Investig Magn Reson Imaging.
2022 Dec;26(4):208-219. 10.13104/imri.2022.26.4.208.
Diffusion Encoding Methods in MRI: Perspectives and Challenges
- Finkelstein A
1 - Cao X2
- Liao C2
- Schifitto G3,4,5
- Zhong J1,5,6
- Affiliations
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- 1Department of Biomedical Engineering, University of Rochester, Rochester, NY, USA
- 2Department of Radiology, Stanford University, Stanford, CA, USA
- 3Department of Electrical Engineering, University of Rochester, Rochester, NY, USA
- 4Department of Neurology, University of Rochester, Rochester, NY, USA
- 5Department of Imaging Sciences, University of Rochester, Rochester, NY, USA
- 6Department of Physics and Astronomy, University of Rochester, Rochester, NY, USA
- KMID: 2538307
- DOI: http://doi.org/10.13104/imri.2022.26.4.208
Abstract
- Diffusion MRI (dMRI) is an important imaging modality that is used extensively to diagnose and monitor diseases. dMRI measures random motion of water molecules and helps elucidate microstructural properties of tissues. Optimal diffusion encoding paradigms have been developed to reduce acquisition time, minimize artifacts, and acquire high fidelity data needed for advanced modeling of tissue properties. To further probe microstructural properties, joint diffusion-relaxometry and diffusion weighted MR fingerprinting have garnered interest. A thorough knowledge of different diffusion encoding methods is essential to accurately encode diffusion in MR experiments. Here, we review fundamental physics of diffusion encoding methods, their associated challenges, and how to address them. Advanced diffusion acquisition methods are also discussed.
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