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A Combined Computational Fluid Dynamics and Arterial Spin Labeling MRI Modeling Strategy to Quantify Patient-Specific Cerebral Hemodynamics in Cerebrovascular Occlusive Disease

Authors :
Jonas Schollenberger
Nicholas H. Osborne
Luis Hernandez-Garcia
C. Alberto Figueroa
Source :
Frontiers in Bioengineering and Biotechnology, Vol 9 (2021)
Publication Year :
2021
Publisher :
Frontiers Media S.A., 2021.

Abstract

Cerebral hemodynamics in the presence of cerebrovascular occlusive disease (CVOD) are influenced by the anatomy of the intracranial arteries, the degree of stenosis, the patency of collateral pathways, and the condition of the cerebral microvasculature. Accurate characterization of cerebral hemodynamics is a challenging problem. In this work, we present a strategy to quantify cerebral hemodynamics using computational fluid dynamics (CFD) in combination with arterial spin labeling MRI (ASL). First, we calibrated patient-specific CFD outflow boundary conditions using ASL-derived flow splits in the Circle of Willis. Following, we validated the calibrated CFD model by evaluating the fractional blood supply from the main neck arteries to the vascular territories using Lagrangian particle tracking and comparing the results against vessel-selective ASL (VS-ASL). Finally, the feasibility and capability of our proposed method were demonstrated in two patients with CVOD and a healthy control subject. We showed that the calibrated CFD model accurately reproduced the fractional blood supply to the vascular territories, as obtained from VS-ASL. The two patients revealed significant differences in pressure drop over the stenosis, collateral flow, and resistance of the distal vasculature, despite similar degrees of clinical stenosis severity. Our results demonstrated the advantages of a patient-specific CFD analysis for assessing the hemodynamic impact of stenosis.

Details

Language :
English
ISSN :
22964185
Volume :
9
Database :
Directory of Open Access Journals
Journal :
Frontiers in Bioengineering and Biotechnology
Publication Type :
Academic Journal
Accession number :
edsdoj.4f5492bcf7a487289b8fc617e8817c4
Document Type :
article
Full Text :
https://doi.org/10.3389/fbioe.2021.722445