631-03-011 / 631-03-011 ISMRM Abstract

Concomitant-gradient dephasing in asymmetric diffusion encoding: a problem worth fixing despite low b-values and small FOVs!

Primary: Diffusion - Diffusion Acquisition

Secondary: Diffusion - DWI/DTI/DKI

631-03-011 · Diffusion Acquisition and Reconstruction · Thursday, 14 May, 4:00 PM–5:36 PM · Roof Terrace

Keywords: Microstructure Diffusion Tensor Imaging Concomitant fields Microstructural Parameter Estimation Cardiac diffusion MRI

Accepted

Viktor Olsson ¹, Malwina Molendowska¹, Derek K Jones², Markus Nilsson³, Daniel B Ennis⁴, Jurgen E Schneider⁵, Frederik Testud⁶, Filip Szczepankiewicz¹

¹Department of Medical Radiation Physics, Lund, Sweden, Lund University, Lund, Sweden

²Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff, UK, Cardiff University, Cardiff, United Kingdom

³Department of Diagnostic Radiology, Lund, Sweden, Lund University, Lund, Sweden

⁴Department of Radiology, Stanford, California, USA, Stanford University, Stanford, United States of America

⁵Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, Leeds, UK, University of Leeds, Leeds, United Kingdom

⁶Malmö, Sweden, Siemens Healthcare AB, Lund, Sweden

Presenting Author: Viktor Olsson

Synopsis

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References

1. C. A. Baron et al. “The effect of concomitant gradient fields on diffusion tensor imaging”. en. In: Magnetic Resonance in Medicine 68.4 (2012). _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.24120, pp. 1190–1201. issn: 1522-2594. doi: 10.1002/mrm.24120. [doi]

2. Filip Szczepankiewicz, Carl-Fredrik Westin, and Markus Nilsson. “Maxwell-compensated design of asymmetric gradient waveforms for tensor-valued diffusion encoding”. en. In: Magnetic Resonance in Medicine 82.4 (Oct. 2019). Publisher: John Wiley & Sons, Ltd, pp. 1424–1437. issn: 1522-2594. doi: 10.1002/mrm.27828. [doi]

3. M. A. Bernstein et al. “Concomitant gradient terms in phase contrast MR: analysis and correction”. eng. In: Magnetic Resonance in Medicine 39.2 (Feb. 1998), pp. 300–308. issn: 0740-3194. doi: 10.1002/mrm.1910390218. [doi]

4. Filip Szczepankiewicz et al. “Motion-compensated gradient waveforms for tensor-valued diffusion encoding by constrained numerical optimization”. eng. In: Magnetic Resonance in Medicine 85.4 (Apr. 2021), pp. 2117–2126. issn: 1522-2594. doi: 10.1002/mrm.28551. [doi]

5. Erica Dall’Armellina et al. “Cardiac diffusion-weighted and tensor imaging: A consensus statement from the special interest group of the Society for Cardiovascular Magnetic Resonance”. eng. In: Journal of Cardiovascular Magnetic Resonance: Official Journal of the Society for Cardiovascular Magnetic Resonance 27.1 (2025), p. 101109. issn: 1532-429X. doi: 10.1016/j.jocmr.2024.101109. [doi]

6. Jens Sjölund et al. “Constrained optimization of gradient waveforms for generalized diffusion encoding”. In: Journal of Magnetic Resonance 261 (Dec. 2015), pp. 157–168. issn: 1090-7807. doi: 10.1016/j.jmr.2015.10.012. [doi]

7. Filip Szczepankiewicz et al. “Tensor-valued diffusion encoding for diffusional variance decomposition (DIVIDE): Technical feasibility in clinical MRI systems”. eng. In: PloS One 14.3 (2019), e0214238. issn: 1932-6203. doi: 10.1371/journal.pone.0214238. [doi]

8. Markus Nilsson et al. “An open-source framework for analysis of multidimensional di usion MRI data implemented in MATLAB”. en. In: Soc. Mag. Reson. Med. 26, 2018 Paris, France.

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http://echo.ismrm.org/p/ISMRM2026/631-03-011