Kirill Aristovich

A method for reconstructing tomographic images of evoked neural activity with electrical impedance tomography using intracranial planar arrays

A method is presented for reconstructing images of fast neural evoked activity in rat cerebral cortex recorded with electrical impedance tomography (EIT) and a 6 × 5 mm(2) epicortical planar 30 electrode array. A finite element model of the rat brain and inverse solution with Tikhonov regularization were optimized in order to improve spatial resolution and accuracy. The optimized FEM mesh had 7 M tetrahedral elements, with finer resolution (0.05 mm) near the electrodes. A novel noise-based image processing technique based on t-test significance improved depth localization accuracy from 0.5 to 0.1 mm. With the improvements, a simulated perturbation 0.5 mm in diameter could be localized in a region 4 × 5 mm(2) under the centre of the array to a depth of 1.4 mm, thus covering all six layers of the cerebral cortex with an accuracy of <0.1 mm. Simulated deep brain hippocampal or thalamic activity could be localized with an accuracy of 0.5 mm with a 256 electrode array covering the brain. Parallel studies have achieved a temporal resolution of 2 ms for imaging fast neural activity by EIT during evoked activity; this encourages the view that fast neural EIT can now resolve the propagation of depolarization-related fast impedance changes in cerebral cortex and deeper in the brain with a resolution equal or greater to the dimension of a cortical column.

Imaging fast electrical activity in the brain with electrical impedance tomography

Imaging of neuronal depolarization in the brain is a major goal in neuroscience, but no technique currently exists that could image neural activity over milliseconds throughout the whole brain. Electrical impedance tomography (EIT) is an emerging medical imaging technique which can produce tomographic images of impedance changes with non-invasive surface electrodes. We report EIT imaging of impedance changes in rat somatosensory cerebral cortex with a resolution of 2 ms and < 200 μm during evoked potentials using epicortical arrays with 30 electrodes. Images were validated with local field potential recordings and current source-sink density analysis. Our results demonstrate that EIT can image neural activity in a volume 7 × 5 × 2 mm in somatosensory cerebral cortex with reduced invasiveness, greater resolution and imaging volume than other methods. Modeling indicates similar resolutions are feasible throughout the entire brain so this technique, uniquely, has the potential to image functional connectivity of cortical and subcortical structures.

A Fast Parallel Solver for the Forward Problem in Electrical Impedance Tomography

Electrical impedance tomography (EIT) is a noninvasive imaging modality, where imperceptible currents are applied to the skin and the resulting surface voltages are measured. It has the potential to distinguish between ischaemic and haemorrhagic stroke with a portable and inexpensive device. The image reconstruction relies on an accurate forward model of the experimental setup. Because of the relatively small signal in stroke EIT, the finite-element modeling requires meshes of more than 10 million elements. To study the requirements in the forward modeling in EIT and also to reduce the time for experimental image acquisition, it is necessary to reduce the run time of the forward computation. We show the implementation of a parallel forward solver for EIT using the Dune-Fem C++ library and demonstrate its performance on many CPUs of a computer cluster. For a typical EIT application a direct solver was significantly slower and not an alternative to iterative solvers with multigrid preconditioning. With this new solver, we can compute the forward solutions and the Jacobian matrix of a typical EIT application with 30 electrodes on a 15-million element mesh in less than 15 min. This makes it a valuable tool for simulation studies and EIT applications with high precision requirements. It is freely available for download.

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.

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

Abstract 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.

Are patient specific meshes required for EIT head imaging

Head imaging with electrical impedance tomography (EIT) is usually done with time-differential measurements, to reduce time-invariant modelling errors. Previous research suggested that more accurate head models improved image quality, but no thorough analysis has been done on the required accuracy. We propose a novel pipeline for creation of precise head meshes from magnetic resonance imaging and computed tomography scans, which was applied to four different heads. Voltages were simulated on all four heads for perturbations of different magnitude, haemorrhage and ischaemia, in five different positions and for three levels of instrumentation noise. Statistical analysis showed that reconstructions on the correct mesh were on average 25% better than on the other meshes. However, the stroke detection rates were not improved. We conclude that a generic head mesh is sufficient for monitoring patients for secondary strokes following head trauma.

Characterising the frequency response of impedance changes during evoked physiological activity in the rat brain

OBJECTIVE Electrical impedance tomography (EIT) can image impedance changes associated with evoked physiological activity in the cerebral cortex using an array of epicortical electrodes. An impedance change is observed as the externally applied current, normally confined to the extracellular space is admitted into the conducting intracellular space during neuronal depolarisation. The response is largest at DC and decreases at higher frequencies due to capacitative transfer of current across the membrane. Biophysical modelling has shown that this effect becomes significant above 100 Hz. Recordings at DC, however, are contaminated by physiological endogenous evoked potentials. By moving to 1.7 kHz, images of somatosensory evoked responses have been produced down to 2 mm with a resolution of 2 ms and 200 μm. Hardware limitations have so far restricted impedance measurements to frequencies  <2 kHz. The purpose of this work was to establish the optimal frequency for extending EIT to image throughout the brain and to characterise the response at frequencies  >2 kHz using improved hardware. APPROACH Impedance changes were recorded during forepaw somatosensory stimulation in both cerebral cortex and the VPL nucleus of the thalamus in anaesthetised rats using applied currents of 1 kHz to 10 kHz. MAIN RESULTS In the cortex, impedance changed by -0.04 ± 0.02 % at 1 kHz, reached a peak of -0.13 ± 0.05 % at 1475 Hz and decreased to -0.05 ± 0.02 % at 10 kHz. At these frequencies, changes in the thalamus were -0.26 ± 0.1%, -0.4 ± 0.15 % and -0.08 ± 0.03 % respectively. The signal-to-noise ratio was also highest at 1475 Hz with values of -29.5 ± 8 and -31.6 ±10 recorded from the cortex and thalamus respectively. Signficance: This indicates that the optimal frequency for imaging cortical and thalamic evoked activity using fast neural EIT is 1475 Hz.

Feasibility of imaging epileptic seizure onset with EIT and depth electrodes

&NA; Imaging ictal and interictal activity with Electrical Impedance Tomography (EIT) using intracranial electrode mats has been demonstrated in animal models of epilepsy. In human epilepsy subjects undergoing presurgical evaluation, depth electrodes are often preferred. The purpose of this work was to evaluate the feasibility of using EIT to localise epileptogenic areas with intracranial electrodes in humans. The accuracy of localisation of the ictal onset zone was evaluated in computer simulations using 9M element FEM models derived from three subjects. 5 mm radius perturbations imitating a single seizure onset event were placed in several locations forming two groups: under depth electrode coverage and in the contralateral hemisphere. Simulations were made for impedance changes of 1% expected for neuronal depolarisation over milliseconds and 10% for cell swelling over seconds. Reconstructions were compared with EEG source modelling for a radially orientated dipole with respect to the closest EEG recording contact. The best accuracy of EIT was obtained using all depth and 32 scalp electrodes, greater than the equivalent accuracy with EEG inverse source modelling. The localisation error was 5.2 ± 1.8, 4.3 ± 0 and 46.2 ± 25.8 mm for perturbations within the volume enclosed by depth electrodes and 29.6 ± 38.7, 26.1 ± 36.2, 54.0 ± 26.2 mm for those without (EIT 1%, 10% change, EEG source modelling, n = 15 in 3 subjects, p < 0.01). As EIT was insensitive to source dipole orientation, all 15 perturbations within the volume enclosed by depth electrodes were localised, whereas the standard clinical method of visual inspection of EEG voltages, only localised 8 out of 15 cases. This suggests that adding EIT to SEEG measurements could be beneficial in localising the onset of seizures. HighlightsA new method is proposed to use EIT to localise and ictal activity in patients with depth electrodes.The location accuracy was improved with the best EIT protocol than EEG inverse source or SEEG detection in simulations.EIT was not sensitive to dipole orientation, while EEG detection varied with the field angle demonstrated in modelling.A combination of EIT and SEEG can potentially improve the diagnostic yield in epilepsy.

Conductive Hydrogel Electrodes for Delivery of Long-Term High Frequency Pulses

Nerve block waveforms require the passage of large amounts of electrical energy at the neural interface for extended periods of time. It is desirable that such waveforms be applied chronically, consistent with the treatment of protracted immune conditions, however current metal electrode technologies are limited in their capacity to safely deliver ongoing stable blocking waveforms. Conductive hydrogel (CH) electrode coatings have been shown to improve the performance of conventional bionic devices, which use considerably lower amounts of energy than conventional metal electrodes to replace or augment sensory neuron function. In this study the application of CH materials was explored, using both a commercially available platinum iridium (PtIr) cuff electrode array and a novel low-cost stainless steel (SS) electrode array. The CH was able to significantly increase the electrochemical performance of both array types. The SS electrode coated with the CH was shown to be stable under continuous delivery of 2 mA square pulse waveforms at 40,000 Hz for 42 days. CH coatings have been shown as a beneficial electrode material compatible with long-term delivery of high current, high energy waveforms.

Optimisation of current injection protocol based on a region of interest.

OBJECTIVE Electrical impedance tomography has the potential to image fast neural activity associated with physiological or epileptic activity throughout the brain. These applications pose a particular challenge as expected voltage changes on the electrodes are less than 1% and geometrical constraints of the body under investigation mean that electrodes can not be evenly distributed around its boundary. Unlike other applications, however, information regarding the location of expected activity is typically available. An informative method for choosing current paths that maximise sensitivity to specific regions is desirable. APPROACH Two electrode addressing protocol generation methods based on current density vectors concentrated in a region of interest have been proposed. One focuses solely on maximising its magnitude while the other considers its distribution. The quality of reconstructed images using these protocols was assessed in a simulation study conducted in a human and rat mesh and compared to the protocol that maximises distance between injecting electrodes. MAIN RESULTS When implementing the protocol that focused on maximising magnitude, the current density concentrated in a region of interest increased by up to a factor of 3. When the distribution of the current was maximised, the spread of current density vectors increased by up to fivefold. For the small conductivity changes expected in the applications explored, image quality was best when implementing the protocol that maximised current density. The average image error when using this protocol was 7% better than when employing other protocols. SIGNIFICANCE We conclude that for fast neural EIT applications, the protocol that maximises current density is the best protocol to implement.