Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
301-03-001 ISMRM Abstract

Ultra-high gradient strength diffusion MRI for mapping axonal architecture and microstructure in the primate brain

Primary: Diffusion - Diffusion Acquisition
Secondary: Diffusion - Diffusion Modeling
301-03-001 · Neuroimaging and Spectroscopy in Experimental Models · Monday, 11 May, 1:50 PM–3:40 PM · Hall 1A
Keywords: Microstructure Tractography Diffusion MRI Ex vivo MRI Ultra-high b-value
Accepted
Ting Gong 1, Chiara Maffei1, Dongsuk Sung1, Elissa Bell1, Jasmine Shao1, Jingjing Wu1, Emma W Rosenblum1, Gabriel Ramos Llordén1, Alina Müller2, Mirsad Mahmutovic2, Boris Keil2, Jean C Augustinack1, Susie Huang1, Suzanne N Haber3,4, Anastasia Yendiki1
1Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, United States of America
2Institute of Medical Physics and Radiation Protection, University of Applied Sciences Mittelhessen (THM), Giessen, Germany
3Department of Pharmacology and Physiology, University of Rochester, Rochester, United States of America
4McLean Hospital, Belmont, United States of America
Presenting Author: Ting Gong

Synopsis

Motivation:
Goals:
Approach:
Results:
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 in

References

1. Yendiki, A., Aggarwal, M., Axer, M., Howard, A.F.D., van Walsum, A.M. van C., Haber, S.N., 2022. Post mortem mapping of connectional anatomy for the validation of diffusion MRI. Neuroimage 256. https://doi.org/10.1016/J.NEUROIMAGE.2022.119146 [doi]
2. Ramos-Llordén, G., Lee, H.H., Davids, M., Dietz, P., Krug, A., Kirsch, J.E., Mahmutovic, M., Müller, A., Ma, Y., Lee, H., Maffei, C., Yendiki, A., Bilgic, B., Park, D.J., Tian, Q., Clifford, B., Lo, W.C., Stocker, S., Fischer, J., Ruyters, G., Roesler, M., Potthast, A., Benner, T., Rummert, E., Schuster, R., Basser, P.J., Witzel, T., Wald, L.L., Rosen, B.R., Keil, B., Huang, S.Y., 2025. Ultra-high gradient connectomics and microstructure MRI scanner for imaging of human brain circuits across scales. Nature Biomedical Engineering 2025 1–16. https://doi.org/10.1038/s41551-025-01457-x [doi]
3. Müller, A., Mahmutovic, M., Alem, M., Ramos-Llordén, G., Sung, D., Shrestha, M., Hansen, S.L.J.D., Chemlali, C., Ghotra, A., Stockmann, J., Mekkaoui, C., Wald, L.L., Yendiki, A., Huang, S.Y., Keil, B., 2025. Strong gradients, cool performance: A 64-channel array coil with concurrent field monitoring and thermal control for ex vivo diffusion-weighted brain imaging using the 3T connectome 2.0 MRI scanner. Magn Reson Med 94, 2268–2285. https://doi.org/10.1002/MRM.30599 [doi]
4. Slator, P.J., Hutter, J., Palombo, M., Jackson, L.H., Ho, A., Panagiotaki, E., Chappell, L.C., Rutherford, M.A., Hajnal, J. V., Alexander, D.C., 2019. Combined diffusion-relaxometry MRI to identify dysfunction in the human placenta. Magn Reson Med. https://doi.org/10.1002/mrm.27733 [doi]
5. Gong, T., Maffei, C., Dann, E., Lee, H.H., Lee, H., Augustinack, J.C., Huang, S.Y., Haber, S.N., Yendiki, A., 2025. Interplay between MRI-based axon diameter and myelination estimates in macaque and human brain. Imaging Neuroscience 3, 2025. https://doi.org/10.1162/IMAG_A_00576 [doi]
6. Jones, R., Maffei, C., Augustinack, J., Fischl, B., Wang, H., Bilgic, B., Yendiki, A., 2021. High-fidelity approximation of grid- and shell-based sampling schemes from undersampled DSI using compressed sensing: Post mortem validation. Neuroimage 244. https://doi.org/10.1016/j.neuroimage.2021.118621 [doi]
7. Veraart, J., Novikov, D.S., Christiaens, D., Ades-aron, B., Sijbers, J., Fieremans, E., 2016. Denoising of diffusion MRI using random matrix theory. Neuroimage 142. https://doi.org/10.1016/j.neuroimage.2016.08.016 [doi]
8. Andersson, J.L.R., Graham, M.S., Zsoldos, E., Sotiropoulos, S.N., 2016. Incorporating outlier detection and replacement into a non-parametric framework for movement and distortion correction of diffusion MR images. Neuroimage 141, 556–572. https://doi.org/10.1016/j.neuroimage.2016.06.058 [doi]
9. Tustison, N.J., Avants, B.B., Cook, P.A., Zheng, Y., Egan, A., Yushkevich, P.A., Gee, J.C., 2010. N4ITK: Improved N3 bias correction. IEEE Trans Med Imaging 29, 1310–1320. https://doi.org/10.1109/TMI.2010.2046908 [doi]
10. Andersson, J.L.R., Sotiropoulos, S.N., 2016. An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. Neuroimage 125, 1063–1078. https://doi.org/10.1016/j.neuroimage.2015.10.019 [doi]
11. Jovicich, J., Czanner, S., Greve, D., Haley, E., Van Der Kouwe, A., Gollub, R., Kennedy, D., Schmitt, F., Brown, G., MacFall, J., Fischl, B., Dale, A., 2006. Reliability in multi-site structural MRI studies: Effects of gradient non-linearity correction on phantom and human data. Neuroimage 30, 436–443. https://doi.org/10.1016/J.NEUROIMAGE.2005.09.046 [doi]
12. Fan, Q., Witzel, T., Nummenmaa, A., Van Dijk, K.R.A., Van Horn, J.D., Drews, M.K., Somerville, L.H., Sheridan, M.A., Santillana, R.M., Snyder, J., Hedden, T., Shaw, E.E., Hollinshead, M.O., Renvall, V., Zanzonico, R., Keil, B., Cauley, S., Polimeni, J.R., Tisdall, D., Buckner, R.L., Wedeen, V.J., Wald, L.L., Toga, A.W., Rosen, B.R., 2016. MGH-USC Human Connectome Project datasets with ultra-high b-value diffusion MRI. Neuroimage 124, 1108–1114. https://doi.org/10.1016/J.NEUROIMAGE.2015.08.075 [doi]
13. Vos, S.B., Tax, C.M.W., Luijten, P.R., Ourselin, S., Leemans, A., Froeling, M., 2017. The importance of correcting for signal drift in diffusion MRI. Magn Reson Med 77. https://doi.org/10.1002/mrm.26124 [doi]
14. Lehman, J.F., Greenberg, B.D., Mcintyre, C.C., Rasmussen, S.A., Haber, S.N., 2011. Rules ventral prefrontal cortical axons use to reach their targets: implications for diffusion tensor imaging tractography and deep brain stimulation for psychiatric illness. J Neurosci 31, 10392–10402. https://doi.org/10.1523/JNEUROSCI.0595-11.2011 [doi]
15. Palombo, M., Ianus, A., Guerreri, M., Nunes, D., Alexander, D.C., Shemesh, N., Zhang, H., 2020. SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI. Neuroimage 215. https://doi.org/10.1016/j.neuroimage.2020.116835 [doi]
16. Williams, E.M., Rosenblum, E.W., Pihlstrom, N., Llamas-Rodríguez, J., Champion, S., Frosch, M.P., Augustinack, J.C., 2023. Pentad: A reproducible cytoarchitectonic protocol and its application to parcellation of the human hippocampus. Front Neuroanat 17, 1114757. https://doi.org/10.3389/FNANA.2023.1114757/BIBTEX [doi]
17. Gong, T., Tax, C.M., Mancini, M., Jones, D.K., Zhang, H., Palombo, M., 2023. Multi-TE SANDI: Quantifying compartmental T2 relaxation times in the grey matter, in: ISMRM 2023 Annual Meeting. Toronto.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/301-03-001