Patient-Specific Cerebral Blood Flow Simulation Based on Commonly Available Clinical Datasets

Area of Science:

• Biomedical Engineering
• Computational Fluid Dynamics
• Neuroscience

Background:

• Cerebral hemodynamics are vital in cerebrovascular disease development.
• Patient-specific modeling offers insights into individual blood flow dynamics.
• Existing models may lack integration with diverse clinical data.

Purpose of the Study:

• To develop a numerical framework for patient-specific cerebral blood flow modeling.
• To utilize readily available clinical data for hemodynamic analysis.
• To assess the impact of arterial geometry and flow parameters on the circle of Willis.

Main Methods:

• A hemodynamic model was built using Simulink's Simscape Fluids library.
• Arterial geometry was extracted from computerized tomography angiography (CTA) scans of 59 patients.
• Transcranial Doppler (TCD) measurements calibrated the model's input parameters.

Main Results:

• The numerical model successfully reproduced patient-specific blood flow in the circle of Willis (CoW).
• Distal branch resistance was identified as the primary factor influencing CoW flow distribution.
• The model demonstrated consistency across different patient measurements.

Conclusions:

• The proposed numerical framework is a promising tool for assessing cerebral hemodynamics.
• This approach aids in understanding patient-specific blood flow in cerebrovascular diseases.
• Accurate modeling can support clinical decision-making for conditions like aneurysmal subarachnoid hemorrhage.