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

Cerebral hemodynamics play an important role in the development of cerebrovascular diseases. In this work, we propose a numerical framework for modeling patient-specific cerebral blood flow, using commonly available clinical datasets. Our hemodynamic model was developed using Simscape Fluids library in Simulink, based on a block diagram language. Medical imaging data obtained from computerized tomography angiography (CTA) in 59 patients with aneurysmal subarachnoid hemorrhage was used to extract arterial geometry parameters. Flow information obtained from transcranial Doppler (TCD) measurement was employed to calibrate input parameters of the hemodynamic model. The results show that the proposed numerical model can reproduce blood flow in the circle of Willis (CoW) per patient per measurement set. The resistance at the distal end of each terminal branch was the predominant parameter for the flow distribution in the CoW. The proposed model may be a promising tool for assessing cerebral hemodynamics in patients with cerebrovascular disease.

Automated summary

In this study, a numerical framework for modeling patient-specific cerebral blood flow was proposed. The framework utilized commonly available clinical datasets to extract arterial geometry parameters and employed flow information obtained from transcranial Doppler measurement for calibration. The results demonstrated that the proposed model could accurately reproduce blood flow in the circle of Willis for each patient, with the resistance at the distal end of each terminal branch being the primary parameter for flow distribution. This model holds promise as a useful tool for assessing cerebral hemodynamics in patients with cerebrovascular diseases.