Pharmacodynamics Research on Danggui-Shaoyao-San through Body Fluid Indexes of Spleen Deficiency-water Dampness Rats using Bio-impedance Technology

BACKGROUND

Spleen deficiency-water dampness symptom is closely related to body fluid-mediated organism metabolism and circulation. However, previous clinical evaluation of spleen deficiency-water dampness model was based only on body weight, D-xylose excretion rate, serum gastrin content, etc. Therefore, we established a large sample of normal rats and model rats experiment to verify the scientific nature of bio-impedance measuring body fluid indexes for evaluation of the modeling state. Pharmacodynamics research on Danggui-Shaoyao- San (DSS) was conducted through body fluid index changes of rats using bio-impedance technology.

METHODS

A spleen deficiency-water dampness symptom rat model was established through an inappropriate diet combined with excess fatigue. Experimental rats were divided into a normal control group, a model control group, a positive drug control group (hydrochlorothiazide), a blood-activating group, a water-disinhibiting group, and a DSS group. Total Body Water/Body Weight (TBW%), extracellular fluid/total body water content (ECF%), intracellular fluid/total body water content (ICF%), extracellular fluid/intracellular fluid (ECF/ICF), fat mass/body weight (FM%), fat-free mass/body weight (FFM%), and fat mass/fat-free mass (FM/FFM) of 150 rats were detected by a Bio-Imp Vet Body analyzer.

RESULTS

The TBW% of the model control group increased significantly, and the FM/FFM was significantly reduced compared with the normal group (P < 0.05) (P < 0.01), showing symptoms of spleen deficiency and diarrhea; the TBW% of the blood-activating group, and the waterdisinhibiting group decreased significantly, and the FM/FFM increased significantly (P < 0.05) (P < 0.01). The TBW% and FM/FFM in the water-disinhibiting group had returned to nearnormal values compared with the model control group. The blood-activating and waterdisinhibiting split prescriptions in DSS are both effective in treating spleen deficiency-water dampness rats. Comparatively, the fluid-regulating effect of split prescriptions in DSS was even stronger than that of DSS as shown in the present study.

CONCLUSIONS

These findings suggest that using bio-impedance technology to measure body fluid indexes can pave a road for further exploring the molecular mechanism of the reason why the blood-activating and disinhibit-water split prescriptions in DSS are both effective in treating spleen deficiency-water dampness rats.

Abdominal Aortic Aneurysm Detection in Bioelectrical Impedance Cardiovascular Screenings-A Pilot Study

Screening and diagnosing abdominal aortic aneurysms (AAA) are currently dependent on imaging studies such as ultrasound or computed tomography angiography. All imaging studies offer distinct advantages but also suffer from inherent limitations such as examiner dependency or ionizing radiation. Bioelectrical impedance analysis has previously been investigated with respect to its use in the detection of several cardiovascular and renal pathologies. The present pilot study assessed the feasibility of AAA detection based on bioimpedance analysis. In this single-center exploratory pilot study, measurements were conducted among three different cohorts: patients with AAA, end-stage renal disease patients without AAA, and healthy controls. The device used in the study, CombynECG, is an open-market accessible device for segmental bioelectrical impedance analysis. The data was preprocessed and used to train four different machine learning models on a randomized training sample (80% of the full dataset). Each model was then evaluated on a test set (20% of the full dataset). The total sample included 22 patients with AAA, 16 chronic kidney disease patients, and 23 healthy controls. All four models showed strong predictive performance in the test partitions. Specificity ranged from 71.4 to 100%, while sensitivity ranged from 66.7 to 100%. The best-performing model had 100% accuracy for classification when applied to the test sample. Additionally, an exploratory analysis to approximate the maximum AAA diameter was conducted. An association analysis revealed several impedance parameters that might possess predictive ability with respect to aneurysm size. AAA detection via bioelectrical impedance analysis is technically feasible and appears to be a promising technology for large-scale clinical studies and routine clinical screening assessments.

Electrical Impedance Tomography: From the Traditional Design to the Novel Frontier of Wearables

Electrical impedance tomography (EIT) is a medical imaging technique based on the injection of a current or voltage pattern through electrodes on the skin of the patient, and on the reconstruction of the internal conductivity distribution from the voltages collected by the electrodes. Compared to other imaging techniques, EIT shows significant advantages: it does not use ionizing radiation, is non-invasive and is characterized by high temporal resolution. Moreover, its low cost and high portability make it suitable for real-time, bedside monitoring. However, EIT is also characterized by some technical limitations that cause poor spatial resolution. The possibility to design wearable devices based on EIT has recently given a boost to this technology. In this paper we reviewed EIT physical principles, hardware design and major clinical applications, from the classical to a wearable setup. A wireless and wearable EIT system seems a promising frontier of this technology, as it can both facilitate making clinical measurements and open novel scenarios to EIT systems, such as home monitoring.

Compensation for Electrode Detachment in Electrical Impedance Tomography with Wearable Textile Electrodes

Electrical impedance tomography (EIT) is a radiation-free and noninvasive medical image reconstruction technique in which a current is injected and the reflected voltage is received through electrodes. EIT electrodes require good connection with the skin for data acquisition and image reconstruction. However, detached electrodes are a common occurrence and cause measurement errors in EIT clinical applications. To address these issues, in this study, we proposed a method for detecting faulty electrodes using the differential voltage value of the detached electrode in an EIT system. Additionally, we proposed the voltage-replace and voltage-shift methods to compensate for invalid data from the faulty electrodes. In this study, we present the simulation, experimental, and in vivo chest results of our proposed methods to verify and evaluate the feasibility of this approach.

Electrical Impedance Analysis for Lung Cancer: A Prospective, Multicenter, Blind Validation Study

Hypothesis

Patients with cancer have different impedances or conductances than patients with benign normal tissue; thus, we can apply electrical impedance analysis (EIA) to identify patients with cancer.

Method

To evaluate EIA’s efficacy and safety profile in diagnosing pulmonary lesions, we conducted a prospective, multicenter study among patients with pulmonary lesions recruited from 4 clinical centers (Zhongshan Hospital Ethics Committee, Approval No. 2015-16R and 2017-035(3). They underwent EIA to obtain an Algorithm Composite Score or ‘Prolung Index,’ PI. The classification threshold of 29 was first tested in an analytical validation set of 144 patients and independently validated in a clinical validation set of 418 patients. The subject’s final diagnosis depended on histology and a 2-year follow-up.

Results

In total, 418 patients completed the entire protocol for clinical validation, with 186 true positives, 145 true negatives, 52 false positives, and 35 false negatives. The sensitivity, specificity, and diagnostic yield were 84% (95% CI 79.3%-89.0%), 74% (95% CI 67.4%-79.8%), and 79% (95%CI 75.3%-83.1%), respectively, and did not differ according to age, sex, smoking history, body mass index, or lesion types. The sensitivity of small lesions was comparable to that of large lesions (p = 0.13). Four hundred eighty-four patients who underwent the analysis received a safety evaluation. No adverse events were considered to be related to the test.

Conclusion

Electrical impedance analysis is a safe and efficient tool for risk stratification of pulmonary lesions, especially for patients with a suspicious lung lesion.

System introduction and evaluation of the first Chinese chest EIT device for ICU applications

Chest electrical impedance tomography (EIT) is a promising application which is used to monitor the ventilation and perfusion of the lung at the bedside dynamically. The aim of the study was to introduce the first Chinese made chest EIT device for ICU application (Pulmo EIT-100). The system design of the hardware and software was briefly introduced. The performance of the system was compared to PulmoVista 500 (Dräger Medical) in healthy volunteers. The EIT system Pulmo EIT-100 consists of impedance measurement module, power supply module, PC all-in-one machine, medical cart and accessories. The performance of the system current source and voltage measurement unit was tested. A total of 50 healthy lung volunteers were prospectively examined. Subjects were asked to perform repetitive slow vital capacity (SVC) maneuvers with a spirometer. EIT measurements were performed in the following sequence during each SVC with: (1) Pulmo EIT-100, (2) PulmonVista500, (3) Pulmo EIT-100 and (4) PulmonVista500. Linearity and regional ventilation distribution of the reconstructed images from two devices were compared. The output frequency stability of the current source was 2 ppm. The amplitude error within one hour was less than 0.32‰. The output impedance of the current source was about 50kΩ. The signal-to-noise ratio of each measurement channel was ≥ 60 dB. For fixed resistance measurements, the measured values drifted about 0.08% within one hour. For human subjects, the correlations between the spirometry volume and EIT impedance from two devices were both 0.99 ± 0.01. No statistical significances were found in the parameters investigated. The repeatability (variability) of measures from the same device was comparable. Our EIT device delivers reliable data and might be used for patient measurement in a clinical setting.

Locating Functionalized Gold Nanoparticles Using Electrical Impedance Tomography

OBJECTIVE

An imaging device to locate functionalized nanoparticles, whereby therapeutic agents are transported from the site of administration specifically to diseased tissues, remains a challenge for pharmaceutical research. Here, we show a new method based on electrical impedance tomography (EIT) to provide images of the location of gold nanoparticles (GNPs) and the excitation of GNPs with radio frequencies (RF) to change impedance permitting an estimation of their location in cell models Methods: We have created an imaging system using quantum cluster GNPs as a contrast agent, activated with RF fields to heat the functionalized GNPs, which causes a change in impedance in the surrounding region. This change is then identified with EIT.

RESULTS

Images of impedance changes of around 804% are obtained for a sample of citrate stabilized GNPs in a solution of phosphate-buffered saline. A second quantification was carried out using colorectal cancer cells incubated with culture media, and the internalization of GNPs into the colorectal cancer cells was undertaken to compare them with the EIT images. When the cells were incubated with functionalized GNPs, the change was more apparent, approximately 402%. This change was reflected in the EIT image as the cell area was more clearly identifiable from the rest of the area.

SIGNIFICANCE

EIT can be used as a new method to locate functionalized GNPs in human cells and help in the development of GNP-based drugs in humans to improve their efficacy in the future.

Feasibility of Temperature Control by Electrical Impedance Tomography in Hyperthermia

We present a simulation study investigating the feasibility of electrical impedance tomography (EIT) as a low cost, noninvasive technique for hyperthermia (HT) treatment monitoring and adaptation. Temperature rise in tissues leads to perfusion and tissue conductivity changes that can be reconstructed in 3D by EIT to noninvasively map temperature and perfusion. In this study, we developed reconstruction methods and investigated the achievable accuracy of EIT by simulating HT treatmentlike scenarios, using detailed anatomical models with heterogeneous conductivity distributions. The impact of the size and location of the heated region, the voltage measurement signal-to-noise ratio, and the reference model personalization and accuracy were studied. Results showed that by introducing an iterative reconstruction approach, combined with adaptive prior regions and tissue-dependent penalties, planning-based reference models, measurement-based reweighting, and physics-based constraints, it is possible to map conductivity-changes throughout the heated domain, with an accuracy of around 5% and cm-scale spatial resolution. An initial exploration of the use of multifrequency EIT to separate temperature and perfusion effects yielded promising results, indicating that temperature reconstruction accuracy can be in the order of 1 ∘C. Our results suggest that EIT can provide valuable real-time HT monitoring capabilities. Experimental confirmation in real-world conditions is the next step.

Bedside noninvasive monitoring of mechanically ventilated patients

PURPOSE OF REVIEW

Among noninvasive lung imaging techniques that can be employed at the bedside electrical impedance tomography (EIT) and lung ultrasound (LUS) can provide dynamic, repeatable data on the distribution regional lung ventilation and response to therapeutic manoeuvres.In this review, we will provide an overview on the rationale, basic functioning and most common applications of EIT and Point of Care Ultrasound (PoCUS, mainly but not limited to LUS) in the management of mechanically ventilated patients.

RECENT FINDINGS

The use of EIT in clinical practice is supported by several studies demonstrating good correlation between impedance tomography data and other validated methods of assessing lung aeration during mechanical ventilation. Similarly, LUS also correlates with chest computed tomography in assessing lung aeration, its changes and several pathological conditions, with superiority over other techniques. Other PoCUS applications have shown to effectively complement the LUS ultrasound assessment of the mechanically ventilated patient.

SUMMARY

Bedside techniques - such as EIT and PoCUS - are becoming standards of the care for mechanically ventilated patients to monitor the changes in lung aeration, ventilation and perfusion in response to treatment and to assess weaning from mechanical ventilation.

Using electrical impedance tomography for rapid determination of starch and soluble sugar contents in Rosa hybrida

Soluble sugars and starches are important metabolites of plant life and physiological markers of plant stress response. There is an urgent need to develop a non-destructive and rapid method for determining plant starch and soluble sugar contents. Electrical impedance tomography (EIT) technology has been used to determine the physiological state and cold resistance of select plant tissues. However, so far there have been no reports on the use of EIT for the rapid estimation of soluble sugar and starch contents. In this study, EIT was used to obtain reconstructed voltage values and estimate starch and soluble sugar contents in the stems of three Rosa hybrida cultivars during February to May, which were grown in the Specimen Park (38° 50′ N, 115° 26′ E) of Hebei Agricultural University, Baoding City, Hebei Province, China. Stems from two of the cultivars were used for establishing regression models for starch and soluble sugar contents as functions of reconstructed voltage values. The third cultivar was used to test the accuracy of the regression models. The quadratic regression model was best for determining soluble sugar content and the logarithmic regression model was best for determining starch content. Thus, this research provided technical support for using EIT to analyze changes in physiological parameters and to rapidly estimate physiological indexes of plants. More studies were now needed to validate the results in this paper.

Managing erroneous measurements of dynamic brain electrical impedance tomography after reconnection of faulty electrodes

OBJECTIVE

Electrode detachment may occur during dynamic brain electrical impedance tomography (EIT) measurements. After the faulty electrodes have been reset, EIT can restore to steady monitoring but the corrupted data, which will challenge interpretation of the results, are notoriously difficult to recover.

APPROACH

Here, a piecewise processing method (PPM) is introduced to manage the erroneous EIT data after reattachment of faulty electrodes. In the PPM, we define the three phases before, during and after reconnection of the faulty electrode as PI, PII and PIII, respectively. Using this definition, an empirical mode decomposition-based interpolation method is introduced to compensate the corrupted data in PII, using the valid measurements in PI and PIII. Then, the compensated data in PII are spliced at the end of PI. Thus, there will be a surge at the junction of PII and PIII due to the changes in contact state of the repositioned electrodes. Finally, to ensure all the EIT data are obtained under constant electrode settings, we calculate the above changes and eliminate them from the data after PII. To verify the performance of the PPM, experiments based on head models, with anatomical structures and with human subjects were conducted. Metrics including permutation entropy (PE) and image correlation (IC) were proposed to measure the stability of the signal and the quality of the reconstructed EIT images, respectively.

MAIN RESULTS

The results demonstrated that the PE of the processed data was reduced to 0.25 and the IC improved to 0.78.

SIGNIFICANCE

Without iterative calculations the PPM could efficiently manage the erroneous EIT data after reattachment of the faulty electrodes.

Electrical impedance tomography in perioperative medicine: careful respiratory monitoring for tailored interventions

BACKGROUND

Electrical impedance tomography (EIT) is a non-invasive radiation-free monitoring technique that provides images based on tissue electrical conductivity of the chest. Several investigations applied EIT in the context of perioperative medicine, which is not confined to the intraoperative period but begins with the preoperative assessment and extends to postoperative follow-up.

MAIN BODY

EIT could provide careful respiratory monitoring in the preoperative assessment to improve preparation for surgery, during anaesthesia to guide optimal ventilation strategies and to monitor the hemodynamic status and in the postoperative period for early detection of respiratory complications. Moreover, EIT could further enhance care of patients undergoing perioperative diagnostic procedures. This narrative review summarizes the latest evidence on the application of this technique to the surgical patient, focusing also on possible future perspectives.

CONCLUSIONS

EIT is a promising technique for the perioperative assessment of surgical patients, providing tailored adaptive respiratory and haemodynamic monitoring. Further studies are needed to address the current technological limitations, confirm the findings and evaluate which patients can benefit more from this technology.

Understanding the physical relations governing the noise navigator

Purpose

The noise navigator is a passive way to detect physiological motion occurring in a patient through thermal noise modulations measured by standard clinical radiofrequency receive coils. The aim is to gain a deeper understanding of the potential and applications of physiologically induced thermal noise modulations.

Methods

Numerical electromagnetic simulations and MR measurements were performed to investigate the relative contribution of tissue displacement versus modulation of the dielectric lung properties over the respiratory cycle, the impact of coil diameter and position with respect to the body. Furthermore, the spatial motion sensitivity of specific noise covariance matrix elements of a receive array was investigated.

Results

The influence of dielectric lung property variations on the noise variance is negligible compared to tissue displacement. Coil size affected the thermal noise variance modulation, but the location of the coil with respect to the body had a larger impact. The modulation depth of a 15 cm diameter stationary coil approximately 3 cm away from the chest (i.e. radiotherapy setup) was 39.7% compared to 4.2% for a coil of the same size on the chest, moving along with respiratory motion. A combination of particular noise covariance matrix elements creates a specific spatial sensitivity for motion.

Conclusions

The insight gained on the physical relations governing the noise navigator will allow for optimized use and development of new applications. An optimized combination of elements from the noise covariance matrix offer new ways of performing, e.g. motion tracking.

An on-line processing strategy for head movement interferences removal of dynamic brain electrical impedance tomography based on wavelet decomposition

BACKGROUND

Head movement interferences are a common problem during prolonged dynamic brain electrical impedance tomography (EIT) clinical monitoring. Head movement interferences mainly originate from body movements of patients and nursing procedures performed by medical staff, etc. These body movements will lead to variation in boundary voltage signals, which affects image reconstruction.

METHODS

This study employed a data preprocessing method based on wavelet decomposition to inhibit head movement interferences in brain EIT data. Mixed Gaussian models were applied to describe the distribution characteristics of brain EIT data. We identified head movement signal through the differences in distribution characteristics of corresponding wavelet decomposition coefficients between head movement artifacts and normal signals, and then managed the contaminated data with improved on-line wavelet processing methods.

RESULTS

To validate the efficacy of the method, simulated signal experiments and human data experiments were performed. In the simulation experiment, the simulated movement artifact was significantly reduced and data quality was improved with indicators' increase in PRD and correlation coefficient. Human data experiments demonstrated that this method effectively suppressed head movement in signals and reduce artifacts resulting from head movement artifacts in images.

CONCLUSION

In this paper, we proposed an on-line strategy to manage the head movement interferences from the brain EIT data based on the distribution characteristics of wavelet coefficients. Our strategy is capable of reducing the movement interference in the data and improving the reconstructed images. This work would improve the clinical practicability of brain EIT and contribute to its further promotion.

Monitoring of regional lung ventilation using electrical impedance tomography

Among recent lung imaging techniques and devices, electrical impedance tomography (EIT) can provide dynamic information on the distribution regional lung ventilation. EIT images possess a high temporal and functional resolution allowing the visualization of dynamic physiological and pathological changes on a breath-by-breath basis. EIT detects changes in electric impedance (i.e., changes in gas/fluid ratio) and describes them in real time, both visually through images and waveforms, and numerically, allowing the clinician to monitor disease evolution and response to treatment. The use of EIT in clinical practice is supported by several studies demonstrating a good correlation between impedance tomography data and other validated methods of measuring lung volume. In this review, we will provide an overview on the rationale, basic functioning and most common applications of EIT in the management of mechanically ventilated patients.

Three-Dimensional Holographic Electromagnetic Imaging for Accessing Brain Stroke

The authors recently developed a two-dimensional (2D) holographic electromagnetic induction imaging (HEI) for biomedical imaging applications. However, this method was unable to detect small inclusions accurately. For example, only one of two inclusions can be detected in the reconstructed image if the two inclusions were located at the same XY plane but in different Z-directions. This paper provides a theoretical framework of three-dimensional (3D) HEI to accurately and effectively detect inclusions embedded in a biological object. A numerical system, including a realistic head phantom, a 16-element excitation sensor array, a 16-element receiving sensor array, and image processing model has been developed to evaluate the effectiveness of the proposed method for detecting small stroke. The achieved 3D HEI images have been compared with 2D HEI images. Simulation results show that the 3D HEI method can accurately and effectively identify small inclusions even when two inclusions are located at the same XY plane but in different Z-directions. This preliminary study shows that the proposed method has the potential to develop a useful imaging tool for the diagnosis of neurological diseases and injuries in the future.

Combing signal processing methods with algorithm priori information to produce synergetic improvements on continuous imaging of brain electrical impedance tomography

Dynamic electrical impedance tomography (EIT) promises to be a valuable technique for monitoring the development of brain injury. But in practical long-term monitoring, noise and interferences may cause insufficient image quality. To help unveil intracranial conductivity changes, signal processing methods were introduced to improve EIT data quality and algorithms were optimized to be more robust. However, gains for EIT image reconstruction can be significantly increased if we combine the two techniques properly. The basic idea is to apply the priori information in algorithm to help de-noise EIT data and use signal processing to optimize algorithm. First, we process EIT data with principal component analysis (PCA) and reconstruct an initial CT-EIT image. Then, as the priori that changes in scalp and skull domains are unwanted, we eliminate their corresponding boundary voltages from data sets. After the two-step denoising process, we finally re-select a local optimal regularization parameter and accomplish the reconstruction. To evaluate performances of the signal processing-priori information based reconstruction (SPR) method, we conducted simulation and in-vivo experiments. The results showed SPR could improve brain EIT image quality and recover the intracranial perturbations from certain bad measurements, while for some measurement data the generic reconstruction method failed.

Image Reconstruction Under Contact Impedance Effect in Micro Electrical Impedance Tomography Sensors

Contact impedance has an important effect on micro electrical impedance tomography (EIT) sensors compared to conventional macro sensors. In the present work, a complex contact impedance effect ratio ξ is defined to quantitatively evaluate the effect of the contact impedance on the accuracy of the reconstructed images by micro EIT. Quality of the reconstructed image under various ξ is estimated by the phantom simulation to find the optimum algorithm. The generalized vector sampled pattern matching (GVSPM) method reveals the best image quality and the best tolerance to ξ. Moreover, the images of yeast cells sedimentary distribution in a multilayered microchannel are reconstructed by the GVSPM method under various mean magnitudes of contact impedance effect ratio |ξ|. The result shows that the best image quality that has the smallest voltage error U_E = 0.581 is achieved with measurement frequency f = 1 MHz and mean magnitude |ξ| = 26. In addition, the reconstructed images of cells distribution become improper while f < 10 kHz and mean value of |ξ| > 2400.

Applications of Bioimpedance Measurement Techniques in Tissue Engineering

Rapid development in the field of tissue engineering necessitates implementation of monitoring methods for evaluation of the viability and characteristics of the cell cultures in a real-time, non-invasive and non-destructive manner. Current monitoring techniques are mainly histological and require labeling and involve destructive tests to characterize cell cultures. Bioimpedance measurement technique which benefits from measurement of electrical properties of the biological tissues, offers a non-invasive, label-free and real-time solution for monitoring tissue engineered constructs. This review outlines the fundamentals of bioimpedance, as well as electrical properties of the biological tissues, different types of cell culture constructs and possible electrode configuration set ups for performing bioimpedance measurements on these cell cultures. In addition, various bioimpedance measurement techniques and their applications in the field of tissue engineering are discussed.

Unveiling the development of intracranial injury using dynamic brain EIT: an evaluation of current reconstruction algorithms

OBJECTIVE

Dynamic brain electrical impedance tomography (EIT) is a promising technique for continuously monitoring the development of cerebral injury. While there are many reconstruction algorithms available for brain EIT, there is still a lack of study to compare their performance in the context of dynamic brain monitoring.

APPROACH

To address this problem, we develop a framework for evaluating different current algorithms with their ability to correctly identify small intracranial conductivity changes. Firstly, a simulation 3D head phantom with realistic layered structure and impedance distribution is developed. Next several reconstructing algorithms, such as back projection (BP), damped least-square (DLS), Bayesian, split Bregman (SB) and GREIT are introduced. We investigate their temporal response, noise performance, location and shape error with respect to different noise levels on the simulation phantom. The results show that the SB algorithm demonstrates superior performance in reducing image error. To further improve the location accuracy, we optimize SB by incorporating the brain structure-based conductivity distribution priors, in which differences of the conductivities between different brain tissues and the inhomogeneous conductivity distribution of the skull are considered. We compare this novel algorithm (called SB-IBCD) with SB and DLS using anatomically correct head shaped phantoms with spatial varying skull conductivity. Main results and Significance: The results showed that SB-IBCD is the most effective in unveiling small intracranial conductivity changes, where it can reduce the image error by an average of 30.0% compared to DLS.

A novel 3D-printed head phantom with anatomically realistic geometry and continuously varying skull resistivity distribution for electrical impedance tomography

Phantom experiments are an important step for testing during the development of new hardware or imaging algorithms for head electrical impedance tomography (EIT) studies. However, due to the sophisticated anatomical geometry and complex resistivity distribution of the human head, constructing an accurate phantom for EIT research remains challenging, especially for skull modelling. In this paper, we designed and fabricated a novel head phantom with anatomically realistic geometry and continuously varying skull resistivity distribution based on 3D printing techniques. The skull model was constructed by simultaneously printing the distinct layers inside the skull with resistivity-controllable printing materials. The entire phantom was composed of saline skin, a 3D-printed skull, saline cerebrospinal fluid (CSF) and 3D-printed brain parenchyma. The validation results demonstrated that the resistivity of the phantom was in good agreement with that of human tissue and was stable over time, and the new phantom performed well in EIT imaging. This paper provides a standardized, efficient and reproducible method for the construction of a head phantom for EIT that could be easily adapted to other conditions for manufacturing head phantoms for brain function research, such as transcranial direct current stimulation (TDCS) and electroencephalography (EEG).

A Versatile and Reproducible Multi-Frequency Electrical Impedance Tomography System

A highly versatile Electrical Impedance Tomography (EIT) system, nicknamed the ScouseTom, has been developed. The system allows control over current amplitude, frequency, number of electrodes, injection protocol and data processing. Current is injected using a Keithley 6221 current source, and voltages are recorded with a 24-bit EEG system with minimum bandwidth of 3.2 kHz. Custom PCBs interface with a PC to control the measurement process, electrode addressing and triggering of external stimuli. The performance of the system was characterised using resistor phantoms to represent human scalp recordings, with an SNR of 77.5 dB, stable across a four hour recording and 20 Hz to 20 kHz. In studies of both haeomorrhage using scalp electrodes, and evoked activity using epicortical electrode mats in rats, it was possible to reconstruct images matching established literature at known areas of onset. Data collected using scalp electrode in humans matched known tissue impedance spectra and was stable over frequency. The experimental procedure is software controlled and is readily adaptable to new paradigms. Where possible, commercial or open-source components were used, to minimise the complexity in reproduction. The hardware designs and software for the system have been released under an open source licence, encouraging contributions and allowing for rapid replication.

Fast detection and data compensation for electrodes disconnection in long-term monitoring of dynamic brain electrical impedance tomography

Background

Electrode disconnection is a common occurrence during long-term monitoring of brain electrical impedance tomography (EIT) in clinical settings. The data acquisition system suffers remarkable data loss which results in image reconstruction failure. The aim of this study was to: (1) detect disconnected electrodes and (2) account for invalid data.

Methods

Weighted correlation coefficient for each electrode was calculated based on the measurement differences between well-connected and disconnected electrodes. Disconnected electrodes were identified by filtering out abnormal coefficients with discrete wavelet transforms. Further, previously valid measurements were utilized to establish grey model. The invalid frames after electrode disconnection were substituted with the data estimated by grey model. The proposed approach was evaluated on resistor phantom and with eight patients in clinical settings.

Results

The proposed method was able to detect 1 or 2 disconnected electrodes with an accuracy of 100%; to detect 3 and 4 disconnected electrodes with accuracy of 92 and 84% respectively. The time cost of electrode detection was within 0.018 s. Further, the proposed method was capable to compensate at least 60 subsequent frames of data and restore the normal image reconstruction within 0.4 s and with a mean relative error smaller than 0.01%.

Conclusions

In this paper, we proposed a two-step approach to detect multiple disconnected electrodes and to compensate the invalid frames of data after disconnection. Our method is capable of detecting more disconnected electrodes with higher accuracy compared to methods proposed in previous studies. Further, our method provides estimations during the faulty measurement period until the medical staff reconnects the electrodes. This work would improve the clinical practicability of dynamic brain EIT and contribute to its further promotion.

On the influence of spread constant in radial basis networks for electrical impedance tomography

Electrical impedance tomography (EIT) is a non-invasive imaging technique. The main task of this work is to solve a non-linear inverse problem, for which several techniques have been suggested, but none of which gives a very high degree of accuracy. This paper introduces a novel approach, based on radial basis function (RBF) artificial neural networks (ANNs), to solve this problem, and uses several ANNs to obtain the best solution to the EIT inverse problem. ANNs have the potential to directly estimate the solution of the inverse problem with a high degree of accuracy. While different radial basis neural networks do not always perform well on different problems, they usually give good results on some specific problems. This paper evidences a strong correlation between the area of the target and the spread constant of the RBF network that gives the best reconstruction. A solution to automatically estimate the size of the target and pick the best neural network directly from voltage measurements is presented, making the reconstruction process automatic. By automatically selecting the best ANN for each specific set of voltage measurements, the proposed solution gives a more accurate reconstruction of both small and large targets.

The role of blood vessels in high-resolution volume conductor head modeling of EEG

Reconstruction of the electrical sources of human EEG activity at high spatio-temporal accuracy is an important aim in neuroscience and neurological diagnostics. Over the last decades, numerous studies have demonstrated that realistic modeling of head anatomy improves the accuracy of source reconstruction of EEG signals. For example, including a cerebro-spinal fluid compartment and the anisotropy of white matter electrical conductivity were both shown to significantly reduce modeling errors. Here, we for the first time quantify the role of detailed reconstructions of the cerebral blood vessels in volume conductor head modeling for EEG. To study the role of the highly arborized cerebral blood vessels, we created a submillimeter head model based on ultra-high-field-strength (7T) structural MRI datasets. Blood vessels (arteries and emissary/intraosseous veins) were segmented using Frangi multi-scale vesselness filtering. The final head model consisted of a geometry-adapted cubic mesh with over 17×10(6) nodes. We solved the forward model using a finite-element-method (FEM) transfer matrix approach, which allowed reducing computation times substantially and quantified the importance of the blood vessel compartment by computing forward and inverse errors resulting from ignoring the blood vessels. Our results show that ignoring emissary veins piercing the skull leads to focal localization errors of approx. 5 to 15mm. Large errors (>2cm) were observed due to the carotid arteries and the dense arterial vasculature in areas such as in the insula or in the medial temporal lobe. Thus, in such predisposed areas, errors caused by neglecting blood vessels can reach similar magnitudes as those previously reported for neglecting white matter anisotropy, the CSF or the dura - structures which are generally considered important components of realistic EEG head models. Our findings thus imply that including a realistic blood vessel compartment in EEG head models will be helpful to improve the accuracy of EEG source analyses particularly when high accuracies in brain areas with dense vasculature are required.

Ultrafast traveling wave dominates the electric organ discharge of Apteronotus leptorhynchus: an inverse modelling study

Identifying and understanding the current sources that give rise to bioelectric fields is a fundamental problem in the biological sciences. It is very difficult, for example, to attribute the time-varying features of an electroencephalogram recorded from the head surface to the neural activity of specific brain areas; model systems can provide important insight into such problems. Some species of fish actively generate an oscillating (c. 1000 Hz) quasi-dipole electric field to communicate and sense their environment in the dark. A specialized electric organ comprises neuron-like cells whose collective signal underlies this electric field. As a step towards understanding the detailed biophysics of signal generation in these fish, we use an anatomically-detailed finite-element modelling approach to reverse-engineer the electric organ signal over one oscillation cycle. We find that the spatiotemporal profile of current along the electric organ constitutes a travelling wave that is well-described by two spatial Fourier components varying in time. The conduction velocity of this wave is faster than action potential conduction in any known neuronal axon (>200 m/s), suggesting that the spatiotemporal features of high-frequency electric organ discharges are not constrained by the conduction velocities of spinal neuron pathways.

Bioimpedance Detection of Oral Lichen Planus Used as Preneoplastic Model

INTRODUCTION

Bioimpedance is a measure of the electrical properties of biological tissues. In the last two decades bioimpedance has been successfully introduced in clinical diagnosis of cancer. It has been demonstrated that tumoral tissues often show lower bioimpedance values than healthy tissues. The aim of this work is to assess the bioimpedentiometric differences between healthy and Oral Lichen Planus (OLP) affected oral mucosa, taking attention to the erosive form which may represent a potential pre-cancerous condition.

METHODS

52 patients affected by OLP were recruited for bioimpedance examination of oral mucosa. Four electrical properties, resistance (R), reactance (Xc), phase angle (θ) and impedance (Z) of the tongue and of the intraoral mucosa, were measured.

RESULTS

We observed a significant increase of Z and a significant decrease of θ values in correspondence of OLP lesions compared to healthy oral mucosa, and a marked decrease of Z values in correspondence of erosive OLP lesions.

CONCLUSIONS

These results provide evidence of the usefulness of bioimpedance assay for the characterization of healthy and clinically OLP affected mucosa. Bioimpedance is a valid aid in the early detection and clinical monitoring of the suspicious lesions which could lead to a potentially malignant evolution. The present research article is a valuable addition to the scientific literature of cancer prevention, and our findings can be considered extremely encouraging as they represent the initial step for a more wide clinical study for better define the different cut-off values in the different precancerous conditions occurring in the oral mucosa.

KDI: A wireless ECoG recording platform with impedance spectroscopy, electrical stimulation and real-time, lossless data compression

A power-efficient modular wireless platform has been designed for prototyping and pre-clinical evaluations of neural recording implants. This Kit for Designing Implants (KDI) is separated in function specific modules of 34×34mm which can be assembled as needed. This paper presents the design of new modules for this existing wireless KDI platform. These modules cover the functionalities of electrical stimulation for BCI neurofeedback, impedance spectroscopy for monitoring tissue reaction around implanted electrodes and a real-time lossless data compression algorithm for ECoG signals. This algorithm has been implemented using two different hardware solutions and its performances compared. The design and evaluation of these modules are a first step towards the inclusion of these functionalities into the next generation of WIMAGINE(®) implants.

A Sinusoidal Current Driver With an Extended Frequency Range and Multifrequency Operation for Bioimpedance Applications

This paper describes an alternative sinusoidal current driver suitable for bioimpedance applications where high frequency operation is required. The circuit is based on a transconductor and provides current outputs with low phase error for frequencies around its pole frequency. This extends the upper frequency operational limit of the current driver. Multifrequency currents can be generated where each individual frequency is phase corrected. Analysis of the circuit is presented together with simulation and experimental results which demonstrate the proof of concept for both single and dual frequency current drivers. Measurements on a discrete test version of the circuit demonstrate a phase reduction from 25° to 4° at 3 MHz for 2 mAp-p output current. The output impedance of the current driver is essentially constant at about 1.1 M Ω over a frequency range of 100 kHz to 5 MHz due to the introduction of the phase compensation. The compensation provides a bandwidth increase of a factor of about six for a residual phase delay of 4°.

A robust electrode configuration for bioimpedance measurement of respiration

Electrode configuration is an important issue in the continuous measurement of respiration using impedance pneumography (IP). The robust configuration is usually confirmed by comparing the amplitude of the IP signals acquired with different electrode configurations, while the relative change in waveform and the effects of body posture and respiratory pattern are ignored. In this study, the IP signals and respiratory volume are simultaneously acquired from 8 healthy subjects in supine, left lying, right lying and prone postures, and the subjects are asked to perform four respiratory patterns including free breathing, thoracic breathing, abdominal breathing and apnea. The IP signals are acquired with four different chest electrode configurations, and the volume are measured using pneumotachograph (PNT). Differences in correlation and absolute deviation between the IP-derived and PNT-derived respiratory volume are assessed. The influences of noise, respiratory pattern and body posture on the IP signals of different configurations have significant difference (p < 0.05). The robust electrode configuration is found on the axillary midline, which is suitable for long term respiration monitoring.

High-power CMOS current driver with accurate transconductance for electrical impedance tomography

Current drivers are fundamental circuits in bioimpedance measurements including electrical impedance tomography (EIT). In the case of EIT, the current driver is required to have a large output impedance to guarantee high current accuracy over a wide range of load impedance values. This paper presents an integrated current driver which meets these requirements and is capable of delivering large sinusoidal currents to the load. The current driver employs a differential architecture and negative feedback, the latter allowing the output current to be accurately set by the ratio of the input voltage to a resistor value. The circuit was fabricated in a 0.6- μm high-voltage CMOS process technology and its core occupies a silicon area of 0.64 mm (2) . It operates from a ± 9 V power supply and can deliver output currents up to 5 mA p-p. The accuracy of the maximum output current is within 0.41% up to 500 kHz, reducing to 0.47% at 1 MHz with a total harmonic distortion of 0.69%. The output impedance is 665 k Ω at 100 kHz and 372 k Ω at 500 kHz.

Electrical impedance tomography during major open upper abdominal surgery: a pilot-study

Background

Electrical impedance tomography (EIT) of the lungs facilitates visualization of ventilation distribution during mechanical ventilation. Its intraoperative use could provide the basis for individual optimization of ventilator settings, especially in patients at risk for ventilation-perfusion mismatch and impaired gas exchange, such as patients undergoing major open upper abdominal surgery. EIT throughout major open upper abdominal surgery could encounter difficulties in belt positioning and signal quality. Thus, we conducted a pilot-study and tested whether EIT is feasible in patients undergoing major open upper abdominal surgery.

Methods

Following institutional review board’s approval and written informed consent, we included patients scheduled for major open upper abdominal surgery of at least 3 hours duration. EIT measurements were conducted prior to intubation, at the time of skin incision, then hourly during surgery until shortly prior to extubation and after extubation. Number of successful intraoperative EIT measurements and reasons for failures were documented. From the valid measurements, a functional EIT image of changes in tidal impedance was generated for every time point. Regions of interest were defined as horizontal halves of the picture. Monitoring of ventilation distribution was assessed using the center of ventilation index, and also using the total and dorsal ventilated lung area. All parameter values prior to and post intubation as well as extubation were compared. A p < 0.05 was considered statistically significant.

Results

A total of 120 intraoperative EIT measurements during major abdominal surgery lasting 4-13 hours were planned in 14 patients. The electrode belt was attached between the 2^nd and 4^th intercostal space. Consecutive valid measurements could be acquired in 13 patients (93%). 111 intraoperative measurements could be retrieved as planned (93%). Main obstacle was the contact of skin electrodes. Despite the high belt position, distribution of tidal volume showed a significant shift of ventilation towards ventral lung regions after intubation. This was reversed after weaning from mechanical ventilation.

Conclusions

Despite a high belt position, monitoring of ventilation distribution is feasible in patients undergoing major open upper abdominal surgery lasting from 4 to 13 hours. Therefore, further interventional trials in order to optimize ventilatory management should be initiated.

Technological assessment of the biogalvanic method for tissue characterization

Biogalvanic cells have the potential to be used in characterizing biological tissue properties and ultimately tissue health. A biogalvanic cell is established by placing two differing metal electrodes across a target tissue allowing an electrical tissue-specific internal resistance to be determined. A novel data analysis method using least-squares fitting has been developed to more effectively determine the parameters of the biogalvanic system model proposed in the literature. The validity of the method has been examined through characterization of electrical models, ex vivo porcine tissue, and in vivo porcine tissue. Strong agreement between test results and the proposed characterization model has been shown. However, determined internal resistances are influenced by mechanical strain, current modulation direction and tissue thickness, indicating complexities at the electrode–tissue interface. These complexities undermine some assumptions upon which the biogalvanic model is based. Ultimately this technique could offer potential for use in minimally invasive surgery for discriminating tissue health but requires improved understanding and control of testing conditions.

Intracranial electrical impedance tomography: a method of continuous monitoring in an animal model of head trauma

BACKGROUND

Electrical impedance tomography (EIT) is a method that can render continuous graphical cross-sectional images of the brain's electrical properties. Because these properties can be altered by variations in water content, shifts in sodium concentration, bleeding, and mass deformation, EIT has promise as a sensitive instrument for head injury monitoring to improve early recognition of deterioration and to observe the benefits of therapeutic intervention. This study presents a swine model of head injury used to determine the detection capabilities of an inexpensive bedside EIT monitoring system with a novel intracranial pressure (ICP)/EIT electrode combination sensor on induced intraparenchymal mass effect, intraparenchymal hemorrhage, and cessation of brain blood flow. Conductivity difference images are shown in conjunction with ICP data, confirming the effects.

METHODS

Eight domestic piglets (3-4 weeks of age, mean 10 kg), under general anesthesia, were subjected to 4 injuries: induced intraparenchymal mass effect using an inflated, and later, deflated 0.15-mL Fogarty catheter; hemorrhage by intraparenchymal injection of 1-mL arterial blood; and ischemia/infarction by euthanasia. EIT and ICP data were recorded 10 minutes before inducing the injury until 10 minutes after injury. Continuous EIT and ICP monitoring were facilitated by a ring of circumferentially disposed cranial Ag/AgCl electrodes and 1 intraparenchymal ICP/EIT sensor electrode combination. Data were recorded at 100 Hz. Two-dimensional tomographic conductivity difference (Δσ) images, rendered using data before and after an injury, were displayed in real time on an axial circular mesh. Regions of interest (ROI) within the images were automatically selected as the upper or lower 5% of conductivity data depending on the nature of the injury. Mean Δσ within the ROIs and background were statistically analyzed. ROI Δσ was compared with the background Δσ after an injury event using an unpaired, unequal variance t test. Conductivity change within an ROI after injury was likewise compared with the same ROI before the injury making use of unpaired t tests with unequal variance.

RESULTS

Eight animal subjects were studied, each undergoing 4 injury events including euthanasia. Changes in conductivity due to injury showed expected pathophysiologic effects in an ROI identified within the middle of the left hemisphere; this localization is reasonable given the actual site of injury (left hemisphere) and spatial warping associated with estimating a 3-dimensional conductivity distribution in 2-dimensional space. Results are shown as mean ± 1 SD. When averaged across all 8 animals, balloon inflation caused the mean Δσ within the ROI to shift by -11.4 ± 10.9 mS/m; balloon deflation by +9.4 ± 8.8 mS/m; blood injection by +19.5 ± 11.5 mS/m; death by -12.6 ± 13.2 mS/m. All induced injuries were detectable to statistical significance (P < 0.0001).

CONCLUSION

This study confirms that the bedside EIT system with ICP/EIT combination sensor can detect induced trauma. Such a technique may hold promise for further research in the monitoring and management of traumatically brain-injured individuals.