The temperature dependence of gradient system response characteristics

Stich, Manuel; Pfaff, Christiane; Wech, Tobias; Slawig, Anne; Ruyters, Gudrun; Dewdney, Andrew; Ringler, R; Köstler, Herbert

doi:10.1002/mrm.28013

Cited by 12 publications

(21 citation statements)

References 24 publications

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“…The primary uncertainty in the signal model is coupled to the assumption that gradient system was modeled as a linear time‐invariant system. Previous work showed that the assumption is valid to a certain extent, but may be violated due to for example gradient heating . The second limitation is that we did not perform higher order gradient impulse response measurements, which may induce additional phase errors that we did not account for.…”

Section: Discussionmentioning

confidence: 97%

“…Previous work showed that the assumption is valid to a certain extent, but may be violated due to for example gradient heating. 28,29 The second limitation is that we did not perform higher order gradient impulse response measurements, which may induce additional phase errors that we did not account for. However, including the higher order phase errors in the RF-PC compensation strategy is not straightforward because these errors have heterogeneous spatial distributions.…”

Section: Discussionmentioning

confidence: 99%

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Prospective GIRF‐based RF phase cycling to reduce eddy current‐induced steady‐state disruption in bSSFP imaging

Bruijnen

Stemkens

Berg

et al. 2019

Magnetic Resonance in Med

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Purpose To propose an explicit Balanced steady‐state free precession (bSSFP) signal model that predicts eddy current‐induced steady‐state disruptions and to provide a prospective, practical, and general eddy current compensation method. Theory and Methods Gradient impulse response functions (GIRF) were used to simulate trajectory‐specific eddy current‐induced phase errors at the end of a repetition block. These phase errors were included in bloch simulations to establish a bSSFP signal model to predict steady‐state disruptions and their corresponding image artifacts. The signal model was embedded in the MR system and used to compensate the phase errors by prospectively modifying the phase cycling scheme of the RF pulse. The signal model and eddy current compensation method were validated in phantom and in vivo experiments. In addition, the signal model was used to analyze pre‐existing eddy current mitigation methods, such as 2D tiny golden angle radial and 3D paired phase encoded Cartesian acquisitions. Results The signal model predicted eddy current‐induced image artifacts, with the zeroth‐order GIRF being the primary factor to predict the steady‐state disruption. Prospective RF phase cycling schemes were automatically computed online and considerably reduced eddy current‐induced image artifacts. The signal model provides a direct relationship for the smoothness of k‐space trajectories, which explains the effectiveness of phase encode pairing and tiny golden angle trajectory. Conclusions The proposed signal model can accurately predict eddy current‐induced steady‐state disruptions for bSSFP imaging. The signal model can be used to derive the eddy current‐induced phase errors required for trajectory‐specific RF phase cycling schemes, which considerably reduce eddy current‐induced image artifacts.

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Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

Prospective GIRF‐based RF phase cycling to reduce eddy current‐induced steady‐state disruption in bSSFP imaging

Bruijnen

Stemkens

Berg

et al. 2019

Magnetic Resonance in Med

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“…These can be divided into two components, (a) non-LTI effects such as fluctuations caused by the subject, (b) changes in the GIRF over time. The latter could be addressed by measuring temperature dependent GIRFs (Nussbaum et al, 2018) (Stich et al, 2019). The hardware temperature can easily be assessed via the scanner's temperature monitoring system or using separate temperature sensors and this information can then be used to select the optimal GIRF for each measurement.…”

Section: Discussionmentioning

confidence: 99%

Feasibility of spiral fMRI based on an LTI gradient model

Graedel

Kasper

Engel

et al. 2019

Preprint

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Highlights• This work investigates the feasibility of using a one-time system calibration (called GIRF) based on a linear time-invariant gradient model to account for k-space trajectory deviations in spiral fMRI.• We show that the image quality and the spatial specificity of the fMRI activation are substantially improved when using the GIRF-prediction for trajectory correction while the nominal reconstructions suffer from artifacts and mis-placed fMRI activation.• We demonstrate that system characterization via the GIRF can enable spiral fMRI in situations when concurrent monitoring is not available. AbstractPurpose: Spiral imaging is very well suited for functional MRI, however its use has been limited by the fact that artifacts caused by gradient imperfections and B 0 inhomogeneity are more difficult to correct compared to EPI and requires accurate knowledge of the traversed k-space trajectory. With the goal of making spiral fMRI more accessible we have evaluated image reconstruction using trajectories predicted by the gradient impulse response function (GIRF), which can be determined in a one-time calibration step. Methods:GIRF-predicted reconstruction was tested for high-resolution (0.8mm) fMRI at 7T. Image quality and functional results of the reconstructions using GIRF-prediction were compared to reconstructions using the delay corrected nominal trajectory and concurrent field monitoring. Results:The reconstructions using nominal spiral trajectories contain substantial artifacts and activation maps contain mis-placed activation. Image artifacts are substantially reduced when using the GIRF-predicted reconstruction and the activation maps for the GIRF-predicted and monitored reconstructions largely overlap. The GIRF reconstruction provides a large increase in the spatial specificity of the activation compared to the nominal reconstruction. Conclusion:The GIRF-reconstruction generates image quality and fMRI results similar to using a concurrently monitored trajectory. The presented approach does not prolong or complicate the fMRI acquisition. Using GIRF-predicted trajectories has the potential to enable high-quality highresolution fMRI in situations where concurrent monitoring is not available.

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“…The required field measurements for these calibrations may either rely on a dedicated NMR-probe based field camera De Zanche et al, 2008) or on off-the-shelf NMR phantoms (Duyn et al, 1998), with certain trade-offs to measurement precision and acquisition duration (Graedel et al, 2017). To account for the aforementioned dynamic field effects as well, the spiral sequence could be augmented by higher-order field navigators (Splitthoff and Zaitsev, 2009) or a temperature-dependent gradient response model Stich et al, 2019).…”

Section: Signal Model Limitations and Alternativesmentioning

confidence: 99%

Advances in Spiral fMRI: A High-resolution Study with Single-shot Acquisition

Kasper

Engel

Heinzle

et al. 2019

Preprint

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Spiral fMRI has been put forward as a viable alternative to rectilinear echo-planar imaging, in particular due to its enhanced average k-space speed and thus high acquisition efficiency. This renders spirals attractive for contemporary fMRI applications that require high spatiotemporal resolution, such as laminar or columnar fMRI. However, in practice, spiral fMRI is typically hampered by its reduced robustness and ensuing blurring artifacts, which arise from unaccounted imperfections in both static and dynamic magnetic fields.Recently, these limitations have been overcome by the concerted application of an expanded signal model factoring in such field imperfections, and its corresponding inversion by iterative image reconstruction. In the challenging ultra-high field environment of 7 Tesla, where field inhomogeneity effects are aggravated, both multi-shot and single-shot 2D spiral imaging at sub-millimeter resolution was demonstrated with high depiction quality and anatomical congruency.In this work, we further these advances towards a time series application of spiral readouts, namely, single-shot spiral BOLD fMRI at 0.8mm in-plane resolution. We report that spiral fMRI at 7T is feasible, delivering both competitive image quality and BOLD sensitivity, with a spatial specificity of the activation maps that is not compromised by artifactual blurring. Furthermore, we show the versatility of the approach with a combined in/out spiral readout at a more typical resolution (1.5 mm), where the high acquisition efficiency allows to acquire two images per shot for improved sensitivity by echo combination. Advances in Spiral fMRI 3/42 Advances in Spiral fMRI 5/42

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The temperature dependence of gradient system response characteristics

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 12 publications

References 24 publications

Prospective GIRF‐based RF phase cycling to reduce eddy current‐induced steady‐state disruption in bSSFP imaging

Prospective GIRF‐based RF phase cycling to reduce eddy current‐induced steady‐state disruption in bSSFP imaging

Feasibility of spiral fMRI based on an LTI gradient model

Advances in Spiral fMRI: A High-resolution Study with Single-shot Acquisition

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