Nitish Katoch^{1}, Bup Kyung Choi^{1}, Saurav ZK Sajib^{1}, Hyung Joong Kim^{1}, Oh In Kwon^{2}, and Eung Je Woo^{1}
^{1}Biomedical Engineering, Kyung Hee University, Seoul, Republic of Korea, ^{2}Konkuk University, Seoul, Republic of Korea
Synopsis
Electrical
conductivity is a passive material property primarily determined by
concentrations of charge carriers and their mobility. The macroscopic
conductivity of biological tissue at low frequency may exhibit anisotropy
related with its structural directionality. When expressed as a tensor and
properly quantified, the conductivity tensor can provide diagnostic information
of numerous diseases. Imaging of conductivity distributions inside the human
body requires probing it by externally injecting conduction currents or
inducing eddy currents. Here we propose a novel method to reconstruct
conductivity tensor images using an MRI scanner without any current injection.
PURPOSE
In
this study, a new electrodeless lowfrequency conductivity tensor imaging (CTI)
method is proposed based on the following two observations. Information about
the concentration of a charge carrier is embedded in the highfrequency
conductivity and the concentration is independent of frequency. Mobility of a
charge carrier is proportional to that of a water molecule when they exist in
the same microscopic environment.METHODS
The key
idea of electrodeless conductivity tensor imaging (CTI) is utilizes B1 mapping
to recover a highfrequency isotropic conductivity image which is influenced by
contents in both extracellular and intracellular spaces.^{1} Multib
diffusion weighted imaging is then utilized to extract the effects of the
extracellular space and incorporate the directional structural property.^{2}
We defined the physical quantities of CTI in Table 1 and summarized CTI
formula in figure 1.
RESULTS AND DISCUSSION
Figure
2 depicts the image reconstruction process of the proposed CTI method. Motions
of charge carriers contributing to lowfrequency conduction currents are
restricted in the extracellular space and hindered by cells and extracellular
matrix materials. This results in σ_{L} that is smaller
than σ_{H} (Fig.
2a). Structural directionality of a tissue gives rise to an anisotropic
conductivity that can be expressed as a tensor C (Fig. 2b).^{3} The electrodeless CTI method requires two
separate MRI scans. One is the multib diffusion weighted imaging method to
estimate d_{e}^{w}, d_{i}^{w}, χ, D_{e}^{w}.
The other is the B1 mapping method to estimate σ_{H} (Fig. 2c). Since
we did not know how to measure β, we
assumed that β was
constant for all pixels. We used the diffusion weighted image data with b = 700 s/mm^{2} to compute the
estimate of D_{e}^{w}. From
these, we reconstructed C images
by computing η using equation
10.CONCLUSION
CTI can provide conductivity tensor or
conductivity weighted images using a clinical MRI scanner without any added
hardware. Since the image contrast is based on ensemble averages of microscopic
motions of charge carriers in a structured tissue, macroscopic CTI image
parameters may lead to new methods to extract quantitative information about
the tissue microstructure and its functions. Future study will focus on
providing not only imaging of tumor, ischemia, inflammation, cirrhosis,
but also patientspecific models for source imaging and electrical stimulations.Acknowledgements
This work was supported by the National Research Foundation of Korea (NRF) grants funded by the Korea government (No. 2015R1D1A1A09058104, 2016R1A2B4014534, 2017R1A2A1A05001330)References

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