Developing Biomechanical Predictors of Ascending Thoracic Aortic Aneurysm Growth and Dissection

Veterans Affairs (VA) Healthcare System services >9 million veterans at 144 hospitals nationwide. Aortic aneurysms are the 16th leading cause of death in patients >35 years old in the United States. Dissection and rupture of aTAAs are catastrophic cardiovascular emergencies carrying significant pre-hospital (40%) and operative (17-25%) mortality. Surgical guidelines rely on aTAA maximum diameter, growth rate, and symptoms to guide elective repair, which can be performed with low operative mortality. However, we and others have demonstrated that diameter alone is not adequate to predict dissection or rupture—~60-90% of type A dissection events occur in aTAAs with diameter <5.5cm and otherwise not meeting elective surgical repair indications. From a biomechanics perspective, rupture or dissection is a mechanical failure that can occur when aneurysm wall stress exceeds wall strength. Guidelines simply use diameter as a surrogate for wall stress based on LaPlace’s Law for cylinders. Our published studies showed that diameter was a poor predictor of wall stress due to the complexity of individual aTAA geometries. We propose to prospectively evaluate changes in aTAA wall stresses and distensibility to determine their ability to improve on diameter criterion to predict dissection or death or need for surgery in veterans with aneurysms that do not meet criteria for surgery. We propose to prospectively evaluate changes in aneurysm wall shear stresses, flow velocities, and vortices in veterans with nonsurgical sized aTAAs over time to determine their ability to predict aneurysm growth and need for surgery. This proposal lays the foundation for practical clinical application of patient-specific biomechanics and fluid dynamics to improve risk prediction of aortic dissection, sudden death, aTAA growth, and need for surgery with the following aims: Aim 1: To determine changes in longitudinal wall stresses using finite element analysis (FEA) to correlate with clinical composite endpoint of aortic dissection, need for surgical repair, or sudden death in prospectively followed veterans (n=400) with nonsurgical aTAA <5.5cm over 4 years. Aim 2: To determine changes in aTAA wall strength using the surrogate of in vivo aortic distensibility to correlate with clinical composite endpoint of aortic dissection, aTAA surgical repair, or sudden death in prospectively followed veterans (n=400) with nonsurgical aTAA <5.5cm over 4 years. Aim 3: To determine changes in aTAA circumferential wall stresses and wall shear stresses, flow velocities, and eccentricity using fluid structure interaction (FSI), validate with 4D flow magnetic resonance imaging (MRI), and correlate with clinical composite endpoint of aortic growth or need for surgical repair in prospectively followed veterans (n=400) with nonsurgical aTAA <5.5cm over 4 years. Aim 4: To develop a machine learning (ML) approach to determine biomechanical and fluid dynamic parameters in Aim 1-3 in prospectively followed veterans (n=320) with nonsurgical aTAA <5.5cm, validate the results (n=80), and simplify the process of personalized biomechanics prediction. At the end of the project, we will have developed a new biomechanics based clinical tool for effective clinical management for non-surgical aTAA patients.