Tissue Conductivity Research Articles

A one-step method for quantitative microwave-induced thermoacoustic tomography.

Electrical conductivity directly correlates with tissue functional information such as blood and water contents, and quantitative extraction of tissue conductivity is of significant importance for disease detection and diagnosis using microwave-induced thermoacoustic tomography (TAT). The existing quantitative TAT (qTAT) approaches capable of extracting tissue conductivity require two steps for the recovery of conductivity. Such two steps approaches depend on an accurate knowledge of the microwave energy loss distribution in tissue and offer a slow computational convergence rate. The purpose of this study is to develop a new algorithm to reconstruct tissue conductivity with higher reconstruction accuracy and greater computational efficiency. We propose an improved qTAT method for direct recovery of tissue conductivity from thermoacoustic data measured along the boundary with only one step without the dependence of microwave energy loss information. The feasibility of our one-step qTAT method is validated in both simulated and tissue-mimicking phantom experiments with single-target and multi-target configurations with different contrast levels. Compared with the previous two-step methods, our one-step qTAT method improves the accuracy of conductivity recovery with approximately one-fold reduction in the mean absolute error (MAE) and root mean square error (RMSE) with p-values greater than 0.05. In addition, the convergence rate is improved by more than two folds for the one-step method. The study demonstrates that new method can quantitatively reconstruct conductivity of tissue more accurately and efficiently over the existing qTAT methods, leading to potentially enhanced accuracy for disease detection and diagnosis.

Assessing the effects of head modelling errors and measurement noise on EEG source localization accuracy in preterm newborns: A single-subject study.

The accuracy of electroencephalogram (EEG) source localization is compromised because of head modelling errors. In this study, we investigated the effect of inaccuracy in the conductivity of head tissues and head model structural deficiencies on the accuracy of EEG source analysis in premature neonates. A series of EEG forward and inverse simulations was performed by introducing structural deficiencies into the reference head models to generate test models, which were then used to investigate head modelling errors caused by cerebrospinal fluid (CSF) exclusion, lack of grey matter (GM)-white matter (WM) distinction, fontanel exclusion and inaccuracy in skull conductivity. The modelling errors were computed between forward and inverse solutions obtained using the reference and test models generated for each deficiency. Our results showed that the exclusion of CSF from the head model had a strong widespread effect on the accuracy of the EEG source localization with position errors lower than 4.17 mm. The GM and WM distinction also caused strong localization errors (up to 3.5mm). The exclusion of fontanels from the head model also strongly affected the accuracy of the EEG source localization for sources located beneath the fontanels with a maximum localization error of 4.37 mm. Similarly, inaccuracies in the skull conductivity caused errors in EEG forward and inverse modelling in sources beneath cranial bones. Our results indicate that the accuracy of EEG source imaging in premature neonates can be largely improved by using head models, which include not only the brain, skull and scalp but also the CSF, GM, WM and fontanels.

Evaluation of the Possible Ameliorative Effects of Anemarrhena asphodeloides Extract on Liver Cirrhosis by Combining Biochemical Analysis and Electrical Tissue Conductivity

Anemarrhena asphodeloides extract (AAE) has been used for the treatment of inflammatory diseases and its anti-inflammatory effects have been reported. In this feasibility study, the hepato-protective effect of AAE was evaluated in a rat liver cirrhosis model by a combination of biochemical analysis and electrical tissue conductivity. Liver cirrhosis was induced by dimethylnitrosamine (DMN) injection. A total of 32 Sprague–Dawley rats were divided into four groups such as normal liver, cirrhotic liver, cirrhotic liver with AAE treatment, and cirrhotic liver with lactulose treatment. Effects of AAE were compared with those of lactulose. Cirrhotic liver with both AAE and lactulose treatments showed increased body weight, decreased levels of aspartate aminotransferase and alanine aminotransferase, and increased albumin level compared with cirrhotic liver (p < 0.05). The expression levels of α-smooth muscle actin (α-SMA) and cyclooxygenase-2 (COX-2) in immunohistochemical analysis showed reduced fibrosis and inflammatory response in both AAE and lactulose treatments compared with cirrhotic liver (p < 0.05). The levels of AAE treatment were relatively lower than those of lactulose. The western blot analysis of α-SMA and COX-2 protein in both AAE and lactulose treatments was similar to that of normal liver. When comparing electrical conductivity to normal liver, difference in conductivity was 21.2%, 11.5%, and 7.7% in cirrhotic liver, lactulose treatment, and AAE treatment, respectively. These results suggest that the anti-inflammatory effect of AAE may delay or prevent the progress from liver fibrosis to cirrhosis. In summary, a more precise analysis of tissue conditions following the induction of liver cirrhosis was possible by combining electrical tissue conductivity with conventional biochemical analysis.

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.

A Technique of Measurement of Gastrointestinal Luminal Nutrient Sensing and These Absorptions: Ussing Chamber (Short-Circuit Current) Technique.

The gastrointestinal (GI) tract is a series of hollow organs that play roles in food digestion and nutrient absorption. To perform these functions, they should recognize the luminal environment and elicit adequate physiological responses, including digestive juice secretion, peristaltic movements, etc. The Ussing chamber technique is an electrophysiological method for measuring transepithelial ion transport and permeability as short-circuit current (Isc) and transepithelial electrical tissue conductance (Gt) or resistance (TEER), respectively, in vitro. This technique can be applied for the measurement of luminal nutrient sensing and absorption. This article introduces practical methods for measuring luminal nutrient sensing and absorption using intestinal mucosa specimens isolated from humans and experimental animals.

The influence of tissue conductivity on the calculation of electric field in the transcranial magnetic stimulation head model

In transcranial magnetic stimulation (TMS), the conductivity of brain tissue is obtained by using diffusion tensor imaging (DTI) data processing. However, the specific impact of different processing methods on the induced electric field in the tissue has not been thoroughly studied. In this paper, we first used magnetic resonance image (MRI) data to create a three-dimensional head model, and then estimated the conductivity of gray matter (GM) and white matter (WM) using four conductivity models, namely scalar (SC), direct mapping (DM), volume normalization (VN) and average conductivity (MC), respectively. Isotropic empirical conductivity values were used for the conductivity of other tissues such as the scalp, skull, and cerebrospinal fluid (CSF), and then the TMS simulations were performed when the coil was parallel and perpendicular to the gyrus of the target. When the coil was perpendicular to the gyrus where the target was located, it was easy to get the maximum electric field in the head model. The maximum electric field in the DM model was 45.66% higher than that in the SC model. The results showed that the conductivity component along the electric field direction of which conductivity model was smaller in TMS, the induced electric field in the corresponding domain corresponding to the conductivity model was larger. This study has guiding significance for TMS precise stimulation.

Feasibility of Magnetic Resonance-Based Conductivity Imaging as a Tool to Estimate the Severity of Hypoxic-Ischemic Brain Injury in the First Hours After Cardiac Arrest.

Early identification of the severity of hypoxic-ischemic brain injury (HIBI) after cardiac arrest can be used to help plan appropriate subsequent therapy. We evaluated whether conductivity of cerebral tissue measured using magnetic resonance-based conductivity imaging (MRCI), which provides contrast derived from the concentration and mobility of ions within the imaged tissue, can reflect the severity of HIBI in the early hours after cardiac arrest. Fourteen minipigs were resuscitated after 5min or 12min of untreated cardiac arrest. MRCI was performed at baseline and at 1h and 3.5h after return of spontaneous circulation (ROSC). In both groups, the conductivity of cerebral tissue significantly increased at 1h after ROSC compared with that at baseline (P = 0.031 and 0.016 in the 5-min and 12-min groups, respectively). The increase was greater in the 12-min group, resulting in significantly higher conductivity values in the 12-min group (P = 0.030). At 3.5h after ROSC, the conductivity of cerebral tissue in the 12-min group remained increased (P = 0.022), whereas that in the 5-min group returned to its baseline level. The conductivity of cerebral tissue was increased in the first hours after ROSC, and the increase was more prominent and lasted longer in the 12-min group than in the 5-min group. Our findings suggest the promising potential of MRCI as a tool to estimate the severity of HIBI in the early hours after cardiac arrest.

Exploring within-plant hydraulic trait variation: A test of the vulnerability segmentation hypothesis.

Observations show vulnerability segmentation between stems and leaves is highly variable within and between environments. While a number of species exhibit conventional vulnerability segmentation (stem leaf ), others exhibit no vulnerability segmentation and others reverse vulnerability segmentation (stem leaf ). We developed a hydraulic model to test hypotheses about vulnerability segmentation and how it interacts with other traits to impact plant conductance. We do this using a series of experiments across a broad parameter space and with a case study of two species with contrasting vulnerability segmentation patterns: Quercus douglasii and Populus trichocarpa. We found that while conventional vulnerability segmentation helps to preserve conductance in stem tissues, reverse vulnerability segmentation can better maintain conductance across the combined stem-leaf hydraulic pathway, particularly when plants have more vulnerable s and have hydraulic segmentation with greater resistance in the leaves. These findings show that the impacts of vulnerability segmentation are dependent upon other plant traits, notably hydraulic segmentation, a finding that could assist in the interpretation of variable observations of vulnerability segmentation. Further study is needed to examine how vulnerability segmentation impacts transpiration rates and recovery from water stress.

Conductive polymers for cardiac tissue engineering and regeneration.

Cardiovascular diseases, such as myocardial infarction, are considered a significant global burden and the leading cause of death. Given the inability of damaged cardiac tissue to self-repair, cell-based tissue engineering and regeneration may be the only viable option for restoring normal heart function. To maintain the normal excitation-contraction coupling function of cardiac tissue, uniform electronic and ionic conductance properties are required. To transport cells to damaged cardiac tissues, several techniques, including the incorporation of cells into conductive polymers (CPs) and biomaterials, have been utilized. Due to the complexity of cardiac tissues, the success of tissue engineering for the damaged heart is highly dependent on several variables, such as the cell source, growth factors, and scaffolds. In this review, we sought to provide a comprehensive overview of the electro CPs and biomaterials used in the engineering and regeneration of heart tissue.

Validated computational models predict vagus nerve stimulation thresholds in preclinical animals and humans

Objective. We demonstrated how automated simulations to characterize electrical nerve thresholds, a recently published open-source software for modeling stimulation of peripheral nerves, can be applied to simulate accurately nerve responses to electrical stimulation. Approach. We simulated vagus nerve stimulation (VNS) for humans, pigs, and rats. We informed our models using histology from sample-specific or representative nerves, device design features (i.e. cuff, waveform), published material and tissue conductivities, and realistic fiber models. Main results. Despite large differences in nerve size, cuff geometry, and stimulation waveform, the models predicted accurate activation thresholds across species and myelinated fiber types. However, our C fiber model thresholds overestimated thresholds across pulse widths, suggesting that improved models of unmyelinated nerve fibers are needed. Our models of human VNS yielded accurate thresholds to activate laryngeal motor fibers and captured the inter-individual variability for both acute and chronic implants. For B fibers, our small-diameter fiber model underestimated threshold and saturation for pulse widths >0.25 ms. Our models of pig VNS consistently captured the range of in vivo thresholds across all measured nerve and physiological responses (i.e. heart rate, Aδ/B fibers, Aγ fibers, electromyography, and Aα fibers). In rats, our smallest diameter myelinated fibers accurately predicted fast fiber thresholds across short and intermediate pulse widths; slow unmyelinated fiber thresholds overestimated thresholds across shorter pulse widths, but there was overlap for pulse widths >0.3 ms. Significance. We elevated standards for models of peripheral nerve stimulation in populations of models across species, which enabled us to model accurately nerve responses, demonstrate that individual-specific differences in nerve morphology produce variability in neural and physiological responses, and predict mechanisms of VNS therapeutic and side effects.

Extending bioelectric navigation for displacement and direction detection

PurposeBioelectric navigation is a navigation modality for minimally invasive endovascular procedures promising non-fluoroscopic navigation. However, the method offers only limited navigation accuracy between anatomical features and expects the tracked catheter to move only in one direction at all times. We propose to extend bioelectric navigation with additional sensing capabilities, allowing for the estimation of the distance traveled by the catheter, thereby improving accuracy between feature locations and allowing to track also under alternating forward- and backward motion.MethodsWe perform experiments in finite element method (FEM) simulations and in a 3D printed phantom. A solution for estimating the traveled distance using a stationary electrode is proposed, together with an approach on how to evaluate the signals obtained with this additional electrode. We investigate the effects of surrounding tissue conductance on this approach. Finally, the approach is refined in order to mitigate the effects of parallel conductance on the navigation accuracy.ResultsThe approach allows to estimate the catheter movement direction and the distance traveled. Simulations show absolute errors below 0.89 mm for non-conducting surrounding tissue, but errors up to 60.27 mm when the tissue is electrically conductive. This effect can be mitigated by a more sophisticated modeling (errors up to 33.96 mm). In experiments in a 3D printed phantom, the mean absolute error over 6 catheter paths is 6.3 mm, with standard deviations smaller than or equal to 1.1 mm.ConclusionsExtending the setup of bioelectric navigation with an additional stationary electrode allows to estimate the distance traveled by the catheter, as well as the movement direction. The effects of parallel conductive tissue could be partially mitigated in simulations, but further research is needed to investigate these effects in real biological tissue, and to bring the introduced errors down to a clinically acceptable level.

Development of active jejunal glucose absorption in broiler chickens

Growth in chickens, especially meat-type chickens (broilers), is extremely rapid, but studies on the regulatory mechanism of intestinal glucose absorption with growth are few, contradictory, and unclear. Here, we investigated the regulation of intestinal glucose absorption with growth in broiler chickens using oral glucose gavage, intestinal Evans blue transit, intestinal glucose absorption, scanning electron microscopy, and glucose absorption- and cell junction-related gene expression analyses. Peak blood glucose levels after oral glucose gavage occurred at 10 and 50 min in chickens at 1 wk (C1W) and 5 wk (C5W) of age, respectively. The area under the curve for glucose levels was greater for the C5W than the C1W (P=0.035). The stain ratio in the small intestine in the C5W was lower than that in the C1W (P=0.01), but there were no differences in the tissue regions stained with Evans blue and the migration distance of Evans blue from Meckel's diverticulum. In everted sac and Ussing chamber experiments, we observed reduced intestinal glucose uptake and electrogenic glucose absorption in the jejunum of the C5W. Phloridzin, an inhibitor of sodium/glucose cotransporter 1 (SGLT1), suppressed the glucose-induced short-circuit current in the C1W (P=0.016) but not the C5W. Although the addition of NaCl solution stimulated the glucose-induced short-circuit current in the C1W, no differences between the treatments were observed (P=0.056), which was also the case in the C5W. Additionally, tissue conductance was diminished in the C5W compared with that in the C1W. Moreover, in the C5W, the intestinal tract was more developed and the jejunal villi were enlarged. In conclusion, glucose absorption throughout the intestine could be greater in C5W than in C1W; however, reduced SGLT1 sensitivity, decreased ion permeability, and intestinal overdevelopment lead to decreased local glucose absorption in the jejunum with growth in broiler chickens. These data provide a detailed analysis of intestinal glucose absorption in growing broiler chickens, and can contribute to the development of novel feeds.

Effect of sodium concentration and mucosal pH on apical uptake of acetate and butyrate, and barrier function of the isolated bovine ruminal epithelium

This study was conducted to investigate the role of Na+ on ruminal short-chain fatty acid (SCFA) absorption and barrier function when isolated ruminal epithelium was exposed to high and low pH ex vivo. Nine Holstein steer calves (322 ± 50.9 kg of BW) consuming 7.05 ± 1.5 kg DM of a TMR were euthanized and ruminal tissue was collected from the caudal-dorsal blind sac. Tissues were mounted between 2 halves of Ussing chambers (3.14 cm2) and exposed to buffers that contained low (10 mM) or high (140 mM) Na+ with low (6.2) or high (7.4) mucosal pH. The same buffer solutions were used on the serosal side except that pH was maintained at 7.4. Buffers used to evaluate SCFA uptake contained bicarbonate to determine total uptake or excluded bicarbonate and included nitrate to determine non-inhibitable uptake. Bicarbonate-dependent uptake was calculated as the difference between the total and non-inhibitable uptake. Acetate (25 mM) and butyrate (25 mM) were spiked with 2-3H-acetate and 1-14C-butyrate, respectively, and were then added to the mucosal side, incubated for 1 min, and tissues were analyzed to evaluate rates of SCFA uptake. Tissue conductance (Gt) and the mucosal-to-serosal flux of 1-3H-mannitol were used to assess barrier function. There were no Na+ × pH interactions for butyrate or acetate uptake. Decreasing mucosal pH from 7.4 to 6.2 increased total acetate and butyrate uptake, and bicarbonate-dependent acetate uptake. Flux of 1-3H-mannitol was not affected by treatment. However, high Na+ concentration reduced Gt and prevented an increase in Gt from flux period 1 to flux period 2. The results of this study indicate that although providing more Na+ to the ruminal epithelium does not affect SCFA uptake or mannitol flux, it may help stabilize tissue integrity.

Use of machine learning to improve the estimation of conductivity and permittivity based on longitudinal relaxation time T1 in magnetic resonance at 7 T

Electrical property tomography (EPT) is a noninvasive method that uses magnetic resonance imaging (MRI) to estimate the conductivity and permittivity of tissues, and hence, can be used as a biomarker. One branch of EPT is based on the correlation of water and relaxation time T1 with the conductivity and permittivity of tissues. This correlation was applied to a curve-fitting function to estimate electrical properties, it was found to have a high correlation between permittivity and T1 however the computation of conductivity based on T1 requires to estimate the water content. In this study, we developed multiple phantoms with several ingredients that modify the conductivity and permittivity and explored the use of machine learning algorithms to have a direct estimation of conductivity and permittivity based on MR images and the relaxation time T1. To train the algorithms, each phantom was measured using a dielectric measurement device to acquire the true conductivity and permittivity. MR images were taken for each phantom, and the T1 values were measured. Then, the acquired data were tested using curve fitting, regression learning, and neural fit models to estimate the conductivity and permittivity values based on the T1 values. In particular, the regression learning algorithm based on Gaussian process regression showed high accuracy with a coefficient of determination R2 of 0.96 and 0.99 for permittivity and conductivity, respectively. The estimation of permittivity using regression learning demonstrated a lower mean error of 0.66% compared to the curve fitting method, which resulted in a mean error of 3.6%. The estimation of conductivity also showed that the regression learning approach had a lower mean error of 0.49%, whereas the curve fitting method resulted in a mean error of 6%. The findings suggest that utilizing regression learning models, specifically Gaussian process regression, can result in more accurate estimations for both permittivity and conductivity compared to other methods.

Electrical properties of tissues from a microscopic model of confined electrolytes

Objective. In the presence of oscillatory electric fields, the motion of electrolyte ions in biological tissues is often limited by the confinement created by cell and organelle walls. This confinement induces the organization of the ions into dynamic double layers. This work determines the contribution of these double layers to the bulk conductivity and permittivity of tissues. Approach. Tissues are modeled as repeated units of electrolyte regions separated by dielectric walls. Within the electrolyte regions, a coarse-grained model is used to describe the associated ionic charge distribution. The model emphasizes the role of the displacement current in addition to the ionic current and enables the evaluation of macroscopic conductivities and permittivities. Main results. We obtain analytical expressions for the bulk conductivity and permittivity as a function of the frequency of the oscillatory electric field. These expressions explicitly include the geometric information of the repeated structure and the contribution of the dynamic double layers. The low-frequency limit of the conductivity expression yields a result predicted by the Debye permittivity form. The model also provides a microscopic interpretation of the Maxwell–Wagner effect. Significance. The results obtained contribute to the interpretation of the macroscopic measurements of electrical properties of tissues in terms of their microscopic structure. The model enables a critical assessment of the justification for the use of macroscopic models to analyze the transmission of electrical signals through tissues.

Emerging nanomaterials to enhance electrochemical impedance spectroscopy for biomedical applications

Over the last few decades, electrical impedance-based sensors have been investigated for clinical translation to detect changes in tissue conductivities, including cardiac output and pulmonary function. Recently, electrochemical impedance spectroscopy (EIS) provides metabolic measurements that occur at the electrode-tissue interface, and the 3-D EIS can be reconstructed to generate electrical impedance tomography (EIT) for detecting the impedimetric properties of the vascular wall or fatty liver disease. In both EIS and EIT applications, the electrochemical properties of the interface electrodes are essential to address the signal-to-noise ratio or sensitivity of measurements in the biological environment. To enhance the conductive properties, we will survey a series of carbon-based nanomaterials as the emerging candidates for coating the electrodes of bioimpedance sensors. In this review, we will provide a theoretical background on impedance-based measurements and highlight the current state of EIS and EIT, including their applications for cancer screening and detection of vulnerable atherosclerotic plaques. Next, we will focus on the strengths of different nanomaterials when used as an electrode coating to optimize charge transfer across the electric double layers and to enhance measurement sensitivity. We will also identify some unmet clinical needs, such as the ability to adapt to different hemodynamic conditions and blood vessel geometries, that can be realized by the novel biomaterials for the future EIS-based sensors.

Numerical examination of wall properties for the magnetohydrodynamics stagnation point flow of micro-rotating fluid subject to weak concentration

In this investigation, stagnation point flow of non-Newtonian fluid is considered under the impact of magnetohydrodynamics, porous medium, and mixed convection effects. Additionally, angular momentum and energy transport constitutive equations are also taken into account in order to explore the fluid micro-rotational effects. The fluid motion develops by virtue of linear stretching and slip factors. Furthermore, the energy transport equation is raised with the effect of viscous dissipation and heat source phenomena. Mathematical formulations lead to a set of ordinary differential equations by introducing similarity variables. The proposed model has been solved numerically using fourth-order Runge–Kutta method with shooting technique. Influence of pertinent flow parameters for the case of weak concentration of micro-elements on velocity, temperature, skin friction, and local heat flux at the surface is computed and discussed. Different ranges are chosen for the flow parameters, for example; magnetic field variation is taken [0, 0.9], micro-rotation [0,1], stretching ratio [0,0.2], surface condition [0,1], the Prandtl number [3, 12], and the Eckert number [3, 11]. The fluid velocity slows down when the magnetic number varies from 0.0 to 0.5 in the presence of weak concentration (m = 0.5) of micro-elements. In addition, the maximum increasing percentage of skin friction is obtained when the porosity parameter varies from 0.0 to 0.6. The maximum decreasing percentage of the Nusselt number is obtained when the thermal slip parameter varies from 0.0 to 0.8. The current study has multiple fascinating applications in polymeric solutions, bio-medical functions like magnetic drug targeting, heat conduction in tissues, surface roughness, and squeeze film lubrication problems between conical bearings.

PO-03-096 DEFINING RECORDING ANTENNA FOR ATRIAL ELECTRODES BY ENDOCARDIAL AND EPICARDIAL COMPUTER MAPPING

Mapping arrhythmias and concretely atrial fibrillation (AF) is complicated by our inability to determine local from far field electrograms, as far field interfere with the identification of local activity in the specific electrode location. In particular, how “local” is local field on any specific electrode and catheter is not yet biophysically defined. We tested the hypothesis that EGM conformation on specific electrode configurations can be explained by modelling the biophysical relation between the electrode size and separation in active myocardial tissue. We modelled laminar conduction in atrial tissue of 30x30x3 mm on a 1 mm electrode, discretized into 100.000 and 100 nodes respectively (fig. A) and simulating propagation waves with constant propagation direction at different conduction velocities. The EGM was constructed using the electric potential transfer equation between the tissue and the electrode, and this equation was discretized for each tissue node to evaluate individual contributions of atrial regions to construct unipolar (fig B) and bipolar (fig C) EGM signals. This allowed to unify the near field definition for all types of electrodes as regions contributing at least 30% respect to the maximal tissue contribution. In Figure B, the unipolar electrode recorded near field from a circle of radius 8 mm endocardially, and 2.7 mm transmurally with a 1.9 ratio of endo-to-epicardial amplitude. Bipolar electrodes showed directional antennas for near field aligned with the propagation direction (fig. C) with radii of 1.7, 5.7 and 8.3 mm for 2, 5, and 10 mm spacing (fig. C). Bipolar electrodes showed less transmural variability on the near field antenna, from 2 to 2.7 mm (fig. D). These data show that local signals on clinical catheters can represent near field activity in 1.7 to ∼8 mm radius spheres. Studies are required to define optimal electrode configurations to map AF, ventricular fibrillation, atrial and ventricular tachycardia.

Electrical impedance myography method of measuring anisotropic tongue tissue

Objective. To date, measurement of the conductivity and relative permittivity properties of anisotropic biological tissues using electrical impedance myography (EIM) has only been possible through an invasive ex vivo biopsy procedure. Here, we present a novel forward and inverse theoretical modeling framework to estimate these properties combining surface and needle EIM measurements. Methods. The framework here presented models the electrical potential distribution within a monodomain, homogeneous, and three-dimensional anisotropic tissue. Finite-element method (FEM) simulations and tongue experimental results verify the validity of our method to reverse-engineer three-dimensional conductivity and relative permittivity properties from EIM measurements. Results. FEM-based simulations confirm the validity of our analytical framework, with relative errors between analytical predictions and simulations smaller than 0.12% and 2.6% in a cuboid and tongue model, respectively. Experimental results confirm qualitative differences in the conductivity and the relative permittivity properties in the x, y, and z directions. Conclusion. Our methodology enables EIM technology to reverse-engineer the anisotropic tongue tissue conductivity and relative permittivity properties, thus unfolding full forward and inverse EIM predictability capabilities. Significance. This new method of evaluating anisotropic tongue tissue will lead to a deeper understanding of the role of biology necessary for the development of new EIM tools and approaches for tongue health measurement and monitoring.

Improved Magneto-Acousto-Electrical Computed Tomography (MAE-CT) With Multi-Angle Plane Wave Excitation.

As a tissue conductivity imaging method, magneto-acousto-electric tomography (MAET) has the advantage of high axial spatial resolution compared with traditional electrical impedance imaging methods. However, it has the problems of difficulty in imaging targets with irregular conductivity distribution and poor lateral spatial resolution. Although the rotation-based MAET method can partly solve the irregular target problem, there is still a poor imaging signal-to-noise ratio (SNR) problem. Our previous study established a framework of an innovative MAET method, which has a very similar imaging theory and reconstruction algorithm to those of computed tomography (CT). Therefore, we name the method magneto-acoustic-electric computed tomography (MAE-CT). This paper proposes an improved implementation of MAE-CT based on multi-angle plane wave excitation. This method combines the electronic steering of the linear array transducer with the mechanical rotation to increase the number of projection angles while keeping the imaging complexity. In this study, we first established a finite element simulation model to verify the method's feasibility. Then phantom experiments were conducted to systematically investigate the performance of the proposed method. Finally, in vitro liver tissue experiment was conducted to further explore the feasibility of the method. The experimental results show that our method improves both the SNR and spatial resolution of the reconstructed image. For the phantom results, this method can detect conductivity of 0.67 S/m in an area with a size of 2 mm. To the best of our knowledge, this is the best result of spatial resolution available for MAET.