Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
363-02-004 ISMRM Abstract

Introducing the GAussian-Sum Propagator (GASP). Range-Limited Microstructure Mapping Exemplified in Stroke

Primary: Diffusion - Microstructure
Secondary: Neuro - Stroke and Cerebrovascular Disorders
363-02-004 · All About Diffusion · Monday, 11 May, 9:15 AM–10:10 AM · Digital Posters Row D
Keywords: Stroke Lesion Characterization Diffusion Propagator Data Driven Diffusion Regimes Nonnegative least squares Brain tissue microstructure
Accepted
Ana-Maria Oros-Peusquens 1, N. Jon Shah2,3,4,5
1Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, Jülich, Germany
2Institute of Neuroscience and Medicine 4, Forschungszentrum Juelich, Juelich, Germany
3Institute of Neuroscience and Medicine 11, JARA, Forschungszentrum Juelich, Juelich, Germany
4Department of Neurology, RWTH Aachen University Hospital, Aachen, Germany
5Aachen, JARA - BRAIN - Translational Medicine, Aachen, Germany
Presenting Author: Ana-Maria Oros-Peusquens

Synopsis

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References

1. [1] Callaghan PT. Principles of Nuclear Magnetic Resonance Microscopy. Clarendon Press; 1991.
2. [2] Lawson CL, Hanson RJ. Solving Least Squares Problems. Prentice‑Hall; 1974.
3. [3] Stejskal EO, Tanner JE. Spin diffusion measurements: spin echoes in the presence of a time‑dependent field gradient. J Chem Phys. 1965;42:288–292.
4. [4] Özarslan E, Koay CG, Shepherd TM, et al. Mean apparent propagator (MAP) MRI: mapping tissue microstructure. NeuroImage. 2013;78:16–32.
5. [5] Jensen JH, Helpern JA, Ramani A, Lu H, Kaczynski K. Diffusional kurtosis imaging. Magn Reson Med. 2005;53:1432–1440.
6. [6] Oros‑Peusquens A‑M, Shah NJ. A Simple and Efficient Method for Acceleration and Denoising of Multi‑Contrast Diffusion Data: Application to Q‑Space and HARDI. Proc. ISMRM. 2013;21:3219.
7. [7] Oros‑Peusquens A‑M, Nikoubashman O, Wiesmann M, Shah NJ. Investigating the nature of distinct regions in brain tissue affected by stroke with principal component analysis of multi‑b valued diffusion data. Proc. ISMRM. 2018;26:5022.
8. [8] Tikhonov AN. Solution of incorrectly formulated problems and the regularization method. Sov Math Dokl. 1963;4:1035–1038.
9. [9] Veraart J, Novikov DS, Christiaens D, et al. Denoising of diffusion MRI using random matrix theory. NeuroImage. 2016;142:394–406.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/363-02-004