Maximum admittance method for cerebrovascular outlet boundary conditions and importance of stenosis severity as a dominant factor on hemodynamics
Abstract In this study, we propose the maximum admittance method based on an analytical solution of two-element Windkessel model to generate pressure waveforms for imposing outlet boundary conditions in blood flow simulations in the absence of in vivo pressure data. The lumped parameters of the Wind...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-90604-0 |
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| Summary: | Abstract In this study, we propose the maximum admittance method based on an analytical solution of two-element Windkessel model to generate pressure waveforms for imposing outlet boundary conditions in blood flow simulations in the absence of in vivo pressure data. The lumped parameters of the Windkessel model, which were not calibrated from the in vivo pressure, were determined to maximize peripheral admittance. By applying the pressure waveforms at outlet boundaries, hemodynamic characteristics of human cerebrovascular networks, including stenotic middle cerebral arteries (MCAs), were investigated through transient flow simulations. Two age-related flow waveforms, in addition to three different blood viscosities, were applied across each severity case (total 24 simulation cases). The age-related flow waveforms introduced normalized relative residence time disparities exceeding 30% in post-stenosis regions with over 50% severity. Additionally, stenosis exceeding 50% severity redirected more blood flow toward anterior cerebral artery, leading to MCA ischemia at 88% severity. The maximum pressure gradient on the stenotic walls and fractional pressure ratio exhibited changes below 9% and 3%, respectively, despite a 54.5% increase in viscosity. The stenosis severity was a dominant physiological factor, suggesting 50% severity as a critical transition point in cerebral hemodynamics. This threshold can help in quickly identifying risky locations. |
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| ISSN: | 2045-2322 |