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

项目摘要/摘要 这项以问题为导向的研究的总体目标是为实施 腹主动脉瘤(AAA)破裂风险评估的非线性膜分析 克服了基于有限元分析(FEA)方法的科学和技术限制。对这件事 最后，我们建议开发和应用一种量化破裂潜在指数(RPI)的方法，该方法不需要 对AAA壁和腔内血栓的组织特性的了解，也不需要估计 非应力AAA形状或残余应力，不需要有限元求解器。建议的方法是 基于非线性弹性膜分析(NEMA)理论，受我们先前的几何工作的启发 量化特定患者的AAA模型。因此，这是一种物理驱动的RPI量化方法。我们 我还建议在进行预期的人类受试者研究时应用该方法，并评估其 基于其预测未来增长率的能力，有可能进行破裂风险评估。我们假设 计算RPI的新方法将能够预测未来AAA增长率，最小概率为80%。 我们将完成以下具体目标，以实现上述目标并检验拟议的 假设：(I)开发计算RPI的非有限元方法；(Ii)计算个人RPI和增长率 监测下的AAA；以及(Iii)根据当前RPI对AAA未来增长进行预测分析。这个 这项研究的主要预期结果是一种物理驱动的方法，通过以下方式预测未来的AAA增长 使用当前护理标准的腹部CT图像计算RPI。这种方法没有任何局限性。 这是典型的基于生物力学的方法的特征。如果被证明成功，这种方法可能会 被设想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.