The stray magnetic fields in Magnetic Resonance Current Density Imaging (MRCDI)

Investigating the neural mechanisms of transcranial direct current stimulation effects on human cognition: current issues and potential solutions

Transcranial direct current stimulation (tDCS) has been studied extensively for its potential to enhance human cognitive functions in healthy individuals and to treat cognitive impairment in various clinical populations. However, little is known about how tDCS modulates the neural networks supporting cognition and the complex interplay with mediating factors that may explain the frequently observed variability of stimulation effects within and between studies. Moreover, research in this field has been characterized by substantial methodological variability, frequent lack of rigorous experimental control and small sample sizes, thereby limiting the generalizability of findings and translational potential of tDCS. The present manuscript aims to delineate how these important issues can be addressed within a neuroimaging context, to reveal the neural underpinnings, predictors and mediators of tDCS-induced behavioral modulation. We will focus on functional magnetic resonance imaging (fMRI), because it allows the investigation of tDCS effects with excellent spatial precision and sufficient temporal resolution across the entire brain. Moreover, high resolution structural imaging data can be acquired for precise localization of stimulation effects, verification of electrode positions on the scalp and realistic current modeling based on individual head and brain anatomy. However, the general principles outlined in this review will also be applicable to other imaging modalities. Following an introduction to the overall state-of-the-art in this field, we will discuss in more detail the underlying causes of variability in previous tDCS studies. Moreover, we will elaborate on design considerations for tDCS-fMRI studies, optimization of tDCS and imaging protocols and how to assure high-level experimental control. Two additional sections address the pressing need for more systematic investigation of tDCS effects across the healthy human lifespan and implications for tDCS studies in age-associated disease, and potential benefits of establishing large-scale, multidisciplinary consortia for more coordinated tDCS research in the future. We hope that this review will contribute to more coordinated, methodologically sound, transparent and reproducible research in this field. Ultimately, our aim is to facilitate a better understanding of the underlying mechanisms by which tDCS modulates human cognitive functions and more effective and individually tailored translational and clinical applications of this technique in the future.

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.

Magnetic Resonance Electrical Impedance Tomography

Magnetic Resonance Electrical Impedance Tomography (MREIT) is a high-resolution bioimpedance imaging technique that has developed over a period beginning in the early 1990s to measure low-frequency (<1 kHz) tissue electrical properties. Low-frequency electrical properties are particularly important because they provide valuable information on cell structures and ionic composition of tissues, which may be very useful for diagnostic purposes. MREIT uses one component of the magnetic flux density data induced due to an exogenous-current administration, measured using an MRI machine, to reconstruct isotropic or anisotropic electrical property distributions. The MREIT technique typically requires two linearly independent current administrations to reconstruct conductivity uniquely. Since its invention, researchers have explored its potential for measuring electrical conductivity in regions such as the brain and muscle tissue. It has also been investigated in disease models, for example, cerebral ischemia and early tumor detection. In this chapter, we aim to provide a solid foundation of the different MREIT image reconstruction algorithms, including both isotropic and anisotropic conductivity reconstruction approaches. We will also explore the newly developed diffusion tensor magnetic resonance electrical impedance tomography (DT-MREIT) method, a practical method for anisotropic tissue property imaging, at the end of the chapter.

SNR and total acquisition time analysis of multi-echo FLASH pulse sequence for current density imaging

Magnetic Resonance Current Density Imaging (MRCDI) is an imaging modality providing cross-sectional current density (J¯) information inside the body. The clinical applicability of MRCDI is highly dependent on the sensitivity of the acquired noisy current-induced magnetic flux density (B∼_z) distributions. Here, a novel analysis is developed to investigate the combined effect of relevant parameters of the RF spoiled gradient echo (FLASH) pulse sequence on the SNR level and the total acquisition time (TAT) of the acquired B∼_z images. The proposed analysis then is expanded for a multi-echo FLASH (ME-FLASH) pulse sequence to take advantage of combining the multiple echoes to achieve B∼_z^comb distribution with a higher SNR than the one achievable with a single echo acquisition. The optimized sequence parameters to acquire a B∼_z distribution with the highest possible SNR for a given acquisition time or the desired SNR in the shortest scan time are estimated using the proposed analysis. The analysis also provides different sets of sequence parameters to acquire B∼_z distributions with the same SNR at almost the same TAT. Furthermore, the effects of intensive utilization of the gradients and the magnetohydrodynamic (MHD) flow velocity on the acquired B∼_z distribution in MRCDI experiments is investigated. The analytical results of the proposed analysis are validated experimentally using an imaging phantom having the conductivity and the relaxation parameters of the brain white matter tissue.

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.

Safety evaluation of a new setup for transcranial electric stimulation during magnetic resonance imaging

BACKGROUND

Transcranial electric stimulation during MR imaging can introduce safety issues due to coupling of the RF field with the stimulation electrodes and leads.

OBJECTIVE

To optimize the stimulation setup for MR current density imaging (MRCDI) and increase maximum stimulation current, a new low-conductivity (σ = 29.4 S/m) lead wire is designed and tested.

METHOD

The antenna effect was simulated to investigate the effect of lead conductivity. Subsequently, specific absorption rate (SAR) simulations for realistic lead configurations with low-conductivity leads and two electrode types were performed at 128 MHz and 298 MHz being the Larmor frequencies of protons at 3T and 7T. Temperature measurements were performed during MRI using high power deposition sequences to ensure that the electrodes comply with MRI temperature regulations.

RESULTS

The antenna effect was found for copper leads at ¼ RF wavelength and could be reliably eliminated using low-conductivity leads. Realistic lead configurations increased the head SAR and the local head SAR at the electrodes only minimally. The highest temperatures were measured on the rings of center-surround electrodes, while circular electrodes showed little heating. No temperature increase above the safety limit of 39 °C was observed.

CONCLUSION

Coupling to the RF field can be reliably prevented by low-conductivity leads, enabling cable paths optimal for MRCDI. Compared to commercial copper leads with safety resistors, the low-conductivity leads had lower total impedance, enabling the application of higher currents without changing stimulator design. Attention must be paid to electrode pads.

In-vivo imaging of targeting and modulation of depression-relevant circuitry by transcranial direct current stimulation: a randomized clinical trial

Recent clinical trials of transcranial direct current stimulation (tDCS) in depression have shown contrasting results. Consequently, we used in-vivo neuroimaging to confirm targeting and modulation of depression-relevant neural circuitry by tDCS. Depressed participants (N = 66, Baseline Hamilton Depression Rating Scale (HDRS) 17-item scores ≥14 and <24) were randomized into Active/Sham and High-definition (HD)/Conventional (Conv) tDCS groups using a double-blind, parallel design, and received tDCS individually targeted at the left dorsolateral prefrontal cortex (DLPFC). In accordance with Ampere's Law, tDCS currents were hypothesized to induce magnetic fields at the stimulation-target, measured in real-time using dual-echo echo-planar-imaging (DE-EPI) MRI. Additionally, the tDCS treatment trial (consisting of 12 daily 20-min sessions) was hypothesized to induce cerebral blood flow (CBF) changes post-treatment at the DLPFC target and in the reciprocally connected anterior cingulate cortex (ACC), measured using pseudo-continuous arterial spin labeling (pCASL) MRI. Significant tDCS current-induced magnetic fields were observed at the left DLPFC target for both active stimulation montages (Brodmann's area (BA) 46: p_HD = 0.048, Cohen's d_HD = 0.73; p_Conv = 0.018, d_Conv = 0.86; BA 9: p_HD = 0.011, d_HD = 0.92; p_Conv = 0.022, d_Conv = 0.83). Significant longitudinal CBF increases were observed (a) at the left DLPFC stimulation-target for both active montages (p_HD = 3.5E-3, d_HD = 0.98; p_Conv = 2.8E-3, d_Conv = 1.08), and (b) at ACC for the HD-montage only (p_HD = 2.4E-3, d_HD = 1.06; p_Conv = 0.075, d_Conv = 0.64). These results confirm that tDCS-treatment (a) engages the stimulation-target, and (b) modulates depression-relevant neural circuitry in depressed participants, with stronger network-modulations induced by the HD-montage. Although not primary outcomes, active HD-tDCS showed significant improvements of anhedonia relative to sham, though HDRS scores did not differ significantly between montages post-treatment.

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.