bridging the micro-macro gap with diffusion MRI

Biophysical Modeling

We operate at the "mesoscopic" level, intermediate between the molecular scale where the NMR signal originates, and the macroscopic scale of MRI imaging resolution (millimeters). The mesoscopic scale is often referred to as that of "tissue microstructure", since it covers the span of microns to a few tens of microns. This scale is commensurate to the root-means-squared molecular displacement (diffusion length) of water molecules in living tissues, which is accessible with diffusion MRI. The sensitivity of MRI to the scale of cellular microstructure is a gift of nature, as it gives us sensitivity to microanatomy 100-1000 times below the nominal MRI resolution. 

The measured diffusion signal is equivalent to the diffusion propagator (the probability density function of molecular displacements over the diffusion time t) averaged over an imaging voxel. Technically, diffusion MRI measures its Fourier transform with respect to the spatial displacement. This rich physical object depends on both the displacement, via the 3-dimensional Fourier wave vector q, and the diffusion time t. The q-t imaging maps such propagator for each MRI voxel, and by virtue of biophysical modeling of the non-Gaussian diffusion signal in biological tissues, reveals vital tissue parameters such as water fractions in different cell types or in the extra-cellular space, membrane permeability, amount of myelin and so on. 


The above q-t diagram is taken from our recent comprehensive review of biophysical modeling: Quantifying brain microstructure with diffusion MRI: Theory and parameter estimation, NMR Biomed 2019; 32:e3998


D. S. Novikov, Kiselev, V. G., and Jespersen, S. N., On modeling., Magn Reson Med, vol. 79, pp. 3172–3193, 2018.
D. S. Novikov, Jensen, J. H., Helpern, J. A., and Fieremans, E., Revealing mesoscopic structural universality with diffusion, Proceedings of the National Academy of Sciences of the United States of America (PNAS), vol. 111, pp. 5088-5093, 2014.
M. Reisert, Kiselev, V. G., Dihtal, B., Kellner, E., and Novikov, D. S., MesoFT: unifying diffusion modelling and fiber tracking, Medical image computing & computer-assisted intervention : MICCAI, vol. 17, pp. 201-208, 2014.
D. S. Novikov, Fieremans, E., Jensen, J. H., and Helpern, J. A., Random walk with barriers, Nature physics, vol. 7, pp. 508-514, 2011.
D. S. Novikov and Kiselev, V. G., Effective medium theory of a diffusion-weighted signal, NMR in biomedicine, vol. 23, pp. 682-697, 2010.
D. S. Novikov and Kiselev, V. G., Transverse NMR relaxation in magnetically heterogeneous media, Journal of Magnetic Resonance, vol. 195, pp. 33 - 39, 2008.

Scholarly Lite is a free theme, contributed to the Drupal Community by More than Themes.