Imaging of cortical spreading depression by EIT: implications for localization of epileptic foci

Emerging trends and hot spots on electrical impedance tomography extrapulmonary applications

Objective

Electrical impedance tomography (EIT) develops rapidly in technology and applications. Nowadays EIT is used in multiple clinical and experimental scenarios including pulmonary, brain, and tissue monitoring, etc. The present study explores the research trends and hotspots on EIT extrapulmonary application research by bibliometrics analysis.

Approach

Publications on EIT extrapulmonary applications between 1987 and 2021 were retrieved from the Web of Science Core Collection database. For precise screening, search strategy "electrical impedance tomography" plus "hemodynamic" or "brain" or "nerve" or "cancer" or "venous" or "vessel" or "tumor" or "veterinary" or "tissue" or "cell" or "wearable" or "application" and excluding "lung", "ventilation" "respiratory", "pulmonary", "algorithm", "current", "voltage" or "electrode" were used. CiteSpace and VOSviewer were used to analyze the publication features, collaboration, keywords co-occurrence, and co-cited reference.

Main results

A total of 506 articles were finally identified. The global publication numbers on extrapulmonary applications gradually increased yearly in the past 30 years. The US, UK, and China contributed most three publications concerning EIT extrapulmonary applications. "tissues", "conductivity", "model" were research hotspots, and "cutaneous melanoma", "microstructure", "diagnosis" were recent topics (Portions of this research have previously been presented in poster form).

Significance

Overall, EIT extrapulmonary applications bibliometrics analysis provides a unique insight into research focus, current trends, and future directions.

Advances of deep learning in electrical impedance tomography image reconstruction

Electrical impedance tomography (EIT) has been widely used in biomedical research because of its advantages of real-time imaging and nature of being non-invasive and radiation-free. Additionally, it can reconstruct the distribution or changes in electrical properties in the sensing area. Recently, with the significant advancements in the use of deep learning in intelligent medical imaging, EIT image reconstruction based on deep learning has received considerable attention. This study introduces the basic principles of EIT and summarizes the application progress of deep learning in EIT image reconstruction with regards to three aspects: a single network reconstruction, deep learning combined with traditional algorithm reconstruction, and multiple network hybrid reconstruction. In future, optimizing the datasets may be the main challenge in applying deep learning for EIT image reconstruction. Adopting a better network structure, focusing on the joint reconstruction of EIT and traditional algorithms, and using multimodal deep learning-based EIT may be the solution to existing problems. In general, deep learning offers a fresh approach for improving the performance of EIT image reconstruction and could be the foundation for building an intelligent integrated EIT diagnostic system in the future.

Suppressing interferences of EIT on synchronous recording EEG based on comb filter for seizure detection

Background and objective

The purpose of this study was to eliminate the interferences of electrical impedance tomography (EIT) on synchronous recording electroencephalography (EEG) for seizure detection.

Methods

The simulated EIT signal generated by COMSOL Multiphysics was superimposed on the clinical EEG signal obtained from the CHB-MIT Scalp EEG Database, and then the spectrum features of superimposed mixed signals were analyzed. According to the spectrum analysis, in addition to high-frequency interference at 51.2 kHz related to the drive current, there was also low-frequency interference caused by switching of electrode pairs, which were used to inject drive current. A low pass filter and a comb filter were used to suppress the high-frequency interference and low-frequency interference, respectively. Simulation results suggested the low-pass filter and comb filter working together effectively filtered out the interference of EIT on EEG in the process of synchronous monitoring.

Results

As a result, the normal EEG and epileptic EEG could be recognized effectively. Pearson correlation analysis further confirmed the interference of EIT on EEG was effectively suppressed.

Conclusions

This study provides a simple and effective interference suppression method for the synchronous monitoring of EIT and EEG, which could be served as a reference for the synchronous monitoring of EEG and other medical electromagnetic devices.

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.

Advances in electrical impedance tomography-based brain imaging

Novel advances in the field of brain imaging have enabled the unprecedented clinical application of various imaging modalities to facilitate disease diagnosis and treatment. Electrical impedance tomography (EIT) is a functional imaging technique that measures the transfer impedances between electrodes on the body surface to estimate the spatial distribution of electrical properties of tissues. EIT offers many advantages over other neuroimaging technologies, which has led to its potential clinical use. This qualitative review provides an overview of the basic principles, algorithms, and system composition of EIT. Recent advances in the field of EIT are discussed in the context of epilepsy, stroke, brain injuries and edema, and other brain diseases. Further, we summarize factors limiting the development of brain EIT and highlight prospects for the field. In epilepsy imaging, there have been advances in EIT imaging depth, from cortical to subcortical regions. In stroke research, a bedside EIT stroke monitoring system has been developed for clinical practice, and data support the role of EIT in multi-modal imaging for diagnosing stroke. Additionally, EIT has been applied to monitor the changes in brain water content associated with cerebral edema, enabling the early identification of brain edema and the evaluation of mannitol dehydration. However, anatomically realistic geometry, inhomogeneity, cranium completeness, anisotropy and skull type, etc., must be considered to improve the accuracy of EIT modeling. Thus, the further establishment of EIT as a mature and routine diagnostic technique will necessitate the accumulation of more supporting evidence.

Electrophysiological and pharmacological characterization of spreading depolarization in the adult zebrafish tectum

Spreading depolarization (SD) is a slowly propagating wave of neuronal and glial depolarization. A growing number of studies show that SD and SD-like phenomena play a role in neurological disorders such as migraine, stroke, and traumatic brain injury. Despite the clinical importance of SD, its underlying molecular and cellular mechanisms remain elusive, possibly because of insufficient animal model allowing genetic manipulation. Such a model would also allow high-throughput screening for SD-suppressing drug development. To address this, we developed a novel experimental system to study SD using zebrafish. Electrophysiological recordings in the immobilized adult zebrafish revealed that increasing extracellular potassium concentration elicited SD with a large and long-lasting negative shift of direct current (DC) potential in the optic tectum. It also reduced the oscillatory activity in the extracellular field potential and increased the expression of the immediate early gene c-fos. Pharmacological blocking of the N-methyl-d-aspartate (NMDA) glutamate receptor attenuated the propagation of SD, suggesting that glutamatergic neurotransmission mediated tectal SD in zebrafish. Our analyses revealed that the zebrafish tectum and rodent cortex had similar SD kinetics. The current study provides electrophysiological and pharmacological evidence that zebrafish SD and mammal SD are comparable. This zebrafish SD model is suitable for genetic manipulation and cost-effective high-throughput screening. It could pave the way to novel diagnostic and therapeutic methods applicable to SD-associated neurological disorders.NEW & NOTEWORTHY Previous studies have implicated spreading depolarization (SD) in stroke and migraine. Here, we demonstrate SD, for the first time, in the adult zebrafish tectum showing waveform kinetics, c-fos expression, and attenuation by N-methyl-d-aspartate glutamate receptor blocker as observed in the rodent cortex. Since the zebrafish is an animal model amenable to genetic manipulation and chemical screening, this result could pave the way to novel diagnostic and therapeutic methods applicable to SD-associated neurological disorders.

Review on Electrical Impedance Tomography: Artificial Intelligence Methods and its Applications

Electrical impedance tomography (EIT) has been a hot topic among researchers for the last 30 years. It is a new imaging method and has evolved over the last few decades. By injecting a small amount of current, the electrical properties of tissues are determined and measurements of the resulting voltages are taken. By using a reconstructing algorithm these voltages then transformed into a tomographic image. EIT contains no identified threats and as compared to magnetic resonance imaging (MRI) and computed tomography (CT) scans (imaging techniques), it is cheaper in cost as well. In this paper, a comprehensive review of efforts and advancements undertaken and achieved in recent work to improve this technology and the role of artificial intelligence to solve this non-linear, ill-posed problem are presented. In addition, a review of EIT clinical based applications has also been presented.

Imaging fast electrical activity in the brain during ictal epileptiform discharges with electrical impedance tomography

Electrical Impedance Tomography (EIT) is an emerging medical imaging technique which can produce tomographic images of internal impedance changes within an object using non-penetrating surface electrodes. It has previously been used to image impedance changes due to neuronal depolarisation during evoked potentials in the rat somatosensory cortex with a resolution of 2 ms and <200 μm, using an epicortical electrode array. The purpose of this work was to use this technique to elucidate the intracortical spatiotemporal trajectory of ictal spike-and-wave discharges (SWDs), induced by electrical stimulation in an acute rat model of epilepsy, throughout the cerebral cortex. Seizures lasting 16.5 ± 5.3 s with repetitive 2-5 Hz SWDs were induced in five rats anaesthetised with fentanyl-isoflurane. Transfer impedance measurements were obtained during each seizure with a 57-electrode epicortical array by applying 50 μA current at 1.7 kHz to two electrodes and recording voltages from all remaining electrodes. Images were reconstructed from averaged SWD-related impedance traces obtained from EIT measurements in successive seizures. We report the occurrence of reproducible impedance changes during the initial spike phase, which had an early onset in the whisker barrel cortex and spread posteriorly, laterally and ventrally over 20 ms (p < 0.03125, N = 5). These findings, which confirm and extend knowledge of SWD initiation and expression, suggest that EIT is a valuable neuroimaging tool for improving understanding of neural circuits implicated in epileptic phenomena.

Real-time imaging of epileptic seizures in rats using electrical impedance tomography

The presence of multiple or diffuse lesions on imaging is a contraindication to surgery for patients with intractable epilepsy. Theoretically, as a functional imaging technique, electrical impedance tomography (EIT) can accurately image epileptic foci. However, most current studies are limited to examining epileptic spikes and few studies use EIT for real-time imaging of seizure activity. Moreover, little is known about changes in electrical impedance during seizures. In this study, we used EIT to monitor seizure progression in real time and analyzed changes in electrical impedance during seizures. EIT and electroencephalography data were recorded simultaneously in rats. Sixty-three seizures were recorded from the cortices of eight rats. During 54 seizures, the average impedance decreased by between 4.86 and 9.17% compared with the baseline. Compared with the control group, the average impedance of the experimental group decreased significantly (P=0.004). Our results indicate that EIT can be used to detect and image electrical impedance reduction within lesions during epileptic seizures.

Characterisation and imaging of cortical impedance changes during interictal and ictal activity in the anaesthetised rat

Epilepsy affects approximately 50 million people worldwide, and 20–30% of these cases are refractory to antiepileptic drugs. Many patients with intractable epilepsy can benefit from surgical resection of the tissue generating the seizures; however, difficulty in precisely localising seizure foci has limited the number of patients undergoing surgery as well as potentially lowered its effectiveness. Here we demonstrate a novel imaging method for monitoring rapid changes in cerebral tissue impedance occurring during interictal and ictal activity, and show that it can reveal the propagation of pathological activity in the cortex. Cortical impedance was recorded simultaneously to ECoG using a 30-contact electrode mat placed on the exposed cortex of anaesthetised rats, in which interictal spikes (IISs) and seizures were induced by cortical injection of 4-aminopyridine (4-AP), picrotoxin or penicillin. We characterised the tissue impedance responses during IISs and seizures, and imaged these responses in the cortex using Electrical Impedance Tomography (EIT). We found a fast, transient drop in impedance occurring as early as 12 ms prior to the IISs, followed by a steep rise in impedance within ~ 120 ms of the IIS. EIT images of these impedance changes showed that they were co-localised and centred at a depth of 1 mm in the cortex, and that they closely followed the activity propagation observed in the surface ECoG signals. The fast, pre-IIS impedance drop most likely reflects synchronised depolarisation in a localised network of neurons, and the post-IIS impedance increase reflects the subsequent shrinkage of extracellular space caused by the intense activity. EIT could also be used to picture a steady rise in tissue impedance during seizure activity, which has been previously described. Thus, our results demonstrate that EIT can detect and localise different physiological changes during interictal and ictal activity and, in conjunction with ECoG, may in future improve the localisation of seizure foci in the clinical setting.

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Cortical impedance was measured simultaneously to EEG during epileptic activity.

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Interictal spikes were preceded by fast decreases in cortical impedance.

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Steep increases in impedance followed both interictal spikes and onset of ictal activity.

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Imaging with Electrical Impedance Tomography revealed the location of epilepsy-related impedance changes.

Use of electrical impedance tomography to monitor regional cerebral edema during clinical dehydration treatment

OBJECTIVE

Variations of conductive fluid content in brain tissue (e.g. cerebral edema) change tissue impedance and can potentially be measured by Electrical Impedance Tomography (EIT), an emerging medical imaging technique. The objective of this work is to establish the feasibility of using EIT as an imaging tool for monitoring brain fluid content.

DESIGN

a prospective study.

SETTING

In this study EIT was used, for the first time, to monitor variations in cerebral fluid content in a clinical model with patients undergoing clinical dehydration treatment. The EIT system was developed in house and its imaging sensitivity and spatial resolution were evaluated on a saline-filled tank.

PATIENTS

23 patients with brain edema.

INTERVENTIONS

The patients were continuously imaged by EIT for two hours after initiation of dehydration treatment using 0.5 g/kg intravenous infusion of mannitol for 20 minutes.

MEASUREMENT AND MAIN RESULTS

Overall impedance across the brain increased significantly before and after mannitol dehydration treatment (p = 0.0027). Of the all 23 patients, 14 showed high-level impedance increase and maintained this around 4 hours after the dehydration treatment whereas the other 9 also showed great impedance gain during the treatment but it gradually decreased after the treatment. Further analysis of the regions of interest in the EIT images revealed that diseased regions, identified on corresponding CT images, showed significantly less impedance changes than normal regions during the monitoring period, indicating variations in different patients' responses to such treatment.

CONCLUSIONS

EIT shows potential promise as an imaging tool for real-time and non-invasive monitoring of brain edema patients.

Direct observation of unstained biological specimens in water by the frequency transmission electric-field method using SEM

Scanning electron microscopy (SEM) is a powerful tool for the direct visualization of biological specimens at nanometre-scale resolution. However, images of unstained specimens in water using an atmospheric holder exhibit very poor contrast and heavy radiation damage. Here, we present a new form of microscopy, the frequency transmission electric-field (FTE) method using SEM, that offers low radiation damage and high-contrast observation of unstained biological samples in water. The wet biological specimens are enclosed in two silicon nitride (SiN) films. The metal-coated SiN film is irradiated using a focused modulation electron beam (EB) at a low-accelerating voltage. A measurement terminal under the sample holder detects the electric-field frequency signal, which contains structural information relating to the biological specimens. Our results in very little radiation damage to the sample, and the observation image is similar to the transmission image, depending on the sample volume. Our developed method can easily be utilized for the observation of various biological specimens in water.

Real-time imaging of cerebral infarction in rabbits using electrical impedance tomography

Objective

To investigate the possible use of electrical impedance tomography (EIT) in monitoring focal cerebral infarction in a rabbit model.

Methods

A model of focal cerebral infarction was established in eight New Zealand rabbits using a photochemical method without craniectomy. Focal cerebral infarction was confirmed by histopathological examination. Intracranial impedance variation was measured using 16 electrodes placed in a circle on the scalp. EIT images were obtained using a damped least-squares reconstruction algorithm. The average resistivity value (ARV) of the infarct region on EIT images was calculated to quantify relative resistivity changes. A symmetry index was calculated to evaluate the relative difference in resistivity between the two sides of the cerebrum.

Results

EIT images and ARV curves showed that impedance changes caused by cerebral infarction increased linearly with irradiation time. A difference in ARV was found between measurements taken before and after infarct induction.

Conclusions

Focal cerebral infarction can be monitored by EIT in the proposed animal model. The results are sufficiently encouraging that the authors plan to extend this study to humans, after further technical improvements.

Development of an Anatomically Realistic Forward Solver for Thoracic Electrical Impedance Tomography

Electrical impedance tomography (EIT) has the potential to provide a low cost and safe imaging modality for clinically monitoring patients being treated with mechanical ventilation. Variations in reconstruction algorithms at different clinical settings, however, make interpretation of regional ventilation across institutions difficult, presenting the need for a unified algorithm for thoracic EIT reconstruction. Development of such a consensual reconstruction algorithm necessitates a forward model capable of predicting surface impedance measurements as well as electric fields in the interior of the modeled thoracic volume. In this paper, we present an anatomically realistic forward solver for thoracic EIT that was built based on high resolution MR image data of a representative adult. Accuracy assessment of the developed forward solver in predicting surface impedance measurements by comparing the predicted and observed impedance measurements shows that the relative error is within the order of 5%, demonstrating the ability of the presented forward solver in generating high-fidelity surface thoracic impedance data for thoracic EIT algorithm development and evaluation.

In vivo imaging of twist drill drainage for subdural hematoma: a clinical feasibility study on electrical impedance tomography for measuring intracranial bleeding in humans

Intracranial bleeding is one of the most severe medical emergencies in neurosurgery. Early detection or diagnosis would largely reduce the rate of disability and mortality, and improve the prognosis of the patients. Electrical Impedance Tomography (EIT) can non-invasively image the internal resistivity distribution within a human body using a ring of external electrodes, and is thus a promising technique to promptly detect the occurrence of intracranial bleedings because blood differs from other brain tissues in resistivity. However, so far there is no experimental study that has determined whether the intracranial resistivity changes in humans could be repeatedly detected and imaged by EIT. Hence, we for the first time attempt to clinically validate this by in vivo imaging the influx and efflux of irrigating fluid (5% dextrose in water, D5W) during the twist-drill drainage operation for the patients with subdural hematoma (SDH). In this study, six patients (four male, two female) with subacute or chronic SDH received the surgical operation in order to evacuate the hematoma around subdural region, and EIT measurements were performed simultaneously on each patient's head. The results showed that the resistivity significantly increased on the corresponding position of EIT images during the influx of D5W and gradually decreased back to baseline during the efflux. In the quantitative analysis, the average resistivity values demonstrated the similar results and had highly linear correlation (R(2) = 0.93 ± 0.06) with the injected D5W volumes, as well as the area of the resistivity gain(R(2) = 0.94 ± 0.05). In conclusion, it was clinically validated that intracranial resistivity changes in humans were detectable and quantifiable by the EIT method. After further technical improvements, EIT has the great potential of being a routine neuroimaging tool for early detection of intracranial bleedings.

Induced current magnetic resonance electrical impedance tomography of brain tissues based on the J-substitution algorithm: a simulation study

We have investigated induced current magnetic resonance electrical impedance tomography (IC-MREIT) by means of computer simulations. The J-substitution algorithm was implemented to solve the IC-MREIT reconstruction problem. By providing physical insight into the charge accumulating on the interfaces, the convergence characteristics of the reconstruction algorithm were analyzed. The simulation results conducted on different objects were well correlated with the proposed theoretical analysis. The feasibility of IC-MREIT to reconstruct the conductivity distribution of head-brain tissues was also examined in computer simulations using a multi-compartment realistic head model. The present simulation results suggest that IC-MREIT may have the potential to become a useful conductivity imaging technique.

Images reproducibility of an electrical impedance tomography (EIT) prototype. Analysis of the EIT sensibility in rats in pathological in vivo conditions

The development of a 16 electrode-electrical impedance tomography (EIT) prototype to be applied in neurological fields such as epilepsy in rats has been previously reported. Approaching residual problems in order to improve its performance, this work reports results about changes made in the system hardware as follows: 1) replacing the current source demultiplexing circuit that could impact on a better spatial localization, and 2) a new current source design that increases the current amplitude up to 5 mA/sub rms/. System was evaluated by means of: a) image reproducibility starting from 4 test elements in homogeneous conditions; and b) spatial localization evaluation in conductivity perturbation conditions; this feature is evaluated too in preliminary acute in vivo experiments where an epileptic seizure is induced, and an impedance increase is expected. Results show a 95% of proper images for a) analysis. Spatial localization reports improvement up to 20% transversely and 5.5% longitudinally with regard to previous results. In vivo results are lack of interpretation due poor changes obtained in images. In order to conclude or not a reliable correlation between the perturbation measured and the seizure activity, a new definition of grey scale or other changes could be proposed.

A narrow-band level set method applied to EIT in brain for cryosurgery monitoring

In this paper, we investigate the feasibility of applying a novel level set reconstruction technique to electrical imaging of the human brain. We focus particularly on the potential application of electrical impedance tomography (EIT) to cryosurgery monitoring. In this application, cancerous tissue is treated by a local freezing technique using a small needle-like cryosurgery probe. The interface between frozen and nonfrozen tissue can be expected to have a relatively high contrast in conductivity and we treat the inverse problem of locating and monitoring this interface during the treatment. A level set method is used as a powerful and flexible tool for tracking the propagating interfaces during the monitoring process. For calculating sensitivities and the Jacobian when deforming the interfaces we employ an adjoint formula rather than a direct differentiation technique. In particular, we are using a narrow-band technique for this procedure. This combination of an adjoint technique and a narrow-band technique for calculating Jacobians results in a computationally efficient and extremely fast method for solving the inverse problem. Moreover, due to the reduced number of unknowns in each step of the narrow-band approach compared to a pixel- or voxel-based technique, our reconstruction scheme tends to be much more stable. We demonstrate that our new method also outperforms its pixel-/voxel-based counterparts in terms of image quality in this application.

Factors limiting the application of electrical impedance tomography for identification of regional conductivity changes using scalp electrodes during epileptic seizures in humans

Electrical impedance tomography (EIT) has the potential to produce images during epileptic seizures. This might improve the accuracy of the localization of epileptic foci in patients undergoing presurgical assessment for curative neurosurgery. It has already been shown that impedance increases by up to 22% during induced epileptic seizures in animal models, using cortical or implanted electrodes in controlled experiments. The purpose of this study was to determine if reproducible raw impedance changes and EIT images could be collected during epileptic seizures in patients who were undergoing observation with video-electroencephalography (EEG) telemetry as part of evaluation prior to neurosurgery to resect the region of brain causing the epilepsy. A secondary purpose was to develop an objective method for processing and evaluating data, as seizures arose at unpredictable times from a noisy baseline. Four-terminal impedance measurements from 258 combinations were collected continuously using 32 EEG scalp electrodes in 22 seizure episodes from 7 patients during their presurgical assessment together with the standard EEG recordings. A reliable method for defining the pre-seizure baseline and recording impedance data and EIT images was developed, in which EIT and EEG could be acquired simultaneously after filtering of EIT artefact from the EEG signal. Fluctuations of several per cent over minutes were observed in the baseline between seizures. During seizures, boundary voltage changes diverged with a standard deviation of 1-54% from the baseline. No reproducible changes with the expected time course of some tens of seconds and magnitude of about 0.1% could be reliably measured. This demonstrates that it is feasible to acquire EIT images in parallel with standard EEG during presurgical assessment but, unfortunately, expected EIT changes on the scalp of about 0.1% are swamped by much larger movement and systematic artefact. Nevertheless, EIT has the unique potential to provide invaluable neuroimaging data for this purpose and may still become possible with improvements in electrode design and instrumentation.

Improving the forward solver for the complete electrode model in EIT using algebraic multigrid

Image reconstruction in electrical impedance tomography is an ill-posed nonlinear inverse problem. Linearization techniques are widely used and require the repeated solution of a linear forward problem. To account correctly for the presence of electrodes and contact impedances, the so-called complete electrode model is applied. Implementing a standard finite element method for this particular forward problem yields a linear system that is symmetric and positive definite and solvable via the conjugate gradient method. However, preconditioners are essential for efficient convergence. Preconditioners based on incomplete factorization methods are commonly used but their performance depends on user-tuned parameters. To avoid this deficiency, we apply black-box algebraic multigrid, using standard commercial and freely available software. The suggested solution scheme dramatically reduces the time cost of solving the forward problem. Numerical results are presented using an anatomically detailed model of the human head.

Use of 3-D magnetic resonance electrical impedance tomography in detecting human cerebral stroke: a simulation study

We have developed a new three dimensional (3-D) conductivity imaging approach and have used it to detect human brain conductivity changes corresponding to acute cerebral stroke. The proposed Magnetic Resonance Electrical Impedance Tomography (MREIT) approach is based on the J-Substitution algorithm and is expanded to imaging 3-D subject conductivity distribution changes. Computer simulation studies have been conducted to evaluate the present MREIT imaging approach. Simulations of both types of cerebral stroke, hemorrhagic stroke and ischemic stroke, were performed on a four-sphere head model. Simulation results showed that the correlation coefficient (CC) and relative error (RE) between target and estimated conductivity distributions were 0.9245+/-0.0068 and 8.9997%+/-0.0084%, for hemorrhagic stroke, and 0.6748+/-0.0197 and 8.8986%+/-0.0089%, for ischemic stroke, when the SNR (signal-to-noise radio) of added GWN (Gaussian White Noise) was 40. The convergence characteristic was also evaluated according to the changes of CC and RE with different iteration numbers. The CC increases and RE decreases monotonously with the increasing number of iterations. The present simulation results show the feasibility of the proposed 3-D MREIT approach in hemorrhagic and ischemic stroke detection and suggest that the method may become a useful alternative in clinical diagnosis of acute cerebral stroke in humans.

On the conservation of fast calcium wave speeds

Calcium waves were first seen about 25 years ago as the giant, 10 micro m/s wave or tsunami which crosses the cytoplasm of an activating medaka fish egg [J Cell Biol 76 (1978) 448]. By 1991, reports of such waves with approximately 10 micro m/s velocities through diverse, activating eggs and with approximately 30 micro m/s velocities through diverse, fully active systems had been compiled to form a class of what are now called fast calcium waves [Proc Natl Acad Sci USA 88 (1991) 9883; Bioessays 21 (1999) 657]. This compilation is now updated to include organisms from algae and sponges up to blowflies, squid and men and organizational levels from mammalian brains and hearts as well as chick embryos down to muscle, nerve, epithelial, blood and cancer cells and even cell-free extracts. Plots of these data confirm the narrow, 2-3-fold ranges of fast wave speeds through activating eggs and 3-4-fold ones through fully active systems at a given temperature. This also indicate Q(10)'s of 2.7-fold per 10 degrees C for both activating eggs and for fully activated cells.Speeds through some ultraflat preparations which are a few-fold above the conserved range are attributed to stretch propagated calcium entry (SPCE) rather than calcium-induced calcium release (CICR).

Krylov subspace iterative techniques: on the detection of brain activity with electrical impedance tomography

In this paper, we review some numerical techniques based on the linear Krylov subspace iteration that can be used for the efficient calculation of the forward and the inverse electrical impedance tomography problems. Exploring their computational advantages in solving large-scale systems of equations, we specifically address their implementation in reconstructing localized impedance changes occurring within the human brain. If the conductivity of the head tissues is assumed to be real, the pre-conditioned conjugate gradients (PCGs) algorithm can be used to calculate efficiently the approximate forward solution to a given error tolerance. The performance and the regularizing properties of the PCG iteration for solving ill-conditioned systems of equations (PCGNs) is then explored, and a suitable preconditioning matrix is suggested in order to enhance its convergence rate. For image reconstruction, the nonlinear inverse problem is considered. Based on the Gauss-Newton method for solving nonlinear problems we have developed two algorithms that implement the PCGN iteration to calculate the linear step solution. Using an anatomically detailed model of the human head and a specific scalp electrode arrangement, images of a simulated impedance change inside brain's white matter have been reconstructed.

Validation of a 3D reconstruction algorithm for EIT of human brain function in a realistic head-shaped tank

Previous work has demonstrated that electrical impedance tomography can be used to image human brain activity during evoked responses, but two-thirds of the reconstructed images fail to localize an impedance change to the expected stimulated cortical area. The localization failure may be caused by modelling the head as a homogenous sphere in the reconstruction algorithm. This assumption may lead to errors when used to reconstruct data obtained from the human head. In this study a 3D reconstruction algorithm, based on a model of the head as a homogenous sphere, was characterized by simulating the algorithm model, the head shape and the presence of the skull in saline-filled tanks. EIT images of a sponge, 14 cm3 volume with a resistivity contrast of 12%, were acquired in three different positions in tanks filled with 0.2% saline. In a hemispherical tank, 19 cm in diameter, the sponge was localized to within 3.4-10.7% of the tank diameter. In a head-shaped tank, the errors were between 3.1 and 13.3% without a skull and between 10.3 and 18.7% when a real human skull was present. A significant increase in localization error therefore occurs if an algorithm based on a homogeneous sphere is used on data acquired from a head-shaped tank. The increased error is due to the presence of the skull, as no significant increase in error occurred if a head-shaped tank was used without the skull present, compared to the localization error within the hemispherical tank. The error due to the skull significantly shifted the impedance change within the skull towards the centre of the image. Although the increased localization error due to the skull is not sufficient to explain the localization errors of up to 50% of the image diameter present in the images of some human subjects, the future use of a realistic head model in the reconstruction algorithm is likely to reduce the localization error in the human images due to the presence of the skull.

Three-dimensional electrical impedance tomography of human brain activity

Regional cerebral blood flow and blood volume changes that occur during human brain activity will change the local impedance of that cortical area, as blood has a lower impedance than that of brain. Theoretically, such impedance changes could be measured from scalp electrodes and reconstructed into images of the internal impedance of the head. Electrical Impedance Tomography (EIT) is a newly developed technique by which impedance measurements from the surface of an object are reconstructed into impedance images. It is fast, portable, inexpensive, and noninvasive, but has a relatively low spatial resolution. EIT images were recorded with scalp electrodes and an EIT system, specially optimized for recording brain function, in 39 adult human subjects during visual, somatosensory, or motor activity. Reproducible impedance changes of about 0.5% occurred in 51/52 recordings, which lasted from 6 s after the stimulus onset to 41 s after stimulus cessation. When these changes were reconstructed into impedance images, using a novel 3-D reconstruction algorithm, 19 data sets demonstrated significant impedance changes in the appropriate cortical region. This demonstrates, for the first time, that significant impedance changes, which could form the basis for a novel neuroimaging technology, may be recorded in human subjects with scalp electrodes. The final images contained spatial noise and strategies to reduce this in future work are presented.

Electrical impedance tomography of human brain activity with a two-dimensional ring of scalp electrodes

Previously, electrical impedance tomography (EIT) has been used to image impedance decreases in the exposed cortex of rabbits during brain activity. These are due to increased blood volume at the site of the stimulated cortex; as blood has a lower impedance than brain, the impedance decreases. During human brain activity similar blood flow changes have been detected using positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). If blood volume also changes then the impedance of human cortex will change during brain activity; this could theoretically be imaged with EIT. EIT data were recorded from a ring of 16 scalp electrodes in 34 recordings in 19 adult volunteers before, during and after stimulation with (1) a visual stimulus produced by an 8 Hz oscillating checkerboard pattern or (2) sensory stimulation of the median nerve at the wrist by a 3 Hz electrical square wave stimulus. Reproducible impedance changes, with a similar timecourse to the stimulus, were seen in all experiments. Significant impedance changes were seen in 21 +/- 5% (n = 16, mean +/- SEM) and 19 +/- 3% (n = 18) of the electrode measurements for visual and somatosensory paradigms respectively. The reconstructed 2D EIT images showed reproducible impedance changes in the approximate region of the stimulated cortex in 7/16 visual and 5/18 somatosensory experiments. This demonstrates that reproducible impedance changes can be measured during human brain activity. The final images contained spatial noise; the reasons for this and strategies to reduce this in future are discussed.

Two-dimensional finite element modelling of the neonatal head

Electrical impedance tomography (EIT) could allow the early diagnosis of infant brain injury following birth asphyxia. The purpose of this work was to determine the effect of variations in skull, scalp or cerebrospinal fluid (CSF) resistivity, as these vary in clinical conditions and could degrade image quality. These factors were investigated using finite element models of the adult and neonatal head. The results suggest that there is a wide range over which the resistivity of the neonatal skull has little effect on the sensitivity to a central impedance change. The scalp and CSF appear to shunt current away from the brain; when their resistivity was decreased from normal values, this shunting effect increased and caused a decrease in sensitivity to a central resistance change. The resistivity of neonatal skull has not, to our knowledge, been directly measured and will anyway vary within and between individuals; this work suggests that EIT will be relatively insensitive to variations in neonatal skull impedance.

Electrical conductivity imaging via contactless measurements

A new imaging modality is introduced to image electrical conductivity of biological tissues via contactless measurements. This modality uses magnetic excitation to induce currents inside the body and measures the magnetic fields of the induced currents. In this study, the mathematical basis of the methodology is analyzed and numerical models are developed to simulate the imaging system. The induced currents are expressed using the A-phi formulation of the electric field where A is the magnetic vector potential and phi is the scalar potential function. It is assumed that A describes the primary magnetic vector potential that exists in the absence of the body. This assumption considerably simplifies the solution of the secondary magnetic fields caused by induced currents. In order to solve phi for objects of arbitrary conductivity distribution a three-dimensional (3-D) finite-element method (FEM) formulation is employed. A specific 7 x 7-coil system is assumed nearby the upper surface of a 10 x 10 x 5-cm conductive body. A sensitivity matrix, which relates the perturbation in measurements to the conductivity perturbations, is calculated. Singular-value decomposition of the sensitivity matrix shows various characteristics of the imaging system. Images are reconstructed using 500 voxels in the image domain, with truncated pseudoinverse. The noise level is assumed to produce a representative signal-to-noise ratio (SNR) of 80 dB. It is observed that it is possible to identify voxel perturbations (of volume 1 cm3) at 2 cm depth. However, resolution gradually decreases for deeper conductivity perturbations.

Assessment and calibration of a low-frequency system for electrical impedance tomography (EIT), optimized for use in imaging brain function in ambulant human subjects

An EIT system has been produced that has been optimized for imaging impedance changes with scalp electrodes during brain activity in ambulant subjects. It can record from 225 Hz to 65 kHz, has a small headbox on a lead 10 m long, and has software programmable electrode selection. In calibration experiments in a small cylindrical tank filled with potassium chloride solution and samples of cucumber, noise was less than 1% with averaging, and acceptable images were produced at frequencies down to 1800 Hz. This suggests that EIT can be performed at low frequencies, which are likely to give larger signals during brain activity. Future work will include trials in humans and improvement of the current source and isolation.

On the conservation of calcium wave speeds

Most long distance calcium signals are believed to take the form of actively propagated calcium waves. In 1991, when this proposal was first advanced, all such waves were thought to belong to one class, for which fertilization waves were the prototype. Moreover, the speeds of such waves were found to be conserved at about 10 microns/s for primary fertilization waves and 30 microns/s for waves through fully active systems at 20 degrees C. In 1993, preliminary evidence for a second class of such waves was published and the prototype for these were ones which drive cell cleavage. These move at only about 1 micron/s at 20 degrees C and were, therefore, called slow calcium waves as opposed to the fast ones first considered. Here we compile compelling evidence that slow waves comprise a second distinct class of actively propagated calcium waves. This is based on 30 papers which yield evidence of slow calcium waves in organisms ranging from Dictyostelium to mammals and phenomena ranging from the surface contraction waves seen long ago in axolotl eggs to embryonic cleavage and mitotic waves and to ones recently seen to accompany primary neural induction in axolotls. Ultraslow and ultrafast calcium waves are also considered.

Electrical impedance tomography

Electrical impedance tomography (EIT) is a technique which allows cross-sectional images related to the local electrical impedance within an object to be reconstructed from sets of measurements made on its surface. The main drive behind the development of EIT has been its possible application in medical imaging, as biological tissues are known to exhibit a wide range of electrical impedance and many physiological events are accompanied by electrical impedance changes. This article reviews the technical aspects of EIT as a medical imaging modality, and considers the range of applications over which it might be employed. Existing technical limitations and future developments are discussed. It is concluded that the future of EIT as a clinical diagnostic tool is likely to lie in the area of functional monitoring, where the capability of performing image-guided localized electrical impedance measurements with high acquisition speed, good sensitivity and no hazard can be exploited.

Imaging of physiologically evoked responses by electrical impedance tomography with cortical electrodes in the anaesthetized rabbit

The purpose of this study was to determine if electrical impedance tomography (EIT) could be used to image impedance changes of several per cent over tens of seconds, known to occur during evoked activity of the cerebral cortex. A ring of 16 electrodes was placed on the exposed superior surface of the brain of anaesthetized rabbits. EIT images were acquired every 15 s using a Sheffield Mark 1 EIT system. During periods of 2.5-3 min of intense photic stimulation of both eyes or electrical stimulation of a forepaw, reproducible impedance decreases of 4.5 +/- 2.7% and 2.7 +/- 2.4% (mean +/- SD) respectively occurred in appropriate cortical areas, with a time course similar to the period of stimulation. They were accompanied by adjacent smaller impedance increases. The decreases are probably due to increased blood flow and temperature; the cause of the adjacent increases may be a shadowing artefact of the reconstruction algorithm or due to physiological shrinkage of the extracellular space. This demonstrated, for the first time, that such small changes may be imaged under optimal conditions. These results are encouraging to the prospect that EIT may eventually be suitable for imaging evoked responses or epilepsy in human subjects.

Design considerations and performance of a prototype system for imaging neuronal depolarization in the brain using 'direct current' electrical resistance tomography

The ability to image the impedance changes that accompany neuronal depolarization in the brain would constitute a major advance in neuroscience technology. Unfortunately, these changes are likely to be small and rapid and so difficult to measure. The impedance change at frequencies above 10 kHz, as used by conventional EIT systems, may be estimated to be about 0.1%. Modelling indicates that a much larger impedance change of about 7% may occur with DC or very-low-frequency excitation. Difficulties with this approach include a low permissive current level and high electrode impedance. We constructed a prototype system employing square wave excitation at 5 Hz to evaluate such problems. It was tested in a saline-filled tank, recording 4000 frames s-1 at a current level of 50 microA. After averaging 100 sets of frames, the signal to noise ratio was 40-50 dB, and reciprocity errors were mostly 10-20%. Images of discrete resistivity changes of less than 10% could be obtained, but with significant systematic errors. While our prototype would not be suitable for neurophysiological imaging as it stands, it has enabled us to determine the modifications that would be required to construct a system for this application.