Synopsis
Motivation:
Goals:
Approach:
Results:
631-03-014 / 631-03-014
ISMRM Abstract
MESMERISED with a spiral readout and multiband pTx-pulses for DWI with improved SNR and homogeneity at 7T
Accepted
Full abstract & presentation
The full text, figures, and any recorded presentation for this abstract are not shown here. Log in if you are a member or registered attendee with access.
Full abstracts, figures, and presentations for Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition are available to registered attendees. This content becomes freely available to the public roughly two years after the meeting.
To request or purchase access, contact the ISMRM Central Office at info@ismrm.org.
Log inReferences
1. Fritz FJ, et al. MESMERISED: Super-accelerating T1 relaxometry and diffusion MRI with STEAM at 7 T for quantitative multi-contrast and diffusion imaging, NeuroImage, Volume 239, 2021, 118285,https://doi.org/10.1016/j.neuroimage.2021.118285. [doi]
2. Layton KJ, et al. Pulseq: A rapid and hardware‐independent pulse sequence prototyping framework. Magn. Reson. Med., 2017;77(4):1544-1552. doi: 10.1002/mrm.26 [doi]
3. Ravi K, et al. PyPulseq: A Python Package for MRI Pulse Sequence Design. J. Open Source Softw. 2019;4(42):1725. doi: 10.21105/joss.01 [doi]
4. Lustig M, et al. A fast method for designing time-optimal gradient waveforms for arbitrary k-space trajectories. IEEE Trans Med Imaging. 2008 Jun;27(6):866-73. doi: 10.1109/TMI.2008.922 [doi]
5. Sothynathan M, et al. Laterally Oscillating Trajectory for Undersampling Slices (LOTUS). ISMRM 2025, Honolulu, HI, program no. 1
6. Barmet C, et al. Spatiotemporal magnetic field monitoring for MR. Magn Reson Med. 2008 Jul;60(1):187-97. doi: 10.1002/mrm.21 [doi]
7. Veldmann M, et al. Improving signal homogeneity of whole-brain DWI at 7T with universal multiband GRAPE pTx pulses. ISMRM 2025, Honolulu, HI, program no. 0
8. Ivanov D, et al. A simple low-SAR technique for chemical-shift selection with high-field spin-echo imaging. Magn Reson Med. 2010 Aug;64(2):319-26. doi: 10.1002/mrm.22 [doi]
9. Jiru F, Klose U. Fast 3D radiofrequency field mapping using echo-planar imaging. Magn Reson Med. 2006 Dec;56(6):1375-9. doi: 10.1002/mrm.2 [doi]
10. Baron CA. (2021, February 2). MatMRI: A GPU enabled package for model based MRI image reconstruction. Zenodo. http://doi.org/10.5281/zenodo.4495476 [doi]
11. Wilm BJ, et al. Higher order reconstruction for MRI in the presence of spatiotemporal field perturbations. Magn. Reson. Med., 2011;65:1690-1701. doi: 10.1002/mrm.2 [doi]
12. Varela-Mattatall G, et al. Single-shot spiral diffusion-weighted imaging at 7T using expanded encoding with compressed sensing. Magn Reson Med. 2023 Aug;90(2):615-623. doi: 10.1002/mrm.2 [doi]
13. Uecker M, et al. ESPIRiT—an eigenvalue approach to autocalibrating parallel MRI: Where SENSE meets GRAPPA. Magn. Reson. Med., 2014;71:990-1001. https://doi.org/10.1002/mrm.2 [doi]
14. Cordero-Grande L, et al. Complex diffusion-weighted image estimation via matrix recovery under general noise models. NeuroImage, 2019;200:391
15. Kellner E, et al. Gibbs-ringing artifact removal based on local subvoxel-shifts. Magn. Res. Med, 2016;76:1574–
16. Andersson J, Sotiropoulos S. An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. NeuroImage, 2016;125:1063-
17. Janke A, et al. Use of spherical harmonic deconvolution methods to compensate for nonlinear gradient effects on MRI images, Magn. Reson. Med., 2004;52(1):115-122
18. Harms, R.L., et al., Robust and fast nonlinear optimization of diffusion MRI microstructure models. Neuroimage, 2017. 155: p. 82-96. Doi: 10.1016/j.neuroimage.2017.04.064 [doi]
19. Harms, R.L., et al., Fast and robust quantification of uncertainty in non-linear diffusion MRI models. Neuroimage, 2024. 285: p. 120496. Doi: https://doi.org/10.1016/j.neuroimage.2023.120496 [doi]
Cite this abstract
http://echo.ismrm.org/p/ISMRM2026/631-03-014