Highly accelerated PSF-mapping for EPI distortion correction with improved fidelity

In, Myung‐Ho; Speck, Oliver

doi:10.1007/s10334-011-0275-6

Cited by 58 publications

(79 citation statements)

References 16 publications

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“…Even though there may be no SAR issues related to measuring the corresponding distortion information using both the conventional field mapping (Jezzard and Balaban, 1995) and the original PSF mapping methods (Zaitsev et al, 2004), there is still a limitation in reliably correcting for severe distortions, as previously reported in studies conducted at 7T (Chung et al, 2011; In, 2012). In contrast, the correction fidelity of the proposed approach was well demonstrated in previous studies (In and Speck, 2012; In et al, 2015) and in this study. Therefore, the proposed approach would be a viable method for considering both SAR concerns and the correction fidelity in performing DBS-fMRI studies.…”

Section: Discussionsupporting

confidence: 88%

“…Because an additional PSF- (or spin-warp) PE is added to the conventional 2D-EPI sequence, the PSF mapping sequence acquires 3D k -space data including a readout ( x ) and two PE, PSF-PE ( s ) and EPI-PE ( y ), dimensions, respectively suffering from negligible, no, and strong geometric distortions (Chung et al, 2011; In and Speck, 2012). The spin-warp PE is wrapped around the EPI in a conventional manner and this dimension ( s ) is distortion-free.…”

Section: Methodsmentioning

confidence: 99%

“…Reliable measurements of the PSF profile from the 3D PSF data are particularly important in this approach for the accurate correction of both GE-EPIs with opposite distortions, since the measured PSF profile in the distorted coordinate ( y ) is used as a kernel for distortion correction (In and Speck, 2012). As opposed to SE-EPI, however, summation of the compressed voxels generally causes strong signal dropout in GE-EPI due to the intravoxel dephasing effect of the combined voxels (green arrow in Fig.…”

Section: Methodsmentioning

confidence: 99%

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Correction of metal-induced susceptibility artifacts for functional MRI during deep brain stimulation

Cho

Shu

et al. 2017

NeuroImage

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Functional magnetic resonance imaging (fMRI) is an emerging tool for investigating brain activation associated with, or modulated by, deep brain stimulation (DBS). However, DBS-fMRI generally suffers from severe susceptibility to artifacts in regions near the metallic stimulation electrodes, as well as near tissue/air boundaries of the brain. These result in strong intensity and geometric distortions along the phase-encoding (PE) (i.e., blipped) direction in gradient-echo echo-planar imaging (GE-EPI). Distortion presents a major challenge to conducting reliable data analysis and in interpreting the findings. A recent study showed that the point spread function (PSF) mapping-based reverse gradient approach has a potential to correct for distortions not only in spin-echo EPI, but also in GE-EPI acquired in both the forward and reverse PE directions. In this study, we adapted that approach in order to minimize severe metal-induced susceptibility artifacts for DBS-fMRI, and to evaluate the performance of the approach in a phantom study and a large animal DBS-fMRI study. The method combines the distortion-corrected GE-EPI pair with geometrically different intensity distortions due to the opposing encoding directions. The results demonstrate that the approach can minimize susceptibility artifacts that appear around the metallic electrodes, as well as in the regions near the tissue/air boundaries in the brain. We also demonstrated that an accurate geometric correction is important in improving BOLD contrast in the group dataset, especially in regions where strong susceptibility artifacts appear.

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Section: Discussionsupporting

confidence: 88%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Correction of metal-induced susceptibility artifacts for functional MRI during deep brain stimulation

Cho

Shu

et al. 2017

NeuroImage

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“…Thus, using a fast pre-scan for acquiring low-res sensitivity maps prior to imaging [13, 35] may be possible. Second, although several techniques for dynamic characterization of the B 0 field [44, 45] have been developed, they require additional scan time and assume that the subject remains still for each measurement step. For stronger motion, the distortion caused by B 0 field inhomogeneity has been considered for single-shot EPI time series where each acquisition can provide a field map [19, 46].…”

Section: Discussionmentioning

confidence: 99%

Correction of B 0-induced geometric distortion variations in prospective motion correction for 7T MRI

Yarach

Luengviriya

Stucht

et al. 2016

Magn Reson Mater Phy

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Objective Prospective motion correction can effectively fix the imaging volume of interest. For large motion, this can lead to relative motion of coil sensitivities, distortions associated with imaging gradients and B0 field variations. This work accounts for the B0 field change due to subject movement, and proposes a method for correcting tissue magnetic susceptibility-related distortion in prospective motion correction. Materials and methods The B0 field shifts at the different head orientations were characterized. A volunteer performed large motion with prospective motion correction enabled. The acquired data were divided into multiple groups according to the object positions. The correction of B0-related distortion was applied to each group of data individually via augmented sensitivity encoding with additionally integrated gradient nonlinearity correction. Results The relative motion of the gradients, B0 field and coil sensitivities in prospective motion correction results in residual spatial distortion, blurring, and coil artifacts. These errors can be mitigated by the proposed method. Moreover, iterative conjugate gradient optimization with regularization provided superior results with smaller RMSE in comparison to standard conjugate gradient. Conclusion The combined correction of B0-related distortion and gradient nonlinearity leads to a reduction of residual motion artifacts in prospective motion correction data.

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“…?_bold.nii.gzraw fMRI BOLD images.*rec-dico_run-? ?_bold.nii.gzDistortion corrected BOLD images [11].*motion_physio.tsv.gzWhitespace-delimited 6-column text file with motion estimates with translation along X, Y, Z axes in mm and rotation around X, Y, Z axes in deg. It contains one row per fMRI dynamic for each acquisition run.*_events.tsvText files, one for each acquisition run, with 4-columns.…”

Section: Datamentioning

confidence: 99%

Ultra high-field (7 T) multi-resolution fMRI data for orientation decoding in visual cortex

et al. 2017

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Multivariate pattern classification methods have been successfully applied to decode orientation of visual grating stimuli from BOLD fMRI activity recorded in human visual cortex (Kamitani and Tong, 2005; Haynes and Rees, 2005) [12], [10]. Though there has been extensive research investigating the true spatial scale of the orientation specific signals (Op de Beeck, 2010; Swisher et al., 2010; Alink et al., 2013; Freeman et al., 2011, 2013) [2], [15], [1], [4], [5], it remained inconclusive what spatial acquisition resolution is required, or is optimal, for decoding analyses. The research article entitled “The effect of acquisition resolution on orientation decoding from V1 BOLD fMRI at 7 T” Sengupta et al. (2017) [14] studied the effect of spatial acquisition resolution and also analyzed the strength and spatial scale of orientation discriminating signals. In this article, for the first time, we present empirical ultra high-field fMRI data, obtained as a part of the aforementioned study, which were recorded at four spatial resolutions (0.8 mm, 1.4 mm, 2 mm, and 3 mm isotropic voxel size) for orientation decoding in visual cortex. The dataset is compliant with the BIDS (Brain Imaging Data Structure) format, and freely available from the OpenfMRI portal (dataset accession number: http://openfmri.org/dataset/ds000113c ds000113c).

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Highly accelerated PSF-mapping for EPI distortion correction with improved fidelity

Abstract: The proposed EPI-PSF-based distortion correction improves correction of EPI and accelerates PSF reference data acquisition and computation.

Cited by 58 publications

References 16 publications

Correction of metal-induced susceptibility artifacts for functional MRI during deep brain stimulation

Correction of metal-induced susceptibility artifacts for functional MRI during deep brain stimulation

Correction of B 0-induced geometric distortion variations in prospective motion correction for 7T MRI

Ultra high-field (7 T) multi-resolution fMRI data for orientation decoding in visual cortex

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