Conductivity Of Biological Tissues Research Articles

Ignition process of the plasma scalpel in normal saline: Numerical simulation and comparison to experiment

In this paper, the ignition process of the plasma scalpel is characterized by means of numerical simulation, shadowgraphy, and voltage–current measurements. The ignition process involves two phases: the pre-breakdown phase and the breakdown phase. Our study shows that in the pre-breakdown phase, the vapor layer is first generated around the corners of the active electrode and then gradually extends to cover the entire active electrode. Once the active electrode is fully covered by the vapor layer, the electric field reaches a maximum of 7.3 × 106 V m−1, which can cause discharge in the vapor layer. At this moment, the thickness of the vapor layer is approximately 100 μm. In the breakdown phase, the maximum electron density reaches 1018–1019 m−3. The plasma dissipates about 60% of the total power which is up to 125 W, thus enabling efficient cutting. In addition, we simulate the discharge characteristics of cutting various biological tissues. The results show that under the same voltage level, the higher the conductivity of biological tissues, the greater the discharge current. The biological tissues act as ballast resistors in equivalent circuits.

Four-Electrode System for the Measurement of Biological Tissue Conductivity at ELF and ULF

Four-Electrode System for the Measurement of Biological Tissue Conductivity at ELF and ULF

Liquid metals enabled advanced cryobiology: development and perspectives

Cryosurgery and cryopreservation, as two important categories in cryobiology, have been impeded by the poor thermal conductivity of biological tissues or specimens. To improve this, diverse adjuvants, e.g., carbon-based materials, metallic nanoparticles, metallic oxide nanoparticles, etc ., have been exploited to improve the heat transfer in heat-targeted regions to increase the tumor elimination efficiency as well as the post-thaw viability of cryopreserved specimens. Nevertheless, these materials suffer poor thermal conductivities, controversial biosafety problems, and high expense. Gallium and its alloys, as a class of room-temperature liquid metals (LMs), have been widely studied in the past decade for their low melting point, minor toxicity, outstanding transformability, and conductivity. Integrated with these superior properties, they have been widely applied in multiple fields, such as thermal management, flexible electronics, and soft robotics. Recently, our laboratory has been devoted to fusing LMs with cryobiology and has made a series of progress. In this article, we will first briefly introduce preparation pathways to LM-based functional nanomaterials and composites. Then, how these materials realize improvement in biological heat transfer will be presented, followed by a discussion about the biosafety of these materials, which is an essential concern for the cryobiological field. Recent studies employing LMs in advanced cryosurgery and cryopreservation will also be highlighted. The present challenges and prospects of LMs towards further development in cryobiology will be put forward to point out the possible research direction.

First order chemical reaction response in mixed convective Falkner-Skan Sutterby fluid with Cattaneo-Christov heat and mass flux model

The complex phenomenon of heat transfer plays a pivotal role in a broad spectrum of mechanical and industrial applications, ranging from space and nuclear reactor cooling to medicinal applications like magnetic drug targeting, energy production, heat conduction in biological tissues, among others. Historically, Fourier's law of heat conduction has served as a predictive model for heat transfer in numerous practical scenarios. However, this model's limitation is its generation of a parabolic energy expression, implying an immediate influence on the system by any initial disturbance. Numerous researchers have attempted to address this issue, leading to the Cattaneo's modification to Fourier's law, which introduces a relaxation time for heat flux, meaning the time needed to achieve stable heat conduction following the imposition of a temperature gradient. Christov later tweaked this model into a material invariant version, integrating the upper-connected derivative from the Oldroyd model. These models, now collectively termed as the Cattaneo-Christov (CC) model, form the core of the present study. In this study, we explore the mixed convective MHD Falkner-Skan Suttberby nanofluid flow towards a wedge surface, in the presence of a mixed convection. A two-phase nanofluid based C–C model is utilized to apply the nano-concept. The nonlinear equation system is solved using the bvp4c technique in MATLAB. The effects of various parameters including the magnetic field strength, wedge angle, nanoparticle volume fraction, and Prandtl number on the velocity and temperature profiles are discussed. The results show that the velocity increases with the magnetic parameter, wedge angle, and nanoparticle fraction, while the temperature decreases or increases depending on the suction or injection conditions. The Nusselt numbers and solutal transport rate are also reported for different parameter values. Overall, the study demonstrates that the non-Fourier C–C model yields significantly different solutal and heat transfer characteristics compared to the classical Fourier law. The results provide useful insights into the heat transfer behavior of nanofluids in stagnation point flows over geometries with complex shapes, which have practical applications in areas such as aerodynamics and thermal management of electronic devices.

An Adaptative Savitzky-Golay Kernel for Laplacian Estimation in Magnetic Resonance Electrical Property Tomography.

Magnetic Resonance electrical property tomography (MR-EPT) is a non-invasive imaging modality that reconstructs the living biological tissue's conductivity σ and εr permittivity using spatial derivatives of the measured RF field, also termed B1 data, in a magnetic resonance imaging system. The spatial derivative operator, particularly the Laplacian, amplifies the noise in the reconstructed electrical property (EP) maps, hence decreasing accuracy and increasing boundary artifacts. We propose a novel adaptative convolution kernel for generating numerical derivatives based on 3D Savitzky-Golay (SG) filters and local segmentation in a magnitude image. In comparison to typical SG kernel, the proposed kernel allows arbitrary shapes and sizes to vary with local tissue. It provides an automatic trade-off between noise and resolution, thereby significantly enhancing reconstruction accuracy and eliminating boundary artifacts.

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.

Capacitive Coupler for Wireless Power Transfer to Intravascular Implant Devices

In this letter, we analyze a capacitive coupler for wireless power transfer (WPT) to intravascular implant devices using a stent that contacts the vessel wall for vasodilation as a power receiver. We focus on the effect of conductivity on the transfer efficiency of capacitive WPT and verify the relationship between the maximum transfer efficiency and conductivity based on an equivalent circuit, including arteries and body tissues. We also measure the permittivity and conductivity of biological tissues and explain the appropriate measurement method for each biological tissue. Then, we design the electrode size of the capacitive coupler, and the experimental results of CWPT are presented. We can transfer power into blood vessels through a subcutaneous fatty skin with an efficiency of 35% at 434 MHz, which is the ISM band.

Distinctive ionic transport of freshly excised human epileptogenic brain tissue.

Epileptogenic lesions have higher concentrations of sodium than does normal brain tissue. Such lesions are palpably recognized by a surgeon and then excised in order to eliminate epileptic seizures with their associated abnormal electrical behavior. Here, we study the frequency-dependent electrical conductivities of lesion-laden tissues excised from the brains of epilepsy patients. The low-frequency (<1000 Hz) conductivity of biological tissue primarily probes extracellular solvated sodium-cations traveling parallel to membranes within regions bounded by blockages. This conductivity rises monotonically toward saturation as the frequency surpasses the rate with which diffusing solvated sodium cations encounter blockages. We find that saturation occurs at dramatically higher frequencies in excised brain tissue containing epileptogenic lesions than it does in normal brain tissue. By contrast, such an effect is not reported for tumors embedded in other excised biological tissue. All told, epileptogenic lesions generate frequency-dependent conductivities that differ qualitatively from those of both normal brain tissues and tumors.

The study on the inverse problem of applied current thermoacoustic imaging based on generative adversarial network

Applied Current Thermoacoustic Imaging (ACTAI) is a new imaging method which combines electromagnetic excitation with ultrasound imaging, and takes ultrasonic signal as medium and biological tissue conductivity as detection target. Taking the high contrast advantage of Electrical Impedance Tomography (EIT) and high resolution advantage of ultrasound imaging, ACTAI has broad application prospects in the field of biomedical imaging. Although ACTAI has high excitation efficiency and strong detectable Signal-to-Noise Ratio, yet while under low frequency electromagnetic excitation, it is still a big challenge to reconstruct a high-resolution image of target conductivity. This paper proposes a new method for reconstructing conductivity based on Generative Adversarial Network, and it consists of three main steps: firstly, use Wiener filtering deconvolution to restore the electrical signal output by the ultrasonic probe to a real acoustic signal. Then obtain the initial acoustic source image with filtered backprojection technology. Finally, match the conductivity image with the initial sound source image, which are used as training samples for generating the adversarial network to establish a deep learning model for conductivity reconstruction. After theoretical analysis and simulation research, it is found that by introducing machine learning, the new method can dig out the inverse problem solving model contained in the data, which further reconstruct a high-resolution conductivity image and has strong anti-interference characteristics. The new method provides a new way to solve the problem of conductivity reconstruction in Applied Current Thermoacoustic Imaging.

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.

Thermal Conductivity Measurement of Anisotropic Biological Tissue In Vitro

The accurate determination of the thermal conductivity of biological tissues has implications on the success of cryosurgical/hyperthermia treatments. In light of the evident anisotropy in some biological tissues, a new modified stepwise transient method was proposed to simultaneously measure the transverse and longitudinal thermal conductivities of anisotropic biological tissues. The physical and mathematical models were established, and the analytical solution was derived. Sensitivity analysis and experimental simulation were performed to determine the feasibility and measurement accuracy of simultaneously measuring the transverse and longitudinal thermal conductivities. The experimental system was set up, and its measurement accuracy was verified by measuring the thermal conductivity of a reference standard material. The thermal conductivities of the pork tenderloin and bovine muscles were measured using the traditional 1D and proposed methods, respectively, at different temperatures. Results indicate that the thermal conductivities of the bovine muscle are lower than those of the pork tenderloin muscle, whereas the bovine muscle was determined to exhibit stronger anisotropy than the pork tenderloin muscle. Moreover, the longitudinal thermal conductivity is larger than the transverse thermal conductivity for the two tissues and all thermal conductivities increase with the increase in temperature. Compared with the traditional 1D method, results obtained by the proposed method are slightly higher although the relative deviation is below 5 %.

A revised approach for an exact analytical solution for thermal response in biological tissues significant in therapeutic treatments

The genesis of the present research paper is to develop a revised exact analytical solution of thermal profile of 1-D Pennes’ bioheat equation (PBHE) for living tissues influenced in thermal therapeutic treatments. In order to illustrate the temperature distribution in living tissue both Fourier and non-Fourier model of 1-D PBHE has been solved by ‘Separation of variables’ technique. Till date most of the research works have been carried out with the constant initial steady temperature of tissue which is not at all relevant for the biological body due to its nonhomogeneous living cells. There should be a temperature variation in the body before the therapeutic treatment. Therefore, a coupled heat transfer in skin surface before therapeutic heating must be taken account for establishment of exact temperature propagation. This approach has not yet been considered in any research work. In this work, an initial condition for solving governing differential equation of heat conduction in biological tissues has been represented as a function of spatial coordinate. In a few research work, initial temperature distribution with PBHE has been coupled in such a way that it eliminates metabolic heat generation. The study has been devoted to establish the comparison of thermal profile between present approach and published theoretical approach for particular initial and boundary conditions inflicted in this investigation. It has been studied that maximum temperature difference of existing approach for Fourier temperature distribution is 19.6% while in case of non-Fourier, it is 52.8%. We have validated our present analysis with experimental results and it has been observed that the temperature response based on the spatial dependent variable initial condition matches more accurately than other approaches.

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.