Aortic dissection is a catastrophic aortic disease initiated by a tear at the intima of aortic wall. It allows blood flow into the wall layers, leading to separation of the aorta into two lumens, i.e. the true and false lumen. As a minimally invasive procedure, thoracic endovascular aortic repair (TEVAR) has been accepted as a standard treatment approach for type B aortic dissection and a potential alternative treatment for type A aortic dissection in scenarios of prohibitive surgical risk. During TEVAR, a stent-graft (SG) is deployed to seal the proximal entry tear and restore blood flow in the true lumen, thereby minimising flow into the false lumen and promoting aortic remodelling.
Although TEVAR has been a great success with its advantage of being less invasive compared to open surgery, there are still unpredictable post-TEVAR complications, including stent-graft migration, stent induced new entry (SINE) and retrograde aortic dissection (RAD). These complications are associated with the SG deployment procedure and biomechanical changes induced by the SG. The underlying mechanical interaction between the SG and aorta can potentially determine the treatment outcome of TEVAR. However, detailed biomechanical conditions and post-TEVAR SG configuration are not available before the actual procedure. Clinicians usually choose the SG size and landing position based on anatomical measurements and guidelines provided by the manufacturer.
In the past decade, promising progress has been made towards developing finite element method (FEM) based simulation tools for biomechanical analysis of interactions between the aorta and medical implants. However, due to the complicated anatomical features of aortic dissection and the associated nonlinear contact problem, patient-specific simulation of SG deployment in aortic dissection is still challenging.
The aim of this study is to develop a FEM-based modelling framework for virtual SG deployment in aortic dissections suitable for patient-specific applications. The model incorporates purpose-built image segmentation for aortic dissection, detailed design features of commercially available SG, precise control of SG deployment, pre-stress in the aortic wall and change of loading conditions after TEVAR. The model is able to mimic the dynamic interaction between SG and aortic wall, predict post-TEVAR SG configuration and biomechanical changes in the aortic wall induced by SG deployment.
The FEM-based simulation workflow is validated against in vivo data, demonstrating its capability of reproducing post-TEVAR SG configuration to a good degree of accuracy. The model has been successfully applied to a type A aortic dissection case, and the simulation results are used to understand the reason for stent-graft migration and whether changing the proximal landing position could potentially offer a different outcome. The simulation model has also been applied to a small selection of type B aortic dissection cases, in an initial attempt to identify potential biomechanical differences between patients with and without post-TEVAR SINE. Finally, the virtual SG deployment model is extended to investigate the impact of SG length and design on post-TEVAR biomechanical stresses in the aortic wall, demonstrating its potential to serve as a pre-surgical planning tool in the future.