Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
464-01-015 ISMRM Abstract

Influence of Pulsating CSF Flow on Spinal Cord DTI in Partial Volume Voxels: A Simulation and In Vivo Study

Primary: Diffusion - Diffusion Modeling
Secondary: Diffusion - DWI/DTI/DKI
464-01-015 · Diffusion MRI Analysis · Tuesday, 12 May, 8:20 AM–9:15 AM · Digital Posters Row E
Keywords: Spinal Cord Cerebrospinal fluid flow Partial volume Diffusion Tensor Imaging (DTI) Spinal cord microstructure
Accepted
Alma Blombäck 1, Maria Ljungberg1,2, Kerstin Lagerstrand1,2
1Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
2Department of Biomedical Engineering and Medical Physics, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden
Presenting Author: Alma Blombäck

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References

1. A. M. Wright, Y. C. Wu, L. Feng, and Q. Wen, “Diffusion magnetic resonance imaging of cerebrospinal fluid dynamics: Current techniques and future advancements,” NMR Biomed, vol. 37, no. 9, Sep. 2024, doi: 10.1002/nbm.5162. [doi]
2. A. S. Becker, A. Boss, M. Klarhoefer, T. Finkenstaedt, M. C. Wurnig, and C. Rossi, “Investigation of the pulsatility of cerebrospinal fluid using cardiac-gated Intravoxel Incoherent Motion imaging,” Neuroimage, vol. 169, pp. 126–133, Apr. 2018, doi: 10.1016/j.neuroimage.2017.12.017. [doi]
3. Y. Bito, K. Harada, H. Ochi, and K. Kudo, “Low b-value diffusion tensor imaging for measuring pseudorandom flow of cerebrospinal fluid,” Magn Reson Med, vol. 86, no. 3, pp. 1369–1382, Sep. 2021, doi: 10.1002/mrm.28806. [doi]
4. T. Otani, Y. Bito, S. Yamada, Y. Watanabe, and S. Wada, “A theoretical interpretation of diffusion weighted and intravoxel incoherent motion imaging for cerebrospinal fluid flow,” Magn Reson Med, 2025, doi: 10.1002/mrm.70062. [doi]
5. B. De Leener et al., “SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data,” Neuroimage, vol. 145, pp. 24–43, Jan. 2017, doi: 10.1016/j.neuroimage.2016.10.009. [doi]
6. S. Bédard et al., “Towards contrast-agnostic soft segmentation of the spinal cord,” Med Image Anal, vol. 101, Apr. 2025, doi: 10.1016/j.media.2025.103473. [doi]
7. E. Garyfallidis et al., “Dipy, a library for the analysis of diffusion MRI data,” Front Neuroinform, vol. 8, no. FEB, Feb. 2014, doi: 10.3389/fninf.2014.00008. [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/464-01-015