The Application of Non-linear Flow Resistance in Cerebral Artery: Compared with Windkessel Model based on Genetic...

Area of Science:

• Biomedical Engineering
• Physiology
• Medical Imaging

Background:

• Continuous blood pressure monitoring is crucial, but extracranial measurements differ in amplitude and phase from intracranial blood pressure.
• The accuracy of the Windkessel model for estimating intracranial pressure is influenced by these extracranial-intracranial differences.
• Further investigation is needed to refine models used for non-invasive intracranial pressure estimation.

Purpose of the Study:

• To propose and validate a novel model with non-linear flow resistance (R-DT) for estimating intracranial blood pressure.
• To compare the accuracy of the R-DT model against the traditional 3-element Windkessel (RCR) model.
• To assess the applicability of non-linear flow resistance in simulating cerebral artery dynamics.

Main Methods:

• Developed a non-linear flow resistance (R-DT) model to represent the relationship between blood pressure and intracranial flow rate.
• Utilized measured blood flow velocity data from the middle cerebral artery.
• Optimized model parameters using a genetic algorithm and compared estimation errors against measured blood pressure.

Main Results:

• The R-DT model demonstrated superior accuracy in estimating blood pressure compared to the RCR model.
• The averaged relative error for the RCR model was 5.19%, while the R-DT model achieved a significantly lower error of 2.49%.
• The capacitance element in the RCR model showed limitations in accounting for time shifts, which the R-DT model addressed more effectively.

Conclusions:

• The proposed R-DT model with non-linear flow resistance is more accurate for simulating cerebral artery blood flow.
• The R-DT model provides a better estimation of intracranial blood pressure compared to the conventional RCR model.
• Non-linear flow resistance is a valuable component for accurately modeling cerebral arterial dynamics.