ArticleJournal of biomechanics2019
An efficient full space-time discretization method for subject-specific hemodynamic simulations of cerebral arterial blood flow with distensible wall mechanics.
Article in Journal of biomechanics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Vascular synthesis based on hemodynamic efficiency principle recapitulates measured cerebral circulation properties in the human brain.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2024Article
- Multi-Dimensional Modeling of Cerebral Hemodynamics: A Systematic Review.Bioengineering (Basel, Switzerland) · 2024Review
- Physics-Informed Neural Networks for Brain Hemodynamic Predictions Using Medical Imaging.IEEE transactions on medical imaging · 2022Article
- Mathematical synthesis of the cortical circulation for the whole mouse brain-part II: Microcirculatory closure.Microcirculation (New York, N.Y. : 1994) · 2021Article
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5 authors.
Funding
Abstract
A computationally inexpensive mathematical solution approach using orthogonal collocations for space discretization with temporal Fourier series is proposed to compute subject-specific blood flow in distensible vessels of large cerebral arterial networks. Several models of wall biomechanics were considered to assess their impact on hemodynamic predictions. Simulations were validated against in vivo blood flow measurements in six human subjects. The average root-mean-square relative differences were found to be less than 4.3% for all subjects with a linear elastic wall model. This discrepancy decreased further in a viscoelastic Kelvin-Voigt biomechanical wall. The results provide support for the use of collocation-Fourier series approach to predict clinically relevant blood flow distribution and collateral blood supply in large portions of the cerebral circulation at reasonable computational costs. It thus opens the possibility of performing computationally inexpensive subject-specific simulations that are robust and fast enough to predict clinical results in real time on the same day.
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