0587

Compartmental brain sodium concentrations in human brain tissues in white matter and grey matter: a multi-echo ultra-high field 23Na-MRI study

Ben Ridley^1,2, Armin M. Nagel^3,4, Mark Bydder^1,2, Adil Maarouf^1,2, Jan-Patrick Stellmann^1,2, Soraya Gherib^1,2, Jeremy Verneuil^1,2, Patrick Viout^1,2, Maxime Guye^1,2, Jean-Philippe Ranjeva^1,2, and Wafaa Zaaraoui^1,2

¹CRMBM, Aix-Marseille University, Marseille, France, ²CEMEREM, APHM Hôpitaux de la Timone, Marseille, France, ³Institute of Radiology, University Hospital Erlangen, Erlangen, Germany, ⁴German Cancer Research Centre, Division of Medical Physics in Radiology, Heidelberg, Germany

Synopsis

Using multi-echo ²³Na-MRI at 7T acquired in 13 healthy subjects and modelling the relationship between signal and reference concentration and applying it to in vivo ²³Na-MRI signal, we quantify both T2* decay times and concentrations associated with short and long components for the first time. Relaxation times and concentrations differed between grey and white matter and subregions of differing tissues, suggesting sensitivity of ²³Na toward features of tissue composition. As such, these results raise the prospect of multi-echo ²³Na-MRI as an adjunct source of information on biochemical mechanisms in both physiological and pathophysiological states.

Introduction

Sodium ion transmembrane homeostasis is a precondition for several critical neuronal functions, subject to pathological modification as shown by ²³Na-MRI methods including ultra-short echo times (UTE, ~0.2ms), multiple quantum filtering (MQF) or inversion recovery (IR)¹. However, uncertainty can arise in in vivo ²³Na estimates from signal losses given the rapidity of T2* decay given biexponential relaxation with both short (T2*_short) and long (T2*_long) components. Existing approaches attempt to minimize uncertainty but are insensible to different compartments (UTE), or weight toward rapidly relaxing components but suffer from strong SNR and resolution penalties (MQF), or are not easily amenable to providing quantitative estimates of sodium (IR). In contrast, we build on previous work by characterizing the decay curve directly via multi-echo imaging with the requisite number, distribution and range to assess the distribution of both^2,3 in vivo T2*_short and T2*_long and in variation between grey (GM) and white matter (WM) and subregions for the first time^4,5. Furthermore, by modelling the relationship between signal and reference concentration and applying it to in vivo ²³Na-MRI signal, we quantify Na concentrations associated with short and long components for the first time.

Methods

²³Na-MRI from 13 healthy subjects was acquired at 7T using a multi-echo (24 TEs, 0.3 ms-100 ms (Figure 1)) density adapted 3D projection reconstruction pulse sequence (TR=120 ms, 10000 spokes, 3.5mm³ resolution, 60 mins). Six tubes of 2% agar gel doped with a range of sodium concentrations (10-75 mM) were arrayed in the FOV. A high-resolution ¹H MRI 3D-MP2RAGE (TR=5000ms / TE=3ms / TI1=900ms / TI2=2750ms, 256 slices, 0.6mm³ isotropic resolution, 10 mins) was was used to define subject masks for GM, WM (SPM12, 0.9 tissue probability threshold) and 8 manually-defined regional ROIs (FSL 6.0). A biexponential fitting procedure was applied to the images of different TE derived from each individual to obtain T2*_short and T2*_long relaxation times for each ROI (Figure 2a). We measured M0 and the time of transverse relaxation (T2*) for a given reference tube across the 24 TEs, through monoexponential fitting via MATLAB (R2012a, MathWorks), and modelled a linear relationship between obtained M0 and known concentrations across all tubes (Figure 2b,c). Applying this to parameters estimated from the biexponential model of in vivo data, yielded quantitative estimates (Na_shortand Na_long) for each brain ROI. To permit literature comparisons, total sodium concentrations (TSC) and extracellular fractions (EcF) were also calculated. Two ANOVAs (JMP v.9) were applied to investigate factors of interest Tissue Type (2 levels: GM, WM) and Region (8 levels), in addition to Sex and Age. Factors of interest were further investigated via non-parametric Steel-Dwass tests.

Results

See Figure 3 for mean estimates of each parameter. Effect of Tissue type was significant for all parameters except Na_short (Figure 3, bottom), while post-hoc tests (Figure 4a) reveal relative levels GM>WM for Na_long, T2*_short, EcF and TSC and WM>GM for T2*_long. Effect of Region was significant for all parameters, and a significant effect of Sex was also observed for TSC. Overall, post-hoc (Figure 4b) tests revealed substantial variation for each parameter between subcortical regions, in addition to wide distributions between subjects for certain structures (especially centrum semiovale and corpus callosum (CC)) for certain parameters (T2*_long, EcF).

Discussion

The current data suggest that GM & WM give rise to different time constants of decay, which, given regional variation, may reflect the influence of tissue composition on observed relaxation. This would be consistent with observed differences in relative fluid content^6–8 and tissue density including the distribution, relative density and structure of neuronal and glial subtypes^9–12 influencing the volume of intra-/extracellular spaces¹³. For example, a restricted sodium pool determined mainly by the highly anisotropic¹⁴ axonal environment and small-bodied¹⁵ oligodendrocytes, versus a wider variety of cellular environments in GM, could lead to shorter estimates of T2*_short in WM and in axon/myelin-rich structures such as the pallidum, pons or CC. Consistency with previous estimates of EcF and TSC in GM vs WM and various regions^16–19 in controls samples, as well as ‘bound’ sodium estimates via ²³Na-MRI IR at 3T^20,21 and MQF at 7T^22,23, suggests that the current methods appropriately characterize the compartmental and overall ²³Na signal. Crucially, the current methods achieve this without a high SNR penalty and permit quantification.

Conclusion

We provide the first ²³Na-MRI data to address regional variation in T2*_short at UHF, and to quantify the ²³Na concentrations associated with short and long components. This provides a foundation for investigating alterations due to disease processes and the factors underlying normal ionic homeostatic mechanisms as imaged by ²³Na-MRI.

Acknowledgements

This work was supported by the ANR grant ‘NEUROintraSOD-7T’.

References

1. Thulborn, K. R. Quantitative Sodium MR Imaging: A Review of its Evolving Role in Medicine. NeuroImage (2016). doi:10.1016/j.neuroimage.2016.11.056

2. Bartha, R. & Menon, R. S. Long component time constant of 23Na T*2 relaxation in healthy human brain. Magn. Reson. Med. 52, 407–410 (2004).

3. Fleysher, L., Oesingmann, N., Stoeckel, B., Grossman, R. I. & Inglese, M. Sodium long-component T(2)(*) mapping in human brain at 7 Tesla. Magn. Reson. Med. 62, 1338–1341 (2009).

4. Nagel, A. M. et al. The potential of relaxation-weighted sodium magnetic resonance imaging as demonstrated on brain tumors. Invest. Radiol. 46, 539–547 (2011).

5. Blunck, Y. et al. 3D-multi-echo radial imaging of (23) Na (3D-MERINA) for time-efficient multi-parameter tissue compartment mapping. Magn. Reson. Med. (2017). doi:10.1002/mrm.26848

6. Koessler, L. et al. In-vivo measurements of human brain tissue conductivity using focal electrical current injection through intracerebral multicontact electrodes. Hum. Brain Mapp. 38, 974–986 (2017).

7. Gelman, N., Ewing, J. R., Gorell, J. M., Spickler, E. M. & Solomon, E. G. Interregional variation of longitudinal relaxation rates in human brain at 3.0 T: relation to estimated iron and water contents. Magn. Reson. Med. 45, 71–79 (2001).

8. Krebs, N. et al. Assessment of trace elements in human brain using inductively coupled plasma mass spectrometry. J. Trace Elem. Med. Biol. Organ Soc. Miner. Trace Elem. GMS 28, 1–7 (2014).

9. von Bartheld, C. S., Bahney, J. & Herculano-Houzel, S. The search for true numbers of neurons and glial cells in the human brain: A review of 150 years of cell counting. J. Comp. Neurol. 524, 3865–3895 (2016).

10. Mota, B. & Herculano-Houzel, S. All brains are made of this: a fundamental building block of brain matter with matching neuronal and glial masses. Front. Neuroanat. 8, 127 (2014).

11. Herculano-Houzel, S. The glia/neuron ratio: how it varies uniformly across brain structures and species and what that means for brain physiology and evolution. Glia 62, 1377–1391 (2014).

12. Azevedo, F. A. C. et al. Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain. J. Comp. Neurol. 513, 532–541 (2009).

13. Syková, E. & Nicholson, C. Diffusion in brain extracellular space. Physiol. Rev. 88, 1277–1340 (2008).

14. Assaf, Y. & Pasternak, O. Diffusion tensor imaging (DTI)-based white matter mapping in brain research: a review. J. Mol. Neurosci. MN 34, 51–61 (2008).

15. Pelvig, D. P., Pakkenberg, H., Stark, A. K. & Pakkenberg, B. Neocortical glial cell numbers in human brains. Neurobiol. Aging 29, 1754–1762 (2008).

16. Madelin, G., Lee, J.-S., Regatte, R. R. & Jerschow, A. Sodium MRI: methods and applications. Prog. Nucl. Magn. Reson. Spectrosc. 79, 14–47 (2014).

17. Inglese, M. et al. Brain tissue sodium concentration in multiple sclerosis: a sodium imaging study at 3 tesla. Brain J. Neurol. 133, 847–857 (2010).

18. Reetz, K. et al. Increased brain tissue sodium concentration in Huntington’s Disease - a sodium imaging study at 4 T. NeuroImage 63, 517–524 (2012).

19. Zaaraoui, W. et al. Distribution of brain sodium accumulation correlates with disability in multiple sclerosis: a cross-sectional 23Na MR imaging study. Radiology 264, 859–867 (2012).

20. Madelin, G., Kline, R., Walvick, R. & Regatte, R. R. A method for estimating intracellular sodium concentration and extracellular volume fraction in brain in vivo using sodium magnetic resonance imaging. Sci. Rep. 4, 4763 (2014).

21. Madelin, G., Babb, J., Xia, D. & Regatte, R. R. Repeatability of quantitative sodium magnetic resonance imaging for estimating pseudo-intracellular sodium concentration and pseudo-extracellular volume fraction in brain at 3 T. PloS One 10, e0118692 (2015).

22. Petracca, M. et al. Brain intra- and extracellular sodium concentration in multiple sclerosis: a 7 T MRI study. Brain J. Neurol. 139, 795–806 (2016).

23. Fleysher, L. et al. Noninvasive quantification of intracellular sodium in human brain using ultrahigh-field MRI. NMR Biomed. 26, 9–19 (2013).

Figures

Figure 1 – Exemplar ²³Na-MRI images from a single subject across echo times. Note the decrease in signal as a function of the length of echo time (TE), and the change in the relative contributions from tissue and cerebrospinal fluid, with the latter providing most signal at long TEs.

Figure 2 – Schematic workflow of processing procedure applied to data and the six measures obtained. After image post-processing, several fitting procedures were applied: a) a biexponential model to obtain M0_short and M0_long estimates from in vivo ROIs; b) a monoexponential model to obtain estimates of M0 for each reference tube and c) a linear model of the relationship between M0 and known reference concentrations. The six output parameters and their derivation are marked: two T2* components (dashed outline), a Na concentration for each component (double outline), total sodium concentrations (TSC, solid outline) and extracellular fraction (EcF, dotted outline).

Figure 3 – Results for 6 dependent variables in terms of (top) Mean (Mn) and standard deviation (s.d) for each dependent variable for each tissue type and region, and (bottom) significant bonferroni corrected (P<0.008) main effects (F) for ANOVAs applied to a) data from whole GM, WM masks and b) sub-regions. Numbers in brackets indicate degree of freedom. Non-significant main effects indicated by a dash (-).

Figure 4 - Post-hoc differences (z, Steel-dwass). Note the y-axis scale differs between parameters. Results of tests applied to a) data from whole GM, WM masks (Significant differences of P<0.008 marked with a bar and asterisk), and b) sub-regions. Due to the number of comparisons between subregions, significant differences at Bonferroni-corrected level between a region (circle with dark grey interior) with other regions (full black circles) are indicated below each graph. Regions: Th, thalamus; Pu, putamen; Pa, pallidum; Ca, caudate; Cc, corpus callosum; Cb, cerebellar WM, Cs, centrum semiovale; Po, pons.

Proc. Intl. Soc. Mag. Reson. Med. 26 (2018)

0587