Evaluating the accuracy of cerebrovascular computational fluid dynamics modeling through time-resolved experimental validation

Evaluating the accuracy of cerebrovascular computational fluid dynamics modeling through time-resolved experimental validation

Accurate modeling of cerebral hemodynamics is crucial for better understanding the hemodynamics of stroke, for which computational fluid dynamics (CFD) modeling is a viable tool to obtain information. However, a comprehensive study on the accuracy of cerebrovascular CFD models including both transie...

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Bibliographic Details
Published in:Scientific reports Vol. 14; no. 1; p. 8194
Main Authors: Luisi, Claudio A., Witter, Tom L., Nikoubashman, Omid, Wiesmann, Martin, Steinseifer, Ulrich, Neidlin, Michael
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 08-04-2024
Nature Publishing Group
Nature Portfolio
Subjects:
639/166/985
639/705/1042
639/766/189
692/699/375/1370/534
Accuracy
Arterial Pressure
Blood flow
Blood Flow Velocity
Blood pressure
Boundary conditions
Cerebral blood flow
Cerebrovascular Circulation
Computer applications
Computer Simulation
Data acquisition
Fluid dynamics
Hemodynamics
Humanities and Social Sciences
Hydrodynamics
Models, Cardiovascular
multidisciplinary
Science
Science (multidisciplinary)
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Summary:Accurate modeling of cerebral hemodynamics is crucial for better understanding the hemodynamics of stroke, for which computational fluid dynamics (CFD) modeling is a viable tool to obtain information. However, a comprehensive study on the accuracy of cerebrovascular CFD models including both transient arterial pressures and flows does not exist. This study systematically assessed the accuracy of different outlet boundary conditions (BCs) comparing CFD modeling and an in-vitro experiment. The experimental setup consisted of an anatomical cerebrovascular phantom and high-resolution flow and pressure data acquisition. The CFD model of the same cerebrovascular geometry comprised five sets of stationary and transient BCs including established techniques and a novel BC, the phase modulation approach. The experiment produced physiological hemodynamics consistent with reported clinical results for total cerebral blood flow, inlet pressure, flow distribution, and flow pulsatility indices (PI). The in-silico model instead yielded time-dependent deviations between 19–66% for flows and 6–26% for pressures. For cerebrovascular CFD modeling, it is recommended to avoid stationary outlet pressure BCs, which caused the highest deviations. The Windkessel and the phase modulation BCs provided realistic flow PI values and cerebrovascular pressures, respectively. However, this study shows that the accuracy of current cerebrovascular CFD models is limited.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-58925-8