• Diffusion MRI can be used to non-invasively probe
living biological tissues at the micron-scale and extract unique information
about their microstructural organisation.
• The q-space formalism directly links the spin
displacement probability distribution function with the Fourier transform of
the diffusion MR signal. Model “free” descriptions of the underlying diffusion
propagator for complex biological systems are possible.
• Over the years several methods have been developed
but hardware and time constraints have limited direct and widespread clinical
applications. Q-space and similar imaging techniques are mainly limited by the
many diffusion weightings or multiple diffusion times required.
• The advent of new MR technologies and new diffusion
imaging methods has the potential today not only to revitalise q-space methods
but also to reshape the whole field of diffusion imaging. Very complex
diffusion experiments are about to enter the realm of real clinical
applications. Exciting times are ahead!
This lecture is
aimed at all students and researchers working or starting to work in the field
of Diffusion NMR/MRI and that are interested to learn more about the underlying
principles of Diffusion MR and their potential applications to study biological
tissues.
The effects of diffusion on the final NMR signal have
been described since the original 1950 Hann paper on the discovery of
“spin-echoes” [1]. Today diffusion has become one of the major MR contrasts
used to study the microstructural organisation of several systems from minerals
to living biological tissues.
In this lecture the concepts behind q-space and
q-space imaging will be reviewed [2],[3]. Starting from an historical overview
on the major advances, the development of the q-space formalism and the concept
of the diffusion propagator will be described and used to explain the origin of
diffraction peaks and their possible application to infer pore sizes and other
microstructural features [4],[5]. Here, results from traditional single pulsed
gradient spin echo (single-PGSE) experiments will also be presented and
compared with more recent double-PGSE approaches [6].
Q-space and Propagator based imaging techniques (QSI,
DSI, 3D-SHORE, MAP-MRI, etc. [7],[8],[9]) will then be introduced highlighting
advantages and limitations of these techniques and their derived metrics. A
brief comparison will also be shown with alternative model-based approaches
(multi-tensor, spherical deconvolution and multi-compartmental models
[10],[11]).
Finally, the use of diffusion time as an effective
contrast to probe microstructure at different length scales will be discussed [12][13].
It will be shown also how, over the years, diffusion time has become an
increasingly important dimension in some of the most advanced diffusion
experiments (e.g. Axon caliber mapping techniques [14][15] and Oscillating
Gradients [16]).
To conclude the lecture, the practical applicability
of these techniques will be discussed. In particular, focusing on the limiting
constraints that have until now prevented a large adoption of these techniques.
With the advent of new ultra-fast acquisition technologies like multiband and
new custom built “microstructure” MR scanners, exciting opportunities await new
generations of researchers.
References
[1] Hahn, E. L.,
1950, “Spin echoes,” Phys. Rev. 80, 580–594.
[2] Callaghan, P.
T., Eccles C. D., and Xia Y, 1988, “NMR microscopy of dynamic displacements:
k-space and q-space imaging, J Phys. E: Sci Instrum, 21, 820–822
[3] Callaghan, P.
T., A. Coy, D. MacGowan, K. J. Packer, and F. O. Zelaya, 1991, “Diffraction-like
effects in NMR diffusion stud- ies of fluids in porous solids,” Nature , London
351, 467–469.
[4] Callaghan, P.
T. (1995). Pulsed-gradient spin-echo NMR for planar, cylindrical, and spherical
pores under conditions of wall relaxation. Journal of Magnetic Resonance,
Series A, 113(1), 53–59.
[5] Bar-Shir, A.,
Avram, L., Ozarslan, E., Basser, P. J., & Cohen, Y. (2008). The effect of
the diffusion time and pulse gradient duration ratio on the diffraction pattern
and the structural information estimated from q-space diffusion MR: experiments
and simulations. Journal of Magnetic Resonance 194(2), 230–236.
[6] Shemesh, N.,
Ozarslan, E., Bar-Shir, A., Basser, P. J., & Cohen, Y. 2009. Observation of
restricted diffusion in the presence of a free diffusion compartment: single-
and double-PFG experiments. Journal of Magnetic Resonance 200(2), 214–225.
[7] King M.D.,
Houseman J, Roussel S.A, van Bruggen N, Williams SR, Gadian DG, 1994, q-Space
imaging of the brain. Magn Reson Med. 32(6):707–13.
[8] Wedeen, V. J.,
Hagmann, P., Tseng, W.-Y. I., Reese, T. G., & Weisskoff, R. M. (2005).
Mapping complex tissue architecture with diffusion spectrum magnetic resonance
imaging. Magnetic Resonance in Medicine, 54(6), 1377–1386.
[9] Ozarslan, E.,
Koay, C. G., Shepherd, T. M., Komlosh, M. E., Irfanoglu, M. O., Pierpaoli, C.,
& Basser, P. J. (2013). Mean apparent propagator (MAP) MRI: a novel
diffusion imaging method for mapping tissue microstructure., 78, 16–32.
[10] Tournier,
J.-D., Mori, S., & Leemans, A. (2011). Diffusion tensor imaging and beyond.
Magnetic Resonance in Medicine, 65(6), 1532–1556.
[11] Panagiotaki,
E., Schneider, T., Siow, B., Hall, M. G., Lythgoe, M. F., & Alexander, D.
C. (2012). Compartment models of the diffusion MR signal in brain white matter:
a taxonomy and comparison., Neuroimage, 59(3), 2241–2254.
[12] van Gelderen P, DesPres D, van Zijl PC,
Moonen CT. Evaluation of restricted diffusion in cylinders. Phosphocreatine in
rabbit leg muscle. J Magn Reson B 1994;103(3):255–260.
[13] D. S.
Grebenkov, NMR Survey of Reflected Brownian Motion, Rev. Mod. Phys. 79
1077–1137 (2007).
[14] Assaf, Y.,
Blumenfeld-Katzir, T., Yovel, Y., & Basser, P. J. (2008). AxCaliber: a
method for measuring axon diameter distribution from diffusion MRI. Magnetic
Resonance in Medicine 59(6), 1347–1354.
[15] Alexander, D.
C., Hubbard, P. L., Hall, M. G., Moore, E. A., Ptito, M., Parker, G. J. M.,
& Dyrby, T. B. (2010). Orientationally invariant indices of axon diameter
and density from diffusion MRI. NeuroImage, 52(4), 1374–1389.
[16] Gore, J. C.,
Xu, J., Colvin, D. C., Yankeelov, T. E., Parsons, E. C., & Does, M. D.
(2010). Characterization of tissue structure at varying length scales using
temporal diffusion spectroscopy. NMR in Biomedicine, 23(7), 745–756.