Hemodynamic data assimilation in a subject-specific circle of Willis geometry
- Purpose The 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. Methods To 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). Results Quantitative 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., inPurpose The 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. Methods To 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). Results Quantitative 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. Conclusion This 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.…
Author details: | Franziska GaidzikORCiD, Sahani Darschika PathirajaORCiD, Sylvia SaalfeldORCiD, Daniel Stucht, Oliver SpeckORCiD, Dominique TheveninORCiD, Gabor JanigaORCiD |
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DOI: | https://doi.org/10.1007/s00062-020-00959-2 |
ISSN: | 1869-1439 |
ISSN: | 1869-1447 |
Pubmed ID: | https://pubmed.ncbi.nlm.nih.gov/32974727 |
Title of parent work (English): | Clinical Neuroradiology |
Publisher: | Springer |
Place of publishing: | Heidelberg |
Publication type: | Article |
Language: | English |
Date of first publication: | 2020/09/24 |
Publication year: | 2020 |
Release date: | 2023/06/20 |
Tag: | CFD; LETKF; PC-MRI; hemodynamics; uncertainty quantification |
Volume: | 31 |
Issue: | 3 |
Number of pages: | 9 |
First page: | 643 |
Last Page: | 651 |
Funding institution: | European Structural and Investment Funds (ESF) under the program; "Sachsen-Anhalt WISSENSCHAFT Internationalisierung" [ZS/2016/08/80646]; Ministry of Economics, Science and Digitization of Saxony-Anhalt in; Germany within the Forschungscampus STIMULATE [I 117]; German Research; Foundation (Deutsche Forschungsgemeinschaft, DFG)German Research; Foundation (DFG) [SFB1294/1-318763901]; German Research FoundationGerman; Research Foundation (DFG) [SA 3461/2-1] |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Mathematik |
DDC classification: | 6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit |
Peer review: | Referiert |
Publishing method: | Open Access / Hybrid Open-Access |
License (German): | CC-BY - Namensnennung 4.0 International |