High resolution simulation of basilar artery infarct and flow within the circle of Willis

Jon W S McCullough1, Peter V Coveney2,3,4

  • 1Centre for Computational Science, Department of Chemistry, University College London, London, UK.

Scientific Reports
|December 8, 2023
PubMed

Insights

Understanding individual cerebral vasculature is key to assessing ischemic stroke risk. This study simulated blood flow changes in the circle of Willis after basilar artery blockage, revealing how vessel structure impacts flow redistribution and stroke impact.

Area of Science:

  • Biomedical Engineering
  • Computational Fluid Dynamics
  • Neuroscience

Background:

  • Cerebro- and cardiovascular diseases are leading causes of death and disability globally.
  • Increasing prevalence highlights the need for better stroke risk identification.
  • Cerebral vasculature variability complicates personalized risk assessment.

Purpose of the Study:

  • To investigate blood flow dynamics in common circle of Willis variations after basilar artery blockage.
  • To assess the impact of structural variations on flow redistribution post-stroke.
  • To demonstrate the utility of patient-specific models for stroke risk evaluation.

Main Methods:

  • Utilized the 3D blood flow simulator HemeLB, based on the lattice Boltzmann method.
  • Simulated flow cessation in the basilar artery across three circle of Willis geometries.
  • Analyzed velocity magnitude and wall shear stress in high-resolution 3D domains.

Main Results:

  • Demonstrated how quickly the circle of Willis redistributes flow following a blockage.
  • Observed significant flow reductions (up to 70%) in posterior cerebral arteries.
  • Highlighted the critical role of posterior communicating arteries in maintaining flow.

Conclusions:

  • Patient-specific models of cerebral vasculature are essential for accurate stroke risk assessment.
  • Understanding individual vessel anatomy improves the prediction of stroke impact.
  • Computational modeling provides crucial insights into cerebrovascular disease mechanisms.

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