Electrical Conductivity Of Biological Tissues Research Articles

Intelligent Electrometric Device for Dental Caries Diagnosis

The article deals with the development of a medical device for high-precision measurement and automatic diagnosis of dental caries stage. The analysis of the composition and characteristics of tooth hard tissues, being the cause of caries and its development, is given. It has been established that the main cause of the carious process is the attack of acid-forming bacteria on tooth enamel. It is shown that the most promising method for caries diagnosis is the electrometric method, which consists in measuring electrical conductivity of the tooth hard tissue electrolyte. Conventional devices for the electrometric method implementation are described, using the direct current through the biological tissue of the tooth, but not taking into account the electrochemical features of the current flow. An electrochemical interpretation of the current flow through biological tissues and two electrodes with a polarity switch of these electrodes was performed, which makes it possible to exclude the effect of polarization of biological tissue and electrodes both for teeth in vivo and in vitro. An equivalent diagram of the current flow through the biological tissue is given, which value can reveal the stage of the carious process: intact enamel, pre-carious state, initial, superficial, medium and deep caries. The use of two current-carrying electrodes for measuring the electrical conductivity of biological tissues is considered: an active electrode made of stainless steel using a 10% solution of CaCl2 and a passive electrode also made of stainless steel and using an electrolyte of the biological tissue of a tooth (simulated by a 0.9% solution of NaCl). A comparative assessment of the tooth biological tissue electrolyte electrical conductivity and electrical conductivity of the active and passive electrode electrolytes was performed to assess the error of the electrometric method. A high-precision intelligent electrometric device (protected by a patent for an invention) has been developed, which allows automatic carious process stage determination by the value of the tooth biological tissue electrical conductivity; the operation of this device is described.

МОДЕЛЮВАННЯ АНІЗОТРОПІЇ ПИТОМОЇ ЕЛЕКТРОПРОВІДНОСТІ БІОЛОГІЧНОЇ ТКАНИНИ, ЯКА ВИНИКАЄ ЗА ЛОКАЛЬНОГО СТИСКАННЯ ЕЛЕКТРОДАМИ ДЛЯ БІПОЛЯРНОГО ЗВАРЮВАННЯ

Current publications on bipolar welding use the electrical characteristics of uncompressed biological tissue. This reduces the accuracy of calculating the distribution of the density of the flowing currents and the strength of the electric fields in the zone of the fabric to be welded when it is squeezed. The aim of the work is to show a methodology for calculating the change in the specific electrical conductivity of biological tissue under local compression by electrodes and the effect of this factor on the results of modeling electrical processes of biological welding. A geometric interpretation of the change in the electrical conductivity of the pig's heart muscle when squeezed by bipolar welding electrodes in relative units is proposed. The principle of similarity of the geometric parameters of the physical experiment and the graphic model of COMSOL multyphysics is used, as a result of which the dependences of the three main geometric parameters of the model on the magnitude of the relative compression are determined. The method of successive approximations of the values of the total electrical resistance of biological tissue in a physical experiment at frequencies of 0,3, 30, and 300 kHz and the calculated resistances on the model with a change in the basic geometric parameters of specific electrical conductivity was used. A model of bipolar welding of biological tissues is obtained, which takes into account the anisotropy factor of the electrical conductivity of biological tissue under compression. Some results of investigations of the regularities of the current flow in the tissue, taking into account the arising anisotropy, are presented. References 12, figures 5, tables 4.

Study of change in specific electrical conductivity of biological tissues as a result of local compression by electrodes in bipolar welding

The Paton Welding Journal, 2021, №01. International Scientific-Technical and Production Journal «The Paton Welding Journal» «The Paton Welding Journal» has been published monthly since 2000 in English, ISSN 0957-798X. «The Paton Welding Journal» is a cover-to-cover English translation of the «Avtomaticheskaya Svarka» (Automatic Welding) journal. The «Avtomaticheskaya Svarka» journal has been published monthly since 1948 in Russian, ISSN 005-111X.

Дослідження зміни питомої електропровідності біологічних тканин в результаті локального стискання електродами при біполярному зварюванні

Дослідження зміни питомої електропровідності біологічних тканин в результаті локального стискання електродами при біполярному зварюванні

Mathematical model of electrical conductivity of biological tissues based on ion electrodiffusion equations

A method for modeling of the electrical properties of biological tissues is introduced. It is based on the division of tissue in accordance with the geometry of living cells and the solution of the Nernst-Planck electrodiffusion equation for the calculation of ion currents between individual cells.

Low-frequency dominant electrical conductivity imaging of in vivo human brain using high-frequency conductivity at Larmor-frequency and spherical mean diffusivity without external injection current

Diffusion weighted imaging based on random Brownian motion of water molecules within a voxel provides information on the micro-structure of biological tissues through water molecule diffusivity. As the electrical conductivity is primarily determined by the concentration and mobility of ionic charge carriers, the macroscopic electrical conductivity of biological tissues is also related to the diffusion of electrical ions. This paper aims to investigate the low-frequency electrical conductivity by relying on a pre-defined biological model that separates the brain into the intracellular (restricted) and extracellular (hindered) compartments. The proposed method uses B1 mapping technique, which provides a high-frequency conductivity distribution at Larmor frequency, and the spherical mean technique, which directly estimates the microscopic tissue structure based on the water molecule diffusivity and neurite orientation distribution. The total extracellular ion concentration, which is separated from the high-frequency conductivity, is recovered using the estimated diffusivity parameters and volume fraction in each compartment. We propose a method to reconstruct the low-frequency dominant conductivity tensor by taking into consideration the extracted extracellular diffusion tensor map and the reconstructed electrical parameters. To demonstrate the reliability of the proposed method, we conducted two phantom experiments. The first one used a cylindrical acrylic cage filled with an agar in the background region and four anomalies for the effect of ion concentration on the electrical conductivity. The other experiment, in which the effect of ion mobility on the conductivity was verified, used cell-like materials with thin insulating membranes suspended in an electrolyte. Animal and human brain experiments were conducted to visualize the low-frequency dominant conductivity tensor images. The proposed method using a conventional MRI scanner can predict the internal current density map in the brain without directly injected external currents.

Combined Planar Magnetic Induction Tomography for Local Detection of Intracranial Hemorrhage

Magnetic induction tomography (MIT) is a contactless and harmless technique for intracranial hemorrhage detection. Due to the low electrical conductivity of biological tissues, the phase shift signals are very weak. To improve the sensitivity of the phase shift signals and achieve the local detection of intracranial hemorrhage, a planar MIT method is proposed. The coil parameters were optimized based on the sensitivity analysis. The performance of single planar and combined planar MITs was investigated with a 3-D anatomical head model. Two evaluation indexes, correlation coefficient <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text {cc}_{\text {ima}}$ </tex-math></inline-formula> and localization error <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L_{e}$ </tex-math></inline-formula> , were introduced to evaluate the imaging quality. Finally, experimental tests were carried out to verify the ability of combined planar MIT for hemorrhage detection. The simulation results indicate that the combined planar MIT has better imaging quality and distinguishing ability for the hemorrhage with different deviation positions, depths, and volumes. For the 8-mL hemorrhage, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text {cc}_{\text {ima}}$ </tex-math></inline-formula> of combined planar MIT is increased by 40.2%, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L_{e}$ </tex-math></inline-formula> is reduced by 77.8% compared with single planar MIT. The experimental results indicate that a 16-mL hemorrhage can be reconstructed, and the change in position can be distinguished by combined planar MIT. The study demonstrates that combined planar MIT is a feasible method for hemorrhage detection. The proposed method provides a portable solution for local detection of intracranial hemorrhage and promotes the practical application of MIT in biomedical imaging.

Data acquisition system for MAET with magnetic field measurements

Magneto-acousto-electrical tomography (MAET) is an imaging modality to image the electrical conductivity of biological tissues. It is based on electrical current induction by using ultrasound under a static magnetic field. The aim of this study is to develop a data acquisition system for MAET based on magnetic field measurements. The static magnetic field is generated by six permanent neodymium magnets. A 16-element linear phased array (LPA) transducer is utilized to generate acoustic pressure waves inside the phantom. To measure the magnetic field intensity generated by the induced currents, contactless receiver sensors are developed using two similar disk multiple layer coils, which are Helmholtz coil sensor. Physical properties and electrical characteristics of the sensors are assessed. A two-stage cascaded amplifier is designed and utilized in the receiving system. The gain of the cascaded amplifier at 1 MHz is adjusted to be 96 dB. Experimental studies are conducted with two different phantoms, having 3 S m−1 and 58 S m−1 electrical conductivity, respectively. A-scan and B-scan images of phantoms are obtained with the LPA transducer. Comparison of the ultrasound (A-scan) and MAET signals reveals that 3 S m−1 conductive inhomogeneity can be detected with this data acquisition system. Furthermore, the front and rear interfaces of an inhomogeneity () of 58 S m−1 conductivity are detectable.

Extracellular Total Electrolyte Concentration Imaging for Electrical Brain Stimulation (EBS)

Techniques for electrical brain stimulation (EBS), in which weak electrical stimulation is applied to the brain, have been extensively studied in various therapeutic brain functional applications. The extracellular fluid in the brain is a complex electrolyte that is composed of different types of ions, such as sodium (Na+), potassium (K+), and calcium (Ca+). Abnormal levels of electrolytes can cause a variety of pathological disorders. In this paper, we present a novel technique to visualize the total electrolyte concentration in the extracellular compartment of biological tissues. The electrical conductivity of biological tissues can be expressed as a product of the concentration and the mobility of the ions. Magnetic resonance electrical impedance tomography (MREIT) investigates the electrical properties in a region of interest (ROI) at low frequencies (below 1 kHz) by injecting currents into the brain region. Combining with diffusion tensor MRI (DT-MRI), we analyze the relation between the concentration of ions and the electrical properties extracted from the magnetic flux density measurements using the MREIT technique. By measuring the magnetic flux density induced by EBS, we propose a fast non-iterative technique to visualize the total extracellular electrolyte concentration (EEC), which is a fundamental component of the conductivity. The proposed technique directly recovers the total EEC distribution associated with the water transport mobility tensor.

Image Reconstruction in Magnetoacoustic Tomography With Magnetic Induction With Variable Sound Speeds.

Acoustic and electrical characteristics of biological tissue are important factors in magnetoacoustic tomography with magnetic induction (MAT-MI). Acoustic inhomogeneity significantly affects the propagations of sound waves. Differences in sound speed lead to distortions of the sound sources in the reconstruction process. The objective of this study is to develop a novel algorithm to reconstruct the sound source distribution in an acoustically inhomogeneous medium. The proposed algorithm is developed on the basis of the finite-difference time-domain method and time-reversal acoustic theory; it combines the relationship among symmetrical transducers with the back-projection algorithm. An acoustically inhomogeneous model with different regions of variable sound speeds is established to validate the proposed algorithm. From the data collected by a rotated focused transducer, first, the sound speed distribution is reconstructed, and then, the sound sources of the model are reconstructed. The reconstructed sound sources are obviously distorted when the speed differences are not considered. In contrast, the proposed algorithm yields reconstructed sound sources that are consistent with the model in terms of shape and size. Thus, the proposed algorithm is capable of accurately reconstructing the acoustic sources distribution in an acoustically inhomogeneous medium. This method provides a solution reducing the influence of acoustic inhomogeneity in MAT-MI. The distributions of sound speed can be obtained during the process of reconstructing the sound source. Consequently, the imaging of the acoustic speed and the electrical conductivity of biological tissues can be implemented simultaneously in MAT-MI.

Asymptotic decay under nonlinear and noncoercive dissipative effects for electrical conduction in biological tissues

We consider a nonlinear model for electrical conduction in biological tissues. The nonlinearity appears in the interface condition prescribed on the cell membrane. The purpose of this paper is proving asymptotic convergence for large times to a periodic solution when time-periodic boundary data are assigned. The novelty here is that we allow the nonlinearity to be noncoercive. We consider both the homogenized and the non-homogenized version of the problem.

A method of the forward problem for magneto-acousto-electrical tomography.

Magneto-Acousto-Electrical Tomography (MAET) is a novel hybrid modality that can provide a high spatial resolution in determining the electrical conductivity of biological tissue. The present paper primarily analyzes the existing basic formulations with the MAET, derives the propagation equations of the sound wave when the mass density of the biological tissues are variable, and then solves the respective current density and potential difference in an inhomogeneous and homogeneous density medium based on the sound speeds obtained. Finally, numerical simulations are performed. As is shown, sound waves affect magneto-acousto-electrical tomography while varying the biological tissue mass density.

Exponential decay for a nonlinear model for electrical conduction in biological tissues

We study the asymptotic convergence to a periodic steady state of the solution of a nonlinear system of equations with periodic boundary data modeling electrical conduction in biological tissues, both in the microscopic and in the homogenized version. Such model keeps into account the resistive behavior of the intracellular and extracellular domains and also the capacitive/resistive behavior of the lipidic cellular membrane.The rate of convergence is analyzed and the systems of equations satisfied by the asymptotic limits are exhibited, when the resistive behavior of the membrane is described by a strictly monotone and coercive nonlinear function.The special case of homogeneous boundary conditions is also investigated, where the coercivity assumption can be relaxed.

Uncertainty Analysis in Transcranial Magnetic Stimulation Using Nonintrusive Polynomial Chaos Expansion

We propose a framework of nonintrusive polynomial chaos methods for transcranial magnetic stimulation (TMS) to investigate the influence of the uncertainty in the electrical conductivity of biological tissues on the induced electric field. The conductivities of three different tissues, namely, cerebrospinal fluid, gray matter (GM), and white matter, are modeled as uniformly distributed random variables. The investigations are performed on a simplified model of a cortical gyrus/sulcus structure. The statistical moments are calculated by means of a generalized polynomial chaos expansion using a regression and cubature approach. Furthermore, the results are compared with the solutions obtained by stochastic collocation. The accuracy of the methods to predict random field distributions was compared by applying different grids and orders of expansion. An investigation on the convergence of the expansion showed that in the present framework, an order 4 expansion is sufficient to determine results with an error of <;1%. The results indicate a major influence of the uncertainty in electrical conductivity on the induced electric field. The standard deviation exceeds values of 20%-40% of the mean induced electric field in the GM. A sensitivity analysis revealed that the uncertainty in electrical conductivity of the GM affects the solution the most. This paper outlines the importance of exact knowledge of the electrical conductivities in TMS in order to provide reliable numerical predictions of the induced electric field. Furthermore, it outlines the performance and the applicability of spectral methods in the framework of TMS for future studies.

Modelling of electromagnetic field distribution for optimising electrode configurations in liver MR‐based electrical impedance tomography

In-vivo electromagnetic field distributions of biological systems can be imaged from the measured magnetic flux density of magnetic resonance-based electrical impedance tomography (MREIT), which was induced by the externally injected current through a pair of electrodes. Since the electromagnetic field is affected by the injected current and electrical conductivity of biological tissues, the electrode type and position are important factors for determining the voltage and current density distribution. Using a three-dimensional finite element model, the current pathway and electric field distribution to optimise the electrode configurations in liver MREIT are estimated.

Magnetoacoustic tomography with magnetic induction for high‐resolution bioimepedance imaging through vector source reconstruction under the static field of MRI magnet

Magnetoacoustic tomography with magnetic induction (MAT-MI) is an imaging modality to reconstruct the electrical conductivity of biological tissue based on the acoustic measurements of Lorentz force induced tissue vibration. This study presents the feasibility of the authors' new MAT-MI system and vector source imaging algorithm to perform a complete reconstruction of the conductivity distribution of real biological tissues with ultrasound spatial resolution. In the present study, using ultrasound beamformation, imaging point spread functions are designed to reconstruct the induced vector source in the object which is used to estimate the object conductivity distribution. Both numerical studies and phantom experiments are performed to demonstrate the merits of the proposed method. Also, through the numerical simulations, the full width half maximum of the imaging point spread function is calculated to estimate of the spatial resolution. The tissue phantom experiments are performed with a MAT-MI imaging system in the static field of a 9.4 T magnetic resonance imaging magnet. The image reconstruction through vector beamformation in the numerical and experimental studies gives a reliable estimate of the conductivity distribution in the object with a ∼ 1.5 mm spatial resolution corresponding to the imaging system frequency of 500 kHz ultrasound. In addition, the experiment results suggest that MAT-MI under high static magnetic field environment is able to reconstruct images of tissue-mimicking gel phantoms and real tissue samples with reliable conductivity contrast. The results demonstrate that MAT-MI is able to image the electrical conductivity properties of biological tissues with better than 2 mm spatial resolution at 500 kHz, and the imaging with MAT-MI under a high static magnetic field environment is able to provide improved imaging contrast for biological tissue conductivity reconstruction.

Lorentz force electrical impedance tomography

This article describes a method called Lorentz Force Electrical Impedance Tomography. The electrical conductivity of biological tissues can be measured through their sonication in a magnetic field: the vibration of the tissues inside the field induces an electrical current by Lorentz force. This current, detected by electrodes placed around the sample, is proportional to the ultrasonic pressure, to the strength of the magnetic field and to the electrical conductivity gradient along the acoustic axis. By focusing at different places inside the sample, a map of the electrical conductivity gradient can be established. In this study, experiments were conducted on a gelatin phantom and on a beef sample, successively placed in a 300mT magnetic field and sonicated with an ultrasonic transducer focused at 21cm emitting 500kHz bursts. Although all interfaces are not visible, in this exploratory study a good correlation is observed between the electrical conductivity image and the ultrasonic image. This method offers an alternative to detecting pathologies invisible to standard ultrasonography.

A hierarchy of models for the electrical conduction in biological tissues via two-scale convergence: the nonlinear case

We study a hierarchy of electrical conduction problems in biological tissues. These problems are set in a finely mixed periodic medium, and the unknown electric potentials solve standard elliptic equations set in different conductive regions (the intracellular and extracellular spaces), separated by an interface (the cell membranes), which exhibits a capacitive and a nonlinear conductive behavior, due to its biochemical structure. Different scalings in the interface condition correspond to different problems in the hierarchy. As the spatial period of the medium goes to zero, the problems approach a homogenization limit depending on the initial scaling. The macroscopic models are obtained by using the technique of two-scale convergence.

Detection of temperature distribution via recovering electrical conductivity in MREIT

In radiofrequency (RF) ablation or hyperthermia, internal temperature measurements and tissue property imaging are important to control their outputs and assess the treatment effect. Recently, magnetic resonance electrical impedance tomography (MREIT), as a non-invasive imaging method of internal conductivity distribution using an MR scanner, has been developed. Its reconstruction algorithm uses measured magnetic flux density induced by injected currents. The MREIT technique has the potential to visualize electrical conductivity of tissue with high spatial resolution and measure relative conductivity variation according to the internal temperature change based on the fact that the electrical conductivity of biological tissues is sensitive to the internal temperature distribution. In this paper, we propose a method to provide a non-invasive alternative to monitor the internal temperature distribution by recovering the electrical conductivity distribution using the MREIT technique. To validate the proposed method, we design a phantom with saline solution and a thin transparency film in a form of a hollow cylinder with holes to create anomalies with different electrical and thermal conductivities controlled by morphological structure. We first prove the temperature maps with respect to spatial and time resolution by solving the thermal conductivity partial differential equation with the real phantom experimental environment. The measured magnetic flux density and the reconstructed conductivity distributions using the phantom experiments were compared to the simulated temperature distribution. The relative temperature variation of two testing objects with respect to the background saline was determined by the relative conductivity contrast ratio (rCCR,%). The relation between the temperature and conductivity measurements using MREIT was approximately linear with better accuracy than 0.22 °C.

Multiscale analysis of diffusion processes in composite media

The goal of this paper is to present some homogenization results for a nonlinear problem arising in the modeling of diffusion in a periodic structure formed by two media with different properties, separated by an active interface. Our setting is relevant for modeling heat diffusion in composite materials with imperfect interfaces or electrical conduction in biological tissues. The approach we follow is based on the periodic unfolding method, which allows us to deal with general media.