Diffusion-Relaxation MRI
Jana Hutter1
1King's College London, United Kingdom

Synopsis

This talk will focus on the recent developments combining diffusion MRI with relaxometry. It will first give details on the parameters and choices available on the acquisition side. Next, possible analysis techniques will be presented and finally recent results detailing possible applications will be discussed.

Target Audience

Basic scientists and clinical scientists interested in microstructural information, specifically in gaining an understanding how diffusion MRI and relaxometry can be combined to yield novel insights

Objectives/Outcomes

  • Understanding the intrinsic influence of acquisition parameters on diffusion data
  • Learn about ways to achieve combined diffusion-relaxometry acquisition
  • Discuss analysis methods dedicated to joint diffusion-relaxometry data
  • Learn about examples of applications where diffusion-relaxometry yields novel insights

Purpose

Multi-parametric quantitative MRI techniques combining diffusion MRI and relaxometry have recently gained significant interest due to their ability to produce eloquent data allowing novel insights into the composition of biological tissue in-vivo: While relaxometry accesses chemical properties, diffusion MRI targets mechanical and geometrical properties of the tissue microstructure. Their combination has great potential to characterize biological tissue in ever more detail. The thus achieved window into physiology offers a multitude of applications both for research and for clinical settings. Diffusion MRI signal does not ever originate only from the targeted microstructure, but also contains effects of tissue properties due to the chosen sequence parameters (e.g. echo time TE, repetition time TR, flip angle FA). Ignoring relaxometry effects thus risks to misinterpret signal variations whilst including relaxometry effects in signal equations and models allows potentially to disentangle the effects of T1/T2 weighting and diffusion properties.

Methods/Results

In this lecture both the intrinsic influence and possible consequences for quantitative diffusion analysis as well the opportunities offered by joint diffusion-relaxometry sampling will be discussed.
  • Basic diffusion acquisition using single-shot EPI including the discussion of all relevant acquisition parameters
  • Novel combined acquisition techniques including relevant parameter scheme design
  • Analysis techniques exploiting multi-dimensional diffusion-relaxometry data Examples of multi-dimensional diffusion-relaxometry applications (brain, prostate, placenta, kidney) will be given.

Discussion/Conclusion

An outlook will be given on possible further developments and how relevance for clinical practise can be further increased

Acknowledgements

No acknowledgement found.

References

Veraart J, Novikov DS, Fieremans E. TE dependent Diffusion Imaging (TEdDI) distinguishes between compartmental T2 relaxation times. Neuroimage. 2017 Sep;

De Santis S, Barazany D, Jones DK, Assaf Y. Resolving relaxometry and diffusion properties within the same voxel in the presence of crossing fibres by combining inversion recovery and diffusion-weighted acquisitions. Magn Reson Med [Internet]. 2016 Jan [cited 2017 Nov 13];75(1):372–80. Available from: http://www.ncbi.nlm.nih.gov/pubmed/25735538

de Almeida Martins JP, Topgaard D. Multidimensional correlation of nuclear relaxation rates and diffusion tensors for model-free investigations of heterogeneous anisotropic porous materials. Sci Rep [Internet]. 2018 Dec 6 [cited 2018 Feb 27];8(1):2488. Available from: http://www.nature.com/articles/s41598-018-19826-9

Kim D, Doyle EK, Wisnowski JL, Kim JH, Haldar JP. Diffusion-relaxation correlation spectroscopic imaging: A multidimensional approach for probing microstructure. Magn Reson Med [Internet]. 2017 Dec 1 [cited 2018 Feb 27];78(6):2236–49. Available from: http://doi.wiley.com/10.1002/mrm.26629

Slator PJ,Hutter J, Palombo M, Jackson LH, Ho A, Panagiotaki E, et al. Combined Diffusion- Relaxometry MRI to Identify Dysfunction in the Human Placenta. arXiv [Internet]. 2018 Oct 9 [cited 2018 Dec 7]; Available from: http://arxiv.org/abs/1810.04156

Hutter J, Slator PJ, Christiaens D, Teixeira RPAG, Roberts T, Jackson L, et al. Integrated and efficient diffusion-relaxometry using ZEBRA. Sci Rep [Internet]. 2018 Dec 11 [cited 2018 Oct 11];8(1):15138. Available from: http://www.nature.com/articles/s41598-018-33463-2

Benjamini D, Basser PJ. Magnetic resonance microdynamic imaging reveals distinct tissue microenvironments. Neuroimage. 2017 Dec;163:183–96.

Proc. Intl. Soc. Mag. Reson. Med. 28 (2020)