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<p>The aorta is the principal artery in blood circulation, crucial for cardiovascular health. Although several aspects of its function remain poorly understood, these features are critical to blood circulation and are associated with the onset of aortic diseases. This study qualitatively and comparatively analyzed the hemodynamic characteristics of healthy young and old aortas using image-based computational tools and 4D flow MRI data. The 4D flow MRI provided input for computational hemodynamics, including aortic geometry reconstruction, velocity measurement, boundary condition establishment, and hemodynamic analysis. Due to constraints, 3D computational models were generated and analyzed for 77 out of 100 subjects. Each participant’s cardiac velocity profile was applied to the inlet plane of these models. Computational fluid dynamics simulation was used for computational studies, followed by postprocessing for hemodynamic analysis and flow visualization. The findings showed the computational framework aligned well with 4D flow MRI hemodynamic parameters. Comparatively, older individuals had lower blood velocity, likely due to decreased input velocity and increased aortic diameter, but average turbulent kinetic energy was similar across groups and cycle-averaged TKE values did not differ significantly across age groups, matching existing data. This coupled computational framework has potential for advancing the understanding of aortic diseases and could be clinically applied to investigate flow complexities in individuals.</p>

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Exploring vascular aging for aortic hemodynamics by employing CFD and 4D flow MRI

  • 期刊论文

  • 发表日期：

    2026年2月11日

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  • Ehsan Adeeb,
  • Sangho Ko,
  • Dong Hyun Yang,
  • Hojin Ha

摘要

The aorta is the principal artery in blood circulation, crucial for cardiovascular health. Although several aspects of its function remain poorly understood, these features are critical to blood circulation and are associated with the onset of aortic diseases. This study qualitatively and comparatively analyzed the hemodynamic characteristics of healthy young and old aortas using image-based computational tools and 4D flow MRI data. The 4D flow MRI provided input for computational hemodynamics, including aortic geometry reconstruction, velocity measurement, boundary condition establishment, and hemodynamic analysis. Due to constraints, 3D computational models were generated and analyzed for 77 out of 100 subjects. Each participant’s cardiac velocity profile was applied to the inlet plane of these models. Computational fluid dynamics simulation was used for computational studies, followed by postprocessing for hemodynamic analysis and flow visualization. The findings showed the computational framework aligned well with 4D flow MRI hemodynamic parameters. Comparatively, older individuals had lower blood velocity, likely due to decreased input velocity and increased aortic diameter, but average turbulent kinetic energy was similar across groups and cycle-averaged TKE values did not differ significantly across age groups, matching existing data. This coupled computational framework has potential for advancing the understanding of aortic diseases and could be clinically applied to investigate flow complexities in individuals.