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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer Berlin Heidelberg
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8463518/ https://www.ncbi.nlm.nih.gov/pubmed/32974727 http://dx.doi.org/10.1007/s00062-020-00959-2 |
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author | Gaidzik, Franziska Pathiraja, Sahani Saalfeld, Sylvia Stucht, Daniel Speck, Oliver Thévenin, Dominique Janiga, Gábor |
author_facet | Gaidzik, Franziska Pathiraja, Sahani Saalfeld, Sylvia Stucht, Daniel Speck, Oliver Thévenin, Dominique Janiga, Gábor |
author_sort | Gaidzik, Franziska |
collection | PubMed |
description | 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., 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. |
format | Online Article Text |
id | pubmed-8463518 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-84635182021-10-08 Hemodynamic Data Assimilation in a Subject-specific Circle of Willis Geometry Gaidzik, Franziska Pathiraja, Sahani Saalfeld, Sylvia Stucht, Daniel Speck, Oliver Thévenin, Dominique Janiga, Gábor Clin Neuroradiol Original Article 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., 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. Springer Berlin Heidelberg 2020-09-24 2021 /pmc/articles/PMC8463518/ /pubmed/32974727 http://dx.doi.org/10.1007/s00062-020-00959-2 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Gaidzik, Franziska Pathiraja, Sahani Saalfeld, Sylvia Stucht, Daniel Speck, Oliver Thévenin, Dominique Janiga, Gábor Hemodynamic Data Assimilation in a Subject-specific Circle of Willis Geometry |
title | Hemodynamic Data Assimilation in a Subject-specific Circle of Willis Geometry |
title_full | Hemodynamic Data Assimilation in a Subject-specific Circle of Willis Geometry |
title_fullStr | Hemodynamic Data Assimilation in a Subject-specific Circle of Willis Geometry |
title_full_unstemmed | Hemodynamic Data Assimilation in a Subject-specific Circle of Willis Geometry |
title_short | Hemodynamic Data Assimilation in a Subject-specific Circle of Willis Geometry |
title_sort | hemodynamic data assimilation in a subject-specific circle of willis geometry |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8463518/ https://www.ncbi.nlm.nih.gov/pubmed/32974727 http://dx.doi.org/10.1007/s00062-020-00959-2 |
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