Computer methods and programs in biomedicine · 2022
Component quantification of aortic blood flow energy loss using computational fluid-structure interaction hemodynamics.
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Qiao Yonghui, Luo Kun, Fan Jianren
Аннотация
BACKGROUND AND OBJECTIVES: The aorta serves as the main tube of the human blood circulation system. Energy loss (EL) occurs when blood flows through the aorta and there may be a potential correlation between EL and aortic diseases. However, the components of blood flow EL are still not fully understood. This study aims to quantitatively reveal the EL components in healthy and diseased aortas.
METHODS: We construct an idealized healthy aorta and three idealized representative diseased aortas: aortic aneurysm, coarctation of the aorta, and aortic dissection. Computational hemodynamic studies are carried out by using the fluid-structure interaction simulation framework.
RESULTS: Four kinds of EL components: viscous friction, turbulence dissipation, wall deformation, and local lesion are firstly acquired in healthy and diseased aortas based on the high-resolution blood flow information. Viscous friction contributes most to the EL (45.69%-57.22%). EL caused by the deformation of the aortic wall ranks second (15.18%-33.12%). The proportions of turbulence dissipation and local lesion depend on individual geometric characteristics. Besides, the buffering efficiency of the healthy and diseased aorta is about 80%.
CONCLUSIONS: This study quantitatively reports the components of blood flow EL in healthy and diseased aortas, the finding may provide novel insights into the pathogenesis of aortic diseases.
METHODS: We construct an idealized healthy aorta and three idealized representative diseased aortas: aortic aneurysm, coarctation of the aorta, and aortic dissection. Computational hemodynamic studies are carried out by using the fluid-structure interaction simulation framework.
RESULTS: Four kinds of EL components: viscous friction, turbulence dissipation, wall deformation, and local lesion are firstly acquired in healthy and diseased aortas based on the high-resolution blood flow information. Viscous friction contributes most to the EL (45.69%-57.22%). EL caused by the deformation of the aortic wall ranks second (15.18%-33.12%). The proportions of turbulence dissipation and local lesion depend on individual geometric characteristics. Besides, the buffering efficiency of the healthy and diseased aorta is about 80%.
CONCLUSIONS: This study quantitatively reports the components of blood flow EL in healthy and diseased aortas, the finding may provide novel insights into the pathogenesis of aortic diseases.