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：
9031871
负责人：
Boyce Eugene Griffith
金额：
$ 44.63万
依托单位：
UNIV OF NORTH CAROLINA CHAPEL HILL
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 2018-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9031871
关键词：
Accounting Acute Address Affect Anatomy Animal Model Aorta Aortic Diseases Arteriographies Automobile Driving Blood Blood Circulation Blood Pressure Blood Vessels Blood flow Caliber Chronic Clinical Clinical Management Computer Simulation Data Development Disease Dissection Distal Eating Elasticity Ensure Genetic Geometry Goals Health Human Image Implant Intervention Lesion Liquid substance Magnetic Resonance Magnetic Resonance Imaging Mechanics Medical Methodology Methods Modeling Operative Surgical Procedures Outcome Pathology Patient risk Patients Pattern Physicians Physiological Plant Roots Play Property Residual state Risk Risk Assessment Role Rupture Shapes Specimen Stents Stress Structure Surgical Flaps Surgical Management Syndrome Testing Thoracic aorta Time Tissue Sample Tissues Tube Work X-Ray Computed Tomography ascending aorta base clinical decision-making dacron experience hemodynamics high risk implantation improved in vivo innovation mathematical model mortality non-compliance physical model predictive modeling repaired research study 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, although our understanding of the genetic and cellular bases of such diseases has steadily grown, treatment planning still generally relies on simple risk-assessment models and clinical experience. Some pathological conditions have been mimicked with animal models, but results from such studies may not be 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. Because there are no accepted animal models of aortic dissection, experimental studies 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 tissues, or for the effects of such interactions on the dynamics of the dissected aorta. This project will develop fluid-structure interaction (FSI) models of aortic dissection that overcome th 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 an idealized description of the geometry of the vessel and lesion. Such models are ideally suited for addressing questions that take the form of parameter studies. These 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 patient-specific anatomy by using geometries derived from computed tomography (CT) and/or magnetic resonance (MR) imaging studies. To characterize the elastic response of human aortic tissue, tissue samples will be collected from both normal and diseased human aortas, and tensile tests will be performed to characterize the mechanical properties of these specimens. The data from these tests will be used to develop corresponding healthy and disease-specific constitutive models. The characterization of the elasticity of both the healthy and diseased human aorta has the potential to impact work on a broad range of aortic diseases. Finally, these models will be used to study the medical and surgical management of patients who require or who have undergone only partial surgical repair of the dissection, as is now commonly done in cases in which the dissection involves the proximal ascending aorta (Type A dissections).

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，尽管我们对这些疾病的遗传和细胞基础的理解稳步增长，但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。某些病理状况已经模仿了动物模型，但是此类研究的结果可能不容易被外推向患者。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代一部分主动脉，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。由于没有公认的主动脉夹层动物模型，因此实验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组织之间的相互作用，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模型限制的主动脉夹层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。第一类模型将使用对容器几何形状的理想描述和病变。这样的模型非常适合解决采用参数研究形式的问题。这些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源自计算机断层扫描（CT）和/或磁共振（MR）成像研究的几何形状来解释患者特异性解剖结构的影响。为了表征人主动脉组织的弹性反应，将从正常和患病的人主动脉中收集组织样品，并将进行拉伸测试以表征这些标本的机械性能。这些测试的数据将用于开发相应的健康和疾病特异性的本构模型。健康和患病的人主动脉弹性的表征有可能影响多种主动脉疾病的工作。最后，这些模型将用于研究需要或仅经过部分手术修复解剖的患者的医学和外科手术管理，如现在通常涉及近端升主（type a dissections）的情况下通常所做的那样。）。