Multiscale modeling for vein graft failure risk stratification in CABG patients

冠状动脉旁路移植术（CABG）是治疗晚期冠状动脉疾病的金标准。 动脉疾病，在美国每年有超过40万例。虽然动脉移植物具有更长的- 与静脉移植物相比，它们的使用受到可用性的限制，并且隐静脉移植物（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在术后第一个月内闭塞，40-50%的SVG在10年内失效。的 已知SVG疾病的风险和移植物失败的复杂机械生物学与以下因素相关： 机械刺激，包括血液动力学和血管壁力学。然而，标准计算 断层摄影（CT）成像没有提供表征这些刺激的直接手段。的最新进展 多尺度建模现在允许生理闭环模拟与现实的材料属性，避免 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 能够综合表征旁路移植物血流动力学和壁的冠状动脉模拟框架 仅使用非侵入性临床数据的力学。我们建议，验证模拟与现实 血流动力学和室壁运动，与现代成像技术相结合， 隐静脉移植失败高危患者的风险分层和早期识别。到 为了实现这些目标，我们提出了三个具体的目标：1）设计和验证一种新的闭环多尺度 CABG模拟框架，可预测局部血流动力学和壁力学，仅使用非侵入性 临床数据，2）量化和比较作用于患者动脉和静脉移植物的机械刺激， 特定模型，以及3）通过关联，为CABG后患者开发一个试点风险分层评分系统 机械刺激与有无SVG疾病的血管的临床结局。拟议的工作是 重要和创新，因为它将（1）使用患者特定的模拟来虚拟地逆转SVG疾病 因此使用患者作为其自身对照（2）能够早期识别SVG风险增加的患者 通过更强化的治疗和监测可以改善结果的梗阻，（3）使未来 依赖于机械刺激数据的血管壁生长和重塑模拟，（4）联合收割机高 分辨率成像与完整冠状动脉循环的复杂多尺度建模，以及（5）直接 根据临床数据验证模型预测，并报告模拟结果的置信区间。这 该项目汇集了一个独特的团队，包括一名成人心脏病专家和成像专家， 物理学，以及在心血管生物力学方面具有成熟专业知识的工程团队。我们将建立 基于我们在患者特定血流模拟方面的丰富经验，以及 临床翻译和多学科合作。我们的翻译目标是为临床医生提供新的 用于改善有移植失败风险的CABG患者的管理决策并改善结局的工具。

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 of 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 reverse 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.