ArticleClinical neuroradiology2021
Hemodynamic Data Assimilation in a Subject-specific Circle of Willis Geometry.
Article in Clinical neuroradiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Associations Between Hemodynamics, Shape and Atherosclerosis in M1 of Middle Cerebral Artery: Insights From 4-Dimensional Flow Magnetic Resonance Imaging in Patients With Ischemic Stroke.Journal of the American Heart Association · 2026Article
- Survey and perspective on verification, validation, and uncertainty quantification of digital twins for precision medicine.NPJ digital medicine · 2025Review
- Numerical Modeling of Flow in the Cerebral Vasculature: Understanding Changes in Collateral Flow Directions in the Circle of Willis for a Cohort of Vasospasm Patients Through Image-Based Computational Fluid Dynamics.Annals of biomedical engineering · 2024Article
- Influence of circle of Willis modeling on hemodynamic parameters in anterior communicating artery aneurysms and recommendations for model selection.Scientific reports · 2024Article
- Image-based hemodynamic simulations for intracranial aneurysms: the impact of complex vasculature.International journal of computer assisted radiology and surgery · 2024Article
- Approaches to vascular network, blood flow, and metabolite distribution modeling in brain tissue.Biophysical reviews · 2023Review
- A hybrid hierarchical strategy for registration of 7T TOF-MRI to 7T PC-MRI intracranial vessel data.International journal of computer assisted radiology and surgery · 2023Article
- Inverse problems in blood flow modeling: A review.International journal for numerical methods in biomedical engineering · 2022Review
- Patient-Specific Inverse Modeling of In Vivo Cardiovascular Mechanics with Medical Image-Derived Kinematics as Input Data: Concepts, Methods, and Applications.Applied sciences (Basel, Switzerland) · 2022Article
- SRflow: Deep learning based super-resolution of 4D-flow MRI data.Frontiers in artificial intelligence · 2022Article
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7 authors.
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Abstract
purposeThe anatomy of the circle of Willis (CoW), the brain's main arterial blood supply system, strongly differs between individuals, resulting in highly variable flow fields and intracranial vascularization patterns. To predict subject-specific hemodynamics with high certainty, we propose a data assimilation (DA) approach that merges fully 4D phase-contrast magnetic resonance imaging (PC-MRI) data with a numerical model in the form of computational fluid dynamics (CFD) simulations.
methodsTo the best of our knowledge, this study is the first to provide a transient state estimate for the three-dimensional velocity field in a subject-specific CoW geometry using DA. High-resolution velocity state estimates are obtained using the local ensemble transform Kalman filter (LETKF).
resultsQuantitative evaluation shows a considerable reduction (up to 90%) in the uncertainty of the velocity field state estimate after the data assimilation step. Velocity values in vessel areas that are below the resolution of the PC-MRI data (e.g., in posterior communicating arteries) are provided. Furthermore, the uncertainty of the analysis-based wall shear stress distribution is reduced by a factor of 2 for the data assimilation approach when compared to the CFD model alone.
conclusionThis study demonstrates the potential of data assimilation to provide detailed information on vascular flow, and to reduce the uncertainty in such estimates by combining various sources of data in a statistically appropriate fashion.
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