SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI

Abstract

This work introduces a compartment-based model for apparent cell body (namely soma) and neurite density imaging (SANDI) using non-invasive diffusion-weighted MRI (DW-MRI). The existing conjecture in brain microstructure imaging through DW-MRI presents water diffusion in white (WM) and gray (GM) matter as restricted diffusion in neurites, modelled by infinite cylinders of null radius embedded in the hindered extra-neurite water. The extra-neurite pool in WM corresponds to water in the extra-axonal space, but in GM it combines water in the extra-cellular space with water in soma. While several studies showed that this microstructure model successfully describe DW-MRI data in WM and GM at b ≤ 3,000 s/mm2 (or 3 ms/μm2), it has been also shown to fail in GM at high b values (b≫3,000 s/mm2 or 3 ms/μm2). Here we hypothesise that the unmodelled soma compartment (i.e. cell body of any brain cell type: from neuroglia to neurons) may be responsible for this failure and propose SANDI as a new model of brain microstructure where soma of any brain cell type is explicitly included. We assess the effects of size and density of soma on the direction-averaged DW-MRI signal at high b values and the regime of validity of the model using numerical simulations and comparison with experimental data from mouse (bmax = 40,000 s/mm2, or 40 ms/μm2) and human (bmax = 10,000 s/mm2, or 10 ms/μm2) brain. We show that SANDI defines new contrasts representing complementary information on the brain cyto- and myelo-architecture. Indeed, we show maps from 25 healthy human subjects of MR soma and neurite signal fractions, that remarkably mirror contrasts of histological images of brain cyto- and myelo-architecture. Although still under validation, SANDI might provide new insight into tissue architecture by introducing a new set of biomarkers of potential great value for biomedical applications and pure neuroscience.

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References 105

1. 1.

   Afzali M. Improving neural soma imaging using the power spectrum of the free gradient waveforms. Proc. Intl. Soc. Mag. Reson. Med. 2020.

   Not in our library

2. 2.

   Aggarwal M., Jones M.V., Calabresi P.A., Mori S., Zhang J.Y. Probing mouse brain microstructure using oscillating gradient diffusion MRI. Magn. Reson. Med. 2012;67(1):98-109.

   Not in our library10.1002/mrm.22981

3. 3.

   Alexander D.C. A general framework for experiment design in diffusion MRI and its application in measuring direct tissue-microstructure features. Magn. Reson. Med. 2008;60(2):439-448.

   Not in our library10.1002/mrm.21646

4. 4.

   Alexander D.C. Orientationally invariant indices of axon diameter and density from diffusion MRI. Neuroimage. 2010;52(4):1374-1389.

   Not in our library10.1016/j.neuroimage.2010.05.043

5. 5.

   Alexander D.C., Dyrby T.B., Nilsson M., Zhang H. Imaging brain microstructure with diffusion MRI: practicality and applications. NMR Biomed. 2019;32(4).

   Not in our library10.1002/nbm.3841

6. 6.

   Amunts K., Zilles K. Architectonic mapping of the human brain beyond Brodmann. Neuron. 2015;88(6):1086-1107.

   Not in our library10.1016/j.neuron.2015.12.001

7. 7.

   Amunts K. Broca’s region revisited: cytoarchitecture and intersubject variability. J. Comp. Neurol. 1999;412(2):319-341.

   Not in our library10.1002/(sici)1096-9861(19990920)412:2<319::aid-cne10>3.0.co;2-7

8. 8.

   Amunts K., Malikovic A., Mohlberg H., Schormann T., Zilles K. Brodmann’s areas 17 and 18 brought into stereotaxic space - where and how variable? Neuroimage. 2000;11(1):66-84.

   Not in our library10.1006/nimg.1999.0516

9. 9.

   Aronica E., Muhlebner A. Neuropathology of epilepsy. Handb. Clin. Neurol. 2017;145:193-216.

   Not in our library10.1016/b978-0-12-802395-2.00015-8

10. 10.

    Assaf Y. Imaging laminar structures in the gray matter with diffusion MRI. Neuroimage. 2019;197:677-688.

    Not in our library10.1016/j.neuroimage.2017.12.096

11. 11.

    Assaf Y., Basser P.J. Composite hindered and restricted model of diffusion (CHARMED) MR imaging of the human brain. Neuroimage. 2005;27(1):48-58.

    Not in our library10.1016/j.neuroimage.2005.03.042

12. 12.

    Assaf Y., Blumenfeld-Katzir T., Yovel Y., Basser P.J. AxCaliber: a method for measuring axon diameter distribution from diffusion MRI. Magn. Reson. Med. 2008;59(6):1347-1354.

    Not in our library10.1002/mrm.21577

13. 13.

    Balinov B., Jonsson B., Linse P., Söderman O. The NMR self-diffusion method applied to restricted diffusion. Simulation of echo attenuation from molecules in spheres and between planes. J. Magn. Reson., Ser. A. 1993;104:17-25.

    Not in our library

14. 14.

    Bianciardi M. Toward an in vivo neuroimaging template of human brainstem nuclei of the ascending arousal, autonomic, and motor systems. Brain Connect. 2015;5(10):597-607.

    Not in our library10.1089/brain.2015.0347

15. 15.

    Bianciardi M. Validation and application of soma and neurite density imaging (SANDI) for in vivo human brainstem nuclei atlasing. Proc. Int. Soc. Mag. Reson. Med. 2020.

    Not in our library

16. 16.

    Brodmann K. 1909.

    Not in our library

17. 17.

    Burnham K.P., Anderson D.R. 2002.

    Not in our library

18. 18.

    Callaghan P.T., Soderman O. Examination of the lamellar phase of aerosol ot-water using pulsed field gradient nuclear magnetic-resonance. J Phys. Chem. 1983;87(10):1737-1744.

    Not in our library

19. 19.

    Callaghan P.T., Jolley K.W., Lelievre J. Diffusion of water in the endosperm tissue of wheat grains as studied by pulsed field gradient nuclear magnetic resonance. Biophys. J. 1979;28(1):133-141.

    Not in our library10.1016/s0006-3495(79)85164-4

20. 20.
    An Integrated Micro- and Macroarchitectural Analysis of the Drosophila Brain by Computer-Assisted Serial Section Electron Microscopy · 2010

    No notice
21. 21.

    Celebre G., Coppola L., Ranieri G.A. Water self-diffusion in lyotropic systems by simulation of pulsed field gradient-spin echo nuclear-magnetic-resonance experiments. J. Chem. Phys. 1992;97(10):7781-7785.

    Not in our library

22. 22.

    Cheung M.M. Does diffusion kurtosis imaging lead to better neural tissue characterization? A rodent brain maturation study. Neuroimage. 2009;45(2):386-392.

    Not in our library10.1016/j.neuroimage.2008.12.018

23. 23.

    Coelho S., Pozo J.M., Jespersen S.N., Jones D.K., Frangi A.F. Resolving degeneracy in diffusion MRI biophysical model parameter estimation using double diffusion encoding. Magn. Reson. Med. 2019;82(1):395-410.

    Not in our library10.1002/mrm.27714

24. 24.

    Cook P.A. 2006;vol. 2759:2759.

    Not in our library

25. 25.

    Criminisi A., Shotton J. 2013.

    Not in our library10.1016/j.media.2013.01.001

26. 26.

    Deipolyi A.R. Comparing microstructural and macrostructural development of the cerebral cortex in premature newborns: diffusion tensor imaging versus cortical gyration. Neuroimage. 2005;27(3):579-586.

    Not in our library10.1016/j.neuroimage.2005.04.027

27. 27.

    Dhital B., Reisert M., Kellner E., Kiselev V.G. Intra-axonal diffusivity in brain white matter. Neuroimage. 2019;189:543-550.

    Not in our library10.1016/j.neuroimage.2019.01.015

28. 28.

    Diaz-Cintra S. Ultrastructural analysis of hippocampal pyramidal neurons from apolipoprotein E-deficient mice treated with a cathepsin inhibitor. J. Neurocytol. 2004;33(1):37-48.

    Not in our library10.1023/b:neur.0000029647.41374.98

29. 29.

    Dortch R.D., Harkins K.D., Juttukonda M.R., Gore J.C., Does M.D. Characterizing inter-compartmental water exchange in myelinated tissue using relaxation exchange spectroscopy. Magn. Reson. Med. 2013;70(5):1450-1459.

    Not in our library10.1002/mrm.24571

30. 30.

    Ferizi U. White matter compartment models for in vivo diffusion MRI at 300mT/m. Neuroimage. 2015;118:468-483.

    Not in our library10.1016/j.neuroimage.2015.06.027

31. 31.

    Fieremans E., Jensen J.H., Helpern J.A. White matter characterization with diffusional kurtosis imaging. Neuroimage. 2011;58(1):177-188.

    Not in our library10.1016/j.neuroimage.2011.06.006

32. 32.

    Fukutomi H. Neurite imaging reveals microstructural variations in human cerebral cortical gray matter. Neuroimage. 2018;182:488-499.

    Not in our library10.1016/j.neuroimage.2018.02.017

33. 33.
    Whole brain myelin mapping using T1- and T2-weighted MR imaging data · 2014

    No notice
34. 34.

    Geyer S., Schormann T., Mohlerg H., Zilles K. Areas 3a, 3b, and 1 of human primary somatosensory cortex - 2. Spatial normalization to standard anatomical space. Neuroimage. 2000;11(6):684-696.

    Not in our library10.1006/nimg.2000.0548

35. 35.

    Glasser M.F. The minimal preprocessing pipelines for the Human Connectome Project. Neuroimage. 2013;80:105-124.

    Not in our library10.1016/j.neuroimage.2013.04.127

36. 36.

    Greve D.N., Fischl B. Accurate and robust brain image alignment using boundary-based registration. Neuroimage. 2009;48(1):63-72.

    Not in our library10.1016/j.neuroimage.2009.06.060

37. 37.

    Gyori N., Clark C., Dragonu I., Alexander D.C., Kaden E. In-vivo neural soma imaging using B-tensor encoding and deep learning. Proc. Intl. Soc. Mag. Reson. Med. 2019.

    Not in our library

38. 38.

    Hall M.G., Alexander D.C. Convergence and parameter choice for Monte-Carlo simulations of diffusion MRI. IEEE Trans. Med. Imag. 2009;28(9):1354-1364.

    Not in our library10.1109/tmi.2009.2015756

39. 39.

    Hansen M.B., Jespersen S.N., Leigland L.A., Kroenke C.D. Using diffusion anisotropy to characterize neuronal morphology in gray matter: the orientation distribution of axons and dendrites in the NeuroMorpho.org database. Front. Integr. Neurosci. 2013;7:31.

    Not in our library10.3389/fnint.2013.00031

40. 40.

    Henriques R.N., Jespersen S.N., Shemesh N. Microscopic anisotropy misestimation in spherical-mean single diffusion encoding MRI. Magn. Reson. Med. 2019;81(5):3245-3261.

    Not in our library10.1002/mrm.27606

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