Image distortion correction for MRI in low field permanent magnet systems with strong B0 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 B 0 inhomogeneity and gradient field nonlinearities. Materials and methods Conventional image distortion correction algorithms require accurate Δ B...

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Published in:	Magma (New York, N.Y.) Vol. 34; no. 4; pp. 631 - 642
Main Authors:	Koolstra, Kirsten, O’Reilly, Thomas, Börnert, Peter, Webb, Andrew
Format:	Journal Article
Language:	English
Published:	Cham Springer International Publishing 01.08.2021
Subjects:	Basic Science - Reconstruction algorithms and artificial intelligence Biomedical Engineering and Bioengineering Computer Appl. in Life Sciences Health Informatics Imaging Medicine Medicine & Public Health Radiology Short Communication Solid State Physics Low field MRI Distortion correction B mapping Conjugate phase reconstruction Model-based reconstruction
ISSN:	0968-5243, 1352-8661, 1352-8661
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Abstract	Objective To correct for image distortions produced by standard Fourier reconstruction techniques on low field permanent magnet MRI systems with strong B 0 inhomogeneity and gradient field nonlinearities. Materials and methods Conventional image distortion correction algorithms require accurate Δ B 0 maps which are not possible to acquire directly when the B 0 inhomogeneities also produce significant image distortions. Here we use a readout gradient time-shift in a TSE sequence to encode the B 0 field inhomogeneities in the k-space signals. Using a non-shifted and a shifted acquisition as input, Δ B 0 maps and images were reconstructed in an iterative manner. In each iteration, Δ B 0 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, Δ B 0 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 Δ B 0 map quality can be obtained without a scan time penalty. These findings were confirmed by experimental results. Discussion In case of B 0 inhomogeneities in the order of kHz, iterative MB reconstructions can help to improve both image quality and Δ B 0 map estimation.
AbstractList	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.OBJECTIVETo 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.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.MATERIALS AND METHODSConventional 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.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.RESULTSSimulation 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.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.DISCUSSIONIn 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. Objective To correct for image distortions produced by standard Fourier reconstruction techniques on low field permanent magnet MRI systems with strong B 0 inhomogeneity and gradient field nonlinearities. Materials and methods Conventional image distortion correction algorithms require accurate Δ B 0 maps which are not possible to acquire directly when the B 0 inhomogeneities also produce significant image distortions. Here we use a readout gradient time-shift in a TSE sequence to encode the B 0 field inhomogeneities in the k-space signals. Using a non-shifted and a shifted acquisition as input, Δ B 0 maps and images were reconstructed in an iterative manner. In each iteration, Δ B 0 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, Δ B 0 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 Δ B 0 map quality can be obtained without a scan time penalty. These findings were confirmed by experimental results. Discussion In case of B 0 inhomogeneities in the order of kHz, iterative MB reconstructions can help to improve both image quality and Δ B 0 map estimation.
Author	Koolstra, Kirsten Webb, Andrew O’Reilly, Thomas Börnert, Peter
Author_xml	– sequence: 1 givenname: Kirsten orcidid: 0000-0002-7873-1511 surname: Koolstra fullname: Koolstra, Kirsten email: K.Koolstra@lumc.nl organization: Radiology, Division of Image Processing, Leiden University Medical Center – sequence: 2 givenname: Thomas surname: O’Reilly fullname: O’Reilly, Thomas organization: Radiology, C.J. Gorter Center for High-Field MRI, Leiden University Medical Center – sequence: 3 givenname: Peter surname: Börnert fullname: Börnert, Peter organization: Radiology, C.J. Gorter Center for High-Field MRI, Leiden University Medical Center, Philips Research – sequence: 4 givenname: Andrew surname: Webb fullname: Webb, Andrew organization: Radiology, C.J. Gorter Center for High-Field MRI, Leiden University Medical Center
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Cites_doi	10.1002/mrm.20261 10.1137/040605412 10.1002/mrm.25859 10.1002/cmr.b.20018 10.1109/TMAG.2017.2751001 10.1007/s10334-008-0105-7 10.1109/42.3926 10.1038/s41598-016-0028-x 10.1002/mrm.27371 10.1002/mrm.27547 10.1137/080725891 10.1016/j.neuroimage.2016.07.009 10.1016/j.jmr.2017.03.001 10.1002/mrm.1910380509 10.1016/j.jmr.2019.106578 10.1002/mrm.1910370523 10.1109/TMI.2008.923956 10.1016/j.mri.2019.09.008 10.1002/mrm.1910370619 10.1038/srep15177 10.1002/mrm.1910340111 10.1002/mrm.23085 10.1002/mrm.28396 10.1137/1.9780898718003 10.1109/PIERS-FALL.2017.8293655
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Keywords	Low field MRI Distortion correction B mapping Conjugate phase reconstruction Model-based reconstruction
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References	Jezzard, Balaban (CR10) 1995; 34 CR18 Zaitsev, Hennig, Speck (CR9) 2004; 52 Koolstra, van Gemert, Börnert, Webb, Remis (CR28) 2019 Zimmerman Cooley, Haskell, Cauley (CR5) 2017; 54 Cooley, Stockmann, Armstrong (CR4) 2015; 72 Osher, Burger, Goldfarb, Xu, Yin (CR22) 2005; 4 Goldstein, Osher (CR23) 2009; 2 Galiana, Stockmann, Tam, Constable (CR25) 2012; 67 Hennig, Welz, Schultz (CR26) 2008; 21 Raich, Blümler (CR1) 2004; 23 O’Reilly, Teeuwisse, Webb (CR6) 2019 Maeda, Sano, Yokoyama (CR16) 1988; 7 Han, Moritz, Oberacker, Waiczies, Niendorf, Winter (CR19) 2017; 7 CR2 Dymerska, Poser, Barth, Trattnig, Robinson (CR11) 2018; 168 Cooley, McDaniel, Stockmann (CR13) 2020; 2004 CR29 Funai, Fessler, Yeo, Olafsson, Noll (CR14) 2008; 27 CR24 CR21 Wan, Gullberg, Parker, Zeng (CR8) 1997; 37 Robson, Gore, Constable (CR7) 1997; 38 Man, Pauly, Macovski (CR15) 1997; 37 Usman, Kakkar, Matakos, Kirkham, Arridge, Atkinson (CR17) 2020; 65 Usman, Kakkar, Kirkham, Arridge, Atkinson (CR12) 2019; 81 Sarracanie, Lapierre, Salameh, Waddington, Witzel, Rosen (CR20) 2015; 5 Layton, Kroboth, Jia, Littin, Yu, Zaitsev (CR27) 2016; 76 Tayler, Sakellariou (CR3) 2017; 277 K Koolstra (907_CR28) 2019 MCD Tayler (907_CR3) 2017; 277 P Jezzard (907_CR10) 1995; 34 907_CR21 KJ Layton (907_CR27) 2016; 76 907_CR24 907_CR29 X Wan (907_CR8) 1997; 37 J Hennig (907_CR26) 2008; 21 M Zaitsev (907_CR9) 2004; 52 LC Man (907_CR15) 1997; 37 M Sarracanie (907_CR20) 2015; 5 AK Funai (907_CR14) 2008; 27 H Raich (907_CR1) 2004; 23 T Goldstein (907_CR23) 2009; 2 C Zimmerman Cooley (907_CR5) 2017; 54 G Galiana (907_CR25) 2012; 67 M Usman (907_CR17) 2020; 65 H Han (907_CR19) 2017; 7 MD Robson (907_CR7) 1997; 38 A Maeda (907_CR16) 1988; 7 B Dymerska (907_CR11) 2018; 168 C Cooley (907_CR4) 2015; 72 907_CR18 T O’Reilly (907_CR6) 2019 S Osher (907_CR22) 2005; 4 M Usman (907_CR12) 2019; 81 907_CR2 CZ Cooley (907_CR13) 2020; 2004
References_xml	– volume: 52 start-page: 1156 issue: 5 year: 2004 end-page: 1166 ident: CR9 article-title: Point spread function mapping with parallel imaging techniques and high acceleration factors: fast, robust, and flexible method for echo-planar imaging distortion correction publication-title: Magn Reson Med doi: 10.1002/mrm.20261 – volume: 4 start-page: 460 issue: 2 year: 2005 end-page: 489 ident: CR22 article-title: An iterative regularization method for total variation-based image restoration publication-title: Multiscale Model Simul doi: 10.1137/040605412 – volume: 76 start-page: 104 issue: 1 year: 2016 end-page: 117 ident: CR27 article-title: Trajectory optimization based on the signal-to-noise ratio for spatial encoding with nonlinear encoding fields publication-title: Magn Reson Med doi: 10.1002/mrm.25859 – ident: CR18 – volume: 23 start-page: 16 issue: 1 year: 2004 end-page: 25 ident: CR1 article-title: Design and construction of a dipolar halbach array with a homogeneous field from identical bar magnets: NMR Mandhalas publication-title: Concepts Magn Reson Part B Magn Reson Eng doi: 10.1002/cmr.b.20018 – volume: 54 start-page: 1 issue: 1 year: 2017 end-page: 12 ident: CR5 article-title: Design of Sparse Halbach magnet arrays for portable MRI using a genetic algorithm publication-title: IEEE Trans Magn doi: 10.1109/TMAG.2017.2751001 – ident: CR2 – volume: 21 start-page: 5 issue: 1–2 year: 2008 end-page: 14 ident: CR26 article-title: Parallel imaging in non-bijective, curvilinear magnetic field gradients: a concept study publication-title: Magn Reson Mater Physics, Biol Med doi: 10.1007/s10334-008-0105-7 – volume: 7 start-page: 26 issue: 1 year: 1988 end-page: 31 ident: CR16 article-title: Reconstruction by weighted correlation for MRI with time-varying gradients publication-title: IEEE Trans Med Imaging doi: 10.1109/42.3926 – ident: CR29 – volume: 7 start-page: 1 issue: 1 year: 2017 end-page: 12 ident: CR19 article-title: Open source 3D multipurpose measurement system with submillimetre fidelity and first application in magnetic resonance publication-title: Sci Rep doi: 10.1038/s41598-016-0028-x – year: 2019 ident: CR28 article-title: Accelerating compressed sensing in parallel imaging reconstructions using an efficient circulant preconditioner for cartesian trajectories publication-title: Magn Reson Med doi: 10.1002/mrm.27371 – ident: CR21 – volume: 81 start-page: 1979 issue: 3 year: 2019 end-page: 1992 ident: CR12 article-title: Model-based reconstruction framework for correction of signal pile-up and geometric distortions in prostate diffusion MRI publication-title: Magn Reson Med doi: 10.1002/mrm.27547 – volume: 2 start-page: 323 issue: 2 year: 2009 end-page: 343 ident: CR23 article-title: The split Bregman method for L1-regularized problems publication-title: SIAM J Imaging Sci doi: 10.1137/080725891 – volume: 168 start-page: 321 year: 2018 end-page: 331 ident: CR11 article-title: A method for the dynamic correction of B0-related distortions in single-echo EPI at 7 T publication-title: Neuroimage doi: 10.1016/j.neuroimage.2016.07.009 – volume: 277 start-page: 143 year: 2017 end-page: 148 ident: CR3 article-title: Low-cost, pseudo-Halbach dipole magnets for NMR publication-title: J Magn Reson doi: 10.1016/j.jmr.2017.03.001 – volume: 2004 start-page: 13183 year: 2020 ident: CR13 article-title: A portable brain MRI scanner for underserved settings and point-of-care imaging publication-title: arXiv Prepr arXiv – volume: 38 start-page: 733 issue: 5 year: 1997 end-page: 740 ident: CR7 article-title: Measurement of the point spread function in MRI using constant time imaging publication-title: Magn Reson Med doi: 10.1002/mrm.1910380509 – year: 2019 ident: CR6 article-title: Three-dimensional MRI in a homogenous 27 cm diameter bore Halbach array magnet publication-title: J Magn Reson doi: 10.1016/j.jmr.2019.106578 – volume: 37 start-page: 785 issue: 5 year: 1997 end-page: 792 ident: CR15 article-title: Multifrequency interpolation for fast off-resonance correction publication-title: Magn Reson Med doi: 10.1002/mrm.1910370523 – volume: 27 start-page: 1484 issue: 10 year: 2008 end-page: 1494 ident: CR14 article-title: Regularized field map estimation in MRI publication-title: IEEE Trans Med Imaging doi: 10.1109/TMI.2008.923956 – volume: 65 start-page: 90 year: 2020 end-page: 99 ident: CR17 article-title: Joint B0 and image estimation integrated with model based reconstruction for field map update and distortion correction in prostate diffusion MRI publication-title: Magn Reson Imaging doi: 10.1016/j.mri.2019.09.008 – volume: 37 start-page: 932 issue: 6 year: 1997 end-page: 942 ident: CR8 article-title: Reduction of geometric and intensity distortions in echo-planar imaging using a multireference scan publication-title: Magn Reson Med doi: 10.1002/mrm.1910370619 – volume: 72 start-page: 1 issue: 3 year: 2015 end-page: 15 ident: CR4 article-title: 2D Imaging in a lightweight portable MRI scanner without gradient coils publication-title: Magn Reson Med – volume: 5 start-page: 1 issue: 1 year: 2015 end-page: 9 ident: CR20 article-title: Low-cost high-performance MRI publication-title: Sci Rep doi: 10.1038/srep15177 – volume: 34 start-page: 65 issue: 1 year: 1995 end-page: 73 ident: CR10 article-title: Correction for geometric distortion in echo planar images from B0 field variations publication-title: Magn Reson Med doi: 10.1002/mrm.1910340111 – volume: 67 start-page: 1120 issue: 4 year: 2012 end-page: 1126 ident: CR25 article-title: Spin dephasing under nonlinear gradients: implications for imaging and field mapping publication-title: Magn Reson Med doi: 10.1002/mrm.23085 – ident: CR24 – year: 2019 ident: 907_CR6 publication-title: J Magn Reson doi: 10.1016/j.jmr.2019.106578 – ident: 907_CR21 – volume: 168 start-page: 321 year: 2018 ident: 907_CR11 publication-title: Neuroimage doi: 10.1016/j.neuroimage.2016.07.009 – volume: 67 start-page: 1120 issue: 4 year: 2012 ident: 907_CR25 publication-title: Magn Reson Med doi: 10.1002/mrm.23085 – volume: 54 start-page: 1 issue: 1 year: 2017 ident: 907_CR5 publication-title: IEEE Trans Magn doi: 10.1109/TMAG.2017.2751001 – ident: 907_CR18 doi: 10.1002/mrm.28396 – volume: 52 start-page: 1156 issue: 5 year: 2004 ident: 907_CR9 publication-title: Magn Reson Med doi: 10.1002/mrm.20261 – volume: 72 start-page: 1 issue: 3 year: 2015 ident: 907_CR4 publication-title: Magn Reson Med – volume: 2 start-page: 323 issue: 2 year: 2009 ident: 907_CR23 publication-title: SIAM J Imaging Sci doi: 10.1137/080725891 – volume: 34 start-page: 65 issue: 1 year: 1995 ident: 907_CR10 publication-title: Magn Reson Med doi: 10.1002/mrm.1910340111 – volume: 37 start-page: 785 issue: 5 year: 1997 ident: 907_CR15 publication-title: Magn Reson Med doi: 10.1002/mrm.1910370523 – ident: 907_CR24 – volume: 7 start-page: 1 issue: 1 year: 2017 ident: 907_CR19 publication-title: Sci Rep doi: 10.1038/s41598-016-0028-x – volume: 23 start-page: 16 issue: 1 year: 2004 ident: 907_CR1 publication-title: Concepts Magn Reson Part B Magn Reson Eng doi: 10.1002/cmr.b.20018 – volume: 2004 start-page: 13183 year: 2020 ident: 907_CR13 publication-title: arXiv Prepr arXiv – volume: 4 start-page: 460 issue: 2 year: 2005 ident: 907_CR22 publication-title: Multiscale Model Simul doi: 10.1137/040605412 – volume: 38 start-page: 733 issue: 5 year: 1997 ident: 907_CR7 publication-title: Magn Reson Med doi: 10.1002/mrm.1910380509 – volume: 37 start-page: 932 issue: 6 year: 1997 ident: 907_CR8 publication-title: Magn Reson Med doi: 10.1002/mrm.1910370619 – volume: 76 start-page: 104 issue: 1 year: 2016 ident: 907_CR27 publication-title: Magn Reson Med doi: 10.1002/mrm.25859 – ident: 907_CR29 doi: 10.1137/1.9780898718003 – volume: 27 start-page: 1484 issue: 10 year: 2008 ident: 907_CR14 publication-title: IEEE Trans Med Imaging doi: 10.1109/TMI.2008.923956 – volume: 277 start-page: 143 year: 2017 ident: 907_CR3 publication-title: J Magn Reson doi: 10.1016/j.jmr.2017.03.001 – volume: 7 start-page: 26 issue: 1 year: 1988 ident: 907_CR16 publication-title: IEEE Trans Med Imaging doi: 10.1109/42.3926 – volume: 5 start-page: 1 issue: 1 year: 2015 ident: 907_CR20 publication-title: Sci Rep doi: 10.1038/srep15177 – ident: 907_CR2 doi: 10.1109/PIERS-FALL.2017.8293655 – volume: 21 start-page: 5 issue: 1–2 year: 2008 ident: 907_CR26 publication-title: Magn Reson Mater Physics, Biol Med doi: 10.1007/s10334-008-0105-7 – volume: 65 start-page: 90 year: 2020 ident: 907_CR17 publication-title: Magn Reson Imaging doi: 10.1016/j.mri.2019.09.008 – year: 2019 ident: 907_CR28 publication-title: Magn Reson Med doi: 10.1002/mrm.27371 – volume: 81 start-page: 1979 issue: 3 year: 2019 ident: 907_CR12 publication-title: Magn Reson Med doi: 10.1002/mrm.27547
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Snippet	Objective To correct for image distortions produced by standard Fourier reconstruction techniques on low field permanent magnet MRI systems with strong B 0... To correct for image distortions produced by standard Fourier reconstruction techniques on low field permanent magnet MRI systems with strong [Formula: see...
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SubjectTerms	Basic Science - Reconstruction algorithms and artificial intelligence Biomedical Engineering and Bioengineering Computer Appl. in Life Sciences Health Informatics Imaging Medicine Medicine & Public Health Radiology Short Communication Solid State Physics
Title	Image distortion correction for MRI in low field permanent magnet systems with strong B0 inhomogeneity and gradient field nonlinearities
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