Magnetic resonance-electrical impedance tomography (MR-EIT) was first proposed in 1992. Since then various reconstruction algorithms have been suggested and applied. These algorithms use peripheral voltage measurements and internal current density measurements in different combinations. In this study the problem of MR-EIT is treated as a hyperbolic system of first-order partial differential equations, and three numerical methods are proposed for its solution. This approach is not utilized in any of the algorithms proposed earlier. The numerical solution methods are integration along equipotential surfaces (method of characteristics), integration on a Cartesian grid, and inversion of a system matrix derived by a finite difference formulation. It is shown that if some uniqueness conditions are satisfied, then using at least two injected current patterns, resistivity can be reconstructed apart from a multiplicative constant. This constant can then be identified using a single voltage measurement. The methods proposed are direct, non-iterative, and valid and feasible for 3D reconstructions. They can also be used to easily obtain slice and field-of-view images from a 3D object. 2D simulations are made to illustrate the performance of the algorithms.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1088/0967-3334/24/2/368 | DOI Listing |
Neuroimage
November 2024
Department of Mathematics, Konkuk University, Seoul, 05029, Republic of Korea. Electronic address:
The developed magnetic resonance electrical properties tomography (MREPT) techniques visualize the internal conductivity distribution at Larmor frequency by measuring the B1 transceive phase data. In biological tissues, electrical conductivity is influenced by ion concentrations and mobility. To visualize the anisotropic conductivity tensor of biological tissues, we use the Einstein-Smoluchowski equation, which links the diffusion coefficient to particle mobility.
View Article and Find Full Text PDFJ Neurosci Methods
December 2024
Department of Radiology, Kyung Hee University Hospital at Gangdong, Kyung Hee University College of Medicine, Seoul, Gangdong-Gu, South Korea. Electronic address:
Background: Although blood oxygen level-dependent (BOLD) functional MRI (fMRI) is a standard method, major BOLD signals primarily originate from intravascular sources. Magnetic resonance electrical properties tomography (MREPT)-based fMRI signals may provide additional insights into electrical activity caused by alterations in ion concentrations and mobilities.
Purpose: This study aimed to investigate the neuronal response of conductivity during visual stimulation and compare it with BOLD.
Phys Eng Sci Med
December 2024
Neuroscience Research Australia, 139 Barker St, Randwick, NSW, 2031, Australia.
Theory and modelling suggest that detection of neuronal activity may be feasible using phase sensitive MRI methods. Successful detection of neuronal activity both in vitro and in vivo has been described while others have reported negative results. Magnetic resonance electrical properties tomography may be a route by which signal changes can be identified.
View Article and Find Full Text PDFJ Magn Reson Imaging
August 2024
Neuroscience Research Australia, Sydney, New South Wales, Australia.
Background: How the biophysics of electrical conductivity measures relate to brain activity is poorly understood. The sedative, ethanol, reduces metabolic activity but its impact on brain electrical conductivity is unknown.
Purpose: To investigate whether ethanol reduces brain electrical tissue conductivity.
Magnetic resonance imaging (MRI) can extract the tissue conductivity values from in vivo data using the so-called phase-based magnetic resonance electrical properties tomography (MR-EPT). However, this procedure suffers from noise amplification caused by the use of the Laplacian operator. To counter this issue, we propose a novel preprocessing denoiser for magnetic resonance transceive phase images, operating in an unsupervised manner.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!