Phase division multiplexed EIT for enhanced temporal resolution.

OBJECTIVE: The most commonly used EIT paradigm (time division multiplexing) limits the temporal resolution of impedance images due to the need to switch between injection electrodes. Advances have previously been made using frequency division multiplexing (FDM) to increase temporal resolution, but in cases where a fixed range of frequencies is available, such as imaging fast neural activity, an upper limit is placed on the total number of simultaneous injections. The use of phase division multiplexing (PDM) where multiple out of phase signals can be injected at each frequency is investigated to increase temporal resolution. APPROACH: TDM, FDM and PDM were compared in head tank experiments, to compare transfer impedance measurements and spatial resolution between the three techniques. A resistor phantom paradigm was established to investigate the imaging of one-off impedance changes, of magnitude 1% and with durations as low as 500 µs (similar to those seen in nerve bundles), using both PDM and TDM approaches. MAIN RESULTS: In head tank experiments, a strong correlation (r > 0.85 and p < 0.001) was present between the three sets of measured transfer impedances, and no statistically significant difference was found in reconstructed image quality. PDM was able to image impedance changes down to 500 µs in the phantom experiments, while the minimum duration imaged using TDM was 5 ms. SIGNIFICANCE: PDM offers a possible solution to the imaging of fast moving impedance changes (such as in nerves), where the use of triggering or coherent averaging is not possible. The temporal resolution presents an order of magnitude improvement of the TDM approach, and the approach addresses the limited spatial resolution of FDM by increasing the number of simultaneous EIT injections.

In vivo bioimpedance changes during haemorrhagic and ischaemic stroke in rats: towards 3D stroke imaging using electrical impedance tomography.

Electrical impedance tomography (EIT) could be used as a portable non-invasive means to image the development of ischaemic stroke or haemorrhage. The purpose of this study was to examine if this was possible using time difference imaging, in the anesthetised rat using 40 spring-loaded scalp electrodes with applied constant currents of 50-150 µA at 2 kHz. Impedance changes in the largest 10% of electrode combinations were -12.8% ± 12.0% over the first 10 min for haemorrhage and +46.1% ± 37.2% over one hour for ischaemic stroke (mean ± SD, n = 7 in each group). The volume of the pathologies, assessed by tissue section and histology post-mortem, was 12.6 µl ± 17.6 µl and 12.6 µl ± 17.6 µl for haemorrhage and ischaemia respectively. In time difference EIT images, there was a correspondence with the pathology in 3/7 cases of haemorrhage and none of the ischaemic strokes. Although the net impedance changes were physiologically reasonable and consistent with expectations from the literature, it was disappointing that it was not possible to obtain reliable EIT images. The reason for this are not clear, but probably include confounding effects of secondary ischaemia for haemorrhage and tissue and cerebrospinal fluid shifts for the stroke model. With this method, it does not appear that EIT with scalp electrodes is yet ready for clinical use.

Empirical validation of statistical parametric mapping for group imaging of fast neural activity using electrical impedance tomography.

Electrical impedance tomography (EIT) allows for the reconstruction of internal conductivity from surface measurements. A change in conductivity occurs as ion channels open during neural activity, making EIT a potential tool for functional brain imaging. EIT images can have >10 000 voxels, which means statistical analysis of such images presents a substantial multiple testing problem. One way to optimally correct for these issues and still maintain the flexibility of complicated experimental designs is to use random field theory. This parametric method estimates the distribution of peaks one would expect by chance in a smooth random field of a given size. Random field theory has been used in several other neuroimaging techniques but never validated for EIT images of fast neural activity, such validation can be achieved using non-parametric techniques. Both parametric and non-parametric techniques were used to analyze a set of 22 images collected from 8 rats. Significant group activations were detected using both techniques (corrected p < 0.05). Both parametric and non-parametric analyses yielded similar results, although the latter was less conservative. These results demonstrate the first statistical analysis of such an image set and indicate that such an analysis is an approach for EIT images of neural activity.

Neurovascular Interactions in the Neurologically Compromised Neonatal Brain.

Neurological brain injuries such as hypoxic ischaemic encephalopathy (HIE) and associated conditions such as seizures have been associated with poor developmental outcome in neonates. Our limited knowledge of the neurological and cerebrovascular processes underlying seizures limits their diagnosis and timely treatment. Diffuse optical tomography (DOT) provides haemodynamic information in the form of changes in concentration of de/oxygenated haemoglobin, which can improve our understanding of seizures and the relationship between neural and vascular processes. Using simultaneous EEG-DOT, we observed distinct haemodynamic changes which are temporally correlated with electrographic seizures. Here, we present DOT-EEG data from two neonates clinically diagnosed as HIE. Our results highlight the wealth of mutually-informative data that can be obtained using DOT-EEG techniques to understand neurovascular coupling in HIE neonates.

In vivo bioimpedance measurement of healthy and ischaemic rat brain: implications for stroke imaging using electrical impedance tomography.

In order to facilitate the imaging of haemorrhagic and ischaemic stroke using frequency difference electrical impedance tomography (EIT), impedance measurements of normal and ischaemic brain, and clotted blood during haemorrhage, were gathered using a four-terminal technique in an in vivo animal model, a first for ischaemic measurements. Differences of 5-10% in impedance were seen between the frequency spectrums of healthy and ischaemic brain, over the frequency range 0-3 kHz, while the spectrum of blood was predominately uniform. The implications of imaging blood/ischaemia in the brain using electrical impedance tomography are discussed, supporting the notion that it will be possible to differentiate stroke from haemorrhage.

Comparison of frequency difference reconstruction algorithms for the detection of acute stroke using EIT in a realistic head-shaped tank.

Imaging of acute stroke might be possible using multi-frequency electrical impedance tomography (MFEIT) but requires absolute or frequency difference imaging. Simple linear frequency difference reconstruction has been shown to be ineffective in imaging with a frequency-dependant background conductivity; this has been overcome with a weighted frequency difference approach with correction for the background but this has only been validated for a cylindrical and hemispherical tank. The feasibility of MFEIT for imaging of acute stroke in a realistic head geometry was examined by imaging a potato perturbation against a saline background and a carrot-saline frequency-dependant background conductivity, in a head-shaped tank with the UCLH Mk2.5 MFEIT system. Reconstruction was performed with time difference (TD), frequency difference (FD), FD adjacent (FDA), weighted FD (WFD) and weighted FDA (WFDA) linear algorithms. The perturbation in reconstructed images corresponded to the true position to <9.5% of image diameter with an image SNR of >5.4 for all algorithms in saline but only for TD, WFDA and WFD in the carrot-saline background. No reliable imaging was possible with FD and FDA. This indicates that the WFD approach is also effective for a realistic head geometry and supports its use for human imaging in the future.

Application of a computational model of vagus nerve stimulation.

OBJECTIVES: The most widely used and studied neurostimulation procedure for medically refractory epilepsy is vagus nerve stimulation (VNS) Therapy. The goal of this study was to develop a computational model for improved understanding of the anatomy and neurophysiology of the vagus nerve as it pertains to the principles of electrical stimulation, aiming to provide clinicians with a systematic and rational understanding of VNS Therapy. MATERIALS AND METHODS: Computational modeling allows the study of electrical stimulation of peripheral nerves. We used finite element electric field models of the vagus nerve with VNS Therapy electrodes to calculate the voltage field for several output currents and studied the effects of two programmable parameters (output current and pulse width) on optimal fiber activation. RESULTS: The mathematical models correlated well with strength-duration curves constructed from actual patient data. In addition, digital constructs of chronic versus acute implant models demonstrated that at a given pulse width and current combination, presence of a 110-µm fibrotic tissue can decrease fiber activation by 50%. Based on our findings, a range of output current settings between 0.75 and 1.75 mA with pulse width settings of 250 or 500 µs may result in optimal stimulation. CONCLUSIONS: The modeling illustrates how to achieve full or nearly full activation of the myelinated fibers of the vagus nerve through output current and pulse width settings. This knowledge will enable clinicians to apply these principles for optimal vagus nerve activation and proceed to adjust duty cycle and frequency to achieve effectiveness.

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.

A method for removing artefacts from continuous EEG recordings during functional electrical impedance tomography for the detection of epileptic seizures.

Electrical impedance tomography (EIT) is a portable, non-invasive medical imaging method, which could be employed to image the seizure onset in subjects undergoing assessment prior to epilepsy surgery. Each image is obtained from impedance measurements conducted with imperceptible current at tens of kHz. For concurrent imaging with video electroencephalogram (EEG), the EIT introduces a substantial artefact into the EEG due to current switching at frequencies in the EEG band. We present here a method for its removal, so that EIT and the EEG could be acquired simultaneously. A low-pass analogue filter for EEG channels (-6 dB at 48 Hz) and a high-pass filter (-3 dB at 72 Hz) for EIT channels reduced the artefact from 2-3 mV to 50-300 microV, but still left a periodic artefact at about 3 Hz. This was reduced to less than 10 microV with a software filter, which subtracted an artefact template from the EEG raw traces. The EEG was made clinically acceptable at four times its acquisition speed. This method could enable EIT to become a technique for imaging on telemetry units alongside EEG, without interfering with routine EEG reporting.

A fuzzy logic model for hand posture control using human cortical activity recorded by micro-ECog electrodes.

This paper presents a fuzzy logic model to decode the hand posture from electro-cortico graphic (ECoG) activity of the motor cortical areas. One subject was implanted with a micro-ECoG electrode array on the surface of the motor cortex. Neural signals were recorded from 14 electrodes on this array while Subject participated in three reach and grasp sessions. In each session, Subject reached and grasped a wooden toy hammer for five times. Optimal channels/electrodes which were active during the task were selected. Power spectral densities of optimal channels averaged over a time period of 1/2 second before the onset of the movement and 1 second after the onset of the movement were fed into a fuzzy logic model. This model decoded whether the posture of the hand is open or closed with 80% accuracy. Hand postures along the task time were decoded by using the output from the fuzzy logic model by two methods (i) velocity based decoding (ii) acceleration based decoding. The latter performed better when hand postures predicted by the model were compared to postures recorded by a data glove during the experiment. This fuzzy logic model was imported to MATLABSIMULINK to control a virtual hand.

Human motor cortical activity recorded with Micro-ECoG electrodes, during individual finger movements.

In this study human motor cortical activity was recorded with a customized micro-ECoG grid during individual finger movements. The quality of the recorded neural signals was characterized in the frequency domain from three different perspectives: (1) coherence between neural signals recorded from different electrodes, (2) modulation of neural signals by finger movement, and (3) accuracy of finger movement decoding. It was found that, for the high frequency band (60-120 Hz), coherence between neighboring micro-ECoG electrodes was 0.3. In addition, the high frequency band showed significant modulation by finger movement both temporally and spatially, and a classification accuracy of 73% (chance level: 20%) was achieved for individual finger movement using neural signals recorded from the micro-ECoG grid. These results suggest that the micro-ECoG grid presented here offers sufficient spatial and temporal resolution for the development of minimally-invasive brain-computer interface applications.

Imaging cerebral haemorrhage with magnetic induction tomography: numerical modelling.

Magnetic induction tomography (MIT) is a new electromagnetic imaging modality which has the potential to image changes in the electrical conductivity of the brain due to different pathologies. In this study the feasibility of detecting haemorrhagic cerebral stroke with a 16-channel MIT system operating at 10 MHz was investigated. The finite-element method combined with a realistic, multi-layer, head model comprising 12 different tissues, was used for the simulations in the commercial FE package, Comsol Multiphysics. The eddy-current problem was solved and the MIT signals computed for strokes of different volumes occurring at different locations in the brain. The results revealed that a large, peripheral stroke (volume 49 cm(3)) produced phase changes that would be detectable with our currently achievable instrumentation phase noise level (17 m degrees ) in 70 (27%) of the 256 exciter/sensor channel combinations. However, reconstructed images showed that a lower noise level than this, of 1 m degrees , was necessary to obtain good visualization of the strokes. The simulated MIT measurements were compared with those from an independent transmission-line-matrix model in order to give confidence in the results.

A modelling study to inform specification and optimal electrode placement for imaging of neuronal depolarization during visual evoked responses by electrical and magnetic detection impedance tomography.

Electrical impedance tomography (EIT) has the potential to achieve non-invasive functional imaging of fast neuronal activity in the human brain due to opening of ion channels during neuronal depolarization. Local changes of resistance in the cerebral cortex are about 1%, but the size and location of changes recorded on the scalp are unknown. The purpose of this work was to develop an anatomically realistic finite element model of the adult human head and use it to predict the amplitude and topography of changes on the scalp, and so inform specification for an in vivo measuring system. A detailed anatomically realistic finite element (FE) model of the head was produced from high resolution MRI. Simulations were performed for impedance changes in the visual cortex during evoked activity with recording of scalp potentials by electrodes or magnetic flux density by magnetoencephalography (MEG) in response to current injected with electrodes. The predicted changes were validated by recordings in saline filled tanks and with boundary voltages measured on the human scalp. Peak changes were 1.03 +/- 0.75 microV (0.0039 +/- 0.0034%) and 27 +/- 13 fT (0.2 +/- 0.5%) respectively, which yielded an estimated peak signal-to-noise ratio of about 4 for in vivo averaging over 10 min and 1 mA current injection. The largest scalp changes were over the occipital cortex. This modelling suggests, for the first time, that reproducible changes could be recorded on the scalp in vivo in single channels, although a higher SNR would be desirable for accurate image production. The findings suggest that an in vivo study is warranted in order to determine signal size but methods to improve SNR, such as prolonged averaging or other signal processing may be needed for accurate image production.

An electrode addressing protocol for imaging brain function with electrical impedance tomography using a 16-channel semi-parallel system.

Electrical impedance tomography of brain function poses special problems because applied current is diverted by the resistive skull. In the past, image resolution was maximized with the use of an electrode addressing protocol with widely spaced drive electrode pairs and use of a multiplexer so that many electrode pairs could be flexibly addressed. The purpose of this study was to develop and test an electrode protocol for a 16-channel semi-parallel system which uses parallel recording channels with fixed wiring, the Kyung Hee University (KHU) Mk1. Ten protocols were tested, all addressing pairs of electrodes for recording or current drive, based on recording with a spiral, spiral with suboccipital electrodes (spiral s-o) and zig-zag configurations, and combinations of current injection from electrode pairs at 180 degrees , 120 degrees and 60 degrees . These were compared by assessing the image reconstruction quality of five simulated perturbations in a homogenous model of the human head and of four epileptic foci in an anatomically realistic model in the presence of realistic noise, in terms of localization error, resolution, image distortion and sensitivity in the region of interest. The spiral s-o with current injection at 180 degrees + 120 degrees + 60 degrees gave the best image quality and permitted reconstruction with a localization error of less than 10% of the head diameter. This encourages the view that it might be possible to obtain satisfactory images of focal abnormalities in the human brain with 16 scalp electrodes and improved instrumentation avoiding multiplexers on recording circuits.

A comparison of two EIT systems suitable for imaging impedance changes in epilepsy.

Electrical impedance tomography (EIT) has the potential to produce functional images of the conductivity changes associated with epilepsy to help localization of epileptic foci. Scalp voltage changes associated with internal conductivity changes due to focal seizures have been shown at the limit of detectability for present EIT systems. The performances of two EIT systems, which may be employed in clinical recordings during presurgical assessment of intractable epilepsy, were compared. Those were the 32-channel serial UCH Mk2.5 and the 16-channel semi-parallel KHU Mk1. Images of three conductivity perturbations, simulating epileptic foci, in a head-shaped saline tank without and with a real human skull were recorded using 31-channel and 16-channel protocols with the UCH Mk2.5, while only 16-channel protocols with the KHU Mk1. The UCH Mk2.5 employing the 31-channel protocol had better overall performance with a localization error of 12.7% of the tank diameter, which would be sufficient for lateralization of the epileptic activity. More blurred images, but with similar localization, were obtained using 16 electrodes.

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

Electrical Impedance Tomography (EIT) is a recently developed medical imaging method which could enable fast neural imaging in the brain by recording the resistance changes which occur as ion channels open during neuronal depolarization. In published studies in animal models with intracranial electrodes, changes of 0.005 to 3% have been reported but the amplitude of changes in the human is not known. The purpose of this work was to determine if resistance changes could be recorded non-invasively in humans during evoked activity which could form the basis for EIT of fast neural activity. Resistance was recorded with scalp electrodes during 2 Hz pattern visual evoked responses over 10 min using an insensible 1 Hz square wave constant current of 0.1-1 mA. Significant resistance decreases of 0.0010+/-0.0005% (0.30+/-0.15 microV, signal-to-noise ratio (SNR) of 2:1, n=16 recordings over 6 subjects) (mean+/-SE) were recorded. These are in broad agreement with modelling which estimated changes of 0.0039+/-0.0034% (1.03+/-0.75 microV) using an anatomically realistic finite element model. This is the first demonstration of such changes in humans and so encourages the belief that EIT could be used for neural imaging. Unfortunately, the signal-to-noise ratio was not sufficient to permit imaging at present because recording over multiple injection sites needed for imaging would require impractically long recording times. However, in the future, invasive imaging with intracranial electrodes in animal models or humans and improved signal processing or recording may still enable imaging; this would constitute a significant advance in neuroscience technology.

Code-division-multiplexed electrical impedance tomography spectroscopy.

Electrical impedance tomography uses multiple impedance measurements to image the internal conductivity of an object, such as the human body. Code-division multiplexing is proposed as a new method that can provide simultaneous impedance measurements of the multiple channels. Code division provides clear advantages of a wide frequency range at reduced cost and reduced complexity of sources. A potential drawback is the lack of perfectly orthogonal code sets. This caused an increase of 0.62% in root-mean-square spectral error when two codes were used to record two impedance channels simultaneously on a low-pass filter network. The method described provides images and spectra which are equivalent to the conventional time-multiplexed method, with increases in frequency resolution and measurement speed which may be of benefit in some applications of electrical impedance tomography spectroscopy.

Sub-trochanteric fracture of the femur following electric shock.

We report a case of a unilateral sub-trochanteric femoral fracture resulting from an accidental electric shock: an unusual injury. It is well documented that fractures occurring from electrical injuries commonly involve the upper extremities; those affecting the lower limb have rarely been documented. Such injuries need to be identified and treated without delay.

Use of statistical parametric mapping (SPM) to enhance electrical impedance tomography (EIT) image sets.

Use of statistical parametric mapping (SPM), which is widely used in analysis of neuroimaging studies with fMRI and PET, has the potential to improve quality of EIT images for clinical use. Minimal modification to SPM is needed, but statistical analysis based on height, not extent thresholds, should be employed, due to the 20-80% variation of the point spread function, across EIT images. SPM was assessed in EIT images reconstructed with a linear time difference algorithm utilizing an anatomically realistic finite element model of the human head. Images of the average of data sets were compared with those produced using SPM over 10-40 individual image data sets without averaging. For a point disturbance, a sponge 15% of the diameter of an anatomically realistic saline-filled tank including a skull, with a contrast of 15%, and for visual evoked response data in 14 normal human volunteers, images produced with SPM were less noisy than the average images. For the human data, no consistent physiologically realistic changes were seen with either SPM or direct reconstruction; however, only a small data set was available, limiting the power of the SPM analysis. SPM may be used on EIT images and has the potential to extract improved images from clinical data series with a low signal-to-noise ratio.

A review of errors in multi-frequency EIT instrumentation.

Multi-frequency electrical impedance tomography (MFEIT) was proposed over 10 years ago as a potential spectroscopic impedance imaging method. At least seven systems have been developed for imaging the lung, heart, breast and brain, yet none has yet achieved clinical acceptance. While the absolute impedance varies considerably between different tissues, the changes in the spectrum due to physiological changes are expected to be quite small, especially when measured through a volume. This places substantial requirements on the MFEIT instrumentation to maintain a flat system frequency response over a broad frequency range (dc-MHz). In this work, the EIT measurement problem is described from a multi-frequency perspective. Solutions to the common problems are considered from recent MFEIT systems, and the debate over four-terminal or two-terminal (multiple source) architecture is revisited. An analysis of the sources of MFEIT errors identifies the major sources of error as stray capacitance and common-mode voltages which lead to a load dependence in the frequency response of MFEIT systems. A system that employs active electrodes appears to be the most able to cope with these errors (Li et al 1996). A distributed system with digitization at the electrode is suggested as a next step in MFEIT system development.