Impedance changes recorded with scalp electrodes during visual evoked responses: implications for Electrical Impedance Tomography of fast neural activity

Non-invasive imaging of neural activity with magnetic detection electrical impedance tomography (MDEIT): a modelling study

Objectives.(1) Develop a computational pipeline for three-dimensional fast neural magnetic detection electrical impedance tomography (MDEIT), (2) determine whether constant current or constant voltage is preferable for MDEIT, (3) perform reconstructions of simulated neural activity in a human head model with realistic noise and compare MDEIT to EIT and (4) perform a two-dimensional study in a saline tank for MDEIT with optically pumped magnetometers (OPMs) and compare reconstruction algorithms.Approach.Forward modelling and image reconstruction were performed with a realistic model of a human head in three dimensions and at three noise levels for four perturbations representing neural activity. Images were compared using the error in the position and size of the reconstructed perturbations. Two-dimensional MDEIT was performed in a saline tank with a resistive perturbation and one OPM. Six reconstruction algorithms were compared using the error in the position and size of the reconstructed perturbations.Main results.A computational pipeline was developed in COMSOL Multiphysics, reducing the Jacobian calculation time from months to days. MDEIT reconstructed images with a lower reconstruction error than EIT with a mean difference of 7.0%, 5.5% and 11% for three noise cases representing current noise, reduced current source noise and reduced current source and magnetometer noise. A rank analysis concluded that the MDEIT Jacobian was less rank-deficient than the EIT Jacobian. Reconstructions of a phantom in a saline tank had a best reconstruction error of 13%, achieved using 0th-order Tikhonov regularisation with simulated noise-based correction.Significance.This study demonstrated that three-dimensional MDEIT for neural imaging is feasible and that MDEIT reconstructed superior images to EIT, which can be explained by the lesser rank deficiency of the MDEIT Jacobian. Reconstructions of a perturbation in a saline tank demonstrated a proof of principle for two-dimensional MDEIT with OPMs and identified the best reconstruction algorithm.

Overcoming temporal dispersion for measurement of activity-related impedance changes in unmyelinated nerves

Objective.Fast neural electrical impedance tomography is an imaging technique that has been successful in visualising electrically evoked activity of myelinated fibres in peripheral nerves by measurement of the impedance changes (dZ) accompanying excitation. However, imaging of unmyelinated fibres is challenging due to temporal dispersion (TP) which occurs due to variability in conduction velocities of the fibres and leads to a decrease of the signal below the noise with distance from the stimulus. To overcome TP and allow electrical impedance tomography imaging in unmyelinated nerves, a new experimental and signal processing paradigm is required allowing dZ measurement further from the site of stimulation than compound neural activity is visible. The development of such a paradigm was the main objective of this study.Approach.A finite element-based statistical model of TP in porcine subdiaphragmatic nerve was developed and experimentally validatedex-vivo. Two paradigms for nerve stimulation and processing of the resulting data-continuous stimulation and trains of stimuli, were implemented; the optimal paradigm for recording dispersed dZ in unmyelinated nerves was determined.Main results.While continuous stimulation and coherent spikes averaging led to higher signal-to-noise ratios (SNRs) at close distances from the stimulus, stimulation by trains was more consistent across distances and allowed dZ measurement at up to 15 cm from the stimulus (SNR = 1.8 ± 0.8) if averaged for 30 min.Significance.The study develops a method that for the first time allows measurement of dZ in unmyelinated nerves in simulation and experiment, at the distances where compound action potentials are fully dispersed.

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.

Simplifying the hardware requirements for fast neural EIT of peripheral nerves

OBJECTIVE

The main objective of this study was to assess the feasibility of lowering the hardware requirements for fast neural EIT in order to support the distribution of this technique. Specifically, the feasibility of replacing the commercial modules present in the existing high-end setup with compact and cheap customized circuitry was assessed.

APPROACH

Nerve EIT imaging was performed on rat sciatic nerves with both our standard ScouseTom setup and a customized version in which commercial benchtop current sources were replaced by custom circuitry. Electrophysiological data and images collected in the same experimental conditions with the two setups were compared. Data from the customized setup was subject to a down-sampling analysis to simulate the use of a recording module with lower specifications.

MAIN RESULTS

Compound action potentials (573±287µV and 487±279µV, p=0.28) and impedance changes (36±14µV and 31±16µV, p=0.49) did not differ significantly when measured using commercial high-end current sources or our custom circuitry, respectively. Images reconstructed from both setups showed neglibile (<1voxel, i.e. 40µm) difference in peak location and a high degree of correlation (R2=0.97). When down-sampling from 24 to 16 bits ADC resolution and from 100KHz to 50KHz sampling frequency, signal-to-noise ratio showed acceptable decrease (<-20%), and no meaningful image quality loss was detected (peak location difference <1voxel, pixel-by-pixel correlation R2=0.99).

SIGNIFICANCE

The technology developed for this study greatly reduces the cost and size of a fast neural EIT setup without impacting quality and thus promotes the adoption of this technique by the neuroscience research community.

Fascicle localisation within peripheral nerves through evoked activity recordings: A comparison between electrical impedance tomography and multi-electrode arrays

BACKGROUND

The lack of understanding of fascicular organisation in peripheral nerves limits the potential of vagus nerve stimulation therapy. Two promising methods may be employed to identify the functional anatomy of fascicles within the nerve: fast neural electrical impedance tomography (EIT), and penetrating multi-electrode arrays (MEA). These could provide a means to image the compound action potential within fascicles in the nerve.

NEW METHOD

We compared the ability to localise fascicle activity between silicon shanks (SS) and carbon fibre (CF) multi-electrode arrays and fast neural EIT, with micro-computed tomography (MicroCT) as an independent reference. Fast neural EIT in peripheral nerves was only recently developed and MEA technology has been used only sparingly in nerves and not for source localisation. Assessment was performed in rat sciatic nerves while evoking neural activity in the tibial and peroneal fascicles.

RESULTS

Recorded compound action potentials were larger with CF compared to SS (∼700 μV vs ∼300 μV); however, background noise was greater (6.3 μV vs 1.7 μV) leading to lower SNR. Maximum spatial discrimination between Centres-of-Mass of fascicular activity was achieved by fast neural EIT (402 ± 30 μm) and CF MEA (414 ± 123 μm), with no statistical difference between MicroCT (625 ± 17 μm) and CF (p > 0.05) and between CF and EIT (p > 0.05). Compared to CF MEAs, SS MEAs had a lower discrimination power (103 ± 51 μm, p < 0.05).

COMPARISON WITH EXISTING METHODS

EIT and CF MEAs showed localisation power closest to MicroCT. Silicon MEAs adopted in this study failed to discriminate fascicle location. Re-design of probe geometry may improve results.

CONCLUSIONS

Nerve EIT is an accurate tool for assessment of fascicular position within nerves. Accuracy of EIT and CF MEA is similar to the reference method. We give technical recommendations for performing multi-electrode recordings in nerves.

Freezing resistance evaluation of rose stems during frost dehardening using electrical impedance tomography

BACKGROUND

Electrical impedance tomography (EIT) has rarely been applied in plant science, particularly to study plant resistance to abiotic and biotic stresses. In this study, we evaluated the freezing resistance of floribunda roses (Rosa Floribunda) during frost dehardening using the EIT technique to identify a new method for rapid and non-destructive measurement of plant freezing resistance.

RESULTS

The current was the excitation source, the boundary voltage value was measured, and then the boundary voltage reconstructed value was formed. Using an imaging algorithm, the two-dimensional (2D) distribution of impedance or impedance variation was reconstructed. The EIT reconstructed values decreased obviously with the decline in freezing temperatures. The EIT reconstructed values of stems had the best fit to the logistic equation, and subsequently, the semi-lethal temperatures were calculated. The freezing resistance results evaluated using EIT reconstructed values were linearly correlated with the results of the traditional electrolyte leakage (EL) method (r = 0.93, P < 0.01).

CONCLUSIONS

In conclusion, after freezing tests, the reconstructed values of EIT images could be used to quantitatively evaluate the freezing resistance of floribunda rose stems. The present study provides a reference for the further application of the EIT technique for non-destructive and rapid detection of plant freezing resistance.

Optimization of the electrode drive pattern for imaging fascicular compound action potentials in peripheral nerve with fast neural electrical impedance tomography

OBJECTIVE

The main objective of this study was to investigate which injection pattern led to the best imaging of fascicular compound activity in fast neural EIT of peripheral nerve using an external cylindrical 2  ×  14-electrodes cuff. Specifically, the study addressed the identification of the optimal injection pattern and of the optimal region of the reconstructed volume to image fascicles.

APPROACH

The effect of three different measurement protocol features (transversal/longitudinal injection, drive electrode spacing, referencing configuration) over imaging was investigated in simulation with the use of realistic impedance changes and noise levels. Image-based metrics were employed to evaluate the quality of the reconstructions over the reconstruction domain. The optimal electrode addressing protocol suggested by the simulations was validated in vivo on the tibial and peroneal fascicles of rat sciatic peripheral nerves (N  =  3) against MicroCT reference images.

MAIN RESULTS

Injecting current transversally, with spacing of  ⩾4 electrodes apart (⩾100°) and single-ring referencing of measurements, led to the best overall localization when reconstructing on the edge of the electrode array closest to the reference. Longitudinal injection protocols led to a higher SNR of the reconstructed image but poorer localization. All in vivo EIT recordings had statistically significant impedance variations (p   <  0.05). Overall, fascicle center-of-mass (CoM) localization error was estimated at 141  ±  56 µm (-26  ±  94 µm and 5  ±  29° in radial coordinates). Significant difference was found (p   <  0.05) between mean angular location of the tibial and peroneal CoMs.

SIGNIFICANCE

This study gives the reader recommendations for performing fast neural EIT of fascicular compound activity using the most effective protocol features.

Comparison of electrical impedance tomography and intracranial pressure during dehydration treatment of cerebral edema

Cerebral edema after brain injury can lead to brain damage and death if diagnosis and treatment are delayed. This study investigates the feasibility of employing electrical impedance tomography (EIT) as a non-invasive imaging tool for monitoring the development of cerebral edema, in which impedance imaging of the brain related to brain water content is compared with intracranial pressure (ICP). We enrolled forty patients with cerebral hemorrhage who underwent lateral external ventricular drain with intraventricular ICP and EIT monitoring for 3 h after initiation of dehydration treatment. The average reconstructed impedance value (ARV) calculated from EIT images was compared with ICP. Dehydration effects induced changes in ARV and ICP showed a close negative correlation in all patients, and the mean correlation reached R2 = 0.78 ± 0.16 (p < .001). A regression equation (R2 = 0.62, p < .001) was formulated from the total of measurement data. The 95% limits of agreement were - 6.13 to 6.13 mmHg. Adaptive clustering and variance analysis of normalized changes in ARV and ICP showed 92.5% similarity and no statistically significant differences (p > .05). Moreover, the sensitivity, specificity and area under the curve of changes in ICP >10 mmHg were 0.65, 0.73 and 0.70 respectively. The findings show that EIT can monitor changes in brain water content associated with cerebral edema, which could provide a real-time and non-invasive imaging tool for early identification of cerebral edema and the evaluation of mannitol dehydration.

Image Reconstruction in Electrical Impedance Tomography Based on Structure-Aware Sparse Bayesian Learning

Electrical impedance tomography (EIT) is developed to investigate the internal conductivity changes of an object through a series of boundary electrodes, and has become increasingly attractive in a broad spectrum of applications. However, the design of optimal tomography image reconstruction algorithms has not achieved the adequate level of progress and matureness. In this paper, we propose an efficient and high-resolution EIT image reconstruction method in the framework of sparse Bayesian learning. Significant performance improvement is achieved by imposing structure-aware priors on the learning process to incorporate the prior knowledge that practical conductivity distribution maps exhibit clustered sparsity and intra-cluster continuity. The proposed method not only achieves high-resolution estimation and preserves the shape information even in low signal-to-noise ratio scenarios but also avoids the time-consuming parameter tuning process. The effectiveness of the proposed algorithm is validated through comparisons with state-of-the-art techniques using extensive numerical simulation and phantom experiment results.

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

OBJECTIVE

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

APPROACH

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

Noninvasive Brain Physiology Monitoring for Extreme Environments: A Critical Review

Our ability to monitor the brain physiology is advancing; however, most of the technology is bulky, expensive, and designed for traditional clinical settings. With long-duration space exploration, there is a need for developing medical technologies that are reliable, low energy, portable, and semiautonomous. Our aim was to review the state of the art for noninvasive technologies capable of monitoring brain physiology in diverse settings. A literature review of PubMed and the Texas Medical Center library sites was performed using prespecified search criteria to identify portable technologies for monitoring physiological aspects of the brain physiology. Most brain-monitoring technologies require a moderate to high degree of operator skill. Some are low energy, but many require a constant external power supply. Most of the technologies lack the accuracy seen in gold standard measures, due to the need for calibration, but may be useful for screening or monitoring relative changes in a parameter. Most of the technologies use ultrasound or electromagnetic radiation as energy sources. There is an important need for further development of portable technologies that can be operated in a variety of extreme environments to monitor brain health.

Regional distribution of ventilation in patients with obstructive sleep apnea: the role of thoracic electrical impedance tomography (EIT) monitoring

PURPOSE

The aim of our study was to apply the electrical impedance tomography (EIT) technique to the study of ventilation during wake and NREM and REM sleep in patients with obstructive sleep apneas (OSA).

METHODS

This is a prospective, observational, monocentric, pilot study in a neurology department with a sleep disorder center. Inclusion criteria were age ≥18 years, both gender, and diagnosis of OSA. Exclusion criteria were the contraindications to the thoracic EIT. All patients underwent laboratory-based polysomnography (PSG) alongside thoracic EIT. Primary endpoint was to compare the global impedance (GI) among the conditions: "Wake" vs "Sleep," "NREM" vs "REM," and "OSA" vs "Non-OSA." Secondary endpoint was to measure the regional distribution of impedance in the four regions of interest (ROIs), in each condition.

RESULTS

Of the 17 consecutive patients enrolled, two were excluded because of poor-quality EIT tracings. Fifteen were analyzed, 10 men and 5 women, mean age 51.6 ± 14.4 years. GI was higher in Wake vs Sleep (Wake 13.24 ± 11.23; Sleep 12.56 ± 13.36; p < 0.01), in NREM vs REM (NREM 13.48 ± 13.43; REM 0.59 ± 0.01; p < 0.01), and in Non-OSA vs OSA (Non-OSA 10.50 ± 12.99; OSA 18.98 ± 10.06; p < 0.01). No significant differences were observed in the regional distribution of impedance between Wake and Sleep (χ ² = 3.66; p = 0.299) and between Non-OSA and OSA (χ ² = 1.00; p = 0.799); conversely, a significant difference was observed between NREM and REM sleep (χ ² = 62.94; p < 0.001).

CONCLUSIONS

To our knowledge, this is the first study that addresses the issue of regional ventilation in OSA patients during sleep. Thoracic electrical impedance changes through the sleep-wake cycle and during obstructive events. The application of thoracic EIT can prove a valuable additional strategy for the evaluation of OSA patients.

Investigation of potential artefactual changes in measurements of impedance changes during evoked activity: implications to electrical impedance tomography of brain function

Electrical impedance tomography (EIT) could provide images of fast neural activity in the adult human brain with a resolution of 1 ms and 1 mm by imaging impedance changes which occur as ion channels open during neuronal depolarization. The largest changes occur at dc and decrease rapidly over 100 Hz. Evoked potentials occur in this bandwidth and may cause artefactual apparent impedance changes if altered by the impedance measuring current. These were characterized during the compound action potential in the walking leg nerves of Cancer pagurus, placed on Ag/AgCl hook electrodes, to identify how to avoid artefactual changes during brain EIT. Artefact-free impedance changes (δZ) decreased with frequency from −0.045 ± 0.01% at 225 Hz to −0.02 ± 0.01% at 1025 Hz (mean ± 1 SD, n = 24 in 12 nerves) which matched changes predicted by a finite element model. Artefactual δZ reached c.300% and 50% of the genuine membrane impedance change at 225 Hz and 600 Hz respectively but decreased with frequency of the applied current and was negligible above 1 kHz. The proportional amplitude (δZ (%)) of the artefact did not vary significantly with the amplitude of injected current of 5–20 µA pp. but decreased significantly from −0.09 ± 0.024 to −0.03 ± 0.023% with phase of 0 to 45°. For fast neural EIT of evoked activity in the brain, artefacts may arise with applied current of >10 µA. Independence of δZ with respect to phase but not the amplitude of applied current controls for them; they can be minimized by randomizing the phase of the applied measuring current and excluded by recording at >1 kHz.

Linearly constrained minimum variance spatial filtering for localization of conductivity changes in electrical impedance tomography

We localize dynamic electrical conductivity changes and reconstruct their time evolution introducing the spatial filtering technique to electrical impedance tomography (EIT). More precisely, we use the unit-noise-gain constrained variation of the distortionless-response linearly constrained minimum variance spatial filter. We address the effects of interference and the use of zero gain constraints. The approach is successfully tested in simulated and real tank phantoms. We compute the position error and resolution to compare the localization performance of the proposed method with the one-step Gauss-Newton reconstruction with Laplacian prior. We also study the effects of sensor position errors. Our results show that EIT spatial filtering is useful for localizing conductivity changes of relatively small size and for estimating their time-courses. Some potential dynamic EIT applications such as acute ischemic stroke detection and neuronal activity localization may benefit from the higher resolution of spatial filters as compared to conventional tomographic reconstruction algorithms.

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.

Validation of finite element model of transcranial electrical stimulation using scalp potentials: implications for clinical dose

OBJECTIVE

During transcranial electrical stimulation, current passage across the scalp generates voltage across the scalp surface. The goal was to characterize these scalp voltages for the purpose of validating subject-specific finite element method (FEM) models of current flow.

APPROACH

Using a recording electrode array, we mapped skin voltages resulting from low-intensity transcranial electrical stimulation. These voltage recordings were used to compare the predictions obtained from the high-resolution model based on the subject undergoing transcranial stimulation.

MAIN RESULTS

Each of the four stimulation electrode configurations tested resulted in a distinct distribution of scalp voltages; these spatial maps were linear with applied current amplitude (0.1 to 1 mA) over low frequencies (1 to 10 Hz). The FEM model accurately predicted the distinct voltage distributions and correlated the induced scalp voltages with current flow through cortex.

SIGNIFICANCE

Our results provide the first direct model validation for these subject-specific modeling approaches. In addition, the monitoring of scalp voltages may be used to verify electrode placement to increase transcranial electrical stimulation safety and reproducibility.

SQUID-detected ultra-low field MRI

MRI remains the premier method for non-invasive imaging of soft-tissue. Since the first demonstration of ULF MRI the trend has been towards ever higher magnetic fields. This is because the signal, and efficiency of Faraday detectors, increases with ever higher magnetic fields and corresponding Larmor frequencies. Nevertheless, there are many compelling reasons to continue to explore MRI at much weaker magnetic fields, the so-called ultra-low field or (ULF) regime. In the past decade many excellent proof-of-concept demonstrations of ULF MRI have been made. These include combined MRI and magnetoencephalography, imaging in the presence of metal, unique tissue contrast, and implementation in situations where a high magnetic field is simply impractical. These demonstrations have routinely used pulsed pre-polarization (at magnetic fields from ~10 to 100 mT) followed by read-out in a much weaker (1-100 μT) magnetic fields using the ultra-sensitive Superconducting Quantum Interference Device (SQUID) sensor. Even with pre-polarization and SQUID detection, ULF MRI suffers from many challenges associated with lower magnetization (i.e. signal) and inherently long acquisition times compared to conventional >1 T MRI. These are fundamental limitations imposed by the low measurement and gradient fields used. In this review article we discuss some of the techniques, potential applications, and inherent challenges of ULF MRI.

SQUID-detected ultra-low field MRI

MRI remains the premier method for non-invasive imaging of soft-tissue. Since the first demonstration of ULF MRI the trend has been towards ever higher magnetic fields. This is because the signal, and efficiency of Faraday detectors, increases with ever higher magnetic fields and corresponding Larmor frequencies. Nevertheless, there are many compelling reasons to continue to explore MRI at much weaker magnetic fields, the so-called ultra-low field or (ULF) regime. In the past decade many excellent proof-of-concept demonstrations of ULF MRI have been made. These include combined MRI and magnetoencephalography, imaging in the presence of metal, unique tissue contrast, and implementation in situations where a high magnetic field is simply impractical. These demonstrations have routinely used pulsed pre-polarization (at magnetic fields from ∼10 to 100mT) followed by read-out in a much weaker (1-100μT) magnetic fields using the ultra-sensitive Superconducting Quantum Interference Device (SQUID) sensor. Even with pre-polarization and SQUID detection, ULF MRI suffers from many challenges associated with lower magnetization (i.e. signal) and inherently long acquisition times compared to conventional >1T MRI. These are fundamental limitations imposed by the low measurement and gradient fields used. In this review article we discuss some of the techniques, potential applications, and inherent challenges of ULF MRI.

Cerebrospinal fluid volume measurements in hydrocephalic rats

Object Experimental data about the evolution of intracranial volume and pressure in cases of hydrocephalus are limited due to the lack of available monitoring techniques. In this study, the authors validate intracranial CSF volume measurements within the lateral ventricle, while simultaneously using impedance sensors and pressure transducers in hydrocephalic animals. Methods A volume sensor was fabricated and connected to a catheter that was used as a shunt to withdraw CSF. In vitro bench-top calibration experiments were created to provide data for the animal experiments and to validate the sensors. To validate the measurement technique in a physiological system, hydrocephalus was induced in weanling rats by kaolin injection into the cisterna magna. At 28 days after induction, the sensor was implanted into the lateral ventricles. After sealing the skull using dental cement, an acute CSF drainage/infusion protocol consisting of 4 sequential phases was performed with a pump. Implant location was confirmed via radiography using intraventricular iohexol contrast administration. Results Controlled CSF shunting in vivo with hydrocephalic rats resulted in precise and accurate sensor measurements (r = 0.98). Shunting resulted in a 17.3% maximum measurement error between measured volume and actual volume as assessed by a Bland-Altman plot. A secondary outcome confirmed that both ventricular volume and intracranial pressure decreased during CSF shunting and increased during infusion. Ventricular enlargement consistent with successful hydrocephalus induction was confirmed using imaging, as well as postmortem. These results indicate that volume monitoring is feasible for clinical cases of hydrocephalus. Conclusions This work marks a departure from traditional shunting systems currently used to treat hydrocephalus. The overall clinical application is to provide alternative monitoring and treatment options for patients. Future work includes development and testing of a chronic (long-term) volume monitoring system.

A novel method for recording neuronal depolarization with recording at 125-825 Hz: implications for imaging fast neural activity in the brain with electrical impedance tomography

Electrical impedance tomography (EIT) is a recently developed medical imaging method which has the potential to produce images of fast neuronal depolarization in the brain. Previous modelling suggested that applied current needed to be below 100 Hz but the signal-to-noise ratio (SNR) recorded with scalp electrodes during evoked responses was too low to permit imaging. A novel method in which contemporaneous evoked potentials are subtracted is presented with current applied at 225 Hz to cerebral cortex during evoked activity; although the signal is smaller than at DC by about 10×, the principal noise from the EEG is reduced by about 1000×, resulting in an improved SNR. It was validated with recording of compound action potentials in crab walking leg nerve where peak changes of -0.2% at 125 and 175 Hz tallied with biophysical modelling. In recording from rat cerebral cortex during somatosensory evoked responses, peak impedance decreases of -0.07 ± 0.006% (mean ± SE) with a SNR of >50 could be recorded at 225 Hz. This method provides a reproducible and artefact free means for recording resistance changes during neuronal activity which could form the basis for imaging fast neural activity in the brain.

Real-time imaging and detection of intracranial haemorrhage by electrical impedance tomography in a piglet model

The aim of this study was to use electrical impedance tomography (EIT) to detect and image acute intracranial haemorrhage (ICH) in an animal model. Blood was infused into the frontal lobe of the brains of anaesthetized piglets and impedance was measured using 16 electrodes placed in a circle on the scalp. The EIT images were constructed using a filtered back-projection algorithm. The mean of all the pixel intensities within a region of interest--the mean resistivity value (MRV)--was used to evaluate the relative impedance changes in the target region. A symmetrical index (SI), reflecting the relative impedance on both sides of the brain, was also calculated. Changes in MRV and SI were associated with the injection of blood, demonstrating that EIT can successfully detect ICH in this animal model. The unique features of EIT may be beneficial for diagnosing ICH early in patients after cranial surgery, thereby reducing the risk of complications and mortality.

Real-time imaging of subarachnoid hemorrhage in piglets with electrical impedance tomography

Subarachnoid hemorrhage (SAH) is one of the most severe medical emergencies in neurosurgery. Early detection or diagnosis would significantly reduce the rate of disability and mortality, and improve the prognosis of the patients. Although the present medical imaging techniques generally have high sensitivity to identify bleeding, the use of an additional, non-invasive imaging technique capable of continuously monitoring SAH is required to prevent contingent bleeding or re-bleeding. In this study, electrical impedance tomography (EIT) was applied to detect the onset of SAH modeled on eight piglets in real time, with the subsequent process being monitored continuously. The experimental SAH model was introduced by one-time injection of 5 ml fresh autologous arterial blood into the cisterna magna. Results showed that resistivity variations within the brain caused by the added blood could be detected using the EIT method and may be associated not only with the resistivity difference among brain tissues, but also with variations of cerebrospinal fluid dynamics. In conclusion, EIT has unique potential for use in clinical practice to provide invaluable real-time neuroimaging data for SAH after the improvement of electrode design, anisotropic realistic modeling and instrumentation.