准号:10093121
-
项目类别:
-
资助金额:$71.86万
-
财政年份:2019
-
负责人:Koen Nieman
-
依托单位:
Multi-Disciplinary Training Program in Cardiovascular Imaging at Stanford
-
批准号:10441519
-
项目类别:
-
资助金额:$21.54万
-
财政年份:2008
-
负责人:Koen Nieman
-
依托单位:
Multi-Disciplinary Training Program in Cardiovascular Imaging at Stanford
-
批准号:10686299
-
项目类别:
-
资助金额:$32.79万
-
财政年份:2008
-
负责人:Koen Nieman
-
依托单位:
Multi-Disciplinary Training Program in Cardiovascular Imaging at Stanford
-
批准号:10641349
-
项目类别:
-
资助金额:$16.21万
-
财政年份:2008
-
负责人:Koen Nieman
-
依托单位:
Multi-Disciplinary Training Program in Cardiovascular Imaging at Stanford
-
批准号:10244883
-
项目类别:
-
资助金额:$30.55万
-
财政年份:2008
-
负责人:Koen Nieman
-
依托单位:
海外基金