Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
470-05-114 ISMRM Abstract

Why q-space metrics from Microscopic Propagator Imaging actually matter

Primary: Diffusion - Microstructure
Secondary: Diffusion - Diffusion Modeling
470-05-114 · Advanced Diffusion Modeling for Microstructure Mapping · Tuesday, 12 May, 1:40 PM–2:35 PM · Traditional Posters | Exhibition Hall
Keywords: Diffusion Modeling Diffusion MRI modelling Mean apparent propagator mapping Diffusion Microstructure
Accepted
Tommaso Zajac 1, Gloria Menegaz1, Marco Pizzolato2,3
1Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
2Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark
3Department of Radiology and Nuclear Medicine - Amager and Hvidovre, Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital, Copenhagen, Denmark
Presenting Author: Tommaso Zajac

Synopsis

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References

1. Zhang, H., Schneider, T., Wheeler-Kingshott, C. A., & Alexander, D. C. (2012). NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain. Neuroimage, 61(4), 1000-1016. https://doi.org/10.1016/j.neuroimage.2012.03.072 [doi]
2. Novikov, D. S., Veraart, J., Jelescu, I. O., & Fieremans, E. (2018). Rotationally-invariant mapping of scalar and orientational metrics of neuronal microstructure with diffusion MRI. NeuroImage, 174, 518-538. https://doi.org/10.1016/j.neuroimage.2018.03.006 [doi]
3. 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, 116835. https://doi.org/10.1016/j.neuroimage.2020.116835 [doi]
4. Jelescu, I. O., de Skowronski, A., Geffroy, F., Palombo, M., & Novikov, D. S. (2022). Neurite Exchange Imaging (NEXI): A minimal model of diffusion in gray matter with inter-compartment water exchange. NeuroImage, 256, 119277. https://doi.org/10.1016/j.neuroimage.2022.119277 [doi]
5. Özarslan, E., Koay, C. G., Shepherd, T. M., Komlosh, M. E., İrfanoğlu, M. O., Pierpaoli, C., & Basser, P. J. (2013). Mean apparent propagator (MAP) MRI: a novel diffusion imaging method for mapping tissue microstructure. NeuroImage, 78, 16-32. https://doi.org/10.1016/j.neuroimage.2013.04.016 [doi]
6. Mitra, P. P., & Halperin, B. I. (1995). Effects of finite gradient-pulse widths in pulsed-field-gradient diffusion measurements. Journal of Magnetic Resonance, Series A, 113(1), 94-101. https://doi.org/10.1006/jmra.1995.1060 [doi]
7. Stejskal, E. O., & Tanner, J. E. (1965). Spin diffusion measurements: spin echoes in the presence of a time‐dependent field gradient. The journal of chemical physics, 42(1), 288-292. https://doi.org/10.1063/1.1695690 [doi]
8. Zajac, T., Menegaz, G., & Pizzolato, M. (2025). Microscopic Propagator Imaging (MPI) with Diffusion MRI. arXiv preprint arXiv:2502.21129. https://www.arxiv.org/abs/2502.21129
9. White, N. S., Leergaard, T. B., D'Arceuil, H., Bjaalie, J. G., & Dale, A. M. (2013). Probing tissue microstructure with restriction spectrum imaging: Histological and theoretical validation. Human brain mapping, 34(2), 327-346. https://doi.org/10.1002/hbm.21454 [doi]
10. Christiaens, D., Veraart, J., Cordero-Grande, L., Price, A. N., Hutter, J., Hajnal, J. V., & Tournier, J. D. (2020). On the need for bundle-specific microstructure kernels in diffusion MRI. NeuroImage, 208, 116460. https://doi.org/10.1016/j.neuroimage.2019.116460 [doi]
11. Reisert, M., Kellner, E., Dhital, B., Hennig, J., & Kiselev, V. G. (2017). Disentangling micro from mesostructure by diffusion MRI: a Bayesian approach. Neuroimage, 147, 964-975. https://doi.org/10.1016/j.neuroimage.2016.09.058 [doi]
12. Pizzolato, M., Canales-Rodríguez, E. J., Andersson, M., & Dyrby, T. B. (2023). Axial and radial axonal diffusivities and radii from single encoding strongly diffusion-weighted MRI. Medical Image Analysis, 86, 102767. https://doi.org/10.1016/j.media.2023.102767 [doi]
13. Callaghan, P. T., Eccles, C. D., & Xia, Y. (1988). NMR microscopy of dynamic displacements: k-space and q-space imaging. Journal of Physics E: Scientific Instruments, 21(8), 820. https://doi.org/10.1088/0022-3735/21/8/017 [doi]
14. Jelescu, I. O., Veraart, J., Fieremans, E., & Novikov, D. S. (2016). Degeneracy in model parameter estimation for multi‐compartmental diffusion in neuronal tissue. NMR in Biomedicine, 29(1), 33-47. https://doi.org/10.1002/nbm.3450 [doi]
15. Basser, P. J., & Pierpaoli, C. (1996). Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. Journal of Magnetic Resonance, Series B 111, 0086, 209-219. https://doi.org/10.1006/jmrb.1996.0086 [doi]
16. Kaden, E., Kruggel, F., & Alexander, D. C. (2016). Quantitative mapping of the per‐axon diffusion coefficients in brain white matter. Magnetic resonance in medicine, 75(4), 1752-1763. https://doi.org/10.1002/mrm.25734 [doi]

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http://echo.ismrm.org/p/ISMRM2026/470-05-114