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Blood flow imaging by optimal matching of computational fluid dynamics to 4D-flow data

Töger, Johannes LU ; Zahr, Matthew J. ; Aristokleous, Nicolas LU orcid ; Markenroth Bloch, Karin LU orcid ; Carlsson, Marcus LU and Persson, Per Olof (2020) In Magnetic Resonance in Medicine 84(4). p.2231-2245
Abstract

Purpose: Three-dimensional, time-resolved blood flow measurement (4D-flow) is a powerful research and clinical tool, but improved resolution and scan times are needed. Therefore, this study aims to (1) present a postprocessing framework for optimization-driven simulation-based flow imaging, called 4D-flow High-resolution Imaging with a priori Knowledge Incorporating the Navier-Stokes equations and the discontinuous Galerkin method (4D-flow HIKING), (2) investigate the framework in synthetic tests, (3) perform phantom validation using laser particle imaging velocimetry, and (4) demonstrate the use of the framework in vivo. Methods: An optimizing computational fluid dynamics solver including adjoint-based optimization was developed to fit... (More)

Purpose: Three-dimensional, time-resolved blood flow measurement (4D-flow) is a powerful research and clinical tool, but improved resolution and scan times are needed. Therefore, this study aims to (1) present a postprocessing framework for optimization-driven simulation-based flow imaging, called 4D-flow High-resolution Imaging with a priori Knowledge Incorporating the Navier-Stokes equations and the discontinuous Galerkin method (4D-flow HIKING), (2) investigate the framework in synthetic tests, (3) perform phantom validation using laser particle imaging velocimetry, and (4) demonstrate the use of the framework in vivo. Methods: An optimizing computational fluid dynamics solver including adjoint-based optimization was developed to fit computational fluid dynamics solutions to 4D-flow data. Synthetic tests were performed in 2D, and phantom validation was performed with pulsatile flow. Reference velocity data were acquired using particle imaging velocimetry, and 4D-flow data were acquired at 1.5 T. In vivo testing was performed on intracranial arteries in a healthy volunteer at 7 T, with 2D flow as the reference. Results: Synthetic tests showed low error (0.4%-0.7%). Phantom validation showed improved agreement with laser particle imaging velocimetry compared with input 4D-flow in the horizontal (mean −0.05 vs −1.11 cm/s, P <.001; SD 1.86 vs 4.26 cm/s, P <.001) and vertical directions (mean 0.05 vs −0.04 cm/s, P =.29; SD 1.36 vs 3.95 cm/s, P <.001). In vivo data show a reduction in flow rate error from 14% to 3.5%. Conclusions: Phantom and in vivo results from 4D-flow HIKING show promise for future applications with higher resolution, shorter scan times, and accurate quantification of physiological parameters.

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author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
4D-flow MRI, blood flow, computational fluid dynamics, simulation-based imaging
in
Magnetic Resonance in Medicine
volume
84
issue
4
pages
15 pages
publisher
John Wiley & Sons Inc.
external identifiers
  • pmid:32270549
  • scopus:85083067993
ISSN
0740-3194
DOI
10.1002/mrm.28269
language
English
LU publication?
yes
id
ad184310-0907-4665-a7ab-cc810703c40b
date added to LUP
2020-05-06 16:45:00
date last changed
2024-05-15 10:18:52
@article{ad184310-0907-4665-a7ab-cc810703c40b,
  abstract     = {{<p>Purpose: Three-dimensional, time-resolved blood flow measurement (4D-flow) is a powerful research and clinical tool, but improved resolution and scan times are needed. Therefore, this study aims to (1) present a postprocessing framework for optimization-driven simulation-based flow imaging, called 4D-flow High-resolution Imaging with a priori Knowledge Incorporating the Navier-Stokes equations and the discontinuous Galerkin method (4D-flow HIKING), (2) investigate the framework in synthetic tests, (3) perform phantom validation using laser particle imaging velocimetry, and (4) demonstrate the use of the framework in vivo. Methods: An optimizing computational fluid dynamics solver including adjoint-based optimization was developed to fit computational fluid dynamics solutions to 4D-flow data. Synthetic tests were performed in 2D, and phantom validation was performed with pulsatile flow. Reference velocity data were acquired using particle imaging velocimetry, and 4D-flow data were acquired at 1.5 T. In vivo testing was performed on intracranial arteries in a healthy volunteer at 7 T, with 2D flow as the reference. Results: Synthetic tests showed low error (0.4%-0.7%). Phantom validation showed improved agreement with laser particle imaging velocimetry compared with input 4D-flow in the horizontal (mean −0.05 vs −1.11 cm/s, P &lt;.001; SD 1.86 vs 4.26 cm/s, P &lt;.001) and vertical directions (mean 0.05 vs −0.04 cm/s, P =.29; SD 1.36 vs 3.95 cm/s, P &lt;.001). In vivo data show a reduction in flow rate error from 14% to 3.5%. Conclusions: Phantom and in vivo results from 4D-flow HIKING show promise for future applications with higher resolution, shorter scan times, and accurate quantification of physiological parameters.</p>}},
  author       = {{Töger, Johannes and Zahr, Matthew J. and Aristokleous, Nicolas and Markenroth Bloch, Karin and Carlsson, Marcus and Persson, Per Olof}},
  issn         = {{0740-3194}},
  keywords     = {{4D-flow MRI; blood flow; computational fluid dynamics; simulation-based imaging}},
  language     = {{eng}},
  number       = {{4}},
  pages        = {{2231--2245}},
  publisher    = {{John Wiley & Sons Inc.}},
  series       = {{Magnetic Resonance in Medicine}},
  title        = {{Blood flow imaging by optimal matching of computational fluid dynamics to 4D-flow data}},
  url          = {{http://dx.doi.org/10.1002/mrm.28269}},
  doi          = {{10.1002/mrm.28269}},
  volume       = {{84}},
  year         = {{2020}},
}