Density weighted turbo spin echo imaging

Zeller, Mario; Gutberlet, Marcel; Stäb, Daniel; Ritter, Christian; Beer, Meinrad; Hahn, Dietbert; Köstler, Herbert

doi:10.1002/jmri.23872

Cited by 4 publications

(11 citation statements)

References 22 publications

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“…The FWHM is broadened by a factor of 2 compared to the unfiltered SRF, which corresponds well to the FWHM of the Gaussian filter with σ = 0.85 px in image space. Here, the spatial SNR advantage of density weighted vs. Cartesian EPI amounted to 13% which corresponds very well to the theoretical prediction of 14% [4], [9].…”

Section: Resultssupporting

confidence: 87%

“…The SNR advantage of 13% measured in a homogeneous phantom in vitro and the SNR advantage of 12.4% measured in-vivo (cf. Figure 6) correspond well with the theoretical prediction of 14% [4], [9]. Deviations from the theoretical value may arise from imperfect voxel-to-voxel correspondence between Cartesian and density weighted reconstructions, noise enhancement by parallel imaging [27] or inhomogeneity-induced k-space shifts [32].…”

Section: Discussionsupporting

confidence: 81%

“…For turbo spin echo sequences it has been shown that the actual SNR gain of density weighting vs. Cartesian imaging depends on the tissue relaxation parameters [9]. It increases if the relaxation time is shorter than assumed for the calculation of the density weighted k-space sampling and decreases if the relaxation time is longer.…”

Section: Discussionmentioning

confidence: 99%

“…Spatial SNR was determined by a pseudo multiple replica method [27] utilizing noise scans acquired at the beginning of each examination, and simulations of spatial SNR for different T 2 * were performed for Cartesian and density weighted acquisitions as described in [9]. Spatial SNR was then empirically estimated for all voxels of native Cartesian and density weighted EPI (from the 4 th and 5 th volume of the time-series, corrected only for motion and geometric distortions without further data preprocessing) in 10 consecutive slices centered around the handknob.…”

Section: Methodsmentioning

confidence: 99%

“…The resulting MTF/SRF deviations are compensated by acquiring the k-space with a non-Cartesian trajectory. The variable k-space density ρ(k) = 1/ Δ k then acts as an additional parameter influencing the shape of the MTF [9]:where S(k) describes the decaying signal during the echo train and f(k) is the retrospectively applied SNR matched filter. The target MTF can in principle be of any form, even be identical to the signal envelope given by the signal relaxation [4].…”

Section: Introductionmentioning

confidence: 99%

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Boosting BOLD fMRI by K-Space Density Weighted Echo Planar Imaging

et al. 2013

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Functional magnetic resonance imaging (fMRI) has become a powerful and influential method to non-invasively study neuronal brain activity. For this purpose, the blood oxygenation level-dependent (BOLD) effect is most widely used. T2* weighted echo planar imaging (EPI) is BOLD sensitive and the prevailing fMRI acquisition technique. Here, we present an alternative to its standard Cartesian recordings, i.e. k-space density weighted EPI, which is expected to increase the signal-to-noise ratio in fMRI data. Based on in vitro and in vivo pilot measurements, we show that fMRI by k-space density weighted EPI is feasible and that this new acquisition technique in fact boosted spatial and temporal SNR as well as the detection of local fMRI activations. Spatial resolution, spatial response function and echo time were identical for density weighted and conventional Cartesian EPI. The signal-to-noise ratio gain of density weighting can improve activation detection and has the potential to further increase the sensitivity of fMRI investigations.

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Section: Resultssupporting

confidence: 87%

Section: Discussionsupporting

confidence: 81%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Boosting BOLD fMRI by K-Space Density Weighted Echo Planar Imaging

et al. 2013

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Phase‐labeled reference EPI for frequency‐segmented inhomogeneity corrections (PREFICS)

Zeller

Müller

Hahn

et al. 2013

Magnetic Resonance in Med

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Optimized flip angle schemes for the split acquisition of fast spin‐echo signals (SPLICE) sequence and application to diffusion‐weighted imaging

Rahbek

Schäkel

Mahmood

et al. 2022

Magnetic Resonance in Med

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Purpose The diffusion‐weighted SPLICE (split acquisition of fast spin‐echo signals) sequence employs split‐echo rapid acquisition with relaxation enhancement (RARE) readout to provide images almost free of geometric distortions. However, due to the varying T2$$ {}_2 $$‐weighting during k‐space traversal, SPLICE suffers from blurring. This work extends a method for controlling the spatial point spread function (PSF) while optimizing the signal‐to‐noise ratio (SNR) achieved by adjusting the flip angles in the refocusing pulse train of SPLICE. Methods An algorithm based on extended phase graph (EPG) simulations optimizes the flip angles by maximizing SNR for a flexibly chosen predefined target PSF that describes the desired k‐space density weighting and spatial resolution. An optimized flip angle scheme and a corresponding post‐processing correction filter which together achieve the target PSF was tested by healthy subject brain imaging using a clinical 1.5 T scanner. Results Brain images showed a clear and consistent improvement over those obtained with a standard constant flip angle scheme. SNR was increased and apparent diffusion coefficient estimates were more accurate. For a modified Hann k‐space weighting example, considerable benefits resulted from acquisition weighting by flip angle control. Conclusion The presented flexible method for optimizing SPLICE flip angle schemes offers improved MR image quality of geometrically accurate diffusion‐weighted images that makes the sequence a strong candidate for radiotherapy planning or stereotactic surgery.

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Density weighted turbo spin echo imaging

Abstract: Density weighting is applicable to TSE imaging and results in significantly increased SNR. The gain can be used to shorten the measurement time, which suggests applying density weighting in both time and SNR constrained MRI.

Cited by 4 publications

References 22 publications

Boosting BOLD fMRI by K-Space Density Weighted Echo Planar Imaging

Boosting BOLD fMRI by K-Space Density Weighted Echo Planar Imaging

Phase‐labeled reference EPI for frequency‐segmented inhomogeneity corrections (PREFICS)

Optimized flip angle schemes for the split acquisition of fast spin‐echo signals (SPLICE) sequence and application to diffusion‐weighted imaging

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