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- Andersen, Mads, et al.
(författare)
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Accuracy investigations for volumetric head-motion navigators with and without EPI at 7 T
- 2022
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Ingår i: Magnetic Resonance in Medicine. - : Wiley. - 0740-3194 .- 1522-2594. ; 88:3, s. 1198-1211
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Accuracy investigation of volumetric navigators for motion correction, with emphasis on geometric EPI distortions at ultrahigh field. Methods: High-resolution Dixon images were collected in different head positions and reconstructed to water, fat, T2*, and B0 maps. Resolution reduction was performed, and the T2* and B0 maps were used to apply effects of TE and EPI distortions to simulate various volumetric water and fat navigators. Registrations of the simulated navigators were compared with registrations of the original high-resolution images. Results: Increased accuracy was observed with increased spatial resolution for non-EPI navigators. When using EPI, the distortions had a negative effect on registration accuracy, which was most noticeable for high-resolution navigators. Parallel imaging helped to alleviate those caveats to a certain extent, and 5-fold acceleration gave close to similar accuracy to non-EPI in most cases. Shortening the TE by partial Fourier sampling was shown to be mostly beneficial, except for water navigators with long readout durations. The EPI blip direction had an influence on navigator accuracy, and positive blip gradient polarities (yielding mostly image stretching frontally) typically gave the best accuracy for water navigators, whereas no clear recommendation could be made for fat navigators. Generally, fat EPI navigators had lower accuracy than water EPI navigators with otherwise similar parameters. Conclusions: Echo planar imaging has been widely used for MRI navigators, but the induced distortions reduce navigator accuracy at ultrahigh field. This study can help protocol optimization and guide the complex tradeoff between resolution and EPI acceleration in navigator parameter setup.
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| 2. |
- Laustsen, Malte, et al.
(författare)
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Tracking of rigid head motion during MRI using an EEG system
- 2022
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Ingår i: Magnetic Resonance in Medicine. - : Wiley. - 0740-3194 .- 1522-2594. ; 82:2, s. 986-1001
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To demonstrate a novel method for tracking of head movements during MRI using electroencephalography (EEG) hardware for recording signals induced by native imaging gradients. Theory and Methods: Gradient switching during simultaneous EEG–fMRI induces distortions in EEG signals, which depend on subject head position and orientation. When EEG electrodes are interconnected with high-impedance carbon wire loops, the induced voltages are linear combinations of the temporal gradient waveform derivatives. We introduce head tracking based on these signals (CapTrack) involving 3 steps: (1) phantom scanning is used to characterize the target sequence and a fast calibration sequence; (2) a linear relation between changes of induced signals and head pose is established using the calibration sequence; and (3) induced signals recorded during target sequence scanning are used for tracking and retrospective correction of head movement without prolonging the scan time of the target sequence. Performance of CapTrack is compared directly to interleaved navigators. Results: Head-pose tracking at 27.5 Hz during echo planar imaging (EPI) was demonstrated with close resemblance to rigid body alignment (mean absolute difference: [0.14 0.38 0.15]-mm translation, [0.30 0.27 0.22]-degree rotation). Retrospective correction of 3D gradient-echo imaging shows an increase of average edge strength of 12%/−0.39% for instructed/uninstructed motion with CapTrack pose estimates, with a tracking interval of 1561 ms and high similarity to interleaved navigator estimates (mean absolute difference: [0.13 0.33 0.12] mm, [0.28 0.15 0.22] degrees). Conclusion: Motion can be estimated from recordings of gradient switching with little or no sequence modification, optionally in real time at low computational burden and synchronized to image acquisition, using EEG equipment already found at many research institutions.
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