Computational fluid dynamics validated by micro particle image velocimetry to estimate the risk of hemolysis in arteries with atherosclerotic lesions

Abstract

We aimed to verify the relationship between blood vessel shape and hemolysis risk by using a blood rheological model that reflects the physiological processes related to blood flow. Blood rheology depends on many factors including the red blood cell concentration and local shear stress, which affect the hemolysis process. We introduced a rheology model suitable for modeling hemolysis flows observed in arteries with atherosclerotic lesions in vivo based on the population balance. The model predicts the concentration of single red blood cells and the concentration and size of red blood cell agglomerates, which affect blood rheology and hemolysis. Atherosclerotic lesion geometries were obtained based on image reconstructions from tomographic projections. Computational fluid dynamics (CFD) simulation results were compared with particle image velocimetry measurements of the geometries printed with a 3D printer. Based on the CFD simulation data, a correlation function was established by combining the essential parameters of vessel shape and flow rate with the maximum shear stress, which governs the hemolysis. The chemical engineering methodology was successfully applied to the analysis of biological systems. In future, the model can be implemented in image reconstruction software using tomographic projections to quickly analyze hemolysis risk in medical practice.