4.6 Review

State-of-the-Art Computational Models of Circle of Willis With Physiological Applications: A Review

Journal

IEEE ACCESS
Volume 8, Issue -, Pages 156261-156273

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.3007737

Keywords

Brain modeling; computational modeling; circle of Willis (CoW); Windkessel effect; pulse wave; computational fluid dynamics (CFD); cerebral blood flow; intracranial arteries

Funding

  1. Research Grant Council (RGC) of Hong Kong [14204117, 14106019]
  2. National Natural Science Foundation of China (NSFC) [61828104]
  3. NSFC/RGC Joint Research Scheme [N_CUHK421/16]
  4. Basic Research Foundation of Shenzhen [GJHZ20180928155002157]
  5. Scheme Double First Class Program
  6. Ministry of Education
  7. Ministry of Finance
  8. National Development and Reform Commission, China

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Background: Various computational models of the circle of Willis (CoW) have been developed to non-invasively estimate the blood flow and hemodynamic parameters in intracranial arteries for the assessment of clinical risks such as aneurysms, ischemia, and atherosclerotic plaque growth. This review aims to categorize the latest computational models of CoW and summarize the innovative techniques. Summary of Review: In traditional computational models of CoW, the computational complexity increased from zero-dimensional models to one-dimensional and three-dimensional models. The applications extend from estimating certain hemodynamic parameters to simulating local flow field. The innovative techniques include the combination of models with different dimensions, the extension of vascular structure including heart and veins, as well as the addition of distal fractality, cerebral autoregulation, and intracranial pressure. There are some nontraditional models based on fluid-solid-interaction, control theory, and in-vitro experiments. In all kinds of models, the in-vivo data and non-Newtonian rheological models of blood have been widely applied to improve the accuracy of hemodynamic simulation. Conclusion: Firstly, the selection of model depends on its application scenario. The balance between computational complexity and physiological accuracy deserves further investigation. Secondly, the improvement of CoW models relies on the large-scale validations and the combination of various innovative modeling techniques.

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