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Image distortion correction for MRI in low field permanent magnet systems with strong B(0) inhomogeneity and gradient field nonlinearities

OBJECTIVE: To correct for image distortions produced by standard Fourier reconstruction techniques on low field permanent magnet MRI systems with strong [Formula: see text] inhomogeneity and gradient field nonlinearities. MATERIALS AND METHODS: Conventional image distortion correction algorithms req...

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Autores principales: Koolstra, Kirsten, O’Reilly, Thomas, Börnert, Peter, Webb, Andrew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8338849/
https://www.ncbi.nlm.nih.gov/pubmed/33502668
http://dx.doi.org/10.1007/s10334-021-00907-2
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author Koolstra, Kirsten
O’Reilly, Thomas
Börnert, Peter
Webb, Andrew
author_facet Koolstra, Kirsten
O’Reilly, Thomas
Börnert, Peter
Webb, Andrew
author_sort Koolstra, Kirsten
collection PubMed
description OBJECTIVE: To correct for image distortions produced by standard Fourier reconstruction techniques on low field permanent magnet MRI systems with strong [Formula: see text] inhomogeneity and gradient field nonlinearities. MATERIALS AND METHODS: Conventional image distortion correction algorithms require accurate [Formula: see text] maps which are not possible to acquire directly when the [Formula: see text] inhomogeneities also produce significant image distortions. Here we use a readout gradient time-shift in a TSE sequence to encode the [Formula: see text] field inhomogeneities in the k-space signals. Using a non-shifted and a shifted acquisition as input, [Formula: see text] maps and images were reconstructed in an iterative manner. In each iteration, [Formula: see text] maps were reconstructed from the phase difference using Tikhonov regularization, while images were reconstructed using either conjugate phase reconstruction (CPR) or model-based (MB) image reconstruction, taking the reconstructed field map into account. MB reconstructions were, furthermore, combined with compressed sensing (CS) to show the flexibility of this approach towards undersampling. These methods were compared to the standard fast Fourier transform (FFT) image reconstruction approach in simulations and measurements. Distortions due to gradient nonlinearities were corrected in CPR and MB using simulated gradient maps. RESULTS: Simulation results show that for moderate field inhomogeneities and gradient nonlinearities, [Formula: see text] maps and images reconstructed using iterative CPR result in comparable quality to that for iterative MB reconstructions. However, for stronger inhomogeneities, iterative MB reconstruction outperforms iterative CPR in terms of signal intensity correction. Combining MB with CS, similar image and [Formula: see text] map quality can be obtained without a scan time penalty. These findings were confirmed by experimental results. DISCUSSION: In case of [Formula: see text] inhomogeneities in the order of kHz, iterative MB reconstructions can help to improve both image quality and [Formula: see text] map estimation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10334-021-00907-2.
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spelling pubmed-83388492021-08-20 Image distortion correction for MRI in low field permanent magnet systems with strong B(0) inhomogeneity and gradient field nonlinearities Koolstra, Kirsten O’Reilly, Thomas Börnert, Peter Webb, Andrew MAGMA Short Communication OBJECTIVE: To correct for image distortions produced by standard Fourier reconstruction techniques on low field permanent magnet MRI systems with strong [Formula: see text] inhomogeneity and gradient field nonlinearities. MATERIALS AND METHODS: Conventional image distortion correction algorithms require accurate [Formula: see text] maps which are not possible to acquire directly when the [Formula: see text] inhomogeneities also produce significant image distortions. Here we use a readout gradient time-shift in a TSE sequence to encode the [Formula: see text] field inhomogeneities in the k-space signals. Using a non-shifted and a shifted acquisition as input, [Formula: see text] maps and images were reconstructed in an iterative manner. In each iteration, [Formula: see text] maps were reconstructed from the phase difference using Tikhonov regularization, while images were reconstructed using either conjugate phase reconstruction (CPR) or model-based (MB) image reconstruction, taking the reconstructed field map into account. MB reconstructions were, furthermore, combined with compressed sensing (CS) to show the flexibility of this approach towards undersampling. These methods were compared to the standard fast Fourier transform (FFT) image reconstruction approach in simulations and measurements. Distortions due to gradient nonlinearities were corrected in CPR and MB using simulated gradient maps. RESULTS: Simulation results show that for moderate field inhomogeneities and gradient nonlinearities, [Formula: see text] maps and images reconstructed using iterative CPR result in comparable quality to that for iterative MB reconstructions. However, for stronger inhomogeneities, iterative MB reconstruction outperforms iterative CPR in terms of signal intensity correction. Combining MB with CS, similar image and [Formula: see text] map quality can be obtained without a scan time penalty. These findings were confirmed by experimental results. DISCUSSION: In case of [Formula: see text] inhomogeneities in the order of kHz, iterative MB reconstructions can help to improve both image quality and [Formula: see text] map estimation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10334-021-00907-2. Springer International Publishing 2021-01-27 2021 /pmc/articles/PMC8338849/ /pubmed/33502668 http://dx.doi.org/10.1007/s10334-021-00907-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Short Communication
Koolstra, Kirsten
O’Reilly, Thomas
Börnert, Peter
Webb, Andrew
Image distortion correction for MRI in low field permanent magnet systems with strong B(0) inhomogeneity and gradient field nonlinearities
title Image distortion correction for MRI in low field permanent magnet systems with strong B(0) inhomogeneity and gradient field nonlinearities
title_full Image distortion correction for MRI in low field permanent magnet systems with strong B(0) inhomogeneity and gradient field nonlinearities
title_fullStr Image distortion correction for MRI in low field permanent magnet systems with strong B(0) inhomogeneity and gradient field nonlinearities
title_full_unstemmed Image distortion correction for MRI in low field permanent magnet systems with strong B(0) inhomogeneity and gradient field nonlinearities
title_short Image distortion correction for MRI in low field permanent magnet systems with strong B(0) inhomogeneity and gradient field nonlinearities
title_sort image distortion correction for mri in low field permanent magnet systems with strong b(0) inhomogeneity and gradient field nonlinearities
topic Short Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8338849/
https://www.ncbi.nlm.nih.gov/pubmed/33502668
http://dx.doi.org/10.1007/s10334-021-00907-2
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