Electrical impedance tomography (EIT): a review

Spatial sensitivity distribution assessment and Monte Carlo simulations for needle-based bioimpedance imaging during venipuncture using the finite element method

Despite being among the most common medical procedures, needle insertions suffer from a high error rate. Impedance measurements using electrode-equipped needles offer promise for improved tissue targeting and reduced errors. Impedance visualization usually requires an extensive pre-measured impedance dataset for tissue differentiation and knowledge of the electric fields contributing to the resulting impedances. This work presents two finite element simulation approaches for both problems. The first approach describes the generation of a multitude of impedances with Monte Carlo simulations for both, homogeneous and inhomogeneous tissue to circumvent the need to rely on previously measured data. These datasets could be used for tissue discrimination. The second method describes the simulation of the spatial sensitivity distribution of an electrode layout. Two singularity analysis methods were employed to determine the bulk of the sensitivity within a finite volume, which in turn enables consistent 3D visualization. The modeled electrode layout consists of 12 electrodes radially placed around a hypodermic needle. Electrical excitation was simulated using two neighboring electrodes for current carriage and voltage pickup, which resulted in 12 distinct bipolar excitation states. Both, the impedance simulations and the respective singularity analysis methods were compared with each other. The results show that the statistical spread of impedances is highly dependent on the tissue type and its inhomogeneities. The bounded bulk of sensitivities of both methods are of similar extent and symmetry. Future models should incorporate more detailed tissue properties such as anisotropy or changing material properties due to tissue deformation to gain more accurate predictions.

Modeling Anisotropic Electrical Conductivity of Blood: Translating Microscale Effects of Red Blood Cell Motion into a Macroscale Property of Blood

Cardiovascular diseases are a leading global cause of mortality. The current standard diagnostic methods, such as imaging and invasive procedures, are relatively expensive and partly connected with risks to the patient. Bioimpedance measurements hold the promise to offer rapid, safe, and low-cost alternative diagnostic methods. In the realm of cardiovascular diseases, bioimpedance methods rely on the changing electrical conductivity of blood, which depends on the local hemodynamics. However, the exact dependence of blood conductivity on the hemodynamic parameters is not yet fully understood, and the existing models for this dependence are limited to rather academic flow fields in straight pipes or channels. In this work, we suggest two closely connected anisotropic electrical conductivity models for blood in general three-dimensional flows, which consider the orientation and alignment of red blood cells (RBCs) in shear flows. In shear flows, RBCs adopt preferred orientations through a rotation of their membrane known as tank-treading motion. The two models are built on two different assumptions as to which hemodynamic characteristic determines the preferred orientation. The models are evaluated in two example simulations of blood flow. In a straight rigid vessel, the models coincide and are in accordance with experimental observations. In a simplified aorta geometry, the models yield different results. These differences are analyzed quantitatively, but a validation of the models with experiments is yet outstanding.

Electrical impedance tomography for pulmonary function monitoring without dorsal electrodes

Electrical impedance tomography (EIT) is a non-invasive technology that can visualize conductivity changes inside human body in real time using multiple surface electrodes. For convenience of wearing and application, if no electrodes are attached to the back, a commonly used image reconstruction approach produces poor images of dorsal region. In this study, we developed a special current injection and voltage measurement pattern to well reconstruct the conductivity distribution inside the body even in the absence of dorsal electrodes. The proposed method has proven through numerical and phantom experiments.

MMV-Net: A Multiple Measurement Vector Network for Multifrequency Electrical Impedance Tomography

Multifrequency electrical impedance tomography (mfEIT) is an emerging biomedical imaging modality to reveal frequency-dependent conductivity distributions in biomedical applications. Conventional model-based image reconstruction methods suffer from low spatial resolution, unconstrained frequency correlation, and high computational cost. Deep learning has been extensively applied in solving the EIT inverse problem in biomedical and industrial process imaging. However, most existing learning-based approaches deal with the single-frequency setup, which is inefficient and ineffective when extended to the multifrequency setup. This article presents a multiple measurement vector (MMV) model-based learning algorithm named MMV-Net to solve the mfEIT image reconstruction problem. MMV-Net considers the correlations between mfEIT images and unfolds the update steps of the Alternating Direction Method of Multipliers for the MMV problem (MMV-ADMM). The nonlinear shrinkage operator associated with the weighted l2,1 regularization term of MMV-ADMM is generalized in MMV-Net with a cascade of a Spatial Self-Attention module and a Convolutional Long Short-Term Memory (ConvLSTM) module to better capture intrafrequency and interfrequency dependencies. The proposed MMV-Net was validated on our Edinburgh mfEIT Dataset and a series of comprehensive experiments. The results show superior image quality, convergence performance, noise robustness, and computational efficiency against the conventional MMV-ADMM and the state-of-the-art deep learning methods.

A Pilot Study Examining the Dielectric Response of Human Forearm Tissues

This work aims to describe the dielectric behaviors of four main tissues in the human forearm using mathematical modelling, including fat, muscle, blood and bone. Multi-frequency bioimpedance analysis (MF-BIA) was initially performed using the finite element method (FEM) with a 3D forearm model to estimate impedance spectra from 10 kHz to 1 MHz, followed by a pilot study involving two healthy subjects to characterize the response of actual forearm tissues from 1 kHz to 349 kHz. Both the simulation and experimental results were fitted to a single-dispersion Cole model (SDCM) and a multi-dispersion Cole model (MDCM) to determine the Cole parameters for each tissue. Cole-type responses of both simulated and actual human forearms were observed. A paired t-test based on the root mean squared error (RMSE) values indicated that both Cole models performed comparably in fitting both simulated and measured bioimpedance data. However, MDCM exhibited higher accuracy, with a correlation coefficient (R2) of 0.99 and 0.89, RMSE of 0.22 Ω and 0.56 Ω, mean difference (mean ± standard deviation) of 0.00 ± 0.23 Ω and -0.28 ± 0.23 Ω, and mean absolute error (MAE) of 0.0007 Ω and 0.2789 Ω for the real part and imaginary part of impedance, respectively. Determining the electrical response of multi-tissues can be helpful in developing physiological monitoring of an organ or a section of the human body through MF-BIA and hemodynamic monitoring by filtering out the impedance contributions from the surrounding tissues to blood-flow-induced impedance variations.

A noise-controlling method by hybrid current-stimulation and voltage-measurement for electrical impedance tomography (HCSVM-EIT)

Image reconstruction in electrical impedance tomography (EIT) is a typical ill-posed inverse problem, from which the stability of conductivity reconstruction affects the reliability of physiological parameters evaluation. In order to improve the stability, the effect of boundary voltage noise on conductivity reconstruction should be controlled. A noise-controlling method based on hybrid current-stimulation and voltage-measurement for EIT (HCSVM-EIT) is proposed for stable conductivity reconstruction. In HCSVM-EIT, the boundary voltage is measured by one current-stimulation and voltage-measurement pattern (high-SNRpattern) with a higher signal-to-noise ratio (SNR); the sensitivity matrix is calculated by another current-stimulation and voltage-measurement pattern (low-condpattern) with a lower condition number; the boundary voltage is then transformed from thehigh-SNRpattern into thelow-condpattern by multiplying by an optimized transformation matrix for image reconstruction. The stability of conductivity reconstruction is improved by combining the advantages of thehigh-SNRpattern for boundary voltage measurement and thelow-condpattern for sensitivity matrix calculation. The simulation results show that the HCSVM-EIT increases the correlation coefficient (CC) of conductivity reconstruction. The experiment results show that theCCof conductivity reconstruction of the human lower limb is increased from 0.3424 to 0.5580 by 62.97% compared to the quasi-adjacent pattern, and from 0.4942 to 0.5580 by 12.91% compared to the adjacent pattern. In conclusion, the stable conductivity reconstruction with higherCCin HCSVM-EIT improves the reliability of physiological parameters evaluation for disease detection.

Lung Imaging Acquisition with Electrical Impedance Tomography: Tackling Common Pitfalls

Electrical impedance tomography is a powerful tool for lung imaging that can be employed at the bedside in multiple clinical scenarios. Diagnosing and preventing interpretation pitfalls will ensure reliable data and allow for appropriate clinical decision-making.

Optimization of electrode positions for equalizing local spatial performance of a tomographic tactile sensor

A tomographic tactile sensor based on the contact resistance of conductors is a high sensitive pressure distribution imaging method and has advantages on the flexibility and scalability of device. While the addition of internal electrodes improves the sensor's spatial resolution, there still remain variations in resolution that depend on the contact position. In this study, we propose an optimization algorithm for electrode positions that improves entire spatial resolution by compensating for local variations in spatial resolution. Simulation results for sensors with 16 or 64 electrodes show that the proposed algorithm improves performance to 0.81 times and 0.93 times in the worst spatial resolution region of the detection area compared to equally spaced grid electrodes. The proposed methods enable tomographic tactile sensors to detect contact pressure distribution more accurately than the conventional methods, providing high-performance tactile sensing for many applications.

Towards continuous EIT monitoring for hemorrhagic stroke patients

The practical implementation of continuous monitoring of stroke patients by Electrical Impedance Tomography (EIT) is addressed. In a previous paper, we have demonstrated EIT sensitivity to cerebral hemodynamics, using scalp-mounted electrodes, very low-noise measurements, and a novel image reconstruction method. In the present paper, we investigate the potential to adapt that system for clinical application, by using 50% fewer electrodes and by incorporating into the measurement protocol an additional high-frequency measurement to provide an effective reference. Previously published image reconstruction methods for multi-frequency EIT are substantially improved by exploiting the forward calculations enabled by the detailed head model, particularly to make the referencing method more robust and to attempt to remove the effects of modelling error. Images are presented from simulation of a typical hemorrhagic stroke and its growth. These results are encouraging for exploration of the potential clinical benefit of the methodology in long-term monitoring of hemorrhagic stroke.

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.

Structural priors represented by discrete cosine transform improve EIT functional imaging

Structural prior information can improve electrical impedance tomography (EIT) reconstruction. In this contribution, we introduce a discrete cosine transformation-based (DCT-based) EIT reconstruction algorithm to demonstrate a way to incorporate the structural prior with the EIT reconstruction process. Structural prior information is obtained from other available imaging methods, e.g., thorax-CT. The DCT-based approach creates a functional EIT image of regional lung ventilation while preserving the introduced structural information. This leads to an easier interpretation in clinical settings while maintaining the advantages of EIT in terms of bedside monitoring during mechanical ventilation. Structural priors introduced in the DCT-based approach are of two categories in terms of different levels of information included: a contour prior only differentiates lung and non-lung region, while a detail prior includes information, such as atelectasis, within the lung area. To demonstrate the increased interpretability of the EIT image through structural prior in the DCT-based approach, the DCT-based reconstructions were compared with reconstructions from a widely applied one-step Gauss-Newton solver with background prior and from the advanced GREIT algorithm. The comparisons were conducted both on simulation data and retrospective patient data. In the simulation, we used two sets of forward models to simulate different lung conditions. A contour prior and a detail prior were derived from simulation ground truth. With these two structural priors, the reconstructions from the DCT-based approach were compared with the reconstructions from both the one-step Gauss-Newton solver and the GREIT. The difference between the reconstructions and the simulation ground truth is calculated by the ℓ2-norm image difference. In retrospective patient data analysis, datasets from six lung disease patients were included. For each patient, a detail prior was derived from the patient's CT, respectively. The detail prior was used for the reconstructions using the DCT-based approach, which was compared with the reconstructions from the GREIT. The reconstructions from the DCT-based approach are more comprehensive and interpretable in terms of preserving the structure specified by the priors, both in simulation and retrospective patient data analysis. In simulation analysis, the ℓ2-norm image difference of the DCT-based approach with a contour prior decreased on average by 34% from GREIT and 49% from the Gauss-Newton solver with background prior; for reconstructions of the DCT-based approach with detail prior, on average the ℓ2-norm image difference is 53% less than GREIT and 63% less than the reconstruction with background prior. In retrospective patient data analysis, the reconstructions from both the DCT-based approach and GREIT can indicate the current patient status, but the DCT-based approach yields more interpretable results. However, it is worth noting that the preserved structure in the DCT-based approach is derived from another imaging method, not from the EIT measurement. If the structural prior is outdated or wrong, the result might be misleadingly interpreted, which induces false clinical conclusions. Further research in terms of evaluating the validity of the structural prior and detecting the outdated prior is necessary.

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.

Advanced Enhancement Techniques for Breast Cancer Classification in Mammographic Images

Background:

Breast cancer is one of the most significant health problems in the world. Early diagnosis of breast cancer is very important for treatment. Image enhancement techniques have been used to improve the captured images for quick and accurate diagnosis. These techniques include median filtering, edge enhancement, dilation, erosion, and contrast-limited adaptive histogram equalization. Although these techniques have been used in many studies, their results have not reached optimum values based on image properties and the methods used for feature extraction and classification.

Methods:

In this study, enhancement techniques were implemented to guarantee the best image enhancement. They were applied to 319 images collected from the Mammographic Image Analysis Society (MIAS) database. The Gabor filter and local binary pattern were used as feature extraction methods together with support vector machine (SVM), linear discriminant analysis (LDA), and nearest neighbor (KNN) classifiers.

Results:

The experimental work indicates that by merging the features of the Gabor filter and local binary pattern, the results were 97.8%, 100%, and 94.6% for normal/abnormal and 85.1%, 88.7%, and 81.9% for benign/malignant using the SVM, LDA, and KNN classifiers, respectively.

Conclusion:

The best results were obtained by combining the features of the two tested strategies and using LDA as a classifier.

Multi-Defect Detection in Additively Manufactured Lattice Structures Using 3D Electrical Resistance Tomography

Cellular lattice structures possess high strength-to-weight ratios suitable for advanced lightweight engineering applications. However, their quality and mechanical performance can degrade because of defects introduced during manufacturing or in-service. Their complexity and small length scale features make defects difficult to detect using conventional nondestructive evaluation methods. Here we propose a current injection-based method, electrical resistance tomography (ERT), that can be used to detect damaged struts in conductive cellular lattice structures with their intrinsic electromechanical properties. The reconstructed conductivity distributions from ERT can reveal the severity and location of damaged struts without having to probe each strut. However, the low central sensitivity of ERT may result in image artifacts and inaccurate localization of damaged struts. To address this issue, this study introduces an absolute, high throughput, conductivity reconstruction algorithm for 3D ERT. The algorithm incorporates a strut-based normalized sensitivity map to compensate for lower interior sensitivity and suppresses reconstruction artifacts. Numerical simulations and experiments on fabricated representative cellular lattice structures were performed to verify the ability of ERT to quantitatively identify single and multiple damaged struts. The improved performance of this method compared with classical ERT was observed, based on greatly decreased imaging and reconstructed value errors.

Parasitic Effects on Electrical Bioimpedance Systems: Critical Review

Parasitic capacitance represents the main error source in measurement systems based on electrical impedance spectroscopy. The capacitive nature of electrodes' impedance in tetrapolar configuration can give origin to phase errors when electrodes are coupled to parasitic capacitances. Nevertheless, reactive charges in tissue excitation systems are susceptible to instability. Based on such a scenario, mitigating capacitive effects associated with the electrode is a requirement in order to reduce errors in the measurement system. A literature review about the main compensation techniques for parasitic capacitance was carried out. The selected studies were categorized into three groups: (i) compensation in electronic instrumentation; (ii) compensation in measurement processing, and (iii) compensation by negative impedance converters. The three analyzed methods emerged as effective against fixed capacitance. No method seemed capable of mitigating the effects of electrodes' capacitance, that changes in the frequency spectrum. The analysis has revealed the need for a method to compensate varying capacitances, since electrodes' impedance is unknown.

Animal models for epileptic foci localization, seizure detection, and prediction by electrical impedance tomography

Surgical resection of lesions and closed-loop suppression are the two main treatment options for patients with refractory epilepsy whose symptoms cannot be managed with medicines. Unfortunately, failures in foci localization and seizure prediction are constraining these treatments. Electrical impedance tomography (EIT), sensitive to impedance changes caused by blood flow or cell swelling, is a potential new way to locate epileptic foci and predict seizures. Animal validation is a necessary research process before EIT can be used in clinical practice, but it is unclear which among the many animal epilepsy models is most suited to this task. The selection of an animal model of epilepsy that is similar to human seizures and can be adapted to EIT is important for the accuracy and reliability of EIT research results. This study provides an overview of the animal models of epilepsy that have been used in research on the use of EIT to locate the foci or predict seizures; discusses the advantages and disadvantages of these models regarding inducement by chemical convulsant and electrical stimulation; and finally proposes optimal animal models of epilepsy to obtain more convincing research results for foci localization and seizure prediction by EIT. The ultimate goal of this study is to facilitate the development of new treatments for patients with refractory epilepsy. This article is categorized under: Neuroscience > Clinical Neuroscience Psychology > Brain Function and Dysfunction.

Electric Impedance Spectroscopy in Trees Condition Analysis: Theory and Experiment

Electric impedance spectroscopy is an alternative technology to existing methods that shows promising results in the agro-food industry and plant physiology research. For example, this technology makes it possible to monitor the condition of plants, even in the early stages of development, and to control the quality of finished products. However, the use of electric impedance spectroscopy is often associated with the need to organize special laboratory conditions for measurements. Our aim is to extract information about the state of health of the internal tissues of a plant's branches from impedance measurements. Therefore, we propose a new technique using the device and model developed by us that makes it possible to monitor the condition of tree branch tissues in situ. An apple tree was chosen as the object under study, and the dependence of the impedance of the apple tree branch on the signal frequency and branch length was analyzed. The change in the impedance of an apple tree branch during drying was also analyzed. It was shown that, when a branch dries out, the conductivity of the xylem mainly decreases. The developed technique was also applied to determine the development of the vascular system of an apple tree after grafting. It was shown that the processing of the scion and rootstock sections with the help of cold atmospheric plasma and a plasma-treated solution contributes to a better formation of graft unions.

A structured narrative review of clinical and experimental studies of the use of different positive end-expiratory pressure levels during thoracic surgery

OBJECTIVES

This study aimed to present a review on the general effects of different positive end-expiratory pressure (PEEP) levels during thoracic surgery by qualitatively categorizing the effects into detrimental, beneficial, and inconclusive.

DATA SOURCE

Literature search of Pubmed, CNKI, and Wanfang was made to find relative articles about PEEP levels during thoracic surgery. We used the following keywords as one-lung ventilation, PEEP, and thoracic surgery.

RESULTS

We divide the non-individualized PEEP value into five grades, that is, less than 5, 5, 5-10, 10, and more than 10 cmH₂ O, among which 5 cmH₂ O is the most commonly used in clinic at present to maintain alveolar dilatation and reduce the shunt fraction and the occurrence of atelectasis, whereas individualized PEEP, adjusted by test titration or imaging method to adapt to patients' personal characteristics, can effectively ameliorate intraoperative oxygenation and obtain optimal pulmonary compliance and better indexes relating to respiratory mechanics.

CONCLUSIONS

Available data suggest that PEEP might play an important role in one-lung ventilation, the understanding of which will help in exploring a simple and economical method to set the appropriate PEEP level.

Bio-conductivity characteristics of chronic kidney disease stages examined by portable frequency-difference electrical impedance tomography

Chronic kidney disease (CKD) is an escalating global health concern, and non-invasive means for early CKD detection is eagerly awaited. Here, we explore the potential of using home-based frequency-difference electrical impedance tomography (fdEIT) to evaluate CKD based on bio-conductivity characteristics. We first verified the feasibility of using portable EIT capturing bio-conductivity in fresh pig kidneys ex vivo. We further performed bio-conductivity measurement in vivo paired with standard eGFR measurements on CKD patients by EIT and traditional blood test, respectively. Our results showed a significant correlation between renal bio-conductivity changes captured by fdEIT and standard eGFR scores. These results hold promise to be developed into a non-invasive and portable device for early CKD detection and longitudinal CKD treatment monitoring in clinical, community and home-based settings. Clinical Relevance - A novel non-invasive bio-conductivity approach was developed for CKD classification. The renal assessment with portable EIT device demonstrated the potential to ameliorate the detection and classification of CKD into a portable, accessible, self-administrable home-based process.

Generation of Anatomically Inspired Human Airway Tree Using Electrical Impedance Tomography: A Method to Estimate Regional Lung Filling Characteristics

The purpose of lung recruitment is to improve and optimize the air exchange flow in the lungs by adjusting the respiratory settings during mechanical ventilation. Electrical impedance tomography (EIT) is a monitoring tool that permits measurement of regional pulmonary filling characteristics or filling index (FI) during ventilation. The conventional EIT system has limitations which compromise the accuracy of the FI. This paper proposes a novel and automated methodology for accurate FI estimation based on EIT images of recruitable regional collapse and hyperdistension during incremental positive end-expiratory pressure. It identifies details of the airway tree (AT) to generate a correction factor to the FIs providing an accurate measurement. Multi-scale image enhancement followed by identification of the AT skeleton with a robust and self-exploratory tracing algorithm is used to automatically estimate the FI. AT tracing was validated using phantom data on a ground-truth lung. Based on generated phantom EIT images, including an established reference, the proposed method results in more accurate FI estimation of 65% in all quadrants compared with the current state-of-the-art. Measured regional filling characteristics were also examined by comparing regional and global impedance variations in clinically recorded data from ten different subjects. Clinical tests on filling characteristics based on extraction of the AT from the resolution enhanced EIT images indicated a more accurate result compared with the standard EIT images.

Automated 3D thorax model generation using handheld video-footage

PURPOSE

For the visualization of pulmonary ventilation with Electrical Impedance Tomography (EIT) most devices use standard reconstruction models, featuring common thorax dimensions and predetermined electrode locations. Any discrepancies between the available model and the patient in terms of body shape and electrode position lead to incorrectly displayed impedance distributions. This work addresses that problem by presenting and evaluating a method for 3D model generation of the thorax and any affixed electrodes based on handheld video-footage.

METHODS

Therefore, a process was developed, providing users with the ability to capture a patient's chest and the attached electrodes via smartphone. Once data is collected, extracted images are used to generate a 3D model with a structure from motion approach and locate electrodes with ArUco markers. For the evaluation of the developed method, multiple tests were performed in laboratory environments, which were compared with manually created reference models and differences quantified based on mean distance, standard deviation, and maximum distance.

RESULTS

The implemented workflow allows for automated model reconstruction based on videos or selected images captured with a handheld device. It generates sparse point clouds from which a surface mesh is reconstructed and returns relative coordinates of any identified ArUco marker. The average value for the mean distance error of two model generations was 5.4 mm while the mean standard deviation was 6.0 mm. The average runtime of twelve reconstructions was 5:17 min, with a minimal runtime of 3:22 min and a maximal runtime of 7:29 min.

CONCLUSION

The presented methods and results show that model reconstruction of a patient's thorax and applied electrodes at an emergency site is feasible with already available devices. This is a first step toward the automated generation of patient-specific reconstruction models for Electrical Impedance Tomography based on images recorded with handheld devices.

Multiplexing Error and Noise Reduction in Electrical Impedance Tomography Imaging

Electrical Impedance Tomography design can be simplified to obtain a low cost 16 electrodes edema monitoring clinical instrument by using voltage measurement multiplexing. Multiplexers introduce errors, which we have estimated by consecutive phantom measurements both using voltage multiplexers and by selecting the electrodes by hand, all other things being the same. Noise is taken care of by averaging. The EIDORS reconstruction of the phantom with multiplexed measurements is compared to the hand-selected electrode measurements reconstruction. The difference image obtained is considered an estimation of the multiplexer induced error. This measurement error is subtracted from the multiplexed object measurement matrix, giving a modified reconstruction which is closer to the hand-selected electrodes measurement based reconstruction than the multiplexed reconstruction. The quality factor of the uncorrected multiplexer obtained image of 57% is increased to 83% which is the best increase of three methods described. This suggests the benefit of a “calibration” phase for all 16 electrodes, prior to EIT reconstruction, using a set-up-specific “error matrix” to correct the data matrix before submission to the reconstruction method.

Triple plasmon-induced transparency and dynamically tunable electro-optics switch based on a multilayer patterned graphene metamaterial

A terahertz-band metamaterial composed of multilayer patterned graphene is proposed and triple plasmon-induced transparency is excited by coupling three bright modes with one dark mode. The Lorentz curve calculated by the coupled-mode theory agrees well with the finite-difference time-domain results. Dynamic tuning is investigated by changing the Fermi level. Multimode electro-optics switching can be designed and achieved, and the amplitude modulations of four resonance frequencies are 94.3%, 92.8%, 90.7%, and 93%, respectively, which can realize the design of synchronous and asynchronous electro-optics switches. It is hoped that these results can provide theoretical support and guidance for the future design and application of photonic and optoelectronic devices.

Intra-radiological pathology-calibrated Electrical Impedance Spectroscopy in the evaluation of excision-required breast lesions

PURPOSE

Evaluating a real-time complementary bioelectrical diagnostic device based on Electrical Impedance Spectroscopy(EIS) for improving breast imaging-reporting and data system (BIRADS) scoring accuracy, especially in high-risk or borderline breast diseases. The primary purpose is to characterize breast tumors based on their dielectric properties. Early detection of high-risk lesions and increasing the accuracy of tumor sampling and pathological diagnosis are secondary objectives of the study.

METHODS

The tumor detection probe (TDP) was first applied to the mouse model for electrical safety evaluations by electrical current measurement, then to 138 human palpable breast lesions undergo CNB, VAB, or FNA with the surgeon's requests. Impedance phase slope(IPS) in frequency ranges of 100 kHz to 500 kHz and impedance magnitude in f = 1kHz were extracted as the classification parameters. Consistency of radiological and pathological declarations for the excisional recommendation was then compared with the IPS values.

RESULTS

Considering pathological results as the gold standard, meaningful correlations between IPS and pathophysiological status of lesions recommended for excision (such as atypical ductal hyperplasia, papillary lesions, complex sclerosing adenosis, and fibroadenoma, etc.) were observed (p<0.0001). These pathophysiological properties may include cells size, membrane permeability, packing density, adenosis, cytoplasm structure, etc. Benign breast lesions showed IPS values greater than zero, while high-risk proliferative, precancerous, or cancerous lesions had negative IPS values. Statistical analysis showed 95% sensitivity with Area Under the Curve(AUC) equal to 0.92.

CONCLUSION

Borderline breast diseases and high-risk lesions that should be excised according to standard guidelines can be diagnosed with TDP before any sampling process. It is a precious outcome for high-risk lesions that are radiologically underestimated to BI-RADS3, specifically in younger patients with dense breast masses, challenging in mammographic and sonographic evaluations. Also, the lowest IPS value detects the most pathologic portions of the tumor for increasing sampling accuracy in large tumors.

SIGNIFICANCE

Precise detection of high-risk breast masses, which may be declared BI-RADS3 instead of BI-RADS4a. This article is protected by copyright. All rights reserved.

An efficient and fast multi-band focused bioimpedance solution with EIT-based reconstruction for pulmonary embolism assessment: a simulation study from massive to segmental blockage

OBJECTIVE

Pulmonary embolism (PE) is an acute condition that blocks the perfusion to the lungs and is a common complication of Covid-19. However, PE is often not diagnosed in time, especially in the pandemic time due to complicated diagnosis protocol. In this study, a non-invasive, fast and efficient bioimpedance method with the EIT-based reconstruction approach is proposed to assess the lung perfusion reliably.

APPROACH

Some proposals are presented to improve the sensitivity and accuracy for the bioimpedance method: (1) a new electrode configuration and focused pattern to help study deep changes caused by PE within each lung field separately, (2) a measurement strategy to compensate the effect of different boundary shapes and varied respiratory conditions on the perfusion signals and (3) an estimator to predict the lung perfusion capacity, from which the severity of PE can be assessed. The proposals were tested on the first-time simulation of PE events at different locations and degrees from segmental blockages to massive blockages. Different object boundary shapes and varied respiratory conditions were included in the simulation to represent for different populations in real measurements.

RESULTS

The correlation between the estimator and the perfusion was very promising (R = 0.91, errors < 6%). The measurement strategy with the proposed configuration and pattern has helped stabilize the estimator to non-perfusion factors such as the boundary shapes and varied respiration conditions (3-5% errors).

SIGNIFICANCE

This promising preliminary result has demonstrated the proposed bioimpedance method's capability and feasibility, and might start a new direction for this application.

Homogenizing effect of PEEP on tidal volume distribution during neurally adjusted ventilatory assist: study of an animal model of acute respiratory distress syndrome

BACKGROUND

The physiological response and the potentially beneficial effects of positive end-expiratory pressure (PEEP) for lung protection and optimization of ventilation during spontaneous breathing in patients with acute respiratory distress syndrome (ARDS) are not fully understood. The aim of the study was to compare the effect of different PEEP levels on tidal volume distribution and on the ventilation of dependent lung region during neurally adjusted ventilatory assist (NAVA).

METHODS

ARDS-like lung injury was induced by using saline lavage in 10 anesthetized and spontaneously breathing farm-bred pigs. The animals were ventilated in NAVA modality and tidal volume distribution as well as dependent lung ventilation were assessed using electric impedance tomography during the application of PEEP levels from 0 to 15 cmH₂0, in steps of 3 cmH₂0. Tidal volume distribution and dependent fraction of ventilation were analysed using Wilcoxon signed rank test. Furthermore, airway, esophageal and transpulmonary pressure, as well as airway flow and delivered volume, were continuously measured during the assisted spontaneous breathing.

RESULTS

Increasing PEEP improved oxygenation and re-distributed tidal volume. Specifically, ventilation distribution changed from a predominant non-dependent to a more even distribution between non-dependent and dependent areas of the lung. Dependent fraction of ventilation reached 47 ± 9% at PEEP 9 cmH₂0. Further increasing PEEP led to a predominant dependent ventilation.

CONCLUSION

During assisted spontaneous breathing in this model of induced ARDS, PEEP modifies the distribution of ventilation and can achieve a homogenizing effect on its spatial arrangement. The study indicates that PEEP is an important factor during assisted spontaneous breathing and that EIT can be of valuable interest when titrating PEEP level during spontaneous breathing, by indicating the most homogeneous distribution of gas volumes throughout the PEEP spectrum.

A stroke detection and discrimination framework using broadband microwave scattering on stochastic models with deep learning

Stroke poses an immense public health burden and remains among the primary causes of death and disability worldwide. Emergent therapy is often precluded by late or indeterminate times of onset before initial clinical presentation. Rapid, mobile, safe and low-cost stroke detection technology remains a deeply unmet clinical need. Past studies have explored the use of microwave and other small form-factor strategies for rapid stroke detection; however, widespread clinical adoption remains unrealized. Here, we investigated the use of microwave scattering perturbations from ultra wide-band antenna arrays to learn dielectric signatures of disease. Two deep neural networks (DNNs) were used for: (1) stroke detection ("classification network"), and (2) characterization of the hemorrhage location and size ("discrimination network"). Dielectric signatures were learned on a simulated cohort of 666 hemorrhagic stroke and control subjects using 2D stochastic head models. The classification network yielded a stratified K-fold stroke detection accuracy > 94% with an AUC of 0.996, while the discrimination network resulted in a mean squared error of < 0.004 cm and < 0.02 cm, for the stroke localization and size estimation, respectively. We report a novel approach to intelligent diagnostics using microwave wide-band scattering information thus circumventing conventional image-formation.

A Multi-Frequency Focused Impedance Measurement System Based on Analogue Synchronous Peak Detection

Monitoring of anatomical structures and physiological processes by electrical impedance has attracted scientists as it is noninvasive, nonionizing and the instrumentation is relatively simple. Focused Impedance Method (FIM) is attractive in this context, as it has enhanced sensitivity at the central region directly beneath the electrode configuration minimizing contribution from neighboring regions. FIM essentially adds or averages two concentric and orthogonal combinations of conventional Tetrapolar Impedance Measurements (TPIM) and has three versions with 4, 6, and 8 electrodes. This paper describes the design and testing of a multi-frequency FIM (MFFIM) system capable of measuring all three versions of FIM at 8 frequencies in the range 10 kHz—1 MHz. A microcontroller based multi-frequency signal generator and a balanced Howland current source with high output impedance (476 kΩ at 10 kHz and 58.3 kΩ at 1 MHz) were implemented for driving currents into biological tissues with an error &lt;1%. The measurements were carried out at each frequency sequentially. The peak values of the amplified voltage signals were measured using a novel analogue synchronous peak detection technique from which the transfer impedances were obtained. The developed system was tested using TPIM measurements on a passive RC Cole network placed between two RC networks, the latter representing skin-electrode contact impedances. Overall accuracy of the measurement was very good (error &lt;4% at all frequencies except 1 MHz, with error 6%) and the resolution was 0.1 Ω. The designed MFFIM system had a sampling rate of &gt;45 frames per second which was deemed adequate for noninvasive real-time impedance measurements on biological tissues.

Impact of Local Electrodes on Brain Stroke Type Differentiation using Electrical Impedance Tomography

Electrical impedance tomography (EIT) of the head has the potential to provide rapid characterization of brain stroke. This study builds on previous work by implementing a more anatomically complex head model, contrasting results of bleed and clot simulations, and by establishing the electrodes which dominate in voltage difference measurements. This work provides the basis for machine learning with clusters of small numbers of electrodes as unique features for stroke-type detection and differentiation.Clinical Relevance- This application of EIT can aid in early detection, classification, and localization of brain stroke, allowing for faster treatment.

Robot-Assisted Electrical Impedance Scanning system for 2D Electrical Impedance Tomography tissue inspection

The electrical impedance tomography (EIT) technology is an important medical imaging approach to show the electrical characteristics and the homogeneity of a tissue region noninvasively. Recently, this technology has been introduced to the Robot Assisted Minimally Invasive Surgery (RAMIS) for assisting the detection of surgical margin with relevant clinical benefits. Nevertheless, most EIT technologies are based on a fixed multiple-electrodes probe which limits the sensing flexibility and capability significantly. In this study, we present a method for acquiring the EIT measurements during a RAMIS procedure using two already existing robotic forceps as electrodes. The robot controls the forceps tips to a series of predefined positions for injecting excitation current and measuring electric potentials. Given the relative positions of electrodes and the measured electric potentials, the spatial distribution of electrical conductivity in a section view can be reconstructed. Realistic experiments are designed and conducted to simulate two tasks: subsurface abnormal tissue detection and surgical margin localization. According to the reconstructed images, the system is demonstrated to display the location of the abnormal tissue and the contrast of the tissues' conductivity with an accuracy suitable for clinical applications.

Telemonitoring Techniques for Lung Volume Measurement: Accuracy, Artifacts and Effort

Telemonitoring becomes more important in pulmonary research. It can be used to decrease the pressure on the health care system, to lower the costs of health care and to increase quality of life of patients. Previous studies show contradictory results regarding the effectiveness of telemonitoring. According to multiple researchers, inefficiency can be a result of poor study design, low data quality and usability issues. To counteract these issues, this review proves for an in-depth explanation of four (potential) telemonitoring systems in terms of work principle, accuracy, disturbing factors and usability. The evaluated systems are portable spirometry/breath-by-breath analyzers, respiratory inductance and magnetic plethysmography and electrical impedance tomography. These insights can be used to select the optimal technique for a specific purpose in future studies.

Electrical impedance tomography for non-invasive identification of fatty liver infiltrate in overweight individuals

Non-alcoholic fatty liver disease (NAFLD) is one of the most common causes of cardiometabolic diseases in overweight individuals. While liver biopsy is the current gold standard to diagnose NAFLD and magnetic resonance imaging (MRI) is a non-invasive alternative still under clinical trials, the former is invasive and the latter costly. We demonstrate electrical impedance tomography (EIT) as a portable method for detecting fatty infiltrate. We enrolled 19 overweight subjects to undergo liver MRI scans, followed by EIT measurements. The MRI images provided the a priori knowledge of the liver boundary conditions for EIT reconstruction, and the multi-echo MRI data quantified liver proton-density fat fraction (PDFF%) to validate fat infiltrate. Using the EIT electrode belts, we circumferentially injected pairwise current to the upper abdomen, followed by acquiring the resulting surface-voltage to reconstruct the liver conductivity. Pearson's correlation analyses compared EIT conductivity or MRI PDFF with body mass index, age, waist circumference, height, and weight variables. We reveal that the correlation between liver EIT conductivity or MRI PDFF with demographics is statistically insignificant, whereas liver EIT conductivity is inversely correlated with MRI PDFF (R = -0.69, p = 0.003, n = 16). As a pilot study, EIT conductivity provides a portable method for operator-independent and cost-effective detection of hepatic steatosis.

Hardware for cell culture electrical impedance tomography: A critical review

Human cell cultures are powerful laboratory tools for biological models of diseases, drug development, and tissue engineering. However, the success of biological experiments often depends on real-time monitoring of the culture state. Conventional culture evaluation methods consist of end-point laborious techniques, not capable of real-time operation and not suitable for three-dimensional cultures. Electrical Impedance Tomography (EIT) is a non-invasive imaging technique with high potential to be used in cell culture monitoring due to its biocompatibility, non-invasiveness, high temporal resolution, compact hardware, automatic operation, and high throughput. This review approaches the different hardware strategies for cell culture EIT that are presented in the literature, discussing the main components of the measurement system: excitation circuit, voltage/current sensing, switching stage, signal specifications, electrode configurations, measurement protocols, and calibration strategies. The different approaches are qualitatively discussed and compared, and design guidelines are proposed.

3D ELECTRICAL IMPEDANCE TOMOGRAPHY RECONSTRUCTIONS FROM SIMULATED ELECTRODE DATA USING DIRECT INVERSION texp AND CALDERÓN METHODS

The first numerical implementation of a t ^exp method in 3D using simulated electrode data is presented. Results are compared to Calderón's method as well as more common TV and smoothness regularization-based methods. The t ^exp method for EIT is based on tailor-made non-linear Fourier transforms involving the measured current and voltage data. Low-pass filtering in the non-linear Fourier domain is used to stabilize the reconstruction process. In 2D, t ^exp methods have shown great promise for providing robust real-time absolute and time-difference conductivity reconstructions but have yet to be used on practical electrode data in 3D, until now. Results are presented for simulated data for conductivity and permittivity with disjoint non-radially symmetric targets on spherical domains and noisy voltage data. The 3D t ^exp and Calderón methods are demonstrated to provide comparable quality to their 2D counterparts, and hold promise for real-time reconstructions due to their fast, non-optimized, computational cost.

Electrical impedance tomography detects changes in ventilation after airway clearance in spinal muscular atrophy type I

The effect of mechanical insufflation-exsufflation (MIE) for airway clearance in patients with spinal muscular atrophy type I (SMA-I) on the distribution of ventilation in the lung is unknown, as is the duration of its beneficial effects. A pilot study to investigate the feasibility of using three dimensional (3-D) electrical impedance tomography (EIT) images to estimate lung volumes pre- and post-MIE for assessing the effectiveness of mechanical insufflation-exsufflation (MIE) was conducted in 6 pediatric patients with SMA-I in the neuromuscular clinic at Children's Hospital Colorado. EIT data were collected before, during, and after the MIE procedure on two rows of 16 electrodes placed around the chest. Lung volumes were computed from the images and compared before, during, and after the MIE procedure to assess the ability of EIT to estimate changes in lung volume during insufflation and exsufflation. Images of pulsatile pulmonary perfusion were computed in subjects able to perform breath-holding. In four of the six subjects, lung volumes during tidal breathing increased after MIE (average change from pre to post MIE was 58.8±55.1 mL). The time-dependent plots of lung volume computed from the EIT data clearly show when the MIE device insufflates and exsufflates air and the rest periods between mechanical coughs. Images of pulmonary pulsatile perfusion were computed from data collected during breathing pauses. The results suggest that EIT holds promise for estimating lung volumes and ventilation/perfusion mismatch, both of which are useful for assessing the effectiveness of MIE in clearing mucus plugs.

A bioimpedance-based monitor for real-time detection and identification of secondary brain injury

Secondary brain injury impacts patient prognosis and can lead to long-term morbidity and mortality in cases of trauma. Continuous monitoring of secondary injury in acute clinical settings is primarily limited to intracranial pressure (ICP); however, ICP is unable to identify essential underlying etiologies of injury needed to guide treatment (e.g. immediate surgical intervention vs medical management). Here we show that a novel intracranial bioimpedance monitor (BIM) can detect onset of secondary injury, differentiate focal (e.g. hemorrhage) from global (e.g. edema) events, identify underlying etiology and provide localization of an intracranial mass effect. We found in an in vivo porcine model that the BIM detected changes in intracranial volume down to 0.38 mL, differentiated high impedance (e.g. ischemic) from low impedance (e.g. hemorrhagic) injuries (p < 0.001), separated focal from global events (p < 0.001) and provided coarse 'imaging' through localization of the mass effect. This work presents for the first time the full design, development, characterization and successful implementation of an intracranial bioimpedance monitor. This BIM technology could be further translated to clinical pathologies including but not limited to traumatic brain injury, intracerebral hemorrhage, stroke, hydrocephalus and post-surgical monitoring.

The Core of Medical Imaging: State of the Art and Perspectives on the Detectors

In this review, the roles of detectors in various medical imaging techniques were described. Ultrasound, optical (near-infrared spectroscopy and optical coherence tomography) and thermal imaging, magnetic resonance imaging, computed tomography, single-photon emission tomography, positron emission tomography were the imaging modalities considered. For each methodology, the state of the art of detectors mainly used in the systems was described, emphasizing new technologies applied.

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.

Identification and analysis of stable breathing periods in electrical impedance tomography recordings

Objective. In this paper, an automated stable tidal breathing period (STBP) identification method based on processing electrical impedance tomography (EIT) waveforms is proposed and the possibility of detecting and identifying such periods using EIT waveforms is analyzed. In wearable chest EIT, patients breathe spontaneously, and therefore, their breathing pattern might not be stable. Since most of the EIT feature extraction methods are applied to STBPs, this renders their automatic identification of central importance.Approach. The EIT frame sequence is reconstructed from the raw EIT recordings and the raw global impedance waveform (GIW) is computed. Next, the respiratory component of the raw GIW is extracted and processed for the automatic respiratory cycle (breath) extraction and their subsequent grouping into STBPs.Main results. We suggest three criteria for the identification of STBPs, namely, the coefficient of variation of (i) breath tidal volume, (ii) breath duration and (iii) end-expiratory impedance. The total number of true STBPs identified by the proposed method was 294 out of 318 identified by the expert corresponding to accuracy over 90%. Specific activities such as speaking, eating and arm elevation are identified as sources of false positives and their discrimination is discussed.Significance. Simple and computationally efficient STBP detection and identification is a highly desirable component in the EIT processing pipeline. Our study implies that it is feasible, however, the determination of its limits is necessary in order to consider the implementation of more advanced and computationally demanding approaches such as deep learning and fusion with data from other wearable sensors such as accelerometers and microphones.

Fusing electrical and elasticity imaging

Electrical and elasticity imaging are promising modalities for a suite of different applications, including medical tomography, non-destructive testing and structural health monitoring. These emerging modalities are capable of providing remote, non-invasive and low-cost opportunities. Unfortunately, both modalities are severely ill-posed nonlinear inverse problems, susceptive to noise and modelling errors. Nevertheless, the ability to incorporate complimentary datasets obtained simultaneously offers mutually beneficial information. By fusing electrical and elastic modalities as a joint problem, we are afforded the possibility to stabilize the inversion process via the utilization of auxiliary information from both modalities as well as joint structural operators. In this study, we will discuss a possible approach to combine electrical and elasticity imaging in a joint reconstruction problem giving rise to novel multi-modality applications for use in both medical and structural engineering. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'.

Simultaneous Imaging of Bio- and Non-Conductive Targets by Combining Frequency and Time Difference Imaging Methods in Electrical Impedance Tomography

As a promising medical imaging modality, electrical impedance tomography (EIT) can image the electrical properties within a region of interest using electrical measurements applied at electrodes on the region boundary. This paper proposes to combine frequency and time difference imaging methods in EIT to simultaneously image bio- and non-conductive targets, where the image fusion is accomplished by applying a wavelet-based technique. To enable image fusion, both time and frequency difference imaging methods are investigated regarding the reconstruction of bio- or non-conductive inclusions in the target region at varied excitation frequencies, indicating that none of those two methods can tackle with the scenarios where both bio- and non-conductive inclusions exist. This dilemma can be resolved by fusing the time difference (td) and appropriate frequency difference (fd) EIT images since they are complementary to each other. Through simulation and in vitro experiment, it is demonstrated that the proposed fusion method can reasonably reconstruct both the bio- and non-conductive inclusions within the lung models established to simulate the ventilation process, which is expected to be beneficial for the diagnosis of lung-tissue related diseases by EIT.

Potential Utility of Electrical Impedance Myography in Evaluating Age-Related Skeletal Muscle Function Deficits

Skeletal muscle function deficits associated with advancing age are due to several physiological and morphological changes including loss of muscle size and quality (conceptualized as a reduction in the intrinsic force-generating capacity of a muscle when adjusted for muscle size). Several factors can contribute to loss of muscle quality, including denervation, excitation-contraction uncoupling, increased fibrosis, and myosteatosis (excessive levels of inter- and intramuscular adipose tissue and intramyocellular lipids). These factors also adversely affect metabolic function. There is a major unmet need for tools to rapidly and easily assess muscle mass and quality in clinical settings with minimal patient and provider burden. Herein, we discuss the potential for electrical impedance myography (EIM) as a tool to evaluate muscle mass and quality in older adults. EIM applies weak, non-detectible (e.g., 400 μA), mutifrequency (e.g., 1 kHz–1 MHz) electrical currents to a muscle (or muscle group) through two excitation electrodes, and resulting voltages are measured via two sense electrodes. Measurements are fast (~5 s/muscle), simple to perform, and unaffected by factors such as hydration that may affect other simple measures of muscle status. After nearly 2 decades of study, EIM has been shown to reflect muscle health status, including the presence of atrophy, fibrosis, and fatty infiltration, in a variety of conditions (e.g., developmental growth and maturation, conditioning/deconditioning, and obesity) and neuromuscular diseases states [e.g., amyotrophic lateral sclerosis (ALS) and muscular dystrophies]. In this article, we describe prior work and current evidence of EIM’s potential utility as a measure of muscle health in aging and geriatric medicine.

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.

Bioimpedance analysis as a tool for hemodynamic monitoring: overview, methods and challenges

Recent advances in hemodynamic monitoring have seen the advent of non-invasive methods which offer ease of application and improve patient comfort. Bioimpedance Analysis or BIA is one of the currently employed non-invasive techniques for hemodynamic monitoring. Impedance Cardiography (ICG), one of the implementations of BIA, is widely used as a non-invasive procedure for estimating hemodynamic parameters such as stroke volume (SV) and cardiac output (CO). Even though BIA is not a new diagnostic technique, it has failed to gain consensus as a reliable measure of hemodynamic parameters. Several devices have emerged for estimating CO using ICG which are based on evolving methodologies and techniques to calculate SV. However, the calculations are generally dependent on the electrode configurations (whole body, segmental or localised) as well as the accuracy of different techniques in tracking blood flow changes. Blood volume changes, concentration of red blood cells, pulsatile velocity profile and ambient temperature contribute to the overall conductivity of blood and hence its impedance response during flow. There is a growing interest in investigating limbs for localised BIA to estimate hemodynamic parameters such as pulse wave velocity. As such, this paper summarises the current state of hemodynamic monitoring through BIA in terms of different configurations and devices in the market. The conductivity of blood flow has been emphasized with contributions from both volume and velocity changes during flow. Recommendations for using BIA in hemodynamic monitoring have been mentioned highlighting the suitable range of frequencies (1 kHz-1 MHz) as well as safety considerations for a BIA setup. Finally, current challenges in using BIA such as geometry assumption and inaccuracies have been discussed while mentioning potential advantages of a multi-frequency analysis to cover all the major contributors to blood's impedance response during flow.

Imaging slow brain activity during neocortical and hippocampal epileptiform events with electrical impedance tomography

OBJECTIVE

Electrical impedance tomography (EIT) is an imaging technique that produces tomographic images of internal impedance changes within an object using surface electrodes. It can be used to image the slow increase in cerebral tissue impedance that occurs over seconds during epileptic seizures, which is attributed to cell swelling due to disturbances in ion homeostasis following hypersynchronous neuronal firing and its associated metabolic demands. In this study, we characterised and imaged this slow impedance response during neocortical and hippocampal epileptiform events in the rat brain and evaluated its relationship to the underlying neural activity.

APPROACH

Neocortical or hippocampal seizures, comprising repeatable series of high-amplitude ictal spikes, were induced by electrically stimulating the sensorimotor cortex or perforant path of rats anaesthetised with fentanyl-isoflurane. Transfer impedances were measured during ≥30 consecutive seizures, by applying a sinusoidal current through independent electrode pairs on an epicortical array, and combined to generate an EIT image of slow activity.

MAIN RESULTS

The slow impedance responses were consistently time-matched to the end of seizures and EIT images of this activity were reconstructed reproducibly in all animals (p < 0.03125, N = 5). These displayed foci of activity that were spatially confined to the facial somatosensory cortex and dentate gyrus for neocortical and hippocampal seizures, respectively, and encompassed a larger volume as the seizure progressed. Centre-of-mass analysis of reconstructions revealed that this activity corresponded to the true location of the epileptogenic zone, as determined by EEG recordings and fast neural EIT measurements which were obtained simultaneously.

SIGNIFICANCE

These findings suggest that the slow impedance response presents a reliable marker of hypersynchronous neuronal activity during epileptic seizures and can thus be utilised for investigating the mechanisms of epileptogenesis in vivo and for aiding localisation of the epileptogenic zone during presurgical evaluation of patients with refractory epilepsies.

A multiscale optimization framework for reconstructing binary images using multilevel PCA-based control space reduction

An efficient computational approach for optimal reconstructing parameters of binary-type physical properties for models in biomedical applications is developed and validated. The methodology includes gradient-based multiscale optimization with multilevel control space reduction by using principal component analysis (PCA) coupled with dynamical control space upscaling. The reduced dimensional controls are used interchangeably at fine and coarse scales to accumulate the optimization progress and mitigate side effects at both scales. Flexibility is achieved through the proposed procedure for calibrating certain parameters to enhance the performance of the optimization algorithm. Reduced size of control spaces supplied with adjoint-based gradients obtained at both scales facilitate the application of this algorithm to models of higher complexity and also to a broad range of problems in biomedical sciences. This technique is shown to outperform regular gradient-based methods applied to fine scale only in terms of both qualities of binary images and computing time. Performance of the complete computational framework is tested in applications to 2D inverse problems of cancer detection by the electrical impedance tomography (EIT). The results demonstrate the efficient performance of the new method and its high potential for minimizing possibilities for false positive screening and improving the overall quality of the EIT-based procedures.

Electrical Properties Tomography: A Methodological Review

Electrical properties tomography (EPT) is an imaging method that uses a magnetic resonance (MR) system to non-invasively determine the spatial distribution of the conductivity and permittivity of the imaged object. This manuscript starts by providing clear definitions about the data required for, and acquired in, EPT, followed by comprehensively formulating the physical equations underlying a large number of analytical EPT techniques. This thorough mathematical overview of EPT harmonizes several EPT techniques in a single type of formulation and gives insight into how they act on the data and what their data requirements are. Furthermore, the review describes machine learning-based algorithms. Matlab code of several differential and iterative integral methods is available upon request.