Reproducibility of tailored kT-points pTx pulses in whole-brain 3D-EPI fMRI studies at 7T
Poster No:
1906
Submission Type:
Abstract Submission
Authors:
Yidi Lu1, Chia-Yin Wu1,2,3, Jin Jin2,4, David Reutens1,2, Martijn Cloos1,2,5
Institutions:
1Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia, 2ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Australia, 3Imaging Centre of Excellence, University of Glasgow, Glasgow, United Kingdom, 4Siemens Healthineers Pty Ltd, Brisbane, Australia, 5Donders Institute for Brain Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
First Author:
Co-Author(s):
Chia-Yin Wu
Centre for Advanced Imaging, The University of Queensland|ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland|Imaging Centre of Excellence, University of Glasgow
Brisbane, Australia|Brisbane, Australia|Glasgow, United Kingdom
Centre for Advanced Imaging, The University of Queensland|ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland|Imaging Centre of Excellence, University of Glasgow
Brisbane, Australia|Brisbane, Australia|Glasgow, United Kingdom
Jin Jin
ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland|Siemens Healthineers Pty Ltd
Brisbane, Australia|Brisbane, Australia
ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland|Siemens Healthineers Pty Ltd
Brisbane, Australia|Brisbane, Australia
David Reutens
Centre for Advanced Imaging, The University of Queensland|ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland
Brisbane, Australia|Brisbane, Australia
Centre for Advanced Imaging, The University of Queensland|ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland
Brisbane, Australia|Brisbane, Australia
Martijn Cloos, PhD
Centre for Advanced Imaging, The University of Queensland|ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland|Donders Institute for Brain Cognition and Behaviour, Radboud University
Brisbane, Australia|Brisbane, Australia|Nijmegen, Netherlands
Centre for Advanced Imaging, The University of Queensland|ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland|Donders Institute for Brain Cognition and Behaviour, Radboud University
Brisbane, Australia|Brisbane, Australia|Nijmegen, Netherlands
Introduction:
Parallel transmission (pTx) can be used to mitigate B1+ inhomogeneities at ultra-high field (≥7T). Compared to pre-calibrated universal pulses, tailored pTx pulses are scan-specific, accounting for brain geometry and head position. However, the pulses may exhibit variability in magnitude and phase across scans. This study assessed the reproducibility of non-selective kT-points pTx pulses in a 3D-EPI research sequence at 7T in a scan-rescan, task-free, whole-brain fMRI experiment.
Methods:
Five subjects were scanned twice at 7 Tesla (Siemens Healthineers, Germany) using an 8Tx/32Rx (pTx) head coil array (Nova Medical, USA) with ~15 min rest between scans outside the scanner. For calibration, B1+ maps were acquired using an SA2RAGE and a 2D-GRE sequence (Cloos et al., 2012; Padormo et al., 2016). Subject-specific non-selective water excitation kT-points pTx pulses (16 sub-pulses, total duration=2ms) were designed per scan (Löwen et al., 2022). The segmented 3D-EPI sequence used in the rest of the scan is a research sequence with a high flexibility in EPI train length and CAIPIRINHA (CAIPI) sampling patterns (Jin et al., 2021; Tourell et al., 2021).
For flip-angle (FA) mapping, a 3D-SPGRE-EPI sequence was used to measure the CP and pTx transmit modes (FA=5°, FOV=180x240x240mm3, 4mm iso, TR/TE=100ms/5ms). Resting-state functional data was collected using the research 3D-EPI sequence (two runs, 150 volumes per run, FA=12°, FOV=180x240x240mm3, 1.5mm iso, TRvol/TR/TE=2257ms/37ms/19ms, CAIPI (phase encoding acceleration=2, partition encoding acceleration=4, partition encoding shift=2)). This sequence was then used to collect 20 volumes with each FA of 2° and 20°.
FA maps for CP were derived from the SA2RAGE calibration data. They were then co-registered with the 3D-SPGRE images (SPGRE-EPICP and SPGRE-EPIpTx) in SPM (Friston et al., 2007). The pTx FA map was calculated by multiplying the CP FA maps with the smoothed SPGRE-EPIpTx/SPGRE-EPICP (full width at half maximum(FWHM)=8mm in SPM). Images acquired with 3D-EPI (FA=12°, 2° and 20°) were motion corrected and co-registered in SPM. For each voxel, temporal signal-to-noise ratio (tSNR) was calculated by dividing the mean signal intensity over time by the temporal standard deviation, and cerebellar tSNR was analyzed using MNI-aligned masks. For each subject, using a dual flip angle based approach, a T1-weighted image was obtained by dividing the mean 3D-EPI image of FA 20° over 2° (Wang et al., 1987; Olsson et al., 2020). Grey matter segmentation masks were generated using the ratio image in FSL-FAST (Zhang et al., 2001).
For flip-angle (FA) mapping, a 3D-SPGRE-EPI sequence was used to measure the CP and pTx transmit modes (FA=5°, FOV=180x240x240mm3, 4mm iso, TR/TE=100ms/5ms). Resting-state functional data was collected using the research 3D-EPI sequence (two runs, 150 volumes per run, FA=12°, FOV=180x240x240mm3, 1.5mm iso, TRvol/TR/TE=2257ms/37ms/19ms, CAIPI (phase encoding acceleration=2, partition encoding acceleration=4, partition encoding shift=2)). This sequence was then used to collect 20 volumes with each FA of 2° and 20°.
FA maps for CP were derived from the SA2RAGE calibration data. They were then co-registered with the 3D-SPGRE images (SPGRE-EPICP and SPGRE-EPIpTx) in SPM (Friston et al., 2007). The pTx FA map was calculated by multiplying the CP FA maps with the smoothed SPGRE-EPIpTx/SPGRE-EPICP (full width at half maximum(FWHM)=8mm in SPM). Images acquired with 3D-EPI (FA=12°, 2° and 20°) were motion corrected and co-registered in SPM. For each voxel, temporal signal-to-noise ratio (tSNR) was calculated by dividing the mean signal intensity over time by the temporal standard deviation, and cerebellar tSNR was analyzed using MNI-aligned masks. For each subject, using a dual flip angle based approach, a T1-weighted image was obtained by dividing the mean 3D-EPI image of FA 20° over 2° (Wang et al., 1987; Olsson et al., 2020). Grey matter segmentation masks were generated using the ratio image in FSL-FAST (Zhang et al., 2001).
Results:
In CP, FAs were low in the cerebellum and high in the thalamus, while pTx produced a significantly more uniform FA profiles, with reduced whole-brain FA variability and good scan-rescan reproducibility (Δstandard deviation<1.5%) (Fig. 1a,b).
Improved FA homogeneity in pTx led to higher tSNR in the cerebellum, and both mean and variability of tSNR were comparable between scans (Fig. 2a). The homogeneous FA in pTx also allowed for consistent tissue contrast in the ratio image (3D-EPI20°/3D-EPI2°), facilitating grey matter segmentation (Fig. 2b). In comparison, in CP mode the low B1+ in the cerebellum resulted in a locally poor segmentation. Importantly, the improved segmentation in pTx showed to be reproducible, supporting the use of tailored pTx pulses in tissue mask preparation for 3D-EPI functional data analysis.
Improved FA homogeneity in pTx led to higher tSNR in the cerebellum, and both mean and variability of tSNR were comparable between scans (Fig. 2a). The homogeneous FA in pTx also allowed for consistent tissue contrast in the ratio image (3D-EPI20°/3D-EPI2°), facilitating grey matter segmentation (Fig. 2b). In comparison, in CP mode the low B1+ in the cerebellum resulted in a locally poor segmentation. Importantly, the improved segmentation in pTx showed to be reproducible, supporting the use of tailored pTx pulses in tissue mask preparation for 3D-EPI functional data analysis.
Conclusions:
pTx with non-selective kT-points reproducibly improves B1+ uniformity at 7T, leading to enhanced tSNR in the cerebellum and improved segmentation accuracy for 3D-EPI whole-brain images. This reproducibility supports the use of tailored kT-points pTx pulses in 3D-EPI fMRI studies at 7T where B1+ homogeneity are critical.
Novel Imaging Acquisition Methods:
BOLD fMRI 1
Non-BOLD fMRI 2
Keywords:
MRI
1|2Indicates the priority used for review
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2. Friston, K. J., Ashburner, J. T., Kiebel, S. J., Nichols, T. E., & Penny, W. D. (Eds.). (2007). Statistical parametric mapping: The analysis of functional brain images. Academic Press.
3. Jin, J., et al. (2021). Segmented 3D EPI with CAIPIRINHA for Fast, High-Resolution T2*-weighted Imaging. Proc. Annu. Meeting ISMRM.
4. Löwen, D., Pracht, E. D., Stirnberg, R., Liebig, P., & Stöcker, T. (2022). Interleaved binomial kT -points for water-selective imaging at 7T. Magnetic resonance in medicine, 88(6), 2564–2572. https://doi.org/10.1002/mrm.29376.
5. Olsson, H., Andersen, M., Lätt, J., Wirestam, R., & Helms, G. (2020). Reducing bias in dual flip angle T1 -mapping in human brain at 7T. Magnetic resonance in medicine, 84(3), 1347–1358. https://doi.org/10.1002/mrm.28206
6. Padormo, F., Hess, A. T., Aljabar, P., Malik, S. J., Jezzard, P., Robson, M. D., Hajnal, J. V., & Koopmans, P. J. (2016). Large dynamic range relative B1+ mapping. Magnetic resonance in medicine, 76(2), 490–499. https://doi.org/10.1002/mrm.25884.
7. Tourell, M., Jin, J., Stewart, A., Bollmann, Saskia., Bollmann, Steffen., Robinson, S., O’Brien, K., Barth, M. (2021). Submillimeter, Sub-Minute Quantitative Susceptibility Mapping using a Multi-Shot 3D-EPI with 2D CAIPIRINHA Acceleration. Proc. Annu. Meeting ISMRM.
8. Wang, H. Z., Riederer, S. J., & Lee, J. N. (1987). Optimizing the precision in T1 relaxation estimation using limited flip angles. Magnetic resonance in medicine, 5(5), 399–416. https://doi.org/10.1002/mrm.1910050502.
9. Zhang, Y., Brady, M., & Smith, S. (2001). Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE transactions on medical imaging, 20(1), 45–57. https://doi.org/10.1109/42.906424.