Multiscale modeling for vein graft failure risk stratification in CABG patients

描述(由申请人提供)：冠状动脉旁路移植(CABG)手术是晚期冠状动脉疾病患者的黄金标准治疗方法，在美国每年有超过40万例患者接受手术。虽然动脉移植物与静脉移植物相比具有更大的长期通畅性，但它们的使用受到可用性的限制，而大隐静脉移植物(SVG)在大多数患者中使用。冠状动脉旁路移植术后，SVG失败率高得惊人，5%-10%的SVG在术后1个月内闭塞，40%-50%的SVG在10年内失败。众所周知，SVG病的风险和移植物失败的复杂机械生物学与机械刺激有关，包括血流动力学和血管壁力学。然而，标准的计算机断层扫描(CT)成像不提供直接的手段来表征这些刺激。多尺度建模的最新进展现在允许具有真实材料属性的生理闭环模拟，避免了先前理想化解剖结构、坚硬的壁和不完整的冠状动脉模型的限制。我们提出了一种新的冠状动脉模拟框架，它可以仅使用非侵入性临床数据来综合表征搭桥血管的血流动力学和壁力学。我们认为，经过验证的模拟真实的血流动力学和室壁运动，结合现代成像技术，将使冠状动脉旁路移植术后的风险分层和早期识别具有大隐静脉移植物高危风险的患者。 失败了。为了实现这些目标，我们提出了三个具体的目标：1)设计和验证一个新的闭环多尺度CABG仿真框架，该框架可以仅使用非侵入性的临床数据来预测局部血流动力学和壁力学；2)在特定患者的模型中量化和比较作用于动脉和静脉移植物的机械刺激；以及3)开发一个 通过将机械刺激与有无SVG疾病的血管的临床结果相关联，为CABG术后患者试行风险分层评分系统。拟议的工作具有重大意义和创新性，因为它将(1)使用特定于患者的模拟来虚拟逆转SVG疾病，从而将患者作为自己的对照(2)使患者能够在 (3)可根据机械刺激数据进行未来的血管壁生长和重塑模拟，(4)将高分辨率成像与复杂的完整冠状动脉循环多尺度建模相结合，(5)直接对照临床数据验证模型预测，并报告模拟结果的可信区间。该项目组建了一支独特的团队，其中包括一名具有物理学背景的成年心脏病专家和成像专家，以及一支在心血管生物力学方面拥有成熟专业知识的工程团队。我们将基于我们在患者特定血流模拟方面的丰富经验，以及在临床翻译和多学科合作方面的成功记录。我们的翻译目标是为临床医生提供新的工具，以改善有移植失败风险的CABG患者的管理决策，并改善结果。

DESCRIPTION (provided by applicant): Coronary artery bypass graft (CABG) surgery is a gold standard treatment for patients with advanced coronary artery disease, with over 400,000 cases performed each year in the US. While arterial grafts have greater long- term patency compared to vein grafts, their use is limited by availability, and saphenous vein grafts (SVGs) are used in the majority of patients. Following CABG surgery, SVG failure occurs at alarmingly high rates, with 5- 10% of SVGs occluding within the first month after surgery, and 40-50% of SVGs failing within 10 years. The risk of SVG disease and the complex mechanobiology of graft failure are known to be associated with mechanical stimuli, including hemodynamics and vessel wall mechanics. However, standard computed tomography (CT) imaging provides no direct means to characterize these stimuli. Recent advances in multiscale modeling now permit physiologic closed-loop simulations with realistic material properties, avoiding prior limitations f idealized anatomy, rigid walls, and incomplete coronary models. We propose a novel coronary simulation framework that can comprehensively characterize bypass graft hemodynamics and wall mechanics using only non-invasive clinical data. We propose that validated simulations with realistic hemodynamics and wall motion, in concert with modern imaging techniques will enable post-CABG risk stratification and early identification of patients at high risk for saphenous graft failure. To accomplish these goals, we propose three specific aims: 1) design and validate a novel closed-loop multiscale CABG simulation framework that can predict local hemodynamics and wall mechanics using only non-invasive clinical data, 2) quantify and compare the mechanical stimuli acting on arterial and vein grafts in patient- specific models, and 3) develop a pilot risk stratification scoring system for post-CABG patients by correlating mechanical stimuli with clinical outcomes in vessels with and without SVG disease. The proposed work is significant and innovative because it will (1) use patient-specific simulations to virtually revers SVG disease thus using patients as their own control (2) enable early identification of patients at increased risk of SVG obstruction whose outcomes may be improved by more intensive treatment and monitoring, (3) enable future vessel wall growth and remodeling simulations which rely on mechanical stimuli data, (4) combine high resolution imaging with sophisticated multiscale modeling of the complete coronary circulation, and (5) directly validate model predictions against clinical data and report confidence intervals on simulation results. This project assembles a unique team including an adult cardiologist and imaging specialist with a background in physics, and an engineering team with established expertise in cardiovascular biomechanics. We will build upon our extensive experience with patient-specific blood flow simulations, and a successful track record of clinical translation and multi-disciplinary collaboration. Our translational goal is to provide clinicians with new tools to improve management decisions for CABG patients at risk for graft failure and improve outcomes.