Longitudinal Investigation of Aortic Dissection in Mice with Computational Fluid Dynamics

Abstract

Patients with aortic dissection require lifelong surveillance to monitor disease progression and detect late adverse events such as aneurysmal dilation, malperfusion or refractory pain. The variety and complexity of aortic dissection have so far eluded definitive predictions of occurrence and timing of late adverse events. The search for early indicators of late adverse events has been based mostly on morphologic features, and one commonly observed risk factor is partial thrombosis of the false lumen. While the effect of partial thrombosis on disease progression is incompletely understood, hemodynamic factors, including low velocity or stagnant flow, are likely to play a role. In this study we investigated the progression of false lumen intramural thrombus formation in four mice with angiotensin IIinduced aortic dissection. Based on 3D B-mode ultrasound images, we created segmentations of the diseased aorta including the true lumen, false lumen, and thrombus. These geometries were then used to run computational fluid dynamic simulations with subject-specific boundary conditions. Each mouse was followed for seven days and 4-5 longitudinal image datasets were acquired for each animal. We found that false lumina with a single entry tear tend to have smaller mean relative velocities, and at the same time are subject to a larger false lumen thrombus ratio. Likewise, regions of low velocity correlated with regions of elevated endothelial cell activation potential and higher particle residence times. These findings support the hypothesis that flow stagnation is the predominant hemodynamic factor that results in a large thrombus ratio in false lumina, particularly those with a single entry tear. Additional work will be needed to further explore the intricacies of these complex experimental vascular lesions and how the hemodynamic conditions compare to human aortic dissections.