Volumetric measurements of weak current-induced magnetic fields in the human brain at high resolution.

PURPOSE: Clinical use of transcranial electrical stimulation (TES) requires accurate knowledge of the injected current distribution in the brain. MR current density imaging (MRCDI) uses measurements of the TES-induced magnetic fields to provide this information. However, sufficient sensitivity and image quality in humans in vivo has only been documented for single-slice imaging. METHODS: A recently developed, optimally spoiled, acquisition-weighted, gradient echo-based 2D-MRCDI method has now been advanced for volume coverage with densely or sparsely distributed slices: The 3D rectilinear sampling (3D-DENSE) and simultaneous multislice acquisition (SMS-SPARSE) were optimized and verified by cable-loop experiments and tested with 1-mA TES experiments for two common electrode montages. RESULTS: Comparisons between the volumetric methods against the 2D-MRCDI showed that relatively long acquisition times of 3D-DENSE using a single slab with six slices hindered the expected sensitivity improvement in the current-induced field measurements but improved sensitivity by 61% in the Laplacian of the field, on which some MRCDI reconstruction methods rely. Also, SMS-SPARSE acquisition of three slices, with a factor 2 CAIPIRINHA (controlled aliasing in parallel imaging results in higher acceleration) acceleration, performed best against the 2D-MRCDI with sensitivity improvements for the ∆ B z , c $$ \Delta {B}_{z,c} $$ and Laplacian noise floors of 56% and 78% (baseline without current flow) as well as 43% and 55% (current injection into head). SMS-SPARSE reached a sensitivity of 67 pT for three distant slices at 2 × 2 × 3 mm3 resolution in 10 min of total scan time, and consistently improved image quality. CONCLUSION: Volumetric MRCDI measurements with high sensitivity and image quality are well suited to characterize the TES field distribution in the human brain.

On the reconstruction of magnetic resonance current density images of the human brain: Pitfalls and perspectives.

Magnetic resonance current density imaging (MRCDI) of the human brain aims to reconstruct the current density distribution caused by transcranial electric stimulation from MR-based measurements of the current-induced magnetic fields. So far, the MRCDI data acquisition achieves only a low signal-to-noise ratio, does not provide a full volume coverage and lacks data from the scalp and skull regions. In addition, it is only sensitive to the component of the current-induced magnetic field parallel to the scanner field. The reconstruction problem thus involves coping with noisy and incomplete data, which makes it mathematically challenging. Most existing reconstruction methods have been validated using simulation studies and measurements in phantoms with simplified geometries. Only one reconstruction method, the projected current density algorithm, has been applied to human in-vivo data so far, however resulting in blurred current density estimates even when applied to noise-free simulated data. We analyze the underlying causes for the limited performance of the projected current density algorithm when applied to human brain data. In addition, we compare it with an approach that relies on the optimization of the conductivities of a small number of tissue compartments of anatomically detailed head models reconstructed from structural MR data. Both for simulated ground truth data and human in-vivo MRCDI data, our results indicate that the estimation of current densities benefits more from using a personalized volume conductor model than from applying the projected current density algorithm. In particular, we introduce a hierarchical statistical testing approach as a principled way to test and compare the quality of reconstructed current density images that accounts for the limited signal-to-noise ratio of the human in-vivo MRCDI data and the fact that the ground truth of the current density is unknown for measured data. Our results indicate that the statistical testing approach constitutes a valuable framework for the further development of accurate volume conductor models of the head. Our findings also highlight the importance of tailoring the reconstruction approaches to the quality and specific properties of the available data.

Sensitivity and resolution improvement for in vivo magnetic resonance current-density imaging of the human brain.

PURPOSE: Magnetic resonance current-density imaging (MRCDI) combines MRI with low-intensity transcranial electrical stimulation (TES; 1-2 mA) to map current flow in the brain. However, usage of MRCDI is still hampered by low measurement sensitivity and image quality. METHODS: Recently, a multigradient-echo-based MRCDI approach has been introduced that presently has the best-documented efficiency. This MRCDI approach has now been advanced in three directions and has been validated by phantom and in vivo experiments. First, the importance of optimum spoiling for brain imaging was verified. Second, the sensitivity and spatial resolution were improved by using acquisition weighting. Third, navigators were added as a quality control measure for tracking physiological noise. Combining these advancements, the optimized MRCDI method was tested by using 1 mA TES for two different injection profiles. RESULTS: For a session duration of 4:20 min, the new MRCDI method was able to detect TES-induced magnetic fields at a sensitivity level of 84 picotesla, representing a twofold efficiency increase against our original method. A comparison between measurements and simulations based on personalized head models showed a consistent increase in the coefficient of determination of ΔR2 = 0.12 for the current-induced magnetic fields and ΔR2 = 0.22 for the current flow reconstructions. Interestingly, some of the simulations still clearly deviated from the measurements despite the strongly improved measurement quality. This highlights the utility of MRCDI to improve head models for TES simulations. CONCLUSION: The achieved sensitivity improvement is an important step from proof-of-concept studies toward a broader application of MRCDI in clinical and basic neuroscience research.

Low-frequency conductivity tensor imaging with a single current injection using DT-MREIT.

Diffusion tensor-magnetic resonance electrical impedance tomography (DT-MREIT) is an imaging modality to obtain low-frequency anisotropic conductivity distribution employing diffusion tensor imaging and MREIT techniques. DT-MREIT is based on the linear relationship between the conductivity and water self-diffusion tensors in a porous medium, like the brain white matter. Several DT-MREIT studies in the literature provide cross-sectional anisotropic conductivity images of tissue phantoms, canine brain, and the human brain. In these studies, the conductivity tensor images are reconstructed using the diffusion tensor and current density data acquired by injecting two linearly independent current patterns. In this study, a novel reconstruction algorithm is devised for DT-MREIT to reconstruct the conductivity tensor images using a single current injection. Therefore, the clinical applicability of DT-MREIT can be improved by reducing the total acquisition time, the number of current injection cables, and contact electrodes to half by decreasing the number of current injection patterns to one. The proposed method is evaluated utilizing simulated measurements and physical experiments. The results obtained show the successful reconstruction of the anisotropic conductivity distribution using the proposed single current DT-MREIT.

Magnetohydrodynamic flow imaging of ionic solutions using electrical current injection and MR phase measurements.

In this study, a method is proposed to image magnetohydrodynamic (MHD) flow of ionic solutions, which is caused by externally injected electrical current to an imaging media, during MRI scans. A multi-physics (MP) model is created by using the electrical current, laminar flow, and MR equations. The conventional spoiled gradient echo MRI pulse sequence with bipolar flow encoding gradients is utilized to encode the MHD flow. Using the MP model and the MRI pulse sequence, relationship between the MHD flow related phase in the acquired MR signal, the injection current, and the MRI pulse sequence parameters is stated. Numerical simulations and physical experiments are performed to validate the proposed method. The simulation and experimental results are in agreement and show that the MHD flow related MR phase depends on the amplitude and duration of the flow encoding gradient and the injected current. This method may be used to evaluate the MHD flow of conductive liquid media during MRI scans with simultaneous electrical current injections. The MHD flow related MR phase is 1.5 radian for an injected current of 1 mA amplitude, 30 ms duration and a flow encoding gradient amplitude of 24 mT/m. This large MR phase range exhibits potential use of this method for clinical applications such as investigation of highly conductive cerebrospinal fluid (CSF) during clinical use of electrical current based neuromodulation in MRI. However, very high and time varying velocities of typical CSF flow compared to the MHD flow velocities should also be considered.

Induced Current Magnetic Resonance Electrical Conductivity Imaging With Oscillating Gradients.

In this paper, induced current magnetic resonance electrical impedance tomography (ICMREIT) by means of current induction due to time-varying gradient fields of magnetic resonance imaging (MRI) systems is proposed. Eddy current and secondary magnetic flux density distributions are calculated for a numerical model composed of a z-gradient coil and a cylindrical conductor. An MRI pulse sequence is developed for the experimental evaluation of ICMREIT on a 3T MRI scanner. A relationship between the secondary magnetic flux density and the low-frequency (LF) MR phase is formulated. Characteristics of the LF phase, the eddy current, and the reconstructed conductivity distributions based on the simulated and the physical measurements are in agreement. Geometric shifts, which may contaminate the LF phase measurements, are not observed in the MR magnitude images. Low sensitivity of the LF phase measurements is a major limitation of ICMREIT towards clinical applications. The reconstructed conductivity images are rough estimates of true conductivity distribution of the experimental phantoms. Although the experimental results show that ICMREIT is safe and potentially applicable, its measurement sensitivity and reconstruction accuracy need to be optimized in order to improve the technique towards clinical applications.

Two alternatives for magnetic resonance electrical impedance tomography: injected or induced current.

In this paper, the abilities of injected current magnetic resonance electrical impedance tomography (MREIT) and induced current magnetic resonance electrical impedance tomography (ICMREIT) systems to differentiate a conductivity perturbation from an otherwise uniform conductivity distribution are compared. The sensitivity of MREIT measurements changes as a function of distance to the electrodes used for current injection. The sensitivity of ICMREIT measurements is related to the radial location, being a minimum for concentrically located small conductivity perturbations. The very low sensitivity of ICMREIT to conductivity perturbations at central locations seems to be the major drawback of the method compared with MREIT. When the diameter of a concentric and/or an eccentric circular conductivity inhomogeneity inside an otherwise homogeneous circular conductor is close to half of the diameter of the conductor region, the distinguishability of the perturbation by MREIT increases. MREIT is more sensitive to perturbations with lower conductivity with respect to background conductivity (resistive perturbations) than to conductive perturbations. In the case of ICMREIT, concentric inhomogeneities are equally distinguishable for conductive and resistive conductivity perturbations. Eccentric resistive inhomogeneities are more distinguishable then conductive inhomogeneities. Distinguishability increases with the size and number of conductivity perturbations.

Experimental realization of induced current magnetic resonance current density imaging.

In this paper, recently proposed Induced Current Magnetic Resonance Current Density Imaging (ICMRCDI) is experimentally realized. The reconstructed current density images from the simulated measurements and from the physical measurements are in agreement. The proposed method is promising in reconstructing images of electrical conductivity as well as images of induced current density distribution within the body.

Induced current magnetic resonance electrical impedance tomography with z-gradient coil.

Magnetic Resonance Electrical Impedance Tomography (MREIT) is a medical imaging method that provides images of electrical conductivity at low frequencies (0-1 kHz). In MREIT, electrical current is applied to the body via surface electrodes and corresponding magnetic flux density is measured by means of Magnetic Resonance (MR) phase imaging techniques. By utilizing the magnetic flux density measurements and surface potential measurements images of true conductivity distribution can be reconstructed. In order to overcome difficulties regarding current application via surface electrodes, Induced Current MREIT (ICMREIT) have been proposed in the past. In ICMREIT, electrical currents and corresponding magnetic flux density are generated in the object through electromagnetic induction by means of externally placed coils driven with time varying currents. In this study, use of z-gradient, z-Helmholtz, and circular coil configurations in ICMREIT are proposed and investigated. Finite Element Method (FEM) is used to solve the forward problem of ICMREIT. Consequently, excitation performances and clinical applicability of different coil configurations are analyzed.