Published in

Frontiers Media, Frontiers in Bioengineering and Biotechnology, (10), 2022

DOI: 10.3389/fbioe.2022.835347

Links

Tools

Export citation

Search in Google Scholar

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

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

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.