Unique value of real-time shear stress to enhance coronary disease management

实时剪切应力对于加强冠心病管理的独特价值

• 批准号: 10065016
• 负责人: Peter Howard Stone
• 金额: $ 81.1万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10065016
• 关键词: 3-Dimensional; Algorithms; Anatomy; Angiography; Arterial Fatty Streak; Arteries; Atherosclerosis; Automobile Driving; Behavior; Blood Viscosity; Blood flow; Cardiac; Cardiac Catheterization Procedures; Catheterization; Catheters; Chest Pain; Clinical; Clinical Research; Clinical effectiveness; Computer Models; Computers; Consumption; Coronary; Coronary Arteriosclerosis; Coronary artery; Coronary heart disease; Coupled; Data; Devices; Diagnosis; Disease Management; Drops; Endothelial Cells; Endothelium; Environment; Event; Family suidae; Fluorescence; Friction; Future; Geometry; Goals; Gold; Hour; Human; Hyperemia; Image; Individual; Knowledge; Laboratories; Lead; Lesion; Liquid substance; Low-Density Lipoproteins; Maps; Measurement; Measures; Methods; Modeling; Myocardial Infarction; Natural History; Near-infrared optical imaging; Optical Coherence Tomography; Optics; Outcome; Patient-Focused Outcomes; Patients; Pattern; Permeability; Predictive Value; Prevention; Procedures; Process; Reproducibility; Research; Resources; Role; Running; Scanning; Shapes; Site; Stents; Surface; Syndrome; System; Techniques; Technology; Testing; Time; Ultrasonography; Use Effectiveness; accurate diagnosis; adverse outcome; base; clinical decision-making; clinical practice; coronary event; coronary lesion; coronary plaque; experience; image processing; image registration; improved; improved outcome; in vivo; multimodality; novel; percutaneous coronary intervention; personalized management; point of care; pressure; prevent; prognostic; protein complex; reconstruction; response; shear stress; simulation; single walled carbon nanotube

Management of CAD is hindered by our inability to investigate fundamental pathobiologic processes that lead to individual coronary plaque progression, destabilization, and adverse clinical events. A critical mechanism responsible for plaque behavior is local endothelial shear stress (ESS), the frictional force of blood flowing across the endothelium, which is governed by the artery’s detailed local geometry. Focal regions of low ESS drive a host of proatherogenic, proinflammatory, and prothrombotic processes; it is therefore not surprising that low ESS has now been found to be the most powerful predictor of future coronary events. However, current methods to compute local ESS in vivo require unique expertise and are extremely time- and resource-intensive, involving a lengthy, off-line procedure for reconstructing the 3D artery lumen from separate OCT and angiographic images and a computational fluid dynamics (CFD) simulation that takes many hours. These limitations prevent the use of this vital information to improve the treatment of patients. Our goal is to utilize ESS to guide optimal management during cardiac catheterization for patients with a broad array of coronary syndromes. We will accomplish this goal by developing and validating a single catheter/computer console system that will automatically compute ESS in real time (RT-ESS). Components include a novel, multimodality optical coherence tomography (OCT) catheter that senses its own shape by detecting strain-sensitive changes in fluorescence from single-walled carbon nanotubes (SWCNT) coated inside its sheath. Using OCT images acquired simultaneously with SWCNT fluorescence, we will develop algorithms to automatically create an anatomically-correct 3D artery model for CFD. By accelerating the CFD process, detailed ESS maps from human coronaries will be computed in 1-3 minutes and displayed with anatomic OCT images. The RT-ESS technology will be first validated using a swine coronary atherosclerosis model and then in patients undergoing percutaneous coronary intervention (PCI). In the final Aim, we will conduct a clinical study to determine the relationship between ESS and fractional flow reserve (FFR). The combination of pathobiologic/anatomic RT-ESS data and FFR will likely improve prognostication of individual coronary lesions, leading to more informed clinical decision-making and better patient outcomes.

CAD的管理受到我们无法研究基本病理生物学过程的阻碍 导致个体冠状动脉斑块进展、不稳定和不良临床事件。一个关键 导致斑块行为的机制是局部内皮剪切应力（ESS），即血液的摩擦力 流经内皮，这是由动脉的详细的局部几何形状。低气压聚焦区 ESS驱动一系列致动脉粥样硬化、促炎症和促血栓形成过程;因此，它不是 令人惊讶的是，低ESS现在已被发现是未来冠状动脉事件的最有力的预测因子。 然而，目前在体内计算局部ESS的方法需要独特的专业知识，并且非常耗时， 资源密集型，涉及用于从分离的血管重建3D动脉管腔的冗长的离线程序。 OCT和血管造影图像以及计算流体动力学（CFD）模拟需要数小时。 这些局限性阻碍了使用这些重要信息来改善患者的治疗。 我们的目标是利用ESS来指导患有以下疾病的患者在心导管插入术期间的最佳管理 一系列冠状动脉综合征我们将通过开发和验证一个 导管/计算机控制台系统，将自动计算ESS在真实的时间（RT-ESS）。组件 包括一种新颖多模态光学相干断层扫描（OCT）导管，其通过 检测来自单壁碳纳米管（SWCNT）的荧光的应变敏感变化， 在它的鞘里。使用OCT图像与SWCNT荧光同时获得，我们将开发 算法自动创建CFD的解剖学上正确的3D动脉模型。通过加速CFD 过程中，将在1 - 3分钟内计算来自人类冠状动脉的详细ESS图，并显示 解剖OCT图像。RT-ESS技术将首先使用猪冠状动脉粥样硬化进行验证 模型，然后在接受经皮冠状动脉介入治疗（PCI）的患者。在最后的目标中，我们将 进行临床研究以确定ESS和血流储备分数（FFR）之间的关系。的 病理生物学/解剖学RT-ESS数据和FFR的组合可能会改善个体 冠状动脉病变，导致更明智的临床决策和更好的患者结果。