Advancing a Novel, Density-Driven, Non-Invasive Thoracic Aortic Aneurysm Strength Assessment Tool

About This Grant

Project Summary Thoracic aortic aneurysms (TAA) are irreversible focal dilatations of the aorta. Unrepaired TAAs can lead to death following dissection or rupture. TAA dissection and rupture signifies a biomechanical failure of the TAA tissue where the pressure-induced wall stress surpasses the wall strength. Therefore, a reliable assessment of the wall strength and stress in a given TAA could be a powerful tool for predicting TAA failure. As a TAA progresses, the stress acting on it increases, and the wall strength decreases due to breakdown and damage to the extracellular matrix. While non-invasive estimation of wall stress in TAA through finite element analysis and other techniques is well-established, accurate non-invasive assessment of tissue strength for direct comparison to stress has been elusive in the advent of biomechanics-based assessments for use in TAA care. Studies have established the tensile strength of TAA through uniaxial extension testing, including a mathematical model for the prediction of abdominal TAA wall strength distribution. The algorithm was built using multi-variate linear regression on several patient- and location-specific metrics and regional uniaxial tissue strength measurements. However, the predictive power of this algorithm is only as reliable and robust as the data used to construct it. For example, strength assessed via uniaxial tensile testing assumes material isotropy and homogeneity when TAA tissue is anisotropic and heterogeneous. Further, TAA's physiologic loading is multiaxial, not applied in one direction. Additionally, if the variables used to predict the strength are too few or not robustly measured, the algorithm's accuracy can be decreased. This proposal aims to improve the non-invasive estimation of patient-specific TAA wall strength distribution to enable a translatable, biomechanics-based risk assessment tool for TAA. Broadly, this proposal aims to 1) improve the accuracy and physiologic relevance of the TAA wall strength measurements used in a strength- predicting algorithm and 2) increase the number and robustness of patient- and location-specific variables for more accurate prediction of that strength. Goal 1 will be achieved by employing Bubble Inflation Testing (BIT), which provides more physiologically realistic loading conditions for TAA tissue than uniaxial loading and would provide more accurate tissue strength. BIT has been applied to ascending TAA tissue, revealing dissection-like failure mechanisms, but not to descending TAA or non-aneurysmal aortic tissue. Goal 2 will be achieved by leveraging the microstructural alterations that specify aneurysmal degeneration and weakening and considering density-driven failure, which has been demonstrated in engineered materials. This F31 Fellowship application aims to improve the estimation of TAA tissue strength distribution through innovative and novel approaches. Successful execution of this work could lead to a translatable technology for assessing rupture risk on a patient-specific basis by providing accurate estimates of TAA wall strength.