QUANTITATION OF BIOMECHANICAL DETERMINANTS OF HUMAN AAA

我们的长期目标是定量地定义作用于人胸腹主动脉的不同血液动力学力，其导致血管壁中的生物力学应力和应变，其可能随着时间的推移导致主动脉壁的机械失效和动脉瘤扩大。 由于肾下腹主动脉特别容易形成动脉瘤，而胸主动脉具有抵抗力，我们将比较两段主动脉，以确定动脉瘤形成的诱发因素。 我们的假设是，血液动力学力和累积的生物力学应力和应变，沿着遗传易感性和叠加的致动脉粥样硬化和体液因素联合收割机，导致主动脉壁组织衰竭和动脉瘤形成。 这些因素相吻合，并在腹主动脉中放大，使其更容易发生AAA。我们将描述和对比人类腹主动脉和胸主动脉的结构，成分和生物力学特性，并确定主动脉壁的年龄相关变化。利用磁共振成像技术，我们将无创地评估年轻（20-35岁）和老年（60-75岁）正常成人以及AAA患者的胸主动脉和腹主动脉血流。 我们将确定三维脉动流场，并定量腹主动脉和胸主动脉之间主动脉壁应变的差异。 物理模型和体内动物实验将用于验证MR测量结果，并开发和验证计算方法，以建模和预测主动脉壁的生物力学应力和应变。这些数据将用于构建人体胸腹主动脉的计算模型，该模型表征在各种条件下的3D脉动流环境，例如运动状态、心输出量和血压的变化，并量化真实的时间主动脉壁应力和应变模式。 同样，我们将构建一个人类腹主动脉瘤的计算生物力学模型，该模型将能够计算随时间推移的累积主动脉壁应力负荷。 这将用于组织衰竭和动脉瘤扩大的预测建模，并将有助于评价旨在改变主动脉壁组织特征和基质结构的治疗策略，以及评价治疗策略，如主动脉覆膜支架和腹主动脉瘤开放修复术。

Our long term objective is to quantitively define the varying hemodynamic forces which act on the human thoracoabdominal aorta resulting in biomechanical stresses and strains in the vessel wall which may over time result in mechanical failure of the aortic wall and aneurysmal enlargement. Since the infrarenal abdominal aorta is particularly prone to aneurysm formation and the thoracic aorta is resistant, we will compare the two segments of aorta to determine predisposing factors for aneurysm formation. Our hypothesis is that hemodynamic forces and cumulative biomechanical stresses and strains, along with genetic susceptibility and superimposed atherogenic and humoral factors combine to result in aortic wall tissue failure and aneurysm formation. These factors, coincide, and are magnified in the abdominal aorta making it more prone to AAA. We will characterize and contrast the structural, compositional and biomechanical properties of the abdominal and thoracic aorta in humans and determine age related changes of the aortic wall. Utilizing MR imaging techniques, we will noninvasively assess thoracic and abdominal aortic blood flow in young (20-35 year old) and old (60-75 year old) normal adults as well as in patients with AAA. We will determine the 3 dimensional pulstaile flow field and quantitate differences in aortic wall strain between the abdominal and thoracic aorta. Physical models and in vivo animal experiments will be used to validate MR measurements and to develop and validate computational methods to model and predict biomechanical stress and strain of the aortic wall. These data will be used to construct a computational model of the human thoracoabdominal aorta which characterizes the 3 D pulsatile flow environment under a wide variation of conditions, such as changes in exercise states, cardiac output and blood pressure and quantify the real time aortic wall stress and strain pattern. Similarly, we will construct a computational biomechanical model of a human abdominal aortic aneurysm which will enable calculation of cumulative aortic wall stress loads over time. This will be used for predictive modeling of tissue failure and aneurysm enlargement and will be useful to evaluate strategies for therapies aimed at altering aortic wall tissue characteristics and matrix structure as well as in evaluating treatment strategies such as aortic stent grafts and open repair of the abdominal aortic aneurysms.