Multiscale modeling for vein graft failure risk stratification in CABG patients

描述（由申请人提供）：冠状动脉旁路移植术（CABG）手术是晚期冠状动脉疾病患者的金标准治疗，在美国每年有超过40万例病例。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，但其使用受到可用性的限制，并且大隐静脉移植物（SVG）用于大多数患者。CABG手术后，SVG失败的发生率高得惊人，5- 10%的SVG在手术后第一个月内闭塞，40-50%的SVG在10年内失败。已知SVG疾病的风险和移植物失效的复杂机械生物学与机械刺激相关，包括血液动力学和血管壁力学。然而，标准的计算机断层扫描（CT）成像没有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特性的生理闭环模拟，避免了理想化解剖结构、刚性壁和不完整冠状动脉模型的先前限制。我们提出了一种新的冠状动脉模拟框架，可以全面表征旁路移植物的血流动力学和壁力学，只使用非侵入性的临床数据。我们建议，真实的血流动力学和室壁运动的有效模拟，与现代成像技术相结合，将使CABG后风险分层和早期识别隐静脉移植物高风险患者成为可能 失败为了实现这些目标，我们提出了三个具体目标：1）设计和验证一种新的闭环多尺度CABG模拟框架，该框架可以仅使用非侵入性临床数据来预测局部血流动力学和壁力学，2）量化和比较作用于患者特定模型中的动脉和静脉移植物的机械刺激，以及3）开发 通过将机械刺激与有和无SVG疾病的血管的临床结局相关联，对CABG后患者进行试点风险分层评分系统。拟议的工作是重要的和创新的，因为它将（1）使用患者特定的模拟来虚拟地逆转SVG疾病，从而使用患者作为自己的对照（2）使早期识别患者， SVG阻塞的风险增加，其结果可以通过更密集的治疗和监测来改善，（3）实现依赖于机械刺激数据的未来血管壁生长和重塑模拟，（4）将高分辨率成像与完整冠状动脉循环的复杂多尺度建模相结合，以及（5）根据临床数据直接验证模型预测并报告模拟结果的置信区间。该项目汇集了一个独特的团队，包括一名具有物理学背景的成人心脏病专家和成像专家，以及一个具有心血管生物力学专业知识的工程团队。我们将在患者特定血流模拟方面积累丰富的经验，并在临床翻译和多学科合作方面取得成功。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，并改善结局。

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.