Computational fluid dynamics of abdominal aortic aneurysms with patient-specific inflow boundary conditions

2006 ◽  
Author(s):  
Ursula Kose ◽  
Sander de Putter ◽  
Romhild Hoogeveen ◽  
Marcel Breeuwer
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Boundary Conditions ◽  
Abdominal Aortic Aneurysms ◽  
Aortic Aneurysms ◽  
Patient Specific ◽  
Abdominal Aortic

3D Modeling of Blood Flow in Simulated Abdominal Aortic Aneurysm

2021 ◽  
pp. 153857442110129
Author(s):  
Mauricio Gonzalez-Urquijo ◽  
Raul Garza de Zamacona ◽  
Ana Karen Martinez Mendoza ◽  
Miranda Zamora Iribarren ◽  
Erika Garza Ibarra ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Shear Stress ◽  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Abdominal Aortic Aneurysms ◽  
Aneurysm Rupture ◽  
Aortic Aneurysms ◽  
Abdominal Aortic ◽  
Computer Aided

Background: Besides biological factors, abdominal aortic aneurysm rupture is also caused by mechanical parameters, which are constantly affecting the wall’s tissue due to their abnormal values. The ability to evaluate these parameters could vastly improve the clinical treatment of patients with abdominal aortic aneurysms. The objective of this study was to develop and demonstrate a methodology to analyze the fluid dynamics that cause the wall stress distribution in abdominal aortic aneurysms, using accurate 3D geometry and a realistic, nonlinear, elastic biomechanical model using a computer-aided software. Methods: The geometry of the abdominal aortic aneurysm; was constructed on a 3D scale using computer-aided software SolidWorks (Dassault Systems SolidWorksCorp., Waltham MA). Due to the complex nature of the abdominal aortic aneurysm geometry, the physiological forces and constraints acting on the abdominal aortic aneurysm wall were measured by using a simulation setup using boundary conditions and initial conditions for different studies such as finite element analysis or computational fluid dynamics. Results: The flow pattern showed an increase velocity at the angular neck, followed by a stagnated flow inside the aneurysm sack. Furthermore, the wall shear stress analysis showed to focalized points of higher stress, the top and bottom of the aneurysm sack, where the flow collides against the wall. An increase of the viscosity showed no significant velocity changed but results in a slight increase in overall pressure and wall shear stress. Conclusions: Conducting computational fluid dynamics modeling of the abdominal aortic aneurysm using computer-aided software SolidWorks (Dassault Systems SolidWorksCorp., Waltham MA) proves to be an insightful approach for the clinical setting. The careful consideration of the biomechanics of the abdominal aortic aneurysm may lead to an improved, case-specific prediction of the abdominal aortic aneurysm rupture potential, which could significantly improve the clinical management of these patients.

Evaluating Design of Abdominal Aortic Aneurysm Endografts in a Patient-Specific Model Using Computational Fluid Dynamics

2011 ◽  
Vol 5 (4) ◽  
Author(s):  
Polina A. Segalova ◽  
Guanglei Xiong ◽  
K. T. Venkateswara Rao ◽  
Christopher K. Zarins ◽  
Charles A. Taylor
Keyword(s):  
Fluid Dynamics ◽  
Blood Pressure ◽  
Computational Fluid Dynamics ◽  
Blood Flow ◽  
Surface Area ◽  
Aortic Aneurysms ◽  
Patient Specific ◽  
Total Displacement ◽  
Abdominal Aortic ◽  
Displacement Force

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.

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