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A review of anisotropic conductivity models of brain white matter based on diffusion tensor imaging

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Abstract

The conductivity of brain tissues is not only essential for electromagnetic source estimation (ESI), but also a key reflector of the brain functional changes. Different from the other brain tissues, the conductivity of whiter matter (WM) is highly anisotropic and a tensor is needed to describe it. The traditional electrical property imaging methods, such as electrical impedance tomography (EIT) and magnetic resonance electrical impedance tomography (MREIT), usually fail to image the anisotropic conductivity tensor of WM with high spatial resolution. The diffusion tensor imaging (DTI) is a newly developed technique that can fulfill this purpose. This paper reviews the existing anisotropic conductivity models of WM based on the DTI and discusses their advantages and disadvantages, as well as identifies opportunities for future research on this subject. It is crucial to obtain the linear conversion coefficient between the eigenvalues of anisotropic conductivity tensor and diffusion tensor, since they share the same eigenvectors. We conclude that the electrochemical model is suitable for ESI analysis because the conversion coefficient can be directly obtained from the concentration of ions in extracellular liquid and that the volume fraction model is appropriate to study the influence of WM structural changes on electrical conductivity.

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Funding

This research work was supported by the Natural Science Foundation of Zhejiang Province (project number LY17E070007) and the National Natural Science Foundation of China (project number 51207038).

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Correspondence to Yang Liu.

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Wu, Z., Liu, Y., Hong, M. et al. A review of anisotropic conductivity models of brain white matter based on diffusion tensor imaging. Med Biol Eng Comput 56, 1325–1332 (2018). https://doi.org/10.1007/s11517-018-1845-9

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  • DOI: https://doi.org/10.1007/s11517-018-1845-9

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