Contemporary Role of Computational Analysis in Endovascular Treatment for Thoracic Aortic Disease

Abstract

In the past decade, thoracic endovascular aortic repair (TEVAR) has become the primary treatment option in descending aneurysm and dissection. The clinical outcome of this minimally invasive technique is strictly related to an appropriate patient/stent graft selection, hemodynamic interactions, and operator skills. In this context, a quantitative assessment of the biomechanical stress induced in the aortic wall due to the stent graft may support the planning of the procedure. Different techniques of medical imaging, like computed tomography or magnetic resonance imaging, can be used to evaluate dynamics in the thoracic aorta. Such information can also be combined with dedicated patient-specific computer-based simulations, to provide a further insight into the biomechanical aspects. In clinical practice, computational analysis might show the development of aortic disease, such as the aortic wall segments which experience higher stress in places where rupture and dissection may occur. In aortic dissections, the intimal tear is usually located at the level of the sino-tubular junction and/or at the origin of the left subclavian artery. Besides, computational models may potentially be used preoperatively to predict stent graft behavior, virtually testing the optimal stent graft sizing, deployment, and conformability, in order to provide the best endovascular treatment. The present study reviews the current literature regarding the use of computational tools for TEVAR biomechanics, highlighting their potential clinical applications.

Keywords: Computational analysis; Thoracic endovascular aortic repair (TEVAR); thoracic aortic disease.

Figures

Figure 1.

A. The three measured aortic levels with a central lumen line. Level A, 5 mm distal to the coronary arteries; B, 5 mm proximal to the innominate artery; C, halfway up the ascending aorta. Figure reproduced with permission of the Journal of Endovascular Therapy (© 2007), provided by Copyright Clearance Center. International Society of Endovascular Specialists. Adapted from van Prehn et al [5]. B. The mean percentage of the maximum diameter change is shown at the 3 different levels. The maximum diameter change at all levels is significant, where level A also differs significantly from levels B and C. Figure reproduced with permission of the Journal of Endovascular Therapy (© 2007), provided by Copyright Clearance Center. International Society of Endovascular Specialists. Adapted from van Prehn et al [5].

Figure 2.

A. CT scan showing an aortic dissection and aortic rupture. B. CT scan showing an aortic dissection with involvement of the left subclavian artery and an aortic aneurysm.

Figure 3.

Aortic morphology reconstruction before and after TEVAR as a treatment for chronic type B dissection (left panel). Native mesh (right panel).

Figure 4.

Finite element analysis, after TEVAR for treatment of ascending pseudoaneurysm. Adapted from Auricchio et al [26].

Figure 5.

TEVAR for an aneurysm rupture at the isthmic region. A. Intraoperative angiography. B. Postoperative CTA with stent grafting of the aortic arch. C. Computational Fluid Dynamics. D. Vector-field analysis. Figure reproduced with permission of Springer, provided by Copyright Clearance Center. Adapted from Midulla et al [18].

Figure 6.

Mid-descending thoracic aortic endograft in anterior, lateral, and axial views showing the vector (arrow) of the displacement force (DF). Mean value of the DF vector, its sideways and axial components, and temporal variation over the cardiac cycle are given below. Note that the axial DF vector is in the cranial rather than the caudal direction. The DF magnitude changes over the cardiac cycle, varying from 16.7 N in diastole and 27.8 N at peak systole. Figure reproduced with permission of the Journal of Endovascular Therapy (© 2009), provided by Copyright Clearance Center. International Society of Endovascular Specialists. Adapted from Figueroa et al [9].

Figure 7.

Evolution of the helical flow in the 5 different aortas (two different views). The flow in A and E has a helical structure and the flow in B, C, and D has a bihelical structure. Figure reproduced with permission of Springer, provided by Copyright Clearance Center. Adapted from Morbiducci et al [46].

Figure 8.

Wall shear stress (WSS) is calculated from the 4D PC-MRI data. Figure reproduced with permission of Elsevier, provided by Copyright Clearance Center. Adapted from Frydrychowicz et al [49].