Imaging of focal seizures with Electrical Impedance Tomography and depth electrodes in real time

Early detection of acute ischemic stroke using Contrast-enhanced electrical impedance tomography perfusion

A cerebral contrast-enhanced electrical impedance tomography perfusion method is developed for acute ischemic stroke during intravenous thrombolytic therapy. Several clinical contrast agents with stable impedance characteristics and high-conductivity contrast were screened experimentally as electrical impedance contrast agent candidates. The electrical impedance tomography perfusion method was tested on rabbits with focal cerebral infarction, and its capability for early detection was verified based on perfusion images. The experimental results showed that ioversol 350 performed significantly better as an electrical impedance contrast agent than other contrast agents (p < 0.01). Additionally, perfusion images of focal cerebral infarction in rabbits confirmed that the electrical impedance tomography perfusion method could accurately detect the location and area of different cerebral infarction lesions (p < 0.001). Therefore, the cerebral contrast-enhanced electrical impedance tomography perfusion method proposed herein combines traditional, dynamic continuous imaging with rapid detection and could be applied as an early, rapid-detection, auxiliary, bedside imaging method for patients after a suspected ischemic stroke in both prehospital and in-hospital settings.

Attenuation of initial pilocarpine-induced electrographic seizures by methionine sulfoximine pretreatment tightly correlates with the reduction of extracellular taurine in the hippocampus

OBJECTIVE

Initiation and development of early seizures by chemical stimuli is associated with brain cell swelling resulting in edema of seizure-vulnerable brain regions. We previously reported that pretreatment with a nonconvulsive dose of glutamine (Gln) synthetase inhibitor methionine sulfoximine (MSO) mitigates the intensity of initial pilocarpine (Pilo)-induced seizures in juvenile rats. We hypothesized that MSO exerts its protective effect by preventing the seizure-initiating and seizure-propagating increase of cell volume. Taurine (Tau) is an osmosensitive amino acid, whose release reflects increased cell volume. Therefore, we tested whether the poststimulus rise of amplitude of Pilo-induced electrographic seizures and their attenuation by MSO are correlated with the release of Tau from seizure-affected hippocampus.

METHODS

Lithium-pretreated animals were administered MSO (75 mg/kg ip) 2.5 h before the induction of convulsions by Pilo (40 mg/kg ip). Electroencephalographic (EEG) power was analyzed during 60 min post-Pilo, at 5-min intervals. Extracellular accumulation of Tau (eTau) served as a marker of cell swelling. eTau, extracellular Gln (eGln), and extracellular glutamate (eGlu) were assayed in the microdialysates of the ventral hippocampal CA1 region collected at 15-min intervals during the whole 3.5-h observation period.

RESULTS

The first EEG signal became apparent at ~10 min post-Pilo. The EEG amplitude across most frequency bands peaked at ~40 min post-Pilo, and showed strong (r ~ .72-.96) temporal correlation with eTau, but no correlation with eGln or eGlu. MSO pretreatment delayed the first EEG signal in Pilo-treated rats by ~10 min, and depressed the EEG amplitude across most frequency bands, to values that remained strongly correlated with eTau (r > .92) and moderately correlated (r ~ -.59) with eGln, but not with eGlu.

SIGNIFICANCE

Strong correlation between attenuation of Pilo-induced seizures and Tau release indicates that the beneficial effect of MSO is due to the prevention of cell volume increase concurrent with the onset of seizures.

Indirect Effects of Halorhodopsin Activation: Potassium Redistribution, Nonspecific Inhibition, and Spreading Depolarization

The movement of ions in and out of neurons can exert significant effects on neighboring cells. Here we report several experimentally important consequences of activation of the optogenetic chloride pump, halorhodopsin. We recorded extracellular K+ concentration ([K+]extra) in neocortical brain slices prepared from young adult mice (both sexes) which express halorhodopsin in pyramidal cells. Strong halorhodopsin activation induced a pronounced drop in [K+]extra that persisted for the duration of illumination. Pharmacological blockade of K+ channels reduced the amplitude of this drop, indicating that it represents K+ redistribution into cells during the period of hyperpolarization. Halorhodopsin thus drives the inward movement of both Cl- directly, and K+ secondarily. When the illumination period ended, a rebound surge in extracellular [K+] developed over tens of seconds, partly reflecting the previous inward redistribution of K+, but additionally driven by clearance of Cl- coupled to K+ by the potassium-chloride cotransporter, KCC2. The drop in [K+]extra during light activation leads to a small (2-3 mV) hyperpolarization also of other cells that do not express halorhodopsin. Its activation therefore has both direct and indirect inhibitory effects. Finally, we show that persistent strong activation of halorhodopsin causes cortical spreading depolarizations (CSDs), both in vitro and in vivo This novel means of triggering CSDs is unusual, in that the events can arise during the actual period of illumination, when neurons are being hyperpolarized and [K+]extra is low. We suggest that this fundamentally different experimental model of CSDs will open up new avenues of research to explain how they occur naturally.SIGNIFICANCE STATEMENT Halorhodopsin is a light-activated electrogenic chloride pump, which has been widely used to inhibit neurons optogenetically. Here, we demonstrate three previously unrecognized consequences of its use: (1) intense activation leads to secondary movement of K+ ions into the cells; (2) the resultant drop in extracellular [K+] reduces excitability also in other, nonexpressing cells; and (3) intense persistent halorhodopsin activation can trigger cortical spreading depolarization (CSD). Halorhodopsin-induced CSDs can occur when neurons are hyperpolarized and extracellular [K+] is low. This contrasts with the most widely used experimental models that trigger CSDs with high [K+]. Both models, however, are consistent with the hypothesis that CSDs arise following net inward ionic movement into the principal neuron population.

Intracranial electrophysiological recordings on a swine model of mesial temporal lobe epilepsy

Objective

To test the feasibility and reliability of intracranial electrophysiological recordings in an acute status epilepticus model on laboratory swine.

Method

Intrahippocampal injection of kainic acid (KA) was performed on 17 male Bama pigs (Sus scrofa domestica) weighing between 25 and 35 kg. Two stereoelectroencephalography (SEEG) electrodes with a total of 16 channels were implanted bilaterally along the sensorimotor cortex to the hippocampus. Brain electrical activity was recorded 2 h daily for 9-28 days. Three KA dosages were tested to evaluate the quantities capable of evoking status epilepticus. Local field potentials (LFPs) were recorded and compared before and after the KA injection. We quantified the epileptic patterns, including the interictal spikes, seizures, and high-frequency oscillations (HFOs), up to 4 weeks after the KA injection. Test-retest reliability using intraclass correlation coefficients (ICCs) were performed on interictal HFO rates to evaluate the recording stability of this model.

Results

The KA dosage test suggested that a 10 μl (1.0 μg/μl) intrahippocampal injection could successfully evoke status epilepticus lasting from 4 to 12 h. At this dosage, eight pigs (50% of total) had prolonged epileptic events (tonic-chronic seizures + interictal spikes n = 5, interictal spikes alone n = 3) in the later 4 weeks of the video-SEEG recording period. Four pigs (25% of total) had no epileptic activities, and another four (25%) had lost the cap or did not complete the experiments. Animals that showed epileptiform events were grouped as E + (n = 8) and the four animals showing no signs of epileptic events were grouped as E- (n = 4). A total of 46 electrophysiological seizures were captured in the 4-week post-KA period from 4 E + animals, with the earliest onset on day 9. The seizure durations ranged from 12 to 45 s. A significant increase of hippocampal HFOs rate (num/min) was observed in the E+ group during the post-KA period (weeks 1, 2,4, p < 0.05) compared to the baseline. But the E-showed no change or a decrease (in week 2, p = 0.43) compared to their baseline rate. The between-group comparison showed much higher HFO rates in E + vs. E - (F = 35, p < 0.01). The high ICC value [ICC (1, k) = 0.81, p < 0.05] quantified from the HFO rate suggested that this model had a stable measurement of HFOs during the four-week post-KA periods.

Significance

This study measured intracranial electrophysiological activity in a swine model of KA-induced mesial temporal lobe epilepsy (mTLE). Using the clinical SEEG electrode, we distinguished abnormal EEG patterns in the swine brain. The high test-retest reliability of HFO rates in the post-KA period suggests the utility of this model for studying mechanisms of epileptogenesis. The use of swine may provide satisfactory translational value for clinical epilepsy research.

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.

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.

Lung area estimation using functional tidal electrical impedance variation images and active contouring

OBJECTIVE

Electrical impedance tomography is a valuable tool for monitoring global and regional lung mechanics. To evaluate the recorded data, an accurate estimate of the lung area is crucial.

APPROACH

We present two novel methods for estimating the lung area using functional tidal images or active contouring methods. A convolutional neural network was trained to determine, whether or not the heart region was visible within tidal images. In addition, the effects of lung area mirroring were investigated. The performance of the methods and the effects of mirroring were evaluated via a score based on the impedance magnitudes in functional tidal images.

MAIN RESULTS

Our analyses showed that the method based on functional tidal images provided the best estimate of the lung area. Mirroring of the lung area had an impact on the accuracy of area estimation for both methods. The achieved accuracy of the neural network's classification was 94%. For images without a visible heart area, the subtraction of a heart template proved to be a pragmatic approach with good results.

SIGNIFICANCE

In summary, we developed a routine for estimation of the lung area combined with estimation of the heart area in electrical impedance tomography images.

On-Chip Sinusoidal Signal Generators for Electrical Impedance Spectroscopy: Methodological Review

This paper reviews architectures and circuit implementations of on-chip sinusoidal signal generators (SSGs) for electrical impedance spectroscopy (EIS) applications. In recent years, there have been increasing interests in on-chip EIS systems, which measure a target material's impedance spectrum over a frequency range. The on-chip implementation allows EIS systems to have low power and small form factor, enabling various biomedical applications. One of the key building blocks of on-chip EIS systems is on-chip SSG, which determines the frequency range and the analysis precision of the whole EIS system. On-chip SSGs are generally required to have high linearity, wide frequency range, and high power and area efficiency. They are typically composed of three stages in general: waveform generation, linearity enhancement, and current injection. First, a sinusoidal waveform should be generated in SSGs. The generated waveform's frequency should be accurately adjustable over a wide range. The firstly generated waveform may not be perfectly linear, including unwanted harmonics. In the following linearity-enhancement step, these harmonics are attenuated by using filters typically. As the linearity of the waveform is improved, the precision of the EIS system gets ensured. Lastly, the filtered voltage waveform is now converted to a current by a current driver. Then, the current sinusoidal signal is injected into the target impedance. This review discusses the principles, advantages, and disadvantages of various techniques applied to each step in state-of-the-art on-chip SSGs. In addition, state-of-the-art designs are compared and summarized.

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.