Validation of MR mapping of direct current in a phantom model
Mayank V Jog1, Robert X. Smith2, Kay Jann2, Walter Dunn3, Allan Wu2, and Danny JJ Wang2

1Biomedical Engineering, University of California Los Angeles, Los Angeles, CA, United States, 2Neurology, University of California Los Angeles, Los Angeles, CA, United States, 3Psychiatry, University of California Los Angeles, Los Angeles, CA, United States

Synopsis

Transcranial Direct Current Stimulation(tDCS) is a neuromodulation technique. Reported to improve clinical conditions as well as cognition, tDCS has potential as a treatment modality since it involves only simple scalp electrodes to drive mA currents. To date, only mathematical modeling has been used to visualize tDCS-applied currents.

In previous work, we used MRI field mapping in a novel paradigm to visualize in-vivo, a component of the magnetic field generated by these currents. The present work completes the picture by validating our current visualization technique via comparison between the measured and simulated current-induced fields in a specially constructed phantom.

PURPOSE

Transcranial direct current stimulation (tDCS) is an emerging non-invasive neuromodulation technique that has been shown to improve symptoms in a range of neurologic and psychiatric disorders (epilepsy, Parkinson’s disease, chronic pain, depression and stroke [1,2,3]). Determining the spatial distribution of the applied current is critical to evaluate targeting and improve efficacy of tDCS montages. A MR current mapping technique has recently been introduced for visualizing tDCS induced electromagnetic field changes based on Ampere’s law [4,5]. The goal of the present study was to validate the MR current mapping technique in a conductive phantom model through comparison with theoretical calculations based on the Biot-Savart law.

METHODS

Ampere’s Law states that an applied direct current (DC) induces a magnetic field with its magnitude proportional to the current intensity and its direction orthogonal to the current. The along-B0 component of this induced field can be detected as phase changes using MRI field mapping. A field mapping experiment was performed using a cylindrical phantom fitted with an electrolyte filled plastic U-shaped tube (‘A’) (Fig 1). All applied currents were confined to this tube. An identical U-shaped tube(‘B’) was included as a control. Currents (0.5-1.5mA) were applied in a pseudo random order (Fig 2) over three sessions: ‘Active’, ‘–Active’ and ‘Sham’. The polarity of currents in ‘–Active’ was reversed relative to ‘Active’, while currents were switched off during ‘Sham’. Field mapping data was acquired concurrently with each applied current using a standard field mapping sequence (Quadrature volume coil, field mapping TE1/TE2=4.92/14.76 msec, TR=1.15 sec, FA = 250, 65 slices, 2x2x3mm3 Voxel, Matrix: 128 x128, BW=750 Hz/pix) on a Siemens 3T PRISMA scanner. With these parameters, the minimum detectable field was calculated as ~0.6nT/mA.

Analysis: Acquired phase data was SNR thresholded to preserve voxels with Gaussian noise [6]. Data was subsequently unwrapped using the Region Growing algorithm (implemented in PhaseTools [7]). Phase was modeled as:

Φm = Φ0 + ΦCurrent + ΦNon-Current + ΦDrift + ΦNoise

where Φm is the measured phase, Φ0 is the baseline phase, ΦCurrent is phase due to current-induced fields, ΦNon-Current is phase due to non-current sources (e.g. off resonance), ΦDrift represents the MRI inter-scan field drift and ΦNoise is Gaussian noise. Unwrapped data was modeled voxel-wise using a general linear model (GLM) with applied currents as predictor. By using the phase difference ΔΦm between two TE’s in our analyses, Φ0 was eliminated. ΔΦNon-Current by definition does not vary across currents, and is modeled by the intercept. ΔΦDrift was modeled by interpolating a polynomial to the zero current scans. The degree of the polynomial was adapted to avoid overfitting. The regression coefficient of the predictor (applied current) represents the induced-phase at unit current, and was converted to induced-magnetic field at unit current.

Simulations: The induced magnetic field was simulated from current density using a finite element implementation of the Biot-Savart law. The current density in turn was calculated from the geometry of Tube ‘A’ and the assumption of the electrolyte conductivity being uniform and isotropic. It should be noted that while the Biot-Savart law predicts the magnetic field at a point, MRI measures the induced field averaged over a voxel. Our simulation addresses this by averaging the induced magnetic fields over 175 equi-spaced points within each voxel.

RESULTS

Figure 3a shows the simulated current-induced field. Induced magnetic fields as low as 5nT/mA were reliably detected in the ‘Active’ session (Fig. 3b), and were highly consistent with simulations. The induced fields in the ‘–Active’ session(Fig. 3c) were observed to be similar in magnitude, while opposite in sign. This is expected, since reversing the current polarity reverses the direction of the induced fields (Ampere’s Law). No current-induced fields were detected for the ‘Sham’ session (Fig. 3d), or in the intra-session control tube ‘B’.

DISCUSSION and CONCLUSION

Our results provide a validation of the MR current mapping technique for in vivo studies. Through the phantom experiment, we demonstrated reliable detection of current induced field changes as low as ~5nT/mA. Our technique also demonstrates excellent specificity: No fields were detected in the ‘Control’ session or the intra-session control (Tube ‘B’). One unique advantage of our technique is that it uses information from phase images. Traditional fMRI techniques mapping neurophysiological markers mostly utilize magnitude images. Since every MRI acquisition measures a phase and a magnitude image, it is conceivable that the two techniques may be combined to enable simultaneous measurement of applied current and the brain response from a single MRI experiment.

Acknowledgements

No acknowledgement found.

References

[1] Fregni F, et. al. Transcranial direct current stimulation of the unaffected hemisphere in stroke patients. Neuroreport. 2005; 16(14):1551-5

[2] Fregni F, et. al. Treatment of major depression with transcranial direct current stimulation. Bipolar Disord. 2006; 8(2):203-4

[3] Fregni F, et. al. A sham-controlled, phase II trial of transcranial direct current stimulation for the treatment of central pain in traumatic spinal cord injury. Pain. 2006;122(1-2):197-209. Epub 2006 Mar 27

[4] Jog M, et. al. In-vivo Mapping of transcranial Direct Current Stimulation(tDCS) of Human Brain using MRI. ISMRM 2014, Prog# 0005

[5] Jog M, et. al. In-vivo Evidence of transcranial Direct Current Stimulation (tDCS) induced magnetic-field changes in Human Brain revealed by MRI. ISMRM 2015, Prog# 0515

[6] Gudbjartsson H., et. al. The Rician distribution of noisy MRI data. MRM 1995; 34(6); 910-4

[7] Barnhill E., et. al. Statistical mapping of the effect of knee extension on thigh muscle viscoelastic properties using magnetic resonance elastography. Physiol. Meas. 2013; 34; 1675-98

Figures

Fig 1. U-Tube Phantom Setup: Plastic, electrolyte filled U-Tubes were wrapped around a cylindrical phantom. All currents were confined to Tube ‘A’, while Tube ‘B’ was an intra-session control.

Fig 2. Experimental Protocol: Currents were applied for 3 sessions in a pseudo-random order. The polarity of the currents was reversed for ‘–Active’, while in ‘Sham’, the currents were switched off.

Fig 3. Results: (a) shows the simulation results, and (b),(c) and (d) show the experimentally detected current induced fields from the 'Active', '–Active' and 'Sham' sessions respectively.



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
1565