Computational modeling of platelets and thrombosis in cerebral aneurysm treatment

脑动脉瘤治疗中血小板和血栓形成的计算模型

• 批准号: 10734495
• 负责人: Michael Robert Levitt
• 金额: $ 43.64万
• 依托单位: UNIVERSITY OF WASHINGTON
• 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 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10734495
• 关键词: Aftercare; Aneurysm; Animal Model; Animals; Area; Attention; Biological; Blood; Blood Coagulation Factor; Blood Platelets; Blood Vessels; Blood flow; Brain hemorrhage; Cerebral Aneurysm; Clinical; Computer Models; Computer Simulation; Decision Making; Devices; Environment; Failure; Feasibility Studies; Foundations; Funding; Goals; Histologic; Histology; Human; In Vitro; Liquid substance; Methodology; Methods; Modeling; Oryctolagus cuniculus; Outcome; Patients; Platelet aggregation; Prevalence; Prevention; Prognosis; Public Health; Radiology Specialty; Recording of previous events; Recurrence; Research; Retreatment; Risk; Role; Rupture; Ruptured Aneurysm; Stents; Therapeutic Embolization; Thrombosis; Thrombus; Time; Tissues; Treatment Failure; Treatment outcome; Uncertainty; United States National Institutes of Health; Work; blood product; cerebral hemodynamics; clinical predictors; cohort; direct application; experience; healing; hemodynamics; holistic approach; improved; in vivo; innovation; insight; novel; outcome prediction; particle; predict clinical outcome; residence; shear stress; simulation; success; treatment risk

Here we seek to improve the accuracy of hemodynamic modeling of cerebral aneurysms. This goal of this project is to predict the outcome of cerebral aneurysm treatment. This is significant due to the prevalence of cerebral aneurysms, their dismal prognosis when ruptured, and treatment failure rates (resulting in aneurysm recurrence and risk of either brain hemorrhage or need for retreatment) of up to 40%. Hemodynamic forces are thought to influence aneurysm treatment outcomes, and can be simulated using computational fluid dynamics (CFD) methods, but such studies have not been widely accepted due to conflicting results. Traditional CFD analysis (termed “Eulerian” metrics) only studies the effect of blood flow on the vascular walls, largely ignoring circulating blood products such as platelets that initiate intra-aneurysmal thrombosis (termed “Lagrangian” metrics), which have a critical role in treatment outcome. Better prediction through a holistic approach combining both types of analyses could identify patients at risk for treatment failure, influencing pre-surgical decision-making. This project builds on our ongoing NIH-funded expertise (via a renewal of R01NS105692) in the CFD modeling of cerebral aneurysms before and after treatment. We have developed an innovative method of incorporating novel Lagrangian metrics, such as residence time and shear history, into CFD simulations in with existing Eulerian hemodynamic metrics, to create a holistic approach to modeling the effects of aneurysm treatment. Feasibility studies have characterized the post-treatment hemodynamic environment with special attention to platelet-representative particles that experience prolonged intra-aneurysmal residence time and low cumulative shear history within treated aneurysms. Previous in vitro studies of platelets in similar conditions demonstrate thrombosis in such environments, which would be advantageous after aneurysm treatment to develop a stable thrombus leading to aneurysm healing. First, we will perform CFD simulations before and after treatment on a cohort of cerebral aneurysms whose treatment outcome (success or failure) is known. We will include both Eulerian and Lagrangian metrics to determine associations with treatment outcome. Second, we will use an established animal model of cerebral aneurysms, treated with commercially-available endovascular devices. We will perform CFD simulations a similar holistic model as the human aneurysm cohort, and investigate the relationship between Lagrangian metrics and treatment-related thrombosis on histological analysis. The final result will be an optimized CFD methodology and set of Eulerian and Lagrangian variables predictive of outcome after cerebral aneurysm embolization.

在这里，我们试图提高脑动脉瘤血流动力学建模的准确性。这样做的目的是 该项目是为了预测脑动脉瘤的治疗结果。这一点意义重大，因为 脑动脉瘤，破裂时的悲惨预后，以及治疗失败率(导致动脉瘤 复发和脑出血或需要重新治疗的风险)高达40%。血液动力学力量是 被认为会影响动脉瘤的治疗结果，并可以用计算流体力学进行模拟 (CFD)方法，但由于结果相互矛盾，此类研究尚未被广泛接受。传统CFD 分析(称为欧拉指标)只研究血液流动对血管壁的影响，基本上忽略了这一点 引起动脉瘤内血栓形成的循环血液产物，如血小板(称为“拉格朗日”) 指标)，这些指标对治疗结果具有关键作用。通过整体方法进行更好的预测 结合这两种类型的分析可以确定有治疗失败风险的患者，影响手术前 决策。 该项目建立在我们正在进行的NIH资助的CFD专业知识(通过更新R01NS105692)的基础上 治疗前后脑动脉瘤模型的建立。我们开发了一种创新的方法 将新的拉格朗日指标，如停留时间和剪切历史，纳入到CFD模拟中 现有的欧拉血流动力学指标，以创建一种整体方法来模拟动脉瘤的影响 治疗。可行性研究表明，治疗后的血流动力学环境具有特殊的特点 注意具有代表血小板的颗粒在动脉瘤内停留时间延长和 治疗后动脉瘤内累积剪切史较低。血小板的体外研究已有报道 情况表明在这种环境下血栓形成，这将是动脉瘤后的有利条件。 治疗形成稳定的血栓，导致动脉瘤愈合。 首先，我们将对一组脑动脉瘤进行治疗前后的CFD模拟 其治疗结果(成功或失败)是已知的。我们将包括欧拉度量和拉格朗日度量。 以确定与治疗结果的相关性。第二，我们将使用已建立的动物模型 使用商业血管内设备治疗脑动脉瘤。我们将执行CFD 模拟与人类动脉瘤队列相似的整体模型，并调查两者之间的关系 拉格朗日指标与治疗相关血栓形成的组织学分析。最终结果将是一个 优化的CFD方法和欧拉和拉格朗日变量集预测脑损伤后的预后 动脉瘤栓塞术。