A Nonlinear Membrane Based Analysis for Estimating the Rupture Potential of Abdominal Aortic Aneurysms

The overall goal of this problem-driven research project 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 AAA wall and intraluminal thrombus tissue properties. 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 yield an overall risk assessment accuracy greater than the current clinical standard of care (maximum diameter). 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 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.