MR-based Current Density Imaging during Transcranial Direct Current Stimulation (tDCS)
Saurav ZK Sajib1, Woo Chul Jeong1, Nitish Katoch1, Bup Kyung Choi1, Hyung Joong Kim1, Oh In Kwon2, and Eung Je Woo1

1Kyung Hee University, Seoul, Korea, Republic of, 2Konkuk University, Seoul, Korea, Republic of

Synopsis

Quantitative visualization of induced current density by the electrical stimulation current inside the anisotropic brain region may play an important role to understand the neuro-modulatory effect during transcranial direct current stimulation (tDCS). For ensuring the clinical applications, precise approaches are required to understand the exact responses inside the human body subject to an injected currents, In this study, we reconstruct current density distribution inside the in vivo canine brain region by combing the directional information obtained from a DTI-MRI scan and the z-component of the magnetic flux density data using MREIT technique.

Purpose

The aim of this study is to evaluate the current density distribution induced by the external injected stimulation current from the in vivo canine brain. The anisotropic current density map of brain was calculated from the combination of the directional information obtained by DT-MRI scan and the z-component of the magnetic flux density data by MREIT technique.

Methods

Kwon et al.1 lately develop an iterative method for visualizing the internal distribution of current density inside the anisotropic brain region during transcranial direct current stimulation (tDCS). Using a subject-specific volume conductor model derived from the anatomical MR and the measured diffusion tensor information (D), the proposed method first estimate the model predicted current density (J0 ) and its corresponding z-component of the magnetic flux density (Bz0 ) by solving the Laplace equation. In this step, the electrical conductivity tensor (C) is assumed to be a scaler multiple of the water diffusion tensor, C = η0D, where η0 = 0.844S×sec/mm3 proposed by Tuch et al.2 By comparing the error differences between the measured and the computed magnetic flux density data the proposed method iteratively update the current density distribution1. To evaluate the proposed current density imaging method in this study, we perform the canine head imaging experiment. After clipping the hair from the head, we attached a pair of carbon-hydrogel electrodes and positioned inside the 8-channel knee coil equipped with our 3 T MRI scanner (Phillips Achieva, The Netherlands). We then collect the Bz data induce by 2 mA current injection at three slice position using T1-mFFE pulse sequence. The imaging parameters were set to TR/TE = 200/2.2 msec, echo spacing = 2.2 msec, voxel size = 1.1×1.1×4 mm3. Figs. 1(a) and (b) show the MR magnitude image and its corresponding Bz. We also obtained DTI data with b-values of 1000 sec/mm2 at the same three slice position using single-shot spin-echo EPI (SS-SE-EPI) sequence with TR/TE= 3000/67 msec. One reference MR data was also obtained without diffusion sensitized gradient to measure diffusion tensor. Fig. 1(c) shows the color-codded fractional anisotropic map.

Results and Discussion

By incorporating the DTI information in the canine head model, we first solve the Laplace equation. We then iteratively update the current density distribution using the measured Bz data. Fig 2(a) shows the updated current density at three iteration stage. In order to compare the directionality of the induced current, we also attached a second pair of electrodes mirroring the location of the first electrode montage (ε1). Fig 2(b) shows the estimated current density induced due to same stimulation current amplitude at same slice position for the second electrode montage (ε2) and the iteration vs. convergence plot is shown in the Fig 2(c). Table 1 summarizes the measured current density at five ROI position (Fig. 3) for both electrode montage.

Conclusion

Success of the tDCS treatment depends on the induced current density distribution within different anatomical structures of the brain. The induced current density depends on the electrode position, current amplitude as well as the local conductivity distribution. Since the proposed method incorporates the Bz information we hope the proposed current density imaging method, will play an important role in monitoring the tDCS treatment.

Acknowledgements

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2013R1A2A2A04016066, 2014R1A2A1A09006320).

References

1. Kwon OI, Sajib SZK et al. Current Density Imaging during Transcranial Direct Current Stimulation (tDCS) using DT-MRI and MREIT: Algorithm Development and Numerical Simulations,” IEEE Trans. Biomed. Eng., article in press.

2. Tuch DS, Wedeen VJ et al. Conductivity tensor mapping of human brain using diffusion tensor MRI. Proc. Nat. Acad. Sci. 2001; 98:11697-11701.

Figures

Fig. 1. MR magnitude image (a) and acquired Bz data (b) induced by tDCS current injection. Color coded fractional anisotropy map (c) obtain from DT-MRI.

Fig. 2. Magnitude of the reconstructed current density at axial slice position-1 for electrode montage ε1± (a) and for electrode montage ε2± (b). Iteration vs. convergence plot (c).

Fig. 3. ROI assignment to measure the current density values at brain tissues.

Table 1. Measured current density at five different ROIs (Fig.3) at three different imaging slices.



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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