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Conductivity tensor imaging (CTI) using MRI is an advanced method that can non-invasively measure the electrical properties of living tissues. The contrast of CTI is based on underlying hypothesis about the proportionality between the mobility and diffusivity of ions and water molecules inside tissues. The experimental validation of CTI in both in vitro and in vivo settings is required as a reliable tool to assess tissue conditions. The changes in extracellular space can be indicators for disease progression, such as fibrosis, edema, and cell swelling. In this study, we conducted a phantom imaging experiment to test the feasibility of CTI for measuring the extracellular volume fraction in biological tissue. To mimic tissue conditions with different extracellular volume fractions, four chambers of giant vesicle suspension (GVS) with different vesicle densities were included in the phantom. The reconstructed CTI images of the phantom were compared with the separately-measured conductivity spectra of the four chambers using an impedance analyzer. Moreover, the values of the estimated extracellular volume fraction in each chamber were compared with those measured by a spectrophotometer. As the vesicle density increased, we found that the extracellular volume fraction, extracellular diffusion coefficient, and low-frequency conductivity decreased, while the intracellular diffusion coefficient slightly increased. On the other hand, the high-frequency conductivity could not clearly distinguish the four chambers. The extracellular volume fraction measured by the spectrophotometer and CTI method in each chamber were quite comparable, i.e., (1.00, 0.98 ± 0.01), (0.59, 0.63 ± 0.02), (0.40, 0.40 ± 0.05), and (0.16, 0.18 ± 0.02). The prominent factor influencing the low-frequency conductivity at different GVS densities was the extracellular volume fraction. Further studies are needed to validate the CTI method as a tool to measure the extracellular volume fractions in living tissues with different intracellular and extracellular compartments.

This study aims to find base materials for dry electrode fabrication with high accuracy and without reducing electrode performance for long-term bioelectric potential monitoring after electroless silver plating. Most applications of dry electrodes that have been developed in the past few decades are restricted by low accuracy compared to commercial Ag/AgCl gel electrodes, as in our previous study of PVDF-based dry electrodes. In a recent study, however, nanoweb-based chlorinated polyisoprene (CPI) and poly(styrene-b-butadiene-b-styrene) (SBS) rubber were selected as promising candidates due to their excellent elastic properties, as well as their nanofibril nature, which may improve electrode durability and skin contact. The electroless silver plating technique was employed to coat the nanofiber web with silver, and silver nanoweb(AgNW)-based dry electrodes were fabricated. The key electrode properties (contact impedance, step response, and noise characteristics) for AgNW dry electrodes were investigated thoroughly using agar phantoms. The dry electrodes were subsequently tested on human subjects to establish their realistic performance in terms of ECG, EMG monitoring, and electrical impedance tomography (EIT) measurements. The experimental results demonstrated that the AgNW dry electrodes, particularly the SBS-AgNW dry electrodes, performed similarly to commercial Ag/AgCl gel electrodes and were outperformed in terms of long-term stability.

Abstract The importance of perioperative respiration monitoring is highlighted by high incidences of postoperative respiratory complications unrelated to the original disease. The objectives of this pilot study were to (1) simultaneously acquire respiration rate (RR), tidal volume (TV), minute ventilation (MV), SpO2 and PetCO2 from patients in post-anesthesia care unit (PACU) and (2) identify a practical continuous respiration monitoring method by analyzing the acquired data in terms of their ability and reliability in assessing a patient’s respiratory status. Thirteen non-intubated patients completed this observational study. A portable electrical impedance tomography (EIT) device was used to acquire RREIT, TV and MV, while PetCO2, RRCap and SpO2 were measured by a Capnostream35. Hypoventilation and respiratory events, e.g., apnea and hypopnea, could be detected reliably using RREIT, TV and MV. PetCO2 and SpO2 provided the gas exchange information, but were unable to detect hypoventilation in a timely fashion. Although SpO2 was stable, the sidestream capnography using the oronasal cannula was often unstable and produced fluctuating PetCO2 values. The coefficient of determination (R2) value between RREIT and RRCap was 0.65 with a percentage error of 52.5%. Based on our results, we identified RR, TV, MV and SpO2 as a set of respiratory parameters for robust continuous respiration monitoring of non-intubated patients. Such a respiration monitor with both ventilation and gas exchange parameters would be reliable and could be useful not only for respiration monitoring, but in making PACU discharge decisions and adjusting opioid dosage on general hospital floor. Future studies are needed to evaluate the potential clinical utility of such an integrated respiration monitor.

Electrical impedance tomography (EIT) can monitor the real-time hemodynamic state of a conscious and spontaneously breathing patient noninvasively. However, cardiac volume signal (CVS) extracted from EIT images has a small amplitude and is sensitive to motion artifacts (MAs). This study aimed to develop a new algorithm to reduce MAs from the CVS for more accurate heart rate (HR) and cardiac output (CO) monitoring in patients undergoing hemodialysis based on the source consistency between the electrocardiogram (ECG) and the CVS of heartbeats. Two signals were measured at different locations on the body through independent instruments and electrodes, but the frequency and phase were matched when no MAs occurred. A total of 36 measurements with 113 one-hour sub-datasets were collected from 14 patients. As the number of motions per hour (MI) increased over 30, the proposed algorithm had a correlation of 0.83 and a precision of 1.65 beats per minute (BPM) compared to the conventional statical algorithm of a correlation of 0.56 and a precision of 4.04 BPM. For CO monitoring, the precision and upper limit of the mean ∆CO were 3.41 and 2.82 L per minute (LPM), respectively, compared to 4.05 and 3.82 LPM for the statistical algorithm. The developed algorithm could reduce MAs and improve HR/CO monitoring accuracy and reliability by at least two times, particularly in high-motion environments.

Abstract Background Electrical impedance tomography (EIT) has been used for functional lung imaging of regional air distributions during mechanical ventilation in intensive care units (ICU). From numerous clinical and animal studies focusing on specific lung functions, a consensus about how to use the EIT technique has been formed lately. We present an integrated EIT system implementing the functions proposed in the consensus. The integrated EIT system could improve the usefulness when monitoring of mechanical ventilation for lung protection so that it could facilitate the clinical acceptance of this new technique. Methods Using a custom-designed 16-channel EIT system with 50 frames/s temporal resolution, the integrated EIT system software was developed to implement five functional images and six EIT measures that can be observed in real-time screen view and analysis screen view mode, respectively. We evaluated the performance of the integrated EIT system with ten mechanically ventilated porcine subjects in normal and disease models. Results Quantitative and simultaneous imaging of tidal volume (TV), end-expiratory lung volume change ($$\triangle$$ ▵ EELV), compliance, ventilation delay, and overdistension/collapse images were performed. Clinically useful parameters were successfully extracted including anterior/posterior ventilation ratio (A/P ratio), center of ventilation ($${\mathrm{CoV}}_{{x}}$$ CoVx , $${\mathrm{CoV}}_{{y}}$$ CoVy ), global inhomogeneity (GI), coefficient of variation (CV), ventilation delay and percentile of overdistension/collapse. The integrated EIT system was demonstrated to suggest an optimal positive end-expiratory pressure (PEEP) for lung protective ventilation in normal and in the disease model of an acute injury. Optimal PEEP for normal and disease model was 2.3 and $$7.9 \, {\mathrm{cmH}}_{2}\mathrm{O}$$ 7.9cmH2O , respectively. Conclusions The proposed integrated approach for functional lung ventilation imaging could facilitate clinical acceptance of the bedside EIT imaging method in ICU. Future clinical studies of applying the proposed methods to human subjects are needed to show the clinical significance of the method for lung protective mechanical ventilation and mechanical ventilator weaning in ICU.

The successful management of cervical intraepithelial neoplasia (CIN) with proper screening and treatment methods could prevent cervical cancer progression. We propose a bioimpedance spectroscopic measurement device and a multi-electrode probe as an independent screening tool for CIN. To evaluate the performance of this screening method, we enrolled 123 patients, including 69 patients with suspected CIN and 54 control patients without cervical dysplasia who underwent a hysterectomy for benign disease (non-CIN). Following conization, the electrical properties of the excised cervical tissue were characterized using an electrical bioimpedance spectroscopy-based multi-electrode probe. Twenty-eight multifrequency voltages were collected through the two concentric array electrodes via a sensitivity-optimized measurement protocol based on an electrical energy concentration method. The electrical properties of the CIN and non-CIN groups were compared with the results of the pathology reports. Reconstructed resistivity tended to decrease in the CIN and non-CIN groups as frequency increased. Reconstructed resistivity from 625 Hz to 50 kHz differed significantly between the CIN and non-CIN groups (p < 0.001). Using 100 kHz as the reference, the difference between the CIN and non-CIN groups was significant. Based on the difference in reconstructed resistivity between 100 kHz and the other frequencies, this method had a sensitivity of 94.3%, a specificity of 84%, and an accuracy of 90% in CIN screening. The feasibility of noninvasive CIN screening was confirmed through the difference in the frequency spectra evaluated in the excised tissue using the electrical bioimpedance spectroscopy-based multi-electrode screening probe.

Otitis media is mainly caused by upper respiratory tract infection and eustachian tube dysfunction. If external upper respiratory tract infection is not detected early in the middle ear, or an appropriate immune response does not occur, otitis media can become a chronic state or complications may occur. Therefore, given the important role of Toll-like receptors (TLRs) in the early response to external antigens, we surveyed the role of TLRs in otitis media. To summarize the role of TLR in otitis media, we reviewed articles on the expression of TLRs in acute otitis media (AOM), otitis media with effusion (OME), chronic otitis media (COM) with cholesteatoma, and COM without cholesteatoma. Many studies showed that TLRs 1–10 are expressed in AOM, OME, COM with cholesteatoma, and COM without cholesteatoma. TLR expression in the normal middle ear mucosa is absent or weak, but is increased in inflammatory fluid of AOM, effusion of OME, and granulation tissue and cholesteatoma of COM. In addition, TLRs show increased or decreased expression depending on the presence or absence of bacteria, recurrence of disease, tissue type, and repeated surgery. In conclusion, expression of TLRs is associated with otitis media. Inappropriate TLR expression, or delayed or absent induction, are associated with the occurrence, recurrence, chronicization, and complications of otitis media. Therefore, TLRs are very important in otitis media and closely related to its etiology.

Literature in the field of stem cell therapy indicates that, when stem cells in a state of single-cell suspension are injected systemically, they show poor in vivo survival, while such cells show robust cell survival and regeneration activity when transplanted in the state of being attached on a biomaterial surface. Although an attachment-deprived state induces anoikis, when cell-surface engineering technology was adopted for stem cells in a single-cell suspension state, cell survival and regenerative activity dramatically improved. The biochemical signal coming from ECM (extracellular matrix) molecules activates the cell survival signal transduction pathway and prevents anoikis. According to the target disease, various therapeutic cells can be engineered to improve their survival and regenerative activity, and there are several types of biomaterials available for cell-surface engineering. In this review, biomaterial types and application strategies for cell-surface engineering are presented along with their expected efficacy.

Introduction: The most frequent causes of tinnitus associated with hearing loss are noise-induced hearing loss and presbycusis. The mechanism of tinnitus is not yet clear, although several hypotheses have been suggested. Therefore, we aimed to analyze characteristics of chronic tinnitus between noise-induced hearing loss and presbycusis. Materials and Methods: This paper is a retrospective chart review and outpatient clinic-based study of 248 patients with chronic tinnitus from 2015 to 2020 with noise-induced or presbycusis. Pure tone audiometry (PTA), auditory brainstem response (ABR), distortion product otoacoustic emissions (DPOAE), transient evoked otoacoustic emissions (TEOAE), and tinnitograms were conducted. Results: PTA showed that hearing thresholds at all frequencies were higher in patients with noise-induced hearing loss than the presbycusis group. ABR tests showed that patients with presbycusis had longer wave I and III latencies (p < 0.05 each) than patients with noise-induced hearing loss. TEOAE tests showed lower values in patients with noise-induced hearing loss than presbycusis at 1.5, 2, 3, and 4 kHz (p < 0.05 each). DPOAE tests showed that response rates in both ears at 1.5, 2, and 3 kHz were significantly higher in patients with presbycusis than noise-induced hearing loss (p < 0.05 each). Discussion: This study showed that hearing thresholds were higher, the loudness of tinnitus was smaller, and the degree of damage to outer hair cells was lower in patients with presbycusis than with noise-induced hearing loss. Moreover, wave I and III latencies were more prolonged in patients with presbycusis despite their having lower hearing thresholds. These phenomena may reflect the effects of aging or degeneration of the central nervous system with age. Further studies are needed to evaluate the etiologies of tinnitus.

Previous imaging studies have shown the morphological malformation and the alterations of ionic mobility, water contents, electrical properties, or metabolites in seizure brains. Magnetic resonance electrical properties tomography (MREPT) is a recently developed technique for the measurement of electrical tissue properties with a high frequency that provides cellular information regardless of the cell membrane. In this study, we examined the possibility of MREPT as an applicable technique to detect seizure-induced functional changes in the brain of rats. Ultra-high field (9.4 T) magnetic resonance imaging (MRI) was performed, 2 h, 2 days, and 1 week after the injection of N-methyl-D-aspartate (NMDA; 75 mg/kg). The conductivity images were reconstructed from B1 phase images using a magnetic resonance conductivity imaging (MRCI) toolbox. The high-frequency conductivity was significantly decreased in the hippocampus among various brain regions of NMDA-treated rats. Nissl staining showed shrunken cell bodies and condensed cytoplasm potently at 2 h after NMDA treatment, and neuronal cell loss at all time points in the hippocampus. These results suggest that the reduced electrical conductivity may be associated with seizure-induced neuronal loss in the hippocampus. Magnetic resonance (MR)-based electrical conductivity imaging may be an applicable technique to non-invasively identify brain damage after a seizure.

Near the bone remodeling compartments (BRC), extracellular calcium concentration (Ca2+o) is locally elevated and bone marrow stromal cells (BMSCs) close to the BRC can be exposed to high calcium concentration. The calcium-sensing receptor (CaSR) is known to play a key role in maintaining extracellular calcium homeostasis by sensing fluctuations in the levels of extracellular calcium (Ca2+o). When human BMSCs (hBMSCs) were exposed to various calcium concentrations (1.8, 3, 5, 10, 30 mM), moderate-high extracellular calcium concentrations (3–5 mM) stimulated proliferation, while a high calcium concentration (30 mM) inhibited the proliferation. Exposure to various calcium concentrations did not induce significant differences in the apoptotic cell fraction. Evaluation of multi-lineage differentiation potential showed no significant difference among various calcium concentration groups, except for the high calcium concentration (30 mM) treated group, which resulted in increased calcification after in vitro osteogenic differentiation. Treatment of NPS2143, a CaSR inhibitor, abolished the stimulatory effect on hBMSCs proliferation and migration indicating that CaSR is involved. These results suggest that the calcium concentration gradient near the BRC may play an important role in bone remodeling by acting as an osteoblast–osteoclast coupling mechanism through CaSR.

Purpose To realistically map the electric fields of biological tissues using a diffusion tensor magnetic resonance electrical impedance tomography (DT-MREIT) method to estimate tissue response during electrical stimulation. Methods Imaging experiments were performed using chunks of bovine muscle. Two silver wire electrodes were positioned inside the muscle tissue for electrical stimulation. Electric pulses were applied with a 100-V amplitude and 100-μs width using a voltage stimulator. During electrical stimulation, we collected DT-MREIT data from a 3T magnetic resonance imaging scanner. We adopted the projected current density method to calculate the electric field. Based on the relation between the water diffusion tensor and the conductivity tensor, we computed the position-dependent scale factor using the measured magnetic flux density data. Then, a final conductivity tensor map was reconstructed using the multiplication of the water diffusion tensor and the scale factor. Results The current density images from DT-MREIT data represent the internal current flows that exist not only in the electrodes but also in surrounding regions. The reconstructed electric filed map from our anisotropic conductivity tensor with the projected current density shows coverage that is more than 2 times as wide, and higher signals in both the electrodes and surrounding tissues, than the previous isotropic method owing to the consideration of tissue anisotropy. Conclusions An electric field map obtained by an anisotropic reconstruction method showed different patterns from the results of the previous isotropic reconstruction method. Since accurate electric field mapping is important to correctly estimate the coverage of the electrical treatment, future studies should include more rigorous validations of the new method through in vivo and in situ experiments.

New methods for in vivo mapping of brain responses during deep brain stimulation (DBS) are indispensable to secure clinical applications. Assessment of current density distribution, induced by internally injected currents, may provide an alternative method for understanding the therapeutic effects of electrical stimulation. The current flow and pathway are affected by internal conductivity, and can be imaged using magnetic resonance-based conductivity imaging methods. Magnetic resonance electrical impedance tomography (MREIT) is an imaging method that can enable highly resolved mapping of electromagnetic tissue properties such as current density and conductivity of living tissues. In the current study, we experimentally imaged current density distribution of in vivo canine brains by applying MREIT to electrical stimulation. The current density maps of three canine brains were calculated from the measured magnetic flux density data. The absolute current density values of brain tissues, including gray matter, white matter, and cerebrospinal fluid were compared to assess the active regions during DBS. The resulting current density in different tissue types may provide useful information about current pathways and volume activation for adjusting surgical planning and understanding the therapeutic effects of DBS.

When we use a conductive fabric as a pressure sensor, it is necessary to quantitatively understand its electromechanical property related with the applied pressure. We investigated electromechanical properties of three different conductive fabrics using the electrical impedance spectroscopy (EIS). We found that their electrical impedance spectra depend not only on the electrical properties of the conductive yarns, but also on their weaving structures. When we apply a mechanical tension or compression, there occur structural deformations in the conductive fabrics altering their apparent electrical impedance spectra. For a stretchable conductive fabric, the impedance magnitude increased or decreased under tension or compression, respectively. For an almost non-stretchable conductive fabric, both tension and compression resulted in decreased impedance values since the applied tension failed to elongate the fabric. To measure both tension and compression separately, it is desirable to use a stretchable conductive fabric. For any conductive fabric chosen as a pressure-sensing material, its resistivity under no loading conditions must be carefully chosen since it determines a measurable range of the impedance values subject to different amounts of loadings. We suggest the EIS method to characterize the electromechanical property of a conductive fabric in designing a thin and flexible fabric pressure sensor.

Anisotropy of biological tissues is a low-frequency phenomenon that is associated with the function and structure of cell membranes. Imaging of anisotropic conductivity has potential for the analysis of interactions between electromagnetic fields and biological systems, such as the prediction of current pathways in electrical stimulation therapy. To improve application to the clinical environment, precise approaches are required to understand the exact responses inside the human body subjected to the stimulated currents. In this study, we experimentally evaluate the anisotropic conductivity tensor distribution of canine brain tissues, using a recently developed diffusion tensor-magnetic resonance electrical impedance tomography method. At low frequency, electrical conductivity of the biological tissues can be expressed as a product of the mobility and concentration of ions in the extracellular space. From diffusion tensor images of the brain, we can obtain directional information on diffusive movements of water molecules, which correspond to the mobility of ions. The position dependent scale factor, which provides information on ion concentration, was successfully calculated from the magnetic flux density, to obtain the equivalent conductivity tensor. By combining the information from both techniques, we can finally reconstruct the anisotropic conductivity tensor images of brain tissues. The reconstructed conductivity images better demonstrate the enhanced signal intensity in strongly anisotropic brain regions, compared with those resulting from previous methods using a global scale factor.

Electromagnetic fields provide fundamental data for the imaging of electrical tissue properties, such as conductivity and permittivity, in recent magnetic resonance (MR)-based tissue property mapping. The induced voltage, current density, and magnetic flux density caused by externally injected current are critical factors for determining the image quality of electrical tissue conductivity. As a useful tool to identify bio-electromagnetic phenomena, precise approaches are required to understand the exact responses inside the human body subject to an injected currents. In this study, we provide the numerical simulation results of electromagnetic field mapping of brain tissues using a MR-based conductivity imaging method. First, we implemented a realistic three-dimensional human anisotropic head model using high-resolution anatomical and diffusion tensor MR images. The voltage, current density, and magnetic flux density of brain tissues were imaged by injecting 1 mA of current through pairs of electrodes on the surface of our head model. The current density map of anisotropic brain tissues was calculated from the measured magnetic flux density based on the linear relationship between the water diffusion tensor and the electrical conductivity tensor. Comparing the current density to the previous isotropic model, the anisotropic model clearly showed the differences between the brain tissues. This originates from the enhanced signals by the inherent conductivity contrast as well as the actual tissue condition resulting from the injected currents.

A continuous Nondestructive monitoring method is required to apply proper feedback controls during tissue regeneration. Conductivity is one of valuable information to assess the physiological function and structural formation of regenerated tissues or cultured cells. However, conductivity imaging methods suffered from inherited ill-posed characteristics in image reconstruction, unknown boundary geometry, uncertainty in electrode position, and systematic artifacts. In order to overcome the limitation of microscopic electrical impedance tomography (micro-EIT), we applied a 3D-specific container with a fixed boundary geometry and electrode configuration to maximize the performance of Graz consensus reconstruction algorithm for EIT (GREIT). The separation of driving and sensing electrodes allows us to simplify the hardware complexity and obtain higher measurement accuracy from a large number of small sensing electrodes. We investigated the applicability of the GREIT to 3D micro-EIT images via numerical simulations and large-scale phantom experiments. We could reconstruct multiple objects regardless of the location. The resolution was 5 mm3 with 30 dB SNR and the position error was less than 2.54 mm. This shows that the new micro-EIT system integrated with GREIT is robust with the intended resolution. With further refinement and scaling down to a microscale container, it may be a continuous nondestructive monitoring tool for tissue engineering applications.