Human in-vivo brain magnetic resonance current density imaging (MRCDI)

Abstract

Magnetic resonance current density imaging (MRCDI) and MR electrical impedance tomography (MREIT) are two emerging modalities, which combine weak time-varying currents injected via surface electrodes with magnetic resonance imaging (MRI) to acquire information about the current flow and ohmic conductivity distribution at high spatial resolution. The injected current flow creates a magnetic field in the head, and the component of the induced magnetic field ΔB parallel to the main scanner field causes small shifts in the precession frequency of the magnetization. The measured MRI signal is modulated by these shifts, allowing to determine ΔB for the reconstruction of the current flow and ohmic conductivity. Here, we demonstrate reliable ΔB measurements in-vivo in the human brain based on multi-echo spin echo (MESE) and steady-state free precession free induction decay (SSFP-FID) sequences. In a series of experiments, we optimize their robustness for in-vivo measurements while maintaining a good sensitivity to the current-induced fields. We validate both methods by assessing the linearity of the measured ΔB with respect to the current strength. For the more efficient SSFP-FID measurements, we demonstrate a strong influence of magnetic stray fields on the ΔB images, caused by non-ideal paths of the electrode cables, and validate a correction method. Finally, we perform measurements with two different current injection profiles in five subjects. We demonstrate reliable recordings of ΔB fields as weak as 1 nT, caused by currents of 1 mA strength. Comparison of the ΔB measurements with simulated ΔB images based on FEM calculations and individualized head models reveals significant linear correlations in all subjects, but only for the stray field-corrected data. As final step, we reconstruct current density distributions from the measured and simulated ΔB data. Reconstructions from non-corrected ΔB measurements systematically overestimate the current densities. Comparing the current densities reconstructed from corrected ΔB measurements and from simulated ΔB images reveals an average coefficient of determination R of 71%. In addition, it shows that the simulations underestimated the current strength on average by 24%. Our results open up the possibility of using MRI to systematically validate and optimize numerical field simulations that play an important role in several neuroscience applications, such as transcranial brain stimulation, and electro- and magnetoencephalography.

Simulating individually targeted transcranial electric stimulation for experimental application

“…This non-invasive method allows to directly validate the simulated electric field, based on human in vivo measurements. First results indicate that FEM models yield a reasonable approximation to the measured electric fields (Göksu et al, 2018). Additionally, estimated electric fields from specific FEM head models showed a good correspondence when compared to intracranial recordings from human patients Lafon et al, 2017) and non-human primates (Kar et al, 2017;Opitz et al, 2016).…”

“…Additionally, estimated electric fields from specific FEM head models showed a good correspondence when compared to intracranial recordings from human patients Lafon et al, 2017) and non-human primates (Kar et al, 2017;Opitz et al, 2016). The observed modeling errors in these studies were mostly attributed to tissue conductivities (Göksu et al, 2018;Huang et al, 2017). In the large body of FEM applications these are not adapted to individually varying conductivity values and thus might lead to errors in the estimation of intracranial current densities induced by tES Schmidt et al, 2015).…”

“…Among these, CSF distribution, sulcus morphology, as well as the depth of the stimulation target were shown to have the greatest impact on electric field simulations (Laakso et al, 2015;Opitz et al, 2015). The FEM approach applied here specifically aims at the spatial arrangement of these tissue compartments inside the head and is able to accurately model these features (Göksu et al, 2018;Huang et al, 2017). Consequently, individual targeting of tES induced electric fields increases the level of control over the same individual features.…”

Concurrent Imaging of Markers of Current Flow and Neurophysiological Changes During tDCS

“…Since our initial work, two additional promising techniques have been proposed. Utilizing Magnetic Resonance Electrical Impedance Tomography (MREIT) (Kasinadhuni et al, 2017;Goksu et al, 2018), these techniques utilize alternating currents to map current-induced magnetic fields (along Bz). The published studies derived current-density distributions under the assumption of zero current density in one direction.…”

Comparing and Validating Automated Tools for Individualized Electric Field Simulations in the Human Head

“…On the other hand, (Opitz et al, 2018) found underestimated fields in one of the studied patients, while the calculated e-fields were too high in the second patient. Recently, (Göksu et al, 2018) demonstrated a novel non-invasive approach to reconstruct TES induced current densities in the brain from magnetic resonance images of the currentgenerated magnetic fields (magnetic resonance current density imaging, MRCDI). They present initial results on five subjects showing good agreement between simulated and measured current densities, with a moderate but systematic underestimation of the current densities by the models based on "standard" ohmic conductivities.…”