23Na concentrations and iron deposition in cerebral gray matter have both shown to be increased in degenerative and inflammatory cerebral diseases. This study employs sodium imaging and quantitative susceptibility mapping to assess differences in sodium concentrations and susceptibility within the basal ganglia in healthy volunteers at 7T. Results indicate a fundamentally different distribution of 23Na concentrations compared to the distribution of susceptibility within the nuclei of the basal ganglia and suggest that not only susceptibility but also 23Na concentrations may be physiologically distributed in a characteristic manner.
Although 23Na concentrations and susceptibility of cerebral gray matter have both been shown to be elevated in degenerative and inflammatory diseases, the distribution of 23Na concentrations appears to be fundamentally different compared to the distribution of susceptibility within the nuclei of the basal ganglia. The interpretation of this study is limited by a low number of studied subjects; the results however suggest that not only susceptibility but also 23Na concentrations may be physiologically distributed in a characteristic manner. A recent study also investigating 23Na concentrations within the basal ganglia at a lower nominal isotropic resolution reported similar concentrations in the thalamus while the distribution of 23Na concentrations in the remaining basal ganglia differed in comparison to this study 21. A possible reason for differing results may be partial volume effects.
The results of this study suggest that basal ganglia may not only distinguish themselves through characteristic susceptibilities but also characteristic 23Na concentrations.
1. Deistung A, Schafer A, Schweser F, Biedermann U, Turner R, Reichenbach JR. Toward in vivo histology: A comparison of quantitative susceptibility mapping (QSM) with magnitude-, phase-, and R-2*-imaging at ultra-high magnetic field strength. Neuroimage 2013;65:299-314.
2. Keuken MC, Bazin PL, Crown L, et al. Quantifying inter-individual anatomical variability in the subcortex using 7 T structural MRI. Neuroimage 2014;94:40-46.
3. Dominguez JF, Ng AC, Poudel G, et al. Iron accumulation in the basal ganglia in Huntington's disease: cross-sectional data from the IMAGE-HD study. J Neurol Neurosurg Psychiatry 2016;87:545-549.
4. Juhas M, Sun HF, Brown MRG, et al. Deep grey matter iron accumulation in alcohol use disorder. Neuroimage 2017;148:115-122. 5. Zivadinov R, Tavazzi E, Bergsland N, et al. Brain Iron at Quantitative MRI Is Associated with Disability in Multiple Sclerosis. Radiology 2018;289:487-496.
6. Langkammer C, Pirpamer L, Seiler S, et al. Quantitative Susceptibility Mapping in Parkinson's Disease. Plos One 2016;11.
7. Wallis LI, Paley MNJ, Graham JM, et al. MRI Assessment of Basal Ganglia Iron Deposition in Parkinson's Disease. J Magn Reson Imaging 2008;28:1061-1067.
8. Mellon EA, Pilkinton DT, Clark CM, et al. Sodium MR Imaging Detection of Mild Alzheimer Disease: Preliminary Study. Am J Neuroradiol 2009;30:978-984.
9. Zaaraoui W, Konstandin S, Audoin B, et al. Distribution of brain sodium accumulation correlates with disability in multiple sclerosis: a cross-sectional 23Na MR imaging study. Radiology 2012;264:859-867.
10. O'Brien MD, Jordan MM, Waltz AG. Ischemic cerebral edema and the blood-brain barrier. Distributions of pertechnetate, albumin, sodium, and antipyrine in brains of cats after occlusion of the middle cerebral artery. Arch Neurol 1974;30:461-465.
11. Boada FE, LaVerde G, Jungreis C, Nemoto E, Tanase C, Hancu F. Loss of cell ion homeostasis and cell viability in the brain: What sodium MRI can tell us. Curr Top Dev Biol 2005;70:77-+.
12. Nagel AM, Laun FB, Weber MA, Matthies C, Semmler W, Schad LR. Sodium MRI using a density-adapted 3D radial acquisition technique. Magn Reson Med 2009;62:1565-1573.
13. Eckstein K, Dymerska B, Bachrata B, et al. Computationally Efficient Combination of Multi-channel Phase Data From Multi-echo Acquisitions (ASPIRE). Magn Reson Med 2018;79:2996-3006.
14. Smith SM. Fast robust automated brain extraction. Hum Brain Mapp 2002;17:143-155.
15. Li W, Wu B, Liu CL. Quantitative susceptibility mapping of human brain reflects spatial variation in tissue composition. Neuroimage 2011;55:1645-1656. 16. Li W, Avram AV, Wu B, Xiao X, Liu CL. Integrated Laplacian-based phase unwrapping and background phase removal for quantitative susceptibility mapping. Nmr Biomed 2014;27:219-227. 17. Wu B, Li W, Guidon A, Liu CL. Whole brain susceptibility mapping using compressed sensing. Magn Reson Med 2012;67:137-147.
18. Wei HJ, Dibb R, Zhou Y, et al. Streaking artifact reduction for quantitative susceptibility mapping of sources with large dynamic range. Nmr Biomed 2015;28:1294-1303.
19. Maleike D, Nolden M, Meinzer HP, Wolf I. Interactive segmentation framework of the Medical Imaging Interaction Toolkit. Comput Meth Prog Bio 2009;96:72-83.
20. Nolden M, Zelzer S, Seitel A, et al. The Medical Imaging Interaction Toolkit: challenges and advances. Int J Comput Ass Rad 2013;8:607-620.
21. Ridley B, Nagel AM, Bydder M, et al. Distribution of brain sodium long and short relaxation times and concentrations: a multi-echo ultra-high field (23)Na MRI study. Sci Rep 2018;8:4357.