Three-dimensional forward solver and its performance analysis for magnetic resonance electrical impedance tomography (MREIT) using recessed electrodes

Lee, Byung Il; Oh, Seogil; Woo, Eung Je; Lee, Soo Yeol; Cho, Min Hyoung; Kwon, Ohin; Seo, Jin Keun; Lee, June-Yub; Baek, Woon Sik

doi:10.1088/0031-9155/48/13/309

Cited by 79 publications

(51 citation statements)

References 26 publications

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“…There was still substantial non-uniformity of current injection at the boundary of clover, daisy, and spiralshaped electrodes [57] or with inclusion of openings in defibrillation electrodes [45]. A recessed electrode design was also used in a Magnetic Resonance EIT application to avoid artefacts in MR images near the electrodes due to the RF shielding effect of copper electrode [48]. However, this application did not address the issue of current density uniformity on the surface of the imaged object.…”

Section: Current Safety Limits For Applied Low Frequency Currents To mentioning

confidence: 99%

Design of electrodes and current limits for low frequency electrical impedance tomography of the brain

2007

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For the novel application of recording of resistivity changes related to neuronal depolarization in the brain with electrical impedance tomography, optimal recording is with applied currents below 100 Hz, which might cause neural stimulation of skin or underlying brain. The purpose of this work was to develop a method for application of low frequency currents to the scalp, which delivered the maximum current without significant stimulation of skin or underlying brain. We propose a recessed electrode design which enabled current injection with an acceptable skin sensation to be increased from 100 muA using EEG electrodes, to 1 mA in 16 normal volunteers. The effect of current delivered to the brain was assessed with an anatomically realistic finite element model of the adult head. The modelled peak cerebral current density was 0.3 A/m(2), which was 5 to 25-fold less than the threshold for stimulation of the brain estimated from literature review.

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Section: Current Safety Limits For Applied Low Frequency Currents To mentioning

confidence: 99%

Design of electrodes and current limits for low frequency electrical impedance tomography of the brain

2007

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“…We think it suffices here to mention that although SMM appears to be behaving properly even for RoI reconstructions, it is not comparable to the algebraic method proposed in this study in terms of computation time if the same spatial resolution is requested. Lee et al (2003b) have developed a 3D FEM forward solver to be used in MREIT. In their work and also in this study, where phantoms with rectangular prism blocks are used, hexahedral elements are suitable because their corners are compatible with a Cartesian grid.…”

Section: Discussionmentioning

confidence: 99%

“…In the context of MREIT, a Cartesian grid is advantageous because (i) MR systems return images on an equally spaced Cartesian sampling grid and (ii) such a grid is especially handy when operators such as the Laplacian are applied to process B z data. Lee et al (2003b) have used trilinear interpolation functions to approximate the potential field in a hexahedral element. Since the codes that we have developed previously are based on first-order interpolation functions, we have chosen to decompose each hexahedral element further into six tetrahedral elements.…”

Section: Discussionmentioning

confidence: 99%

Algebraic reconstruction for 3D magnetic resonance–electrical impedance tomography (MREIT) using one component of magnetic flux density

Ider

Onart

2004

Physiol. Meas.

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Magnetic resonance-electrical impedance tomography (MREIT) algorithms fall into two categories: those utilizing internal current density and those utilizing only one component of measured magnetic flux density. The latter group of algorithms have the advantage that the object does not have to be rotated in the magnetic resonance imaging (MRI) system. A new algorithm which uses only one component of measured magnetic flux density is developed. In this method, the imaging problem is formulated as the solution of a non-linear matrix equation which is solved iteratively to reconstruct resistivity. Numerical simulations are performed to test the algorithm both for noise-free and noisy cases. The uniqueness of the solution is monitored by looking at the singular value behavior of the matrix and it is shown that at least two current injection profiles are necessary. The method is also modified to handle region-of-interest reconstructions. In particular it is shown that, if the image of a certain xy-slice is sought for, then it suffices to measure the z-component of magnetic flux density up to a distance above and below that slice. The method is robust and has good convergence behavior for the simulation phantoms used.

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“…Each recessed electrode consisted of a tube filled with lowconductivity material and a metal electrode attached on the far side of the tube. The use of recessed electrodes avoids many of the problems caused by conventional metal electrodes, such as MRI signal void around the metal electrodes due to RF signal blocking, and nonuniform current density at the interface between the metal electrodes and the phantom surface (16). The recessed electrodes were also filled with the electrolyte solution and connected with a current-driving circuitry.…”

Section: Methodsmentioning

confidence: 99%

Magnetic resonance electrical impedance tomography at 3 tesla field strength

Lee

Park

et al. 2004

Magnetic Resonance in Med

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Magnetic resonance electrical impedance tomography (MREIT) is a recently developed imaging technique that combines MRI and electrical impedance tomography (EIT). In MREIT, crosssectional electrical conductivity images are reconstructed from the internal magnetic field density data produced inside an electrically conducting object when an electrical current is injected into the object. In this work we present the results of electrical conductivity imaging experiments, and performance evaluations of MREIT in terms of noise characteristics and spatial resolution. The MREIT experiment was performed with a 3.0 Tesla MRI system on a phantom with an inhomogeneous conductivity distribution. We reconstructed the conductivity images in a 128 ؋ 128 matrix format by applying the harmonic B z algorithm to the z-component of the internal magnetic field density data. Since the harmonic B z algorithm uses only a single component of the internal magnetic field data, it was not necessary to rotate the object in the MRI scan. The root mean squared (RMS) errors of the reconstructed images were between 11% and 35% when the injection current was 24 mA. Information about electrical conductivity distribution inside biological tissues is useful for many purposes, such as modeling tissues to investigate action potential propagations, estimating therapeutic current distribution during electrical stimulation, and monitoring physiological functions (1-3). In combinatory studies of functional MRI (fMRI) with other brain mapping modalities, such as EEG and MEG brain mapping, information about conductivity distribution inside the brain is essential for the precise localization of activated regions (4,6). Electrical impedance tomography (EIT) is a conductivity imaging modality in which many surface electrodes are attached to an object to measure the electric potentials produced by injection currents. However, EIT has many drawbacks, including a limited amount of measured data, low sensitivity of the surface voltage to conductivity changes at the region far from the electrodes, and the ill-posedness of the corresponding inverse problem involved in image reconstruction. Recently, a combination of MRI and EIT (MREIT) was introduced as a new conductivity imaging modality (7-9). With MREIT, one can transform the ill-posed conductivity image reconstruction problem into a well-posed one by incorporating the internal data of magnetic flux density distributions measured by an MRI scanner. In previous MREIT experimental studies (10 -12), the biggest problems were object rotations inside the magnet to acquire the three components of the internal magnetic field data, and low SNR of reconstructed images. However, new MREIT reconstruction algorithms were recently introduced, along with phantom imaging results obtained without any object rotations (13)(14)(15).In this work we present some results of MREIT phantom imaging experiments performed with the harmonic B z algorithm and a 3.0 Tesla MRI system. After briefly introducing the fundamental principle of the...

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Three-dimensional forward solver and its performance analysis for magnetic resonance electrical impedance tomography (MREIT) using recessed electrodes

Cited by 79 publications

References 26 publications

Design of electrodes and current limits for low frequency electrical impedance tomography of the brain

Design of electrodes and current limits for low frequency electrical impedance tomography of the brain

Algebraic reconstruction for 3D magnetic resonance–electrical impedance tomography (MREIT) using one component of magnetic flux density

Magnetic resonance electrical impedance tomography at 3 tesla field strength

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