Magnetic-resonance-based measurement of electromagnetic fields and conductivity in vivo using single current administration—A machine learning approach

Abstract

Diffusion tensor magnetic resonance electrical impedance tomography (DT-MREIT) is a newly developed technique that combines MR-based measurements of magnetic flux density with diffusion tensor MRI (DT-MRI) data to reconstruct electrical conductivity tensor distributions. DT-MREIT techniques normally require injection of two independent current patterns for unique reconstruction of conductivity characteristics. In this paper, we demonstrate an algorithm that can be used to reconstruct the position dependent scale factor relating conductivity and diffusion tensors, using flux density data measured from only one current injection. We demonstrate how these images can also be used to reconstruct electric field and current density distributions. Reconstructions were performed using a mimetic algorithm and simulations of magnetic flux density from complementary electrode montages, combined with a small-scale machine learning approach. In a biological tissue phantom, we found that the method reduced relative errors between single-current and two-current DT-MREIT results to around 10%. For in vivo human experimental data the error was about 15%. These results suggest that incorporation of machine learning may make it easier to recover electrical conductivity tensors and electric field images during neuromodulation therapy without the need for multiple current administrations.

Mini Review: Impedance Measurement in Neuroscience and Its Prospective Application in the Field of Surgical Neurooncology

“…It is an imaging technique that reconstructs the conductivity distribution inside the subject using magnetic flux density or current density measurements acquired by a magnetic resonance imaging system ( 14 , 15 ). Algorithms are currently being developed to optimize the use of acquired images to reconstruct electric field and current density distributions ( 21 ). In a similar way, MR- electrical properties tomography (EPT) non-invasively images the conductivity and permittivity maps in vivo from the radiofrequency field signals obtained with MRI.…”

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

“…Initial successful MRCDI studies in phantoms, animals, and human limbs in vivo 13–31 formed the basis for more recent in vivo measurements in human brain 32–36 . However, accurate current flow mapping in the brain remains very challenging for several reasons: First, because the measured current‐induced magnetic fields are below 1–2 nT due to safety and tolerability limits of about 1–2 mA for the TES currents, 37 thermal and physiological noise as well as instrumental instabilities result in low SNR.…”

“…[5][6][7][8][9][10][11][12][13][14] Initial successful MRCDI studies in phantoms, animals, and human limbs in vivo [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31] formed the basis for more recent in vivo measurements in human brain. [32][33][34][35][36] However, accurate current flow mapping in the brain remains very challenging for several reasons: First, because the measured current-induced magnetic fields are below 1-2 nT due to safety and tolerability limits of about 1-2 mA for the TES currents, 37 thermal and physiological noise as well as instrumental instabilities result in low SNR. Second, the total scan time is limited by the ability of the participant to continuously lie still in the MR scanner.…”

Enhanced magnetic transduction of neuronal activity by nanofabricated inductors quantified via finite element analysis

“…Quantifications of intrinsic neuronal magnetic fields (NMFs) arising from the excitation of single neurons, subcellular compartments, and multicellular neuronal populations, were carried out computationally by several groups and can determine possibilities for NMF detection without the need for invasive transcranial wiring at the time of recording [10][11][12][13]. These studies informed the interpretation of MEG recordings [7,14] and catalyzed the design of specialized pulse sequences, phantom measurements and distilled preparations for magnetic resonance imaging (MRI) in attempts to detect NMFs volumetrically [15][16][17][18][19]. To date, real-time detection of NMFs by MEG at native in vivo scenarios, in the presence of motion artifacts, and blood flow related electromagnetic disturbances [7,20,21] requires severe averaging of consecutive trials evoking coordinated activity of many neurons, and has not yet been demonstrated convincingly by volumetric modalities [15,22].…”