Computational Fluid Dynamics Modeling of Hemodynamic Parameters in the Human Diseased Aorta: A Systematic Review

Chi Wei Ong1, Ian Wee2, Nicholas Syn2

  • 1Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore; SingVaSC, Singapore Vascular Surgical Collaborative, Singapore, Singapore.

Insights

Computational fluid dynamics (CFD) shows promise for predicting aortic disease progression and treatment outcomes. This systematic review highlights CFD

Area of Science:

  • Cardiovascular Science
  • Medical Imaging Analysis
  • Computational Fluid Dynamics (CFD)

Background:

  • Computational fluid dynamics (CFD) analysis correlates blood flow with aortic pathology, aiding disease prediction and treatment guidance.
  • A comprehensive systematic review of CFD applications in aortic diseases and their treatments is lacking.

Purpose of the Study:

  • To systematically review and analyze the published literature on the application of CFD in various aortic diseases.
  • To assess the quality and validation methods of CFD studies in aortic pathology.

Main Methods:

  • Systematic review of 136 articles investigating CFD in aortic aneurysms, dissections, and coarctation.
  • Inclusion of treated and untreated aortic pathologies analyzed with CFD.
  • Grading of studies using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach based on CFD validation.

Main Results:

  • No randomized controlled trials were found for CFD efficacy in aortic pathology.
  • A majority of studies are observational; only 21% utilized clinical imaging for CFD result validation, and these were high-quality.
  • Limited independent validation of CFD results exists in the current literature.

Conclusions:

  • CFD provides valuable hemodynamic parameters (e.g., wall shear stress, vorticity) for both treated and untreated aortic diseases.
  • These parameters hold potential for predicting disease progression and the impact of surgical interventions.
  • CFD can assist clinicians in optimizing treatment choices and timing for aortic conditions.
Abstract

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