Electrical Properties Of Tissues Research Articles

Electrical Impedance Spectroscopy: A Tool for Determining the Harvesting Time of Olive Fruit

The harvesting time of olive (Olea europaea L.) fruit, which significantly affects the characteristics of virgin olive oil, is mainly determined empirically based on the fruit’s skin color. Developing objective methods such as electrical impedance spectroscopy (EIS) for assessing ripeness is essential. This study aimed to explore the potential of EIS as a rapid and objective technique for detecting the harvesting time of olives. Olive fruits from two varieties, ‘Picholine’ and ‘Buža momjanska’, were harvested in two periods and sorted into four color groups. EIS was applied to each color group to establish a relationship between fruit color and electrochemical properties. The distance of the coordinate at the top of the circular arc of the Cole–Cole plot from the origin (LTO) indicated tissue degradation. The LTO values varied depending on the olive variety, fruit color, and harvest date. The LTO values decreased from green to black fruits in both varieties, indicating textural changes in the olive fruit tissue. This study contributes to the knowledge and understanding of the electrical properties of olive fruit tissue during ripening. EIS shows potential as an innovative tool for determining the harvesting time of olives and for ‘in-field’ olive ripeness assessment.

Stochastic Analysis of Epithelial/Absorbed Power Density in Multilayered Planar Skin Model With Uncertain Tissue Electric Properties

AbstractStochastic analysis of the absorbed power density (APD) on skin surface exposed to radiation of halfwave dipole at 10, 30 and 90 GHz and for different antenna‐body distances is presented. Skin tissue is modeled as a half‐space consisting of one layer (skin) or three layers (skin, fat and muscle) whose permittivities and conductivities are uncertain. Deterministic part is based on numerical solution of Pocklington equation via Galerkin Bubnov Indirect Boundary Element method (GB‐IBEM) and numerical integration of the corresponding field integrals. Uncertainty from tissue electric parameters is propagated to APD via non‐intrusive Stochastic Collocation method (SCM) in order to compute stochastic moments of APD. For 1‐layered model APD stochastic moments are computed with 3 deterministic simulations. On the other hand APD mean and variance for 3 layered model are successfully computed with 13 deterministic simulations while skewness and kurtosis require 85 deterministic simulations. The ratio of APD standard deviation and mean decreases with frequency thus indicating that the uncertainty in the tissue electric properties has smaller effect on APD uncertainty at higher frequencies. Finally, sensitivity analysis carried out for both 1‐layered and 3‐layered models indicates the same conclusions. At 10 GHz skin permittivity and conductivity are the two most important parameters. However, as frequency increases the impact of skin conductivity prevails. This indicates that in frequency range 10–90 GHz the APD uncertainty quantification and sensitivity analysis can be carried out by using only 2‐dimensional stochastic model.

90 - Changes in the Microstructure and Electrical Properties of Liver Tissue by Ionizing Radiation

90 - Changes in the Microstructure and Electrical Properties of Liver Tissue by Ionizing Radiation

Ex vivo electrical bioimpedance measurements and Cole modelling on the porcine colon and rectum

Different pathological changes in the large intestine wall, associated with the development of different chronic diseases, including colorectal cancer, could be reflected in electrical bioimpedance readings. Thickness and composition of the mucus bilayer covering it in the luminal side, abundance of bacteria of the intestinal microbiota, the permeability of the epithelium and inflammation are some of these. However, scientific literature on electrical passive properties of the large intestine is scarce. In this study, complex impedance measurements at 8 frequencies were carried out on 6 specimens of porcine colorectal tissue, within half ab hour post-mortem, obtained from a local abattoir. For 5 different distances, measured proximally from the border of the anus, 3 readings were taken at 3 different points with a tetrapolar probe. The results show 2 different dielectric dispersions in the α and β regions and it seems that there is a relationship between the values of resistivities and the thickness of the wall. Also, parameter values both for the Cole and the geometrical models are given. Another set of electrical bioimpedance readings was carried out in order to assess the effect of the mucus layer on electrical properties of the tissue. It seems that these layers are related to the low frequency dispersion. Finally, electrical passive properties of porcine colorectal tissue, reported in this work, give reference values and behaviour patterns that could be applied for further research in human medicine, based on bioimpedance measurements.

Bioimpedance formalism: A new approach for accessing the health status of cell and tissues

This manuscript describes a novel methodology for studying relaxation dynamics in tissues and cells using characteristic frequency of bioimpedance spectroscopy measurements. The Bioimpedance Formalism allows for the simultaneous study of bioelectrical parameters in the frequency and time domains, providing insight into possible relaxation processes occurring in the tissue or cell of interest. Results from the Cole-Cole analysis showed no multiple relaxation processes associated with heterogeneity, with a visible age group separation in males compared with females. The study of the relaxation dynamic in the time domain revealed that the β parameter can be used to analyse the charge carriers in tissues, cells, or cancer cells, potentially leading to new diagnostic and therapeutic approaches for cancer and other diseases. Overall, this approach presents a promising area of research for gaining insights into the electrical properties of tissues and cells using bioimpedance methods.

A Time-varying Equivalent Circuit Modeling and Measuring Approach for Intracardiac Communication in Leadless Pacemakers.

Intracardiac wireless communication is crucial for the development of multi-chamber leadless cardiac pacemakers (LCP). However, the time-varying characteristics of intracardiac channel pose major challenges. As such, mastering the dynamic conduction properties of the intracardiac channel and modeling the equivalent time-varying channel are imperative for realizing LCP multi-chamber pacing. In this paper, we present a limiting volume variational approach based on the electrical properties of cardiac tissues and trends in chamber volume variation. This approach was used to establish a quasi-static and a continuous time-varying equivalent circuit model of an intracardiac channel. An equivalence analysis was conducted on the model, and a discrete time-varying equivalent circuit phantom grounded on the cardiac cycle was subsequently established. Moreover, an ex vivo cardiac experimental platform was developed for verification. Results indicate that in the frequency domain, the congruence between phantom and ex vivo experimental outcomes is as high as 94.3%, affirming the reliability of the equivalent circuit model. In the time domain, the correlation is up to 75.3%, corroborating its effectiveness. The proposed time-varying equivalent circuit model exhibits stable and standardized dynamic attributes, serving as a powerful tool for addressing time-varying challenges and simplifying in vivo or ex vivo experiments.

In-situ electret scaffolds with controllable electric fields printed by MEW for bone tissue regeneration

Physiologically relevant electrical microenvironments play an integral role in manipulating bone metabolism. Although implanted biomaterials using conductive or piezoelectric materials to mimic natural tissue electrical properties have been introduced into the field of bone regeneration, the use of electret materials to provide stable and durable electrical stimulation has rarely been studied in biomaterial design. In this study, the ZnO/PCL composite scaffolds with in-situ electret were fabricated using melt electro-writing to explore its efficacy in bone regeneration. By adjusting the electret concentration, the surface potential of the composite scaffolds could be tuned to the biopotential for promoting bone regeneration, and the prepared scaffolds exhibited good electrical stability over an observation period of up to 42 days. In vitro biological experiments showed that the in-situ electret scaffolds promoted the cell viability and osteogenic differentiation of mesenchymal stem cells. At the same time, the in-situ electret composite scaffolds can induce the phenotype transformation of RAW 264.7 cells from M1 to M2, creating a favorable microenvironment for bone tissue regeneration. The composite scaffolds significantly promoted bone regeneration in vivo through sustained endogenous electrical stimulation. These findings suggest that the in-situ electret scaffolds that maintain a stable and physiological electrical microenvironment are promising candidates for enhanced bone regeneration.

Highly stretchable dynamic hydrogels for soft multilayer electronics.

Recent progress in the development of synthetic polymer networks has enabled the next generation of hydrogel-based machines and devices. The ability to mimic the mechanical and electrical properties of human tissue gives great potential toward the fields of bioelectronics and soft robotics. However, fabricating hydrogel devices that display high ionic conductivity while maintaining high stretchability and softness remains unmet. Here, we synthesize supramolecular poly(ionic) networks, which display high stretchability (>1500%), compressibility (>90%), and rapid self-recovery (<30 s), while achieving ionic conductivities of up to 0.1 S cm -1. Dynamic cross-links give rise to inter-layer adhesion and a stable interface is formed on account of ultrahigh binding affinities (>1013 M-2). Superior adherence between layers enabled the fabrication of an intrinsically stretchable hydrogel power source, paving the way for the next generation of multi-layer tissue mimetic devices.

Bio-Interaction Mechanism of Occupational Extremely Low-Frequency Magnetic Field and its Potential Effects on Human

Human lifestyle is evolving as a result of advancement in technology which is mainly driven by electricity. The presence of extremely low frequency magnetic field in the Earth’s atmosphere produced during the processes of generation, transmission and distribution of electricity in occupational environment has the ability to penetrate human skin, and is potentially hazardous to health of exposed individual, which have become a source of concern. This article presents state of knowledge on the electrical and dielectric properties of human tissues, examine the various phenomena processes during the bio-interaction mechanism, all-inclusive biological effects process explained and identify potential health risk associated with prolonged and excessive exposure to occupational magnetic field at extremely low frequency in addition to the underlining factors that influence the probable threats.

Probing underlying biophysical mechanisms of electrical properties change by pathogenesis at the microscopic cellular level

The electrical properties of human tissue have significant potential as biophysical markers in clinical applications, as they can indicate biochemical/biophysical changes occurring at the cellular and extracellular levels. Magnetic resonance electrical properties tomography (MR-EPT) provides a noninvasive approach for extracting pixel-wise electrical properties by processing the B1 field mapping data. However, our current understanding of the biophysical mechanisms underlying changes in electrical properties at the microscopic cellular level during pathogenesis remains incomplete. In this study, an inhomogeneous liver model was developed to establish a linear correlation between fat fraction and electrical properties. We further fit the correlation of liver phantoms with different fat fractions of 0%, 1%, 9%, 17%, 25%, 30%, and 50% (R2 &amp;gt; 0.93). In addition, an inhomogeneous liver phantom was fabricated and measured through MR-EPT at 128 MHz (3 T). The outcomes of this research have the potential to bridge the gap between microscopic lesions and pixel-wise MR-EPT images, offering a feasible method for extracting electrical properties through fat quantification techniques like MRI-Dixon technique.

Bioelectric phenomena in electroacupuncture analgesia.

Pain is a complex process of electrical signal transmission. Electroacupuncture may adjust the bioelectric state of the tissues in painful sites through electrical characteristic structural units (acupoints), thereby exerting analgesic effect. The treatment of diseases with electroacupuncture results from the interaction between the external electric field and the electrical properties of acupoint tissues. Therefore, the state of biological tissues and the parameters of electroacupuncture all affect the therapeutic effect.

Integrated Sensors for Soft Medical Robotics.

Minimally invasive procedures assisted by soft robots for surgery, diagnostics, and drug delivery have unprecedented benefits over traditional solutions from both patient and surgeon perspectives. However, the translation of such technology into commercialization remains challenging. The lack of perception abilities is one of the obstructive factors paramount for a safe, accurate and efficient robot-assisted intervention. Integrating different types of miniature sensors onto robotic end-effectors is a promising trend to compensate for the perceptual deficiencies in soft robots. For example, haptic feedback with force sensors helps surgeons to control the interaction force at the tool-tissue interface, impedance sensing of tissue electrical properties can be used for tumor detection. The last decade has witnessed significant progress in the development of multimodal sensors built on the advancement in engineering, material science and scalable micromachining technologies. This review article provides a snapshot on common types of integrated sensors for soft medical robots. It covers various sensing mechanisms, examples for practical and clinical applications, standard manufacturing processes, as well as insights on emerging engineering routes for the fabrication of novel and high-performing sensing devices.

Chapter 1 - Structure–function and pharmacologic aspects of ion channels relevant to neurologic channelopathies

Ion channels are membrane proteins that allow the passage of ions across the membrane. They characteristically contain a pore where the selectivity of certain ion species is determined and gates that open and close the pore are found. The pore is often connected to additional domains or subunits that regulate its function. Channels are grouped into families based on their selectivity for specific ions and the stimuli that control channel opening and closing, such as voltage or ligands. Ion channels are fundamental to the electrical properties of excitable tissues. Dysfunction of channels can lead to abnormal electrical signaling of neurons and muscle cells, accompanied by clinical manifestations, known as channelopathies. Many naturally occurring toxins target ion channels and affect excitable cells where the channels are expressed. Furthermore, ion channels, as membrane proteins and key regulators of a number of physiologic functions, are an important target for drugs in clinical use. In this chapter, we give a general overview of the classification, genetics and structure-function features of the main ion channel families, and address some pharmacologic aspects relevant to neurologic channelopathies.

Unrolled Optimization via Physics-Assisted Convolutional Neural Network for MR-Based Electrical Properties Tomography: A Numerical Investigation.

Magnetic Resonance imaging based Electrical Properties Tomography (MR-EPT) is a non-invasive technique that measures the electrical properties (EPs) of biological tissues. In this work, we present and numerically investigate the performance of an unrolled, physics-assisted method for 2D MR-EPT reconstructions, where a cascade of Convolutional Neural Networks is used to compute the contrast update. Each network takes in input the EPs and the gradient descent direction (encoding the physics underlying the adopted scattering model) and returns as output the updated contrast function. The network is trained and tested in silico using 2D slices of realistic brain models at 128 MHz. Results show the capability of the proposed procedure to reconstruct EPs maps with quality comparable to that of the popular Contrast Source Inversion-EPT, while significantly reducing the computational time.

Multiscale Model Development for Electrical Properties of Thyroid and Parathyroid Tissues.

Goal: Electrical impedance spectroscopy (EIS) has been suggested as a possible technique to differentiate between thyroid and parathyroid tissue during surgery. This study aims to explore this potential using computational models to simulate the impedance spectra of these tissues, and examine how they are influenced by specific differences in tissue composition and morphology. Materials and methods: Finite element models of thyroid and parathyroid tissues at multiple scales were created, and simulated spectra were compared to existing data collected using ZedScanTM probe during surgery. Geometrical and material properties were varied in a local sensitivity study to assess their relative influence. Results: Both simulated and measured EIS parathyroid spectra show a higher [Formula: see text] dispersion frequency relative to thyroid. However, impedances exhibit overlap at frequencies below 100 kHz. A computational sensitivity study identified uncertainties in extracellular space dimensions, and properties of colloid and fascia compartments as having a significant effect on simulated impedance spectra characteristics. Conclusions: We have demonstrated the utility of our multiscale model in simulating impedance spectra and providing insight into their sensitivity to variations in tissue features. Our results suggest that distinguishing between the thyroid and parathyroid spectra is challenging, but could be improved by constraining the properties of colloid and fascia through further computational or experimental research.

Treatment of Spontaneous Tumors With Algorithmically Controlled Electroporation.

To study the safety and efficacy of algorithmically controlled electroporation (ACE) against spontaneous equine melanoma. A custom temperature sensing coaxial electrode was paired with a high voltage pulse generation system with integrated temperature feedback controls. Computational modeling and ex vivo studies were conducted to evaluate the system's ability to achieve and maintain target temperatures. Twenty-five equine melanoma tumors were treated with a 2000 V protocol consisting of a 2-5-2 waveform, 45 °C temperature set point, and integrated energized times of 0.005 s, 0.01 s, or 0.02 s (2500x, 5000x, and 10000x 2 μs pulses, respectively). Patients returned 20-50 days post treatment to determine the efficacy of the treatment. ACE temperature control algorithms successfully achieved and maintained target temperatures in a diverse population of spontaneous tumors with significant variation in tissue impedance. All treatments were completed successfully without and without adverse events. Complete response rates greater than 93% were achieved in all treatment groups. ACE is a safe and effective treatment for spontaneous equine melanoma. The temperature control algorithm enabled rapid delivery of electroporation treatments without prior knowledge of tissue electrical or thermal properties and could adjust to real time changes in tissue properties. Real time temperature control in electroporation procedures enables treatments near critical structures where thermal damage is contraindicated. Unlike standard approaches, ACE protocols do not require extensive pretreatment planning or knowledge of tissue properties to determine an optimal energy delivery rate and they can account for changes in tissue state (e.g., perfusion) in real time to simultaneously minimize treatment time and potential for thermal damage.

Implementation of the Hybrid ADI-FDTD Scheme to Maxwell Equation for Mathematical Modeling of Breast Tumor

Breast cancer is the most common cancer in women, and non-destructive detection of the tumor is vital. The interaction of electromagnetic waves with breast tissue and the behavior of waves after interaction are used to model tumor detection mathematically. The behavior of electromagnetic waves in a medium is described using Maxwell's equations. Electromagnetic waves propagate according to the electrical properties of a medium. Since the electrical properties of tumor tissue are different from those of normal breast tissue, it is assumed that the tumor is a lossy dielectric sphere, and the breast is a lossy dielectric medium. Under this assumption, Maxwell's equations are used to calculate the scattered field from the tumor. The field scattered by the tumor is different from other tissues because their dielectric properties are different. The location and size of the tumor can be determined by utilizing the difference in scattering from the tissues. While the scattering field from the tumor in spherical geometric form is analytically calculated, it is not analytically possible to calculate the scattering field from the tumor in different geometric shapes. In addition to non-destructive detection of the tumor, an efficient numerical method, the finite difference time domain method (FDTD), is used to simulate the field distribution. After the location of the tumor is determined, the Alternating Direction Implicit (ADI) FDTD method, which gives simulation results by dividing the computation domain into smaller sub-intervals, can be used. Scattered fields are calculated analytically in the geometry where the tumor is in the form of a smooth sphere, and in more complex geometry, the field distributions are successfully obtained with the help of MATLAB using FDTD and ADI-FDTD algorithms.

Rapid estimation of electroporation-dependent tissue properties in canine lung tumors using a deep neural network

The efficiency of electroporation treatments depends on the application of a critical electric field over the targeted tissue volume. Both the electric field and temperature distribution strongly depend on the tissue-specific electrical properties, which both differ between patients in healthy and malignant tissues and change in an electric field-dependent manner from the electroporation process itself. Therefore, tissue property estimations are paramount for treatment planning with electroporation therapies. Ex vivo methods to find electrical tissue properties often misrepresent the targeted tissue, especially when translating results to tumors. A voltage ramp is an in situ method that applies a series of increasing electric potentials across treatment electrodes and measures the resulting current. Here, we develop a robust deep neural network, trained on finite element model simulations, to directly predict tissue properties from a measured voltage ramp. There was minimal test error (R2>0.94;p<0.0001) in three important electric tissue properties. Further, our model was validated to correctly predict the complete dynamic conductivity curve in a previously characterized ex vivo liver model (R2>0.93;p<0.0001) within 100 s from probe insertion, showing great utility for a clinical application. Lastly, we characterize the first reported electrical tissue properties of lung tumors from five canine patients (R2>0.99;p<0.0001). We believe this platform can be incorporated prior to treatment to quickly ascertain patient-specific tissue properties required for electroporation treatment planning models or real-time treatment prediction algorithms. Further, this method can be used over traditional ex vivo methods for in situ tissue characterization with clinically relevant geometries.

Численное исследование влияния изменения электрической проводимости на решение прямой задачи электроимпедансной томографии

Electrical Impedance Tomography (EIT) uses electrical stimulation and measurement at the body surface to image the electrical properties of internal tissues. It has the advantage of non-invasiveness and high temporal resolution but suffers from poor spatial resolution and sensitivity to electrode movement and contact quality. EIT can be useful to applications where there are conductive contrasts between tissues, fluids or gases, such as imaging of cancerous or ischemic tissue or functional monitoring of breathing, blood flow, gastric motility and neural activity. The work uses a complete electrode model (CEM), which is a practical model in EIT, which most realistically models electrodes. This model can simulate EIT measurements with much greater accuracy than continuum models. The mathematical formulation of the problem is written as follows: In the article [15] shows that in order for the problem to have a unique solution, the following condition must be met: Numerical studies are consistent with the conclusions from the article [14]. Useful information in the EIT is contained mainly on a small part of the boundary, i.e., on the electrodes close to the perturbations of the electrical conductivity. Boundary measurements, which are the input to the inverse conductivity problem, are more sensitive to anomalies near the boundary and to larger anomalies. This study is useful in order to know the critical values of the parameters (size, location) of a low-amplitude perturbation of conductivity, at which the measurements are insensitive and, therefore, inhomogeneities cannot be detected.

Using the stm32f407vg microcontroller to study the amplitude-frequency characteristics of biological tissues

The electrical properties of biological tissues of a plant origin are studied using the microcontroller STM32f407vg. The formulation of the problem of identifying informative signs of the viability of biological tissues when using the method of impedance measurement is given. It is shown that since currently in medical diagnostic practice there is no instrument base that would allow in an operational setting to diagnose the ability of biological tissue to self-heal after injury and damage as a result of thermal exposure, a gunshot wound or prolonged compression, the development of methods and means of instrumental diagnostics in this area of knowledge is an important modern task.&#x0D; The results of experimental measurements of impedance characteristics in the frequency range of 20 Hz – 2.0 MHz are presented. The frequency dependences of the stress modulus of a biological tissue of a plant origin are analyzed in its intact state, as well as after exposure of samples of a biological tissue in a freezer.&#x0D; A comparative analysis of the obtained frequency dependences is carried out. A significant difference between the frequency dependences of the stress modulus on a biological tissue and the frequency dependence of the stress modulus on an isotonic solution is shown. The idea was proposed that the degree of difference in the frequency distribution of the impedance module of the biological tissue from the impedance module of the isotonic solution can serve as a criterion for assessing the degree of damage to the biological tissue.