Quantification of local hemodynamic alterations caused by virtual implantation of three commercially available stents for the treatment of aortic coarctation

Abstract

Patients with coarctation of the aorta (CoA) are prone to morbidity including atherosclerotic plaque that has been shown to correlate with altered wall shear stress (WSS) in the descending thoracic aorta (dAo). We created the first patient-specific computational fluid dynamics (CFD) model of a CoA patient treated by Palmaz stenting to date, and compared resulting WSS distributions to those from virtual implantation of Genesis XD and modified NuMED CP stents, also commonly used for CoA. CFD models were created from magnetic resonance imaging, fluoroscopy and blood pressure data. Simulations incorporated vessel deformation, downstream vascular resistance and compliance to match measured data and generate blood flow velocity and time-averaged WSS (TAWSS) results. TAWSS was quantified longitudinally and circumferentially in the stented region and dAo. While modest differences were seen in the distal portion of the stented region, marked differences were observed downstream along the posterior dAo and depended on stent type. The Genesis XD model had the least area of TAWSS values exceeding the threshold for platelet aggregation in vitro, followed by the Palmaz and NuMED CP stents. Alterations in local blood flow patterns and WSS imparted on the dAo appear to depend on the type of stent implanted for CoA. Following confirmation in larger studies, these findings may aid pediatric interventional cardiologists in selecting the most appropriate stent for each patient, and ultimately reduce long-term morbidity following treatment for CoA by stenting.

Figure 1

Rendering of magnetic resonance imaging (MRI) data (A) and an angiographic image of the same patient obtained by fluoroscopy (B). CFD models were constructed using the MRI data with diameters of the stented region extracted from the fluoroscopy data to account for signal dropout created by artifacts due to the implanted Palmaz stent.

Figure 2

Palmaz (left), NumedCP (middle) and GenesisXD (right) stents created using computer aided design software (top row). These stents were then subtracted from copies of the same patient-specific computational model to produce the flow domain associated with each stent (bottom row).

Figure 3

Example illustrating the meshing approach for the stented region. An adaptive meshing process created elements of appropriate size in proximal intrastrut regions (A, top images), but regions of low velocity adjacent to stents struts and the distal portion of the stented region contained fewer and larger elements after the adaptive process. The minimum edge size of all elements within the proximal stented region after adapting was therefore determined and explicitly applied within the stented region to generate meshes containing ~8.3 million elements (B, bottom images).

Figure 4

Distributions of time-averaged wall shear stress for the Palmaz, NumedCP, and GenesisXD stents. CFD results for the full model are shown next to spatial maps that have been unwrapped about the outer (posterior) surface for the stented region and the distal descending aorta. Circumferential and longitudinal plots are also shown at several locations: proximal stented region (1), distal stented region (2), 15 mm distal to the stent (3), 45 mm distal to the stent (4), as well as the left (5) and right (6) portions of the outer curvature. Note that values occurring atop stent struts have been removed to improve the legibility of plots.

Figure 5

Locations of elevated time-averaged wall shear stress for the Palmaz, NumedCP, and GenesisXD stents. The full CFD model results are shown next to spatial maps that have been unwrapped about the outer (posterior) surface for the descending aorta distal to the stent. Regions with time-averaged wall shear stress above 50 dyn/cm² have been made opaque. Values above this threshold have been previously correlated with platelet aggregation.