As endovascular treatment of abdominal aortic aneurysms (AAAs) gains popularity, it is becoming possible to treat certain challenging aneurysmal anatomies with endografts relying on suprarenal fixation. In such anatomies, the bare struts of the device may be placed across the renal artery ostia, causing partial obstruction to renal artery blood flow. Computational fluid dynamics (CFD) was used to simulate blood flow from the aorta to the renal arteries, utilizing patient-specific boundary conditions, in three patient models and calculate the degree of shear-based blood damage (hemolysis). We used contrast-enhanced computed tomography angiography (CTA) data from three AAA patients who were treated with a novel endograft to build patient-specific models. For each of the three patients, we constructed a baseline model and endoframe model. The baseline model was a direct representation of the patient's 30-day post-operative CTA data. This model was then altered to create the endoframe model, which included a ring of metallic struts across the renal artery ostia. CFD was used to simulate blood flow, utilizing patient-specific boundary conditions. Pressures, flows, shear stresses, and the normalized index of hemolysis (NIH) were quantified for all patients. The overall differences between the baseline and endoframe models for all three patients were minimal, as measured though pressure, volumetric flow, velocity, and shear stress. The average NIH across the three baseline and endoframe models was 0.002 and 0.004, respectively. Results of CFD modeling show that the overall disturbance to flow caused by the presence of the endoframe struts is minimal. The magnitude of the NIH in all models was well below the accepted design and safety threshold for implantable medical devices that interact with blood flow.

Design and evaluation of implantable medical devices often relies on benchtop testing using physical models and animal studies. Although both methods are needed, they can be costly to implement and unable to represent patient-specific physiologic conditions. Computer simulations of blood flow in patient-specific anatomies offer an attractive alternative [1].

Large vessels in the vascular system undergo progressive degeneration with aging. The widely accepted theory is the aorta enlarges and stiffens with age [1] and vascular compliance decreases [2], which increases systolic pressure, decreases diastolic pressure, and greatly affects cardiovascular health and function. Quantifying the dynamics of an aging human aorta yields insight into changes in the vascular compliance and is vital in understanding pathogenesis and progression of disease, such as atherosclerosis and aneurysm formation [3], along with medical device implantation and design.

Computer modeling of blood flow in patient-specific anatomies can be a powerful tool for evaluating the design of implantable medical devices. We assessed three different endograft designs, which are implantable devices commonly used to treat patients with abdominal aortic aneurysms (AAAs). Once implanted, the endograft may shift within the patient’s aorta allowing blood to flow into the aneurismal sac. One potential cause for this movement is the pulsatile force experienced by the endograft over the cardiac cycle. We used contrast-enhanced computed tomography angiography (CTA) data from four patients with diagnosed AAAs to build patient-specific models using 3D segmentation. For each of the four patients, we constructed a baseline model from the patient’s preoperative CTA data. In addition, geometries characterizing three distinct endograft designs were created, differing by where each device bifurcated into two limbs (proximal bifurcation, mid bifurcation, and distal bifurcation). Computational fluid dynamics (CFD) was used to simulate blood flow, utilizing patient-specific boundary conditions. Pressures, flows, and displacement forces on the endograft surface were calculated. The curvature and surface area of each device was quantified for all patients. The magnitude of the total displacement force on each device ranged from 2.43 N to 8.68 N for the four patients examined. Within each of the four patient anatomies, the total displacement force was similar (varying at least by 0.12 N and at most by 1.43 N), although there were some differences in the direction of component forces. Proximal bifurcation and distal bifurcation geometries consistently generated the smallest and largest displacement forces, respectively, with forces observed in the mid bifurcation design falling in between the two devices. The smallest curvature corresponded to the smallest total displacement force, and higher curvature values generally corresponded to higher magnitudes of displacement force. The same trend was seen for the surface area of each device, with lower surface areas resulting in lower displacement forces and vise versa. The patient with the highest blood pressure displayed the highest magnitudes of displacement force. The data indicate that curvature, device surface area, and patient blood pressure impact the magnitude of displacement force acting on the device. Endograft design may influence the displacement force experienced by an implanted endograft, with the proximal bifurcation design showing a small advantage for minimizing the displacement force on endografts.

No abstract