Boundary conditions (BCs) are an essential part in computational fluid dynamics (CFD) simulations of blood flow in large arteries. Although several studies have investigated the influence of BCs on predicted flow patterns and hemodynamic wall parameters in various arterial models, there is a lack of comprehensive assessment of outlet BCs for patient-specific analysis of aortic flow. In this study, five different sets of outlet BCs were tested and compared using a subject-specific model of a normal aorta. Phase-contrast magnetic resonance imaging (PC-MRI) was performed on the same subject and velocity profiles extracted from the in vivo measurements were used as the inlet boundary condition. Computational results obtained with different outlet BCs were assessed in terms of their agreement with the PC-MRI velocity data and key hemodynamic parameters, such as pressure and flow waveforms and wall shear stress related indices. Our results showed that the best overall performance was achieved by using a well-tuned three-element Windkessel model at all model outlets, which not only gave a good agreement with in vivo flow data, but also produced physiological pressure waveforms and values. On the other hand, opening outlet BCs with zero pressure at multiple outlets failed to reproduce any physiologically relevant flow and pressure features.

Atherosclerosis in the superficial femoral artery (SFA) resulting in peripheral arterial disease is more common in men than women and shows a predilection for the region of the adductor canal. Blood flow patterns are related to development of atherosclerosis, and we investigated if curvature and tortuosity of the femoral artery differed between young men and women and if differences resulted in adverse flow patterns. Magnetic resonance imaging (MRI) and computational fluid dynamics (CFD) were combined in 18 young adult volunteers (9 men) to assess the relationship of flow features to likely sites of future atherosclerosis formation. Subjects underwent MRI of the right SFA, three-dimensional vascular geometry was reconstructed, and measures of tortuosity and curvature were calculated. Tortuosity and curvature were significantly greater for men than women, and this was related to increased body surface area, body mass index, or weight in men. In both sexes, “tortuosity” increased from the midthigh to the popliteal fossa. The greatest curvature was found within the distal quarter of the SFA. CFD modeling was undertaken on MRI-based reconstructions of the SFA. Wall shear stresses (WSS) were extracted from the computations. WSS showed greater spatial variation in the men than in the women, and the men exhibited lower mean WSS. These data indicate that sex differences related to body size and anatomical course of the femoral artery may contribute to the enhanced risk of focal atherosclerosis in the adductor canal.

Background: Abdominal aortic aneurysm (AAA) is a dilatation of the aortic wall, which can rupture, if left untreated. Previous work has shown that, maximum diameter is not a reliable determinant of AAA rupture. However, it is currently the most widely accepted indicator. Wall stress may be a better indicator and promising patient specific results from structural models using static pressure, have been published. Since flow and pressure inside AAA are non-uniform, the dynamic interaction between the pulsatile flow and wall may influence the predicted wall stress. The purpose of the present study was to compare static and dynamic wall stress analysis of patient specific AAAs. Method: Patient-specific AAA models were created from CT scans of three patients. Two simulations were performed on each lumen model, fluid structure interaction (FSI) model and static structural (SS) model. The AAA wall was created by dilating the lumen with a uniform 1.5 mm thickness, and was modeled as a non-linear hyperelastic material. Commercial finite element code Adina 8.2 was used for all simulations. The results were compared between the FSI and SS simulations. Results: Results are presented for the wall stress patterns, wall shear stress patterns, pressure, and velocity fields within the lumen. It is demonstrated that including fluid flow can change local wall stresses slightly. However, as far as the peak wall stress is concerned, this effect is negligible as the difference between SS and FSI models is less than 1%. Conclusion: The results suggest that fully coupled FSI simulation, which requires considerable computational power to run, adds little to rupture risk prediction. This justifies the use of SS models in previous studies.

Aortic dissection is a major aortic catastrophe with a high morbidity and mortality risk caused by the formation of a tear in the aortic wall. The development of a second blood filled region defined as the “false lumen” causes highly disturbed flow patterns and creates local hemodynamic conditions likely to promote the formation of thrombus in the false lumen. Previous research has shown that patient prognosis is influenced by the level of thrombosis in the false lumen, with false lumen patency and partial thrombosis being associated with late complications and complete thrombosis of the false lumen having beneficial effects on patient outcomes. In this paper, a new hemodynamics-based model is proposed to predict the formation of thrombus in Type B dissection. Shear rates, fluid residence time, and platelet distribution are employed to evaluate the likelihood for thrombosis and to simulate the growth of thrombus and its effects on blood flow over time. The model is applied to different idealized aortic dissections to investigate the effect of geometric features on thrombus formation. Our results are in qualitative agreement with in-vivo observations, and show the potential applicability of such a modeling approach to predict the progression of aortic dissection in anatomically realistic geometries.

Aortic dissection is the most common acute catastrophic event affecting the thoracic aorta. The majority of patients presenting with an uncomplicated type B dissection are treated medically, but 25% of these patients develop subsequent aneurysmal dilatation of the thoracic aorta. This study aimed at gaining more detailed knowledge of the flow phenomena associated with this condition. Morphological features and flow patterns in a dissected aortic segment of a presurgery type B dissection patient were analyzed based on computed tomography images acquired from the patient. Computational simulations of blood flow in the patient-specific model were performed by employing a correlation-based transitional version of Menter’s hybrid $k-ε/k-ω$ shear stress transport turbulence model implemented in ANSYS CFX 11 . Our results show that the dissected aorta is dominated by locally highly disturbed, and possibly turbulent, flow with strong recirculation. A significant proportion (about 80%) of the aortic flow enters the false lumen, which may further increase the dilatation of the aorta. High values of wall shear stress have been found around the tear on the true lumen wall, perhaps increasing the likelihood of expanding the tear. Turbulence intensity in the tear region reaches a maximum of 70% at midsystolic deceleration phase. Incorporating the non-Newtonian behavior of blood into the same transitional flow model has yielded a slightly lower peak wall shear stress and higher maximum turbulence intensity without causing discernible changes to the distribution patterns. Comparisons between the laminar and turbulent flow simulations show a qualitatively similar distribution of wall shear stress but a significantly higher magnitude with the transitional turbulence model.

Aortic dissection causes splitting of the aortic wall layers, allowing blood to enter a ‘false lumen’ (FL). For type B dissection, a significant predictor of patient outcomes is patency or thrombosis of the FL. Yet, no methods are currently available to assess the chances of FL thrombosis. In this study, we present a new computational model that is capable of predicting thrombus formation, growth and its effects on blood flow under physiological conditions. Predictions of thrombus formation and growth are based on fluid shear rate, residence time and platelet distribution, which are evaluated through convection–diffusion–reaction transport equations. The model is applied to a patient-specific type B dissection for which multiple follow-up scans are available. The predicted thrombus formation and growth patterns are in good qualitative agreement with clinical data, demonstrating the potential applicability of the model in predicting FL thrombosis for individual patients. Our results show that the extent and location of thrombosis are strongly influenced by aortic dissection geometry that may change over time. The high computational efficiency of our model makes it feasible for clinical applications. By predicting which aortic dissection patient is more likely to develop FL thrombosis, the model has great potential to be used as part of a clinical decision-making tool to assess the need for early endovascular intervention for individual dissection patients.