A NONLINEAR MEMBRANE BASED ANALYSIS FOR ESTIMATING THE RUPTURE POTENTIAL OF ABDOMINAL AORTIC ANEURYSMS

项目总结/摘要 这个问题驱动的研究的总体目标是提供一个概念验证策略， 基于非线性膜的腹主动脉瘤（AAA）破裂风险评估分析， 克服了基于有限元分析（FEA）的方法的科学和技术限制。本 最后，我们建议开发和应用一种方法来量化破裂潜力指数（RPI），不需要 了解AAA壁和腔内血栓的组织特性，也不需要估计 无应力AAA形状或残余应力，并且不需要FEA求解器。该方法 基于非线性弹性膜分析（NEMA）理论，由我们先前的几何工作机构提供信息 患者特定AAA模型的量化。因此，这是一种物理驱动的RPI定量方法。我们 还建议在进行前瞻性人类受试者研究时应用该方法，并评估其 根据其预测未来增长率的能力进行破裂风险评估的潜力。我们假设 一种计算RPI的新方法将能够以80%的最小概率预测未来AAA的增长率。 我们将完成以下具体目标，以实现上述目标，并测试拟议的 假设：（I）开发计算RPI的非FEA方法;（II）计算个体RPI和生长率， 监测AAA;（III）根据当前RPI对未来AAA增长进行预测分析。的 这项研究的主要预期成果是一种物理驱动的方法，用于预测未来AAA的增长， 使用当前标准护理腹部CT图像计算RPI。该方法没有局限性 典型的基于生物力学的方法。如果成功的话，这种方法可以 设想作为临床破裂风险评估的计算工具的一部分。

PROJECT SUMMARY / ABSTRACT The overall goal of this problem-driven research is to provide a proof-of-concept strategy for implementing a nonlinear membrane based analysis for abdominal aortic aneurysm (AAA) rupture risk assessment that overcomes the scientific and technological limitations of a finite element analysis (FEA)-based approach. To this end, we propose to develop and apply a method for quantifying rupture potential index (RPI) that does not require knowledge of the tissue properties of the AAA wall and intraluminal thrombus, nor does it need an estimation of the unstressed AAA shape or residual stresses, and does not require an FEA solver. The proposed method is based on nonlinear elastic membrane analysis (NEMA) theory, informed by our prior body of work on geometry quantification of patient-specific AAA models. Therefore, it is a physics-driven method for RPI quantification. We also propose to apply the method while conducting a prospective human subjects research study and assess its potential for rupture risk assessment based on its ability to predict future growth rates. We hypothesize that the new method for calculating RPI will be able to predict future AAA growth rate with a minimum probability of 80%. We will complete the following Specific Aims to accomplish the aforementioned goal and test the proposed hypothesis: (I) Develop a non-FEA approach for calculating RPI; (II) Calculate individual RPI and growth rate for AAAs under surveillance; and (III) Perform a predictive analysis of future AAA growth based on current RPI. The primary expected outcome of this research is a physics-driven method for predicting future AAA growth by calculating RPI using current, standard of care abdominal CT images. The method is devoid of the limitations that characterize typical biomechanics-based approaches. If proven successful, this approach could be envisioned as part of a computational tool for rupture risk assessment in the clinic.