Growth and Remodeling Model of Abdominal Aortic Aneurysm: Toward Clinical Applica

描述（由申请人提供）：在过去二十年中，对腹主动脉瘤（AAA）的病理生理学和生物力学的理解有了显著进展。 特别是，在计算生物力学分析中结合患者特定的几何形状，有望使计算生物力学成为AAA风险评估的重要工具。然而，传统的有限元分析仅使用医学成像的进步来定义患者特定的病变几何形状，而不将几何特征与扩大期间长期血管适应的生物力学改变相关联。我们先前研究了从三名患者的纵向研究中获得的小AAA的CT图像，并使用生长和重塑（G&R）模型， 本课题组开发的AAAs，发现AAAs的应力分布可以通过与椎体的相互作用而改变。我们与韩国首尔国立大学医院的Whal Lee博士合作，从另外8名患者中获得了2至9组随访CT图像，平均监测间隔为355天。因此，该项目的主要目标是i）利用这一独特的数据，从生物力学上理解为什么观察到的AAA形态发生变化，ii）识别将更好地估计应力分布的特定形态特征，以及iii）基于医学图像和少量纵向研究的计算分析，开发一个计算框架，以更好地预测小型AAA的破裂风险。具体目标是：（1）利用一系列3D CT图像开发定量图像分析以表征AAA的形态学变化，并研究几何参数与局部扩张之间的相关性，（2）提出了一种新的G& R模型和来自同一患者的两个纵向图像来预测病变几何形状的演变，（3）利用Aim &2的结果和AAA的G&R模型研究局部壁膨胀和与脊椎的相互作用对病变几何形状、应力分布和破裂风险。 这项研究的独特性源于我们新颖的G&R模型和独特的纵向患者数据集，这对建立和验证此类模型至关重要。拟议的研究将显着增加我们对AAAs进展过程中生物力学的理解，并将为临床应用提供必要的一步。 血管G&R模型用于AAA风险评估和治疗。

DESCRIPTION (provided by applicant): During the past two decades, there have been significant advances in understanding of pathophysiology and biomechanics of abdominal aortic aneurysms (AAAs). In particular, incorporation of patient-specific geometries in computational biomechanical analysis promises that the computational biomechanics becomes an essential tool for AAA risk assessment. Conventional finite element analysis, however, uses advances in medical imaging only to define patient-specific lesion geometry, but do not relate the geometrical features with alterations in biomechanics from long-term vascular adaptation during the enlargement. We previously studied CT images of small AAAs obtained from longitudinal studies of three patients and, using a growth and remodeling (G&R) model of AAAs developed from our group, found that the stress distribution of AAAs can be altered by interacting with spine vertebrae during the enlargement. In collaboration with Dr. Whal Lee at Seoul National University Hospital in South Korea, we have obtained two to nine sets of follow-up CT images from eight more patients with the mean surveillance interval of 355 days. The main goals of this project, therefore, are i) to exploit this unique data ad to understand biomechanically why the observed changes in morphology of AAAs occur, ii) to identify specific morphological features that will estimate the stress distribution better and iii) to develop a computational framework to better predict rupture risk for small AAAs based on medical images and computational analyses over a small number of longitudinal studies. The specific aims are: (1) to develop a quantitative image analysis to characterize morphological changes of AAAs using series of 3D CT images, and investigate correlations between geometrical parameters and the local expansion, (2) to develop a numerical inverse method using a novel G&R model and two longitudinal images from the same patient to predict the evolution of lesion geometry, and (3) to utilize the results from Aim &2 and the G&R model of AAAs to study effects of local wall expansion and interactions with the spinal vertebrae on the lesion geometry, stress distribution, and rupture risk. The uniqueness of this research stems from our novel G&R model and the unique set of longitudinal patient data that is essential for building and validating such models. The proposed research will significantly increase our understanding of biomechanics of AAAs during their progression and will provide a necessary step toward the clinical application of vascular G&R models for AAA risk assessment and treatment.