Literature DB >> 34490929

Comparison of prospective and retrospective motion correction in 3D-encoded neuroanatomical MRI.

Jakob M Slipsager1,2,3,4, Stefan L Glimberg3, Liselotte Højgaard2, Rasmus R Paulsen1, Paul Wighton4, M Dylan Tisdall5, Camilo Jaimes6,7, Borjan A Gagoski7,8, P Ellen Grant7,8, André van der Kouwe4,7, Oline V Olesen1,2,3, Robert Frost4,7.   

Abstract

PURPOSE: To compare prospective motion correction (PMC) and retrospective motion correction (RMC) in Cartesian 3D-encoded MPRAGE scans and to investigate the effects of correction frequency and parallel imaging on the performance of RMC.
METHODS: Head motion was estimated using a markerless tracking system and sent to a modified MPRAGE sequence, which can continuously update the imaging FOV to perform PMC. The prospective correction was applied either before each echo train (before-ET) or at every sixth readout within the ET (within-ET). RMC was applied during image reconstruction by adjusting k-space trajectories according to the measured motion. The motion correction frequency was retrospectively increased with RMC or decreased with reverse RMC. Phantom and in vivo experiments were used to compare PMC and RMC, as well as to compare within-ET and before-ET correction frequency during continuous motion. The correction quality was quantitatively evaluated using the structural similarity index measure with a reference image without motion correction and without intentional motion.
RESULTS: PMC resulted in superior image quality compared to RMC both visually and quantitatively. Increasing the correction frequency from before-ET to within-ET reduced the motion artifacts in RMC. A hybrid PMC and RMC correction, that is, retrospectively increasing the correction frequency of before-ET PMC to within-ET, also reduced motion artifacts. Inferior performance of RMC compared to PMC was shown with GRAPPA calibration data without intentional motion and without any GRAPPA acceleration.
CONCLUSION: Reductions in local Nyquist violations with PMC resulted in superior image quality compared to RMC. Increasing the motion correction frequency to within-ET reduced the motion artifacts in both RMC and PMC.
© 2021 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  MRI motion artifact correction; brain MRI; markerless head motion tracking; prospective motion correction; retrospective motion correction

Mesh:

Year:  2021        PMID: 34490929      PMCID: PMC8635810          DOI: 10.1002/mrm.28991

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  38 in total

1.  Generalized autocalibrating partially parallel acquisitions (GRAPPA).

Authors:  Mark A Griswold; Peter M Jakob; Robin M Heidemann; Mathias Nittka; Vladimir Jellus; Jianmin Wang; Berthold Kiefer; Axel Haase
Journal:  Magn Reson Med       Date:  2002-06       Impact factor: 4.668

2.  Motion tracking for medical imaging: a nonvisible structured light tracking approach.

Authors:  Oline Vinter Olesen; Rasmus R Paulsen; Liselotte Højgaard; Bjarne Roed; Rasmus Larsen
Journal:  IEEE Trans Med Imaging       Date:  2011-08-18       Impact factor: 10.048

3.  Retrospective correction of involuntary microscopic head movement using highly accelerated fat image navigators (3D FatNavs) at 7T.

Authors:  Daniel Gallichan; José P Marques; Rolf Gruetter
Journal:  Magn Reson Med       Date:  2015-04-14       Impact factor: 4.668

4.  Head motion measurement and correction using FID navigators.

Authors:  Tess E Wallace; Onur Afacan; Maryna Waszak; Tobias Kober; Simon K Warfield
Journal:  Magn Reson Med       Date:  2018-07-29       Impact factor: 4.668

5.  T1 -FLAIR imaging during continuous head motion: Combining PROPELLER with an intelligent marker.

Authors:  Ola Norbeck; Adam van Niekerk; Enrico Avventi; Henric Rydén; Johan Berglund; Tim Sprenger; Stefan Skare
Journal:  Magn Reson Med       Date:  2020-09-01       Impact factor: 4.668

6.  Prospective motion correction with NMR markers using only native sequence elements.

Authors:  Alexander Aranovitch; Maximilian Haeberlin; Simon Gross; Benjamin E Dietrich; Bertram J Wilm; David O Brunner; Thomas Schmid; Roger Luechinger; Klaas P Pruessmann
Journal:  Magn Reson Med       Date:  2017-08-24       Impact factor: 4.668

7.  Toward Quantifying the Prevalence, Severity, and Cost Associated With Patient Motion During Clinical MR Examinations.

Authors:  Jalal B Andre; Brian W Bresnahan; Mahmud Mossa-Basha; Michael N Hoff; C Patrick Smith; Yoshimi Anzai; Wendy A Cohen
Journal:  J Am Coll Radiol       Date:  2015-05-09       Impact factor: 5.532

8.  TArgeted Motion Estimation and Reduction (TAMER): Data Consistency Based Motion Mitigation for MRI Using a Reduced Model Joint Optimization.

Authors:  Melissa W Haskell; Stephen F Cauley; Lawrence L Wald
Journal:  IEEE Trans Med Imaging       Date:  2018-05       Impact factor: 10.048

9.  Quantifying the Financial Savings of Motion Correction in Brain MRI: A Model-Based Estimate of the Costs Arising From Patient Head Motion and Potential Savings From Implementation of Motion Correction.

Authors:  Jakob M Slipsager; Stefan L Glimberg; Jes Søgaard; Rasmus R Paulsen; Helle H Johannesen; Pernille C Martens; Alka Seth; Lisbeth Marner; Otto M Henriksen; Oline V Olesen; Liselotte Højgaard
Journal:  J Magn Reson Imaging       Date:  2020-03-07       Impact factor: 4.813

10.  Motion-corrected MRI with DISORDER: Distributed and incoherent sample orders for reconstruction deblurring using encoding redundancy.

Authors:  Lucilio Cordero-Grande; Giulio Ferrazzi; Rui Pedro A G Teixeira; Jonathan O'Muircheartaigh; Anthony N Price; Joseph V Hajnal
Journal:  Magn Reson Med       Date:  2020-01-03       Impact factor: 4.668

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  2 in total

1.  Data-driven motion-corrected brain MRI incorporating pose-dependent B0 fields.

Authors:  Yannick Brackenier; Lucilio Cordero-Grande; Raphael Tomi-Tricot; Thomas Wilkinson; Philippa Bridgen; Anthony Price; Shaihan J Malik; Enrico De Vita; Joseph V Hajnal
Journal:  Magn Reson Med       Date:  2022-05-08       Impact factor: 3.737

2.  Tracking of rigid head motion during MRI using an EEG system.

Authors:  Malte Laustsen; Mads Andersen; Rong Xue; Kristoffer H Madsen; Lars G Hanson
Journal:  Magn Reson Med       Date:  2022-04-25       Impact factor: 3.737

  2 in total

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