Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
465-04-003 ISMRM Abstract

Probing cellular microstructure via time-dependent diffusion MRS and machine learning based modeling in Alzheimer’s disease

Primary: Contrast Mechanisms - Molecular Imaging
Secondary: Diffusion - Microstructure
465-04-003 · Image Analysis for Alzheimer's and Parkinson's · Tuesday, 12 May, 2:35 PM–3:30 PM · Digital Posters Row F
Keywords: Alzheimer's Disease Molecular Imaging MR spectroscopy Brain microstructure
Accepted
Ke Zhou 1, Tiantian Hua2, Yaou Liu2, Yi-Cheng Hsu3, Mengye Lyu4, Min Wang1,5
1Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
2Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
3MR Research Collaboration, Siemens Healthineers Ltd., Shanghai, China
4College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China
5Department of Endocrinology, School of Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
Presenting Author: Ke Zhou

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References

1. De Strooper, B. & Karran, E. The Cellular Phase of Alzheimer’s Disease. Cell 164, 603-615, doi:10.1016/j.cell.2015.12.056 (2016). [doi]
2. Ligneul, C. et al. Diffusion-weighted magnetic resonance spectroscopy enables cell-specific monitoring of astrocyte reactivity in vivo. NeuroImage 191, 457-469, doi:10.1016/j.neuroimage.2019.02.046 (2019). [doi]
3. Marchadour, C., Brouillet, E., Hantraye, P., Lebon, V. & Valette, J. Anomalous diffusion of brain metabolites evidenced by diffusion-weighted magnetic resonance spectroscopy in vivo. Journal of Cerebral Blood Flow and Metabolism: Official Journal of the International Society of Cerebral Blood Flow and Metabolism 32, 2153-2160, doi:10.1038/jcbfm.2012.119 (2012). [doi]
4. Palombo, M. et al. New paradigm to assess brain cell morphology by diffusion-weighted MR spectroscopy in vivo. Proceedings of the National Academy of Sciences of the United States of America 113, 6671-6676, doi:10.1073/pnas.1504327113 (2016). [doi]
5. Zhou, K., Wang, Z., Lin, D., Hsu, Y.-C. & Wang, M. Optimization and comparison of coil combination and spectral registration strategies for in-vivo DW-MRS. ISMRM (2023).
6. Provencher, S. W. Automatic quantitation of localized in vivo 1H spectra with LCModel. NMR in biomedicine 14, 260-264, doi:10.1002/nbm.698 (2001). [doi]
7. Cook, P. et al. Camino: Diffusion MRI reconstruction and processing. The Insight Journal, doi:10.54294/fgfrtv (2005). [doi]
8. Mougel, E., Valette, J. & Palombo, M. Investigating exchange, structural disorder and restriction in Gray Matter via water and metabolites diffusivity and kurtosis time-dependence. Preprint (2023).
9. Deelchand, D. K. et al. Changes in the intracellular microenvironment in the aging human brain. Neurobiology of aging 95, 168-175, doi:10.1016/j.neurobiolaging.2020.07.017 (2020). [doi]

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http://echo.ismrm.org/p/ISMRM2026/465-04-003