(1) Background: Thrombosis is the main complication in patients supported with ventricular assist devices (VAD). Models that accurately predict the risk of thrombus formation in VADs are still lacking. When VADs are clinically assisted, their complex geometric configuration and high rotating speed inevitably generate complex flow fields and high shear stress. These non-physiological factors can damage blood cells and proteins, release coagulant factors and trigger thrombosis. In this study, a more accurate model for thrombus assessment was constructed by integrating parameters such as shear stress, residence time and coagulant factors, so as to accurately assess the probability of thrombosis in three clinical VADs. (2) Methods: A mathematical model was constructed to assess platelet activation and thrombosis within VADs. By solving the transport equation, the influence of various factors such as shear stress, residence time and coagulation factors on platelet activation was considered. The diffusion equation was applied to determine the role of activated platelets and substance deposition on thrombus formation. The momentum equation was introduced to describe the obstruction to blood flow when thrombus is formed, and finally a more comprehensive and accurate model for thrombus assessment in patients with VAD was obtained. Numerical simulations of three clinically VADs (CH-VAD, HVAD and HMII) were performed using this model. The simulation results were compared with experimental data on platelet activation caused by the three VADs. The simulated thrombogenic potential in different regions of MHII was compared with the frequency of thrombosis occurring in the regions in clinic. The regions of high thrombotic risk for HVAD and HMII observed in experiments were compared with the regions predicted by simulation. (3) Results: It was found that the percentage of activated platelets within the VAD obtained by solving the thrombosis model developed in this study was in high agreement with the experimental data (r² = 0.984), the likelihood of thrombosis in the regions of the simulation showed excellent correlation with the clinical statistics (r² = 0.994), and the regions of high thrombotic risk predicted by the simulation were consistent with the experimental results. Further study revealed that the three clinical VADs (CH-VAD, HVAD and HMII) were prone to thrombus formation in the inner side of the secondary flow passage, the clearance between cone and impeller, and the corner region of the inlet pipe, respectively. The risk of platelet activation and thrombus formation for the three VADs was low to high for CH-VAD, HVAD, and HM II, respectively. (4) Conclusions: In this study, a more comprehensive and accurate thrombosis model was constructed by combining parameters such as shear stress, residence time, and coagulation factors. Simulation results of thrombotic risk received with this model showed excellent correlation with experimental and clinical data. It is important for determining the degree of platelet activation in VAD and identifying regions prone to thrombus formation, as well as guiding the optimal design of VAD and clinical treatment.

Purpose: The purpose of this study was to investigate the impact of a new arterial intravascular pump on the hemodynamic surroundings within the aorta. Methods: A new arterial intravascular pump was placed in the descending aorta, and the effects of three positions within the aorta, as well as the number (n = 1 to 3) of pumps, on arterial flow features, organ perfusion, and blood trauma were investigated using a computational fluid dynamics (CFD) method. Results: It was found that as the pump position was moved backward, the perfusion in the three bifurcated vessels of the aorta arch increased and the pump suction flow decreased, resulting in a reduced high shear stress and decreased residence time in the three branches of the aortic arch. The further posterior the location of the pump, the better the blood flow perfusion to the kidneys, while the perfusion at the bifurcation of the abdominal aorta was reduced, due to the pump suction effect. Compared to the condition with single pump support, the multi-pump assist model can significantly reduce the pump rotating speed, while keeping the same flow patterns, leading to a decreased volume of high shear stress and flow loss. When increasing the number of pumps, the perfusion to the three branches of the aortic arch increased, accompanied by a diminished residence time, and the perfusion to the other aortic branches was decreased. However, the perfusion to the other aortic branches, especially for the renal arteries and even under a three-pump condition, was close to that without pump assistance. Conclusion: The placement of an intravascular pump near the beginning of the suprarenal abdominal aorta was considered the optimal location, in order to improve the hemodynamic surroundings. Increasing the number of pumps can significantly reduce the rotational speed, while maintaining the same flowrate, with a decreased fluid energy loss and a reduced high shear stress. This arterial intravascular pump can effectively improve renal blood flow.