A Combined Computational Fluid Dynamics and Arterial Spin Labeling MRI Modeling Strategy to Quantify Patient-Specific
Jonas Schollenberger1, Nicholas H Osborne2, Luis Hernandez-Garcia1,3
1Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States.
Insights
Computational fluid dynamics (CFD) combined with arterial spin labeling MRI (ASL) accurately quantifies cerebral hemodynamics. This patient-specific approach reveals hemodynamic differences in cerebrovascular occlusive disease (CVOD) not apparent from stenosis severity alone.
Area of Science:
- Neuroscience
- Medical Imaging
- Biomedical Engineering
Background:
- Cerebral hemodynamics are complexly influenced by cerebrovascular occlusive disease (CVOD).
- Accurate characterization of cerebral hemodynamics in CVOD is challenging.
- Traditional methods may not fully capture the hemodynamic impact of stenosis.
Purpose of the Study:
- To develop and validate a patient-specific computational fluid dynamics (CFD) strategy for quantifying cerebral hemodynamics.
- To integrate CFD with arterial spin labeling MRI (ASL) for enhanced accuracy.
- To assess the hemodynamic impact of stenosis in patients with CVOD.
Main Methods:
- Patient-specific CFD models were created.
- CFD outflow boundary conditions were calibrated using ASL-derived flow splits in the Circle of Willis.
- Lagrangian particle tracking and vessel-selective ASL (VS-ASL) were used for validation.
Main Results:
- The calibrated CFD model accurately reproduced fractional blood supply to vascular territories, matching VS-ASL.
- Significant hemodynamic differences (pressure drop, collateral flow, distal resistance) were observed between CVOD patients, despite similar stenosis severity.
- The method demonstrated feasibility in two CVOD patients and one healthy control.
Conclusions:
- Patient-specific CFD analysis, integrated with ASL MRI, provides a powerful tool for assessing cerebral hemodynamics in CVOD.
- This approach offers a more detailed understanding of hemodynamic impact beyond simple stenosis grading.
- The findings highlight the clinical utility of advanced computational modeling in cerebrovascular disease management.
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.
More Related Videos
05:23Author Spotlight: Noninvasive Cerebral Blood Flow Determination in Human Functional Brain Region for Diagnosis of Neurological Disorders
Published on: May 31, 2024
12:15Optimized System for Cerebral Perfusion Monitoring in the Rat Stroke Model of Intraluminal Middle Cerebral Artery Occlusion
Published on: February 17, 2013