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Updated: May 5, 2026

Author Spotlight: Noninvasive Cerebral Blood Flow Determination in Human Functional Brain Region for Diagnosis of Neurological Disorders
Published on: May 31, 2024
A Functional Region-Based Approach for the Numerical Simulation of Patient-Specific Cerebral Blood Flows With
Objective:
Imposing accurate outflow boundary conditions remains a significant challenge in 3D computational fluid dynamics simulations of patient-specific cerebral blood flow. Widely used Windkessel models often rely solely on geometric factors, such as outlet numbers and diameters, leading to inaccuracies caused by image quality limitations and simplified vessel representations. This preliminary study proposes a novel functional region-based approach to enhance the accuracy of cerebral blood flow simulations.
Methods:
Cerebral vessels were divided into functional regions by combining population-based cerebral blood flow distributions with patient-specific arterial geometries from medical images. Within each functional region, parameters of Windkessel models for individual outlets are calculated based on their corresponding diameters/areas, accounting for both functional and geometric characteristics. Validation was conducted on a single subject using clinical Transcranial Doppler ultrasound data, with comparisons made to a conventional area-based approach.
Results:
The functional region-based approach demonstrated better alignment with clinical measurements, outperforming the area-based method in velocity profiles at 5 of 7 monitored locations. It also provided closer agreement with measured blood flow distribution, with maximum percentage differences of -4.5%.
Conclusion:
By integrating vascular geometry and functional perfusion data, the proposed approach provides a physiologically informed strategy for setting outlet boundary conditions in cerebral blood flow simulations.
Significance:
Although demonstrated in a single-subject case, this approach shows potential to improve patient-specific simulation reliability by reducing errors caused by imaging artifacts and geometric simplifications, offering value for future clinical and research applications.
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