Computer modeling for the prediction of thoracic aortic stent graft collapse

Objective To assess the biomechanical implications of excessive stent protrusion into the aortic arch in relation to thoracic aortic stent graft (TASG) collapse by simulating the structural load and quantifying the fluid dynamics on the TASG wall protrusion extended into a model arch. Methods One-way coupled fluid-solid interaction analyses were performed to investigate the flow-induced hemodynamic and structural loads exerted on the proximal protrusion of the TASG and aortic wall reconstructed from a patient who underwent traumatic thoracic aortic injury repair. Mechanical properties of a Gore TAG thoracic endoprosthesis (W. L. Gore and Assoc, Flagstaff, Ariz) were assessed via experimental radial compression testing and incorporated into the computational modeling. The TASG wall protrusion geometry was characterized by the protrusion extension (PE) and by the angle () between the TASG and the lesser curvature of the aorta. The effect of was explored with the following four models with PE fixed at 1.1 cm: = 10 degrees, 20 degrees, 30 degrees, and 40 degrees. The effect of PE was evaluated with the following four models with fixed at 10 degrees: PE = 1.1 cm, 1.4 cm, 1.7 cm and 2.0 cm. Results The presence of TASG wall protrusion into the aortic arch resulted in the formation of swirling, complex flow regions in the proximal luminal surface of the endograft. High PE values (PE = 2.0 cm) led to a markedly reduced left subclavian flow rate (0.27 L/min), low systolic perfusion pressure (98 mm Hg), and peak systolic TASG diameter reduction (2 mm). The transmural pressure load across the TASG was maximum for the model with the highest PE and , 15.2 mm Hg for the model with PE = 2.0 cm and = 10 degrees, and 11.6 mm Hg for PE = 1.1 cm and = 40 degrees. Conclusions The findings of this study suggest that increased PE imparts an apparent risk of distal end-organ malperfusion and proximal hypertension and that both increased PE and lead to a markedly increased transmural pressure across the TASG wall, a load that would portend TASG collapse. Patient-specific computational modeling may allow for identification of patients with high risk of TASG collapse and guide preventive intervention.