Mathematical modeling and computer simulation of aortic dissection

主动脉夹层的数学建模和计算机模拟

基本信息

批准号：
8581495
负责人：
Boyce Eugene Griffith
金额：
$ 51.65万
依托单位：
NEW YORK UNIVERSITY SCHOOL OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-08-26 至 2018-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8581495
关键词：
Accounting Acute Affect Anatomy Animal Model Aorta Aortic Diseases Automobile Driving Blood Blood Pressure Blood Vessels Caliber Chronic Clinical Clinical Management Clinical Pathology Computer Simulation Data Descending aorta Disease Dissection Distal Elasticity Ensure Failure Genetic Goals Health Human Human Characteristics Image Implant Injury Intervention Lesion Liquid substance Location Magnetic Resonance Imaging Mechanics Medical Methodology Methods Modeling Operative Surgical Procedures Outcome Pathology Patients Pattern Physicians Plant Roots Play Property Research Residual state Risk Risk Assessment Role Rupture Shapes Simulate Site Stents Stress Structure Study models Surgical Flaps Syndrome Testing Thoracic aorta Time Tissue Model Tissue Sample Tissues Work X-Ray Computed Tomography aortic arch ascending aorta base clinical decision-making experience hemodynamics high risk implantation improved in vivo innovation mathematical model mortality physical model predictive modeling pressure public health relevance repaired response shear stress simulation treatment planning treatment strategy valve replacement

项目摘要

DESCRIPTION (provided by applicant): Management of aortic diseases has progressed dramatically since the first successful, reproducible surgical intervention in 1956; however, while our understanding of the genetic and cellular bases of these diseases has steadily grown, treatment planning still generally relies on simple risk-assessment models and clinical experience. Some pathologies have been successfully replicated in animal models, but results from such studies are not always readily extrapolated to patients. Other pathologies lack any accepted or reproducible animal model. An example is aortic dissection, in which an intimal tear in the aortic wall propagates into the media to form a false lumen within the vessel wall. Surgical treatment for aortic dissection consists of either replacement of a portion of the aorta or endovascular stent implantation to cover the affected segment. Both approaches carry significant risks, and determining the optimal choice and timing of an intervention is challenging. While aortic dissections can be induced in animal models, such models do not replicate the clinical pathology. Consequently, modeling studies of aortic dissection must use physical or computational models. Existing computational models of aortic dissection use conventional computational fluid dynamics (CFD) approaches, in which the vessel wall and flap are treated as rigid structures. Although CFD models are able to predict wall shear stress distributions, they are unable to account for the interactions between the blood and vascular tis- sues, or for the effects of such interactions on the dynamics of the dissected aorta. This project will develop fluid-structure interaction (FSI) models of both the dissected and dissecting aorta that overcome the limitations of CFD models. These predictive models will be used to perform patient-specific simulations that ultimately will aid in clinical decision making, e.g., selecting optimal medical therapies or surgical interventions. This project will develop two types of FSI models of aortic dissection. The first type of model will use a geometrically parameterized, non-patient-specific model of the vessel and lesion. Such models will be used to study systematically how geometry and driving conditions affect the dynamics of both developing dissections and fully developed lesions. The second type of model will account for the effects of subject-specific anatomy by using realistic patient anatomical geometries derived from computed tomography (CT) and/or magnetic resonance (MR) imaging studies. To characterize the mechanical response and the damage and failure characteristics of human aortic tissue, experimental tests will be performed using tissue samples collected from both normal and diseased human aortas. Data from these tests will be used to develop healthy and disease-specific constitutive models that include innovative models of tissue damage and failure. The impact of these characterizations is not limited to aortic dissection, and this work has potential applications to a range of arterial pathologies, including aneurysmal rupture. Finally, these models will be used to study the surgical and medical management of patients who require or who have undergone partial repair of a Stanford Type A dissection.

描述（由申请人提供）：自1956年首次成功，可重复的手术干预以来，主动脉疾病的管理已取得了巨大进展；但是，我们对这些疾病的遗传和细胞基础的理解已经稳步增长，治疗计划通常仍然依赖于简单的风险评估模型和临床经验。在动物模型中已成功复制了一些病理，但是此类研究的结果并不总是很容易推断为患者。其他病理缺乏任何可接受或可重复的动物模型。一个例子是主动脉夹层，其中主动脉壁中的内膜撕裂传播到培养基中，在容器壁内形成一个假管腔。外科主动脉夹层的治疗包括替换一部分主动脉植入或血管内支架植入以覆盖受影响的段。两种方法都有很大的风险，确定干预的最佳选择和时机具有挑战性。虽然可以在动物模型中诱导主动脉解剖，但这种模型不会复制临床病理。因此，对主动脉夹层的建模研究必须使用物理或计算模型。主动脉夹层的现有计算模型使用常规计算流体动力学（CFD）方法，其中容器壁和皮瓣被视为刚性结构。尽管CFD模型能够预测壁剪应力分布，但它们无法说明血液和血管促进之间的相互作用，或者这种相互作用对解剖主动脉动力学的影响。该项目将开发出克服CFD模型局限性的解剖主动脉和解剖主动脉的流体结构相互作用（FSI）模型。这些预测模型将用于执行特定于患者的模拟，最终将有助于临床决策，例如选择最佳的医疗疗法或手术干预措施。该项目将开发两种类型的FSI主动脉夹层模型。第一类模型将使用血管和病变的几何参数化的，非患者特异性的模型。这样的模型将用于系统地研究几何和驱动条件如何影响开发解剖和完全发育的病变的动态。第二种模型将通过使用来自计算机断层扫描（CT）和/或磁共振（MR）成像研究的现实患者解剖几何形状来解释受试者特异性解剖学的影响。为了表征人主动脉组织的机械反应以及损伤和失效特征，将使用从正常人和患病的人主动脉收集的组织样本进行实验测试。这些测试的数据将用于开发健康和疾病特异性的本构模型，包括组织损伤和失败的创新模型。这些特征的影响不仅限于主动脉夹层，而且这项工作可能应用于一系列动脉病理，包括动脉瘤破裂。最后，这些模型将用于研究需要或经过部分修复A型A型的患者的手术和医疗管理。