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Related Experiment Video

Updated: Jun 15, 2025

Author Spotlight: Noninvasive Cerebral Blood Flow Determination in Human Functional Brain Region for Diagnosis of Neurological Disorders
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A computational framework for quantifying blood flow dynamics across myogenically-active cerebral arterial networks.

Alberto Coccarelli1,2, Ioannis Polydoros3, Alex Drysdale3

  • 1Zienkiewicz Institute for Modelling, Data and AI, Faculty of Science and Engineering, Swansea University, Swansea, UK. alberto.coccarelli@swansea.ac.uk.

Biomechanics and Modeling in Mechanobiology
|May 9, 2025
PubMed
Summary

This study introduces a computational method to simulate blood flow in rat cerebral arteries, revealing how myogenic tone stabilizes flow during pressure changes. The findings enhance understanding of cerebral autoregulation dynamics.

Keywords:
1D blood flow dynamicsAutoregulationBiologically-motivated modelCerebral arterial networksFluid-structure interactionMyogenic response

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Area of Science:

  • Biomedical Engineering
  • Computational Fluid Dynamics
  • Physiology

Background:

  • Cerebral autoregulation is vital for stable brain blood flow.
  • Estimating in vivo haemodynamic forces in cerebral arteries is challenging.
  • Vascular tone modulation is key to autoregulation.

Purpose of the Study:

  • To develop a computational framework for evaluating blood flow dynamics in myogenically-active cerebral arteries.
  • To quantify the impact of upstream pressure changes on cerebral arterial networks.
  • To investigate the role of myogenic tone in stabilizing flow and reducing vascular stress.

Main Methods:

  • Integrated a continuum mechanics model of the rat vascular wall with 1D blood flow dynamics.
  • Employed a fluid-structure interaction framework with weak coupling for computational efficiency.
  • Validated the model against various pressure protocols and extracellular calcium conditions.
  • Assessed network robustness using different inlet signals and numerical settings in an idealized vascular network.

Main Results:

  • The computational methodology accurately simulated blood flow dynamics in cerebral arterial networks.
  • Myogenic tone was shown to effectively stabilize flow and redistribute pressure/flow across vessel generations.
  • The study quantified the influence of upstream pressure surges on haemodynamics with and without myogenic tone.

Conclusions:

  • The developed in-silico methodology provides a robust tool for studying cerebral autoregulation.
  • This framework can elucidate how pressure fluctuations are managed by cerebral vasculature.
  • The findings support future experimental-computational studies on cerebral blood flow regulation.