Predicting aneurysmal degeneration of type B aortic dissection with computational fluid dynamics

Stanford Type B aortic dissection (TBAD) is a deadly cardiovascular disease with mortality rates as high as 50% in complicated cases. Patients with TBAD are often medically managed, but in ∼20-40% of cases, patients experience aneurysmal degeneration in the dissected aorta, and surgical intervention is required. In this work, we simulated blood flow using computational fluid dynamics (CFD) to determine relationships between hemodynamics and aneurysmal degeneration, providing an important step towards predicting the need for intervention prior to significant aneurysm occurrence. Currently, surgeons intervene in TBAD cases based on the aneurysms growth rate and overall size, as well as a variety of other factors such as malperfusion, thrombosis, and pain, but predicting future risk of aneurysmal degeneration would allow earlier intervention leading to improved patient outcomes. Here, we hypothesized that hemodynamic metrics play an important role in the formation of aneurysms and that these metrics could be used to predict future aneurysmal degeneration in this patient population. Our retrospective dataset consisted of 16 patients with TBAD where eight required intervention due to aneurysmal degeneration and eight were medically managed. The patients with surgical intervention were examined in our study prior to the formation of an aneurysm. For each patient, we segmented and reconstructed the aortic geometry and simulated blood flow using the lattice Boltzmann method. We then compared hemodynamic metrics between to the two groups of patients, including time-averaged wall shear stress, oscillatory shear index, relative residence time, and flow fractions to the true and false lumen. We found significant differences in each metric between the true and false lumen. We also showed that flow fractions to the false lumen was higher in patients with aneurysmal degeneration (p = 0.02). These results are an important step towards developing more precise methods to predict future aneurysmal degeneration and the need for intervention in TBAD patients.