Purpose

This study reports the results of human brain imaging experiments using conductivity tensor imaging (CTI) method. In vivo CTI of five human brains were performed using a 3T MR scanner with 1.87 mm spatial resolution.

Methods

Five healthy volunteers without a documented history of any disease were recruited (KHSIRB-16-033). The volunteers were 25.4 ± 4.5 years old (3 male and 2 female). All participants were examined before and after each imaging experiment using a 3T clinical MRI scanner (Magnetom Trio A Tim, Siemens Medical Solution, Germany). The image of the conductivity tensor was reconstructed using the CTI formula [1]: C = [χσ_H / χd_e^w +(1-χ)d_i^wβ] D_e^w = η D_e^w (1), where σ_H is the high-frequency conductivity at the Larmor frequency, χ is the extracellular volume fraction, β is the ion concentration ratio of intracellular and extracellular spaces, d_e^w and d_i^w are the extracellular and intracellular water diffusion coefficients, η is position dependent scale factor and D_e^w is the extracellular water diffusion tensor. The multi-echo spin-echo pulse sequence with multiple refocusing pulses was adopted to obtain the high-frequency conductivity (σ_H). The imaging parameters were as follows: TR/TE = 1500/15 ms, number of echoes = 6, NEX = 5, slice thickness = 4 mm, number of slices = 5, matrix size = 128 × 128, and FOV = 240 × 240 mm². Multi-b diffusion weighted imaging data sets were obtained using the single-shot spin-echo echo-planar-imaging pulse sequence to calculate χ, d_e^w, d_i^w and D_e^w . The number of directions of the diffusion-weighting gradients was 15 with b values of 50, 150, 300, 500, 700, 1000, 1400, 1800, 2200, 2600, 3000, 3600, 4000, 4500 and 5000 s/mm². TR/TE = 2000/70 ms, slice thickness = 4 mm, flip angle = 90°, number of excitations = 2, number of slices = 5 and acquisition matrix = 64 × 64. The matrix size of 64 × 64 was extended to 128 × 128 for subsequent data processing steps. An additional conventional T2 weighted scan of 2 minutes was also acquired for anatomical reference. The parameter β is set to the value of 0.41 as suggested in [1].

Results and Discussion

Figure 1(a-d) illustrates the reconstructed CTI images of the brain from one subject using eq. (1). The recovered conductivity values of three different brain tissues including the white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) are shown in Fig. 2 for five subjects. For qualitative analysis (Fig. 2), each T2 images was segmented into WM, GM, and CSF regions. The entire white matter was further segmented into WM1, WM2 and WM3 regions where their longitudinal directions were aligned to x, y and z directions, respectively. The values of C_xx, C_yy, and C_zz were largest among the six elements of the conductivity tensors in WM1, WM2 and WM3, respectively. The values varied from 0.08 to 0.27 S/m. The WM anisotropic ratio (AR) varied from 1.96 to 3.25. For the GM regions, the conductivity values of C_xx, C_yy, and C_zz were in the range of 0.20 to 0.30 S/m. The ARs of the GM regions were between 1.12 and 1.19. In all WM and GM regions, σ_H was always larger than the recovered low-frequency conductivity values. The values of σ_H in the WM regions were between 0.33 to 0.48 S/m. In the GM regions, the values were between 0.60 to 0.72 S/m. The low-frequency conductivity of the isotropic CSF regions ranged from 1.55 to 1.82 S/m whereas its high-frequency conductivity values were in the range of 1.65 to 1.90 S/m. The scale factor η was largest in the CSF regions and smallest in the WM regions. The gray matter conductivity values of the human subjects were 0.20 to 0.30 S/m, which are close to the values of 0.24 to 0.29 S/m measured from in vivo DT-MREIT experiments of human subjects by using injection currents [2]. The ARs of the WM regions had much larger values of 1.96 to 3.25 compared with those of the gray matter regions. The WM regions also exhibited considerably more position and frequency dependency. These indicate that there were different amounts of myelinated fiber bundles with different directions in the voxels belonging to the WM regions depending on their positions. The low-frequency conductivity values of the GM and WM regions shown in Fig. 2 exhibited much stronger frequency dependencies compared to the CSF regions.

Conclusion

Unlike other low-frequency conductivity imaging methods of MREIT and DT-MREIT [2,3], CTI does not require injecting currents into the imaging subject. This allows CTI to be readily applicable to in vivo human imaging studies without causing any adverse effects of electrical stimulations of nerves and muscles. Without adding any special hardware, CTI can be implemented in a clinical MRI scanner for disease diagnosis and volume conduction modeling.

Acknowledgements

This work was supported by the National Research Foundation of Korea (NRF), the Ministry of Health and Welfare of Korea, and Korea Institute of Radiological and Medical Sciences (KIRAMS) grants funded by the Korea Government (2018R1D1A1B07046619, 2019R1A2C2088573, HI18C2435, and 50461-2019).