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

描述(由申请人提供)：在过去的二十年里，对腹主动脉瘤(AAA)的病理生理学和生物力学的了解有了显著的进步。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，传统的有限元分析只利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张术期间长期血管适应所引起的生物力学变化联系起来。我们之前研究了从三名患者的纵向研究中获得的小AAA的CT图像，并使用了生长和重塑(G&R)模型 AAAS由本课题组发展而来，发现AAAS在扩大过程中与脊柱相互作用，可以改变AAAS的应力分布。与韩国首尔国立大学医院的Whal Lee博士合作，我们从另外8名患者那里获得了2至9组随访CT图像，平均监测间隔为355天。因此，本项目的主要目标是：i)利用这一独特的数据来了解观察到的腹主动脉形态变化发生的生物力学原因；ii)识别特定的形态特征，以便更好地估计应力分布；iii)开发一个基于医学图像和少量纵向研究的计算分析的计算框架，以更好地预测小型腹主动脉的破裂风险。其具体目标是：(1)利用一系列三维CT图像建立定量图像分析来表征AAA的形态变化，并研究几何参数与局部扩张之间的相关性；(2)利用新的G&R模型和来自同一患者的两幅纵向图像建立数值逆方法来预测病变几何形状的演变；以及(3)利用AIM&2和AAA的G&R模型的结果来研究局部壁扩张以及与脊柱的相互作用对病变几何形状、应力分布和破裂风险的影响。这项研究的独特性源于我们新的G&R模型和独特的纵向患者数据集，这是建立和验证此类模型所必需的。拟议的研究将显著增加我们对腹主动脉进展过程中生物力学的理解，并将为腹主动脉的临床应用提供必要的步骤。 用于AAA风险评估和治疗的血管G&R模型。

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.