Induced current magnetic resonance electrical impedance tomography of brain tissues based on the J-substitution algorithm: a simulation study

Abstract

We have investigated Induced Current Magnetic Resonance Electrical Impedance Tomography (IC-MREIT) by means of computer simulations. The J-substitution algorithm was implemented to solve the IC-MREIT reconstruction problem. By providing physical insight into the charge accumulating on the interfaces, the convergence characteristics of the reconstruction algorithm were analyzed. The simulation results conducted on different objects were well-correlated with the proposed theoretical analysis. The feasibility of IC-MREIT to reconstruct the conductivity distribution of head-brain tissues was also examined in computer simulations using a multi-compartment realistic head model. The present simulation results suggest that IC-MREIT may have the potential to become a useful conductivity imaging technique.

A feasibility study of magnetic resonance electrical impedance tomography for prostate cancer detection

“…J 1 and V 1 are the corresponding measurements induced by another injected current I 1 . The J-substitution algorithm (Kwon et al 2002, Liu et al 2009) and harmonic B z algorithm (Oh et al 2003), two widely used algorithms for solving the MREIT inverse problem based on current density and magnetic flux density measurements respectively, may then be applied. The steps below were adopted in the J-substitution algorithm to reconstruct the conductivity distribution inside the subject iteratively:

Step 1.

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“…In magnetic resonance electrical impedance tomography (MREIT), magnetic flux density distributions in the 3-dimentional (3D) space of the subject are captured with a magnetic resonance imaging (MRI) system and used to reconstruct the conductivity images (Oh et al 2003, Nam et al 2008, Liu et al 2009, Seo et al 2011). In this case, the ill-posedness of traditional EIT is eliminated, since a huge number of measurements can be acquired not only over the surface but also inside the subject.…”

Low-parametric Induced Current - Magnetic Resonance Electrical Impedance Tomography for quantitative conductivity estimation of brain tissues using a priori information: A simulation study

“…In this paper, we focus on obtaining an as accurate as possible estimation of the conductivity values by using the following methodologies: (1) eddy-current induction gradient: In [6], [8], the proposed MR pulse sequence consists of sinusoidal excitation that induce sinusoidal eddy currents. Here, we use a trapezoidal eddy-current induction gradient.…”

“…We use in this paper segmented MR images. In this way, the high number of parameters, used in [6], [8] that needs to be recovered is reduced to a low number so that the ill-posedness of the inverse problem is significantly reduced. (3) time-efficient Independent Impedance Method (IIM) as forward eddycurrent solver: Since a forward eddy-current solver needs to be evaluated many times in an iterative loop for solving the inverse problem, an efficient forward model is needed so to avoid prohibitive computational times.…”

Electric properties tomography: Biochemical, physical and technical background, evaluation and clinical applications

“…Eddy currents in the tissue can also be induced by gradient switching, corresponding to a much lower frequency in the range of kHz, as is the case for the above‐mentioned MR‐EIT. Discussions are ongoing as to whether these eddy currents enable a ‘low‐frequency’ EPT in contrast with the above‐described ‘RF’‐EPT . As recent results have indicated that these currents are too weak for MR detection, low‐frequency EPT is not considered further in this review.…”