Anatomical and functional organization of cardiac fibers in the porcine cervical vagus nerve allows spatially selective efferent neuromodulation

Cardiac disease progression reflects the dynamic interaction between adversely remodeled neurohumoral control systems and an abnormal cardiac substrate. Vagal nerve stimulation (VNS) is an attractive neuromodulatory option to dampen this dynamic interaction; however, it is limited by off-target effects. Spatially-selective VNS (sVNS) offers a promising solution to induce cardioprotection while mitigating off-target effects by specifically targeting pre-ganglionic parasympathetic efferent cardiac fibers. This approach also has the potential to enhance therapeutic outcomes by eliminating time-consuming titration required for optimal VNS. Recent studies have demonstrated the independent modulation of breathing rate, heart rate, and laryngeal contraction through sVNS. However, the spatial organization of afferent and efferent cardiac-related fibers within the vagus nerve remains unexplored. By using trial-and-error sVNS in vivo in combination with ex vivo micro-computed tomography fascicle tracing, we show the significant spatial separation of cardiac afferent and efferent fibers (179±55° SD microCT, p<0.05 and 200±137° SD, p<0.05 sVNS - degrees of separation across a cross-section of nerve) at the mid-cervical level. We also show that cardiac afferent fibers are located in proximity to pulmonary fibers consistent with recent findings of cardiopulmonary convergent neurons and circuits. We demonstrate the ability of sVNS to selectively elicit desired scalable heart rate decrease without stimulating afferent-related reflexes. By elucidating the spatial organization of cardiac-related fibers within the vagus nerve, our findings pave the way for more targeted neuromodulation, thereby reducing off-target effects and eliminating the need for titration. This, in turn, will enhance the precision and efficacy of VNS therapy in treating cardiac pathology, allowing for improved therapeutic efficacy.

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.

A combined cuff electrode array for organ-specific selective stimulation of vagus nerve enabled by Electrical Impedance Tomography

Previously developed spatially-selective Vagus Nerve Stimulation (sVNS) allows the targeting of specific nerve fascicles through current steering in a multi-electrode nerve cuff but relies on a trial-and-error strategy to identify the relative orientation between electrodes and fascicles. Fast Neural Electrical Impedance Tomography (FN-EIT) has been recently used for imaging neural traffic in the vagus nerves of pigs in a cross-correlation study with sVNS and MicroCT fascicle tracking. FN-EIT has the potential for allowing targeted sVNS; however, up to now, stimulation and imaging have been performed with separate electrode arrays. In this study, different options were evaluated in-silico to integrate EIT and stimulation into a single electrode array without affecting spatial selectivity. The original pig vagus EIT electrode array geometry was compared with a geometry integrating sVNS and EIT electrodes, and with direct use of sVNS electrodes for EIT imaging. Modelling results indicated that both new designs could achieve image quality similar to the original electrode geometry in all tested markers (e.g., co-localisation error <100 µm). The sVNS array was considered to be the simplest due to the lower number of electrodes. Experimental results from testing evoked EIT imaging of recurrent laryngeal activity using electrodes from the sVNS cuff returned a signal-to-noise ratio similar to our previous study (3.9 ± 2.4 vs. 4.1 ± 1.5, N = 4 nerves from 3 pigs) and a lower co-localisation error (≈14% nerve diameter vs. ≈25%, N = 2 nerves from 2 pigs). Performing FN-EIT and sVNS on the same nerve cuff will facilitate translation to humans, simplify surgery and enable targeted neuromodulation strategies.

Organotopic organization of the porcine mid-cervical vagus nerve

Introduction

Despite detailed characterization of fascicular organization of somatic nerves, the functional anatomy of fascicles evident in human and large mammal cervical vagus nerve is unknown. The vagus nerve is a prime target for intervention in the field of electroceuticals due to its extensive distribution to the heart, larynx, lungs, and abdominal viscera. However, current practice of the approved vagus nerve stimulation (VNS) technique is to stimulate the entire nerve. This produces indiscriminate stimulation of non-targeted effectors and undesired side effects. Selective neuromodulation is now a possibility with a spatially-selective vagal nerve cuff. However, this requires the knowledge of the fascicular organization at the level of cuff placement to inform selectivity of only the desired target organ or function.

Methods and results

We imaged function over milliseconds with fast neural electrical impedance tomography and selective stimulation, and found consistent spatially separated regions within the nerve correlating with the three fascicular groups of interest, suggesting organotopy. This was independently verified with structural imaging by tracing anatomical connections from the end organ with microCT and the development of an anatomical map of the vagus nerve. This confirmed organotopic organization.

Discussion

Here we show, for the first time, localized fascicles in the porcine cervical vagus nerve which map to cardiac, pulmonary and recurrent laryngeal function (N = 4). These findings pave the way for improved outcomes in VNS as unwanted side effects could be reduced by targeted selective stimulation of identified organ-specific fiber-containing fascicles and the extension of this technique clinically beyond the currently approved disorders to treat heart failure, chronic inflammatory disorders, and more.

Peritoneal dialysis-associated peritonitis presenting with Ralstonia pickettii infection: A novel series of three cases during the COVID-19 pandemic

Peritoneal dialysis (PD)-associated peritonitis secondary to Ralstonia infection is very rare. Ralstonia pickettii is an organism that can grow in contaminated saline, water, chlorhexidine, and other medical products used in laboratories and the clinical setting. Infective endocarditis, prosthetic joint, and severe chest infections are previously reported with R. pickettii infection. We report a novel series of three cases diagnosed with PD-associated peritonitis caused by R. pickettii, where the cases appeared consecutively to our unit during a span of 4 weeks. During the COVID-19 pandemic, there were increased uses of non-sterile gloves by clinical staff as a form of personal protective equipment throughout patient interaction and PD exchange, as recommended by local hospital policy for all staff attending to patient care. A multidisciplinary team root cause analysis of our cases suggested non-sterile gloves being the likely source of environmental contamination, leading to PD-associated peritonitis caused by R. pickettii in this scenario.

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.

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.

Selective Vagus Nerve Stimulation as a Therapeutic Approach for the Treatment of ARDS: A Rationale for Neuro-Immunomodulation in COVID-19 Disease

Acute respiratory distress syndrome (ARDS) is the most severe form of acute lung injury. It is induced by sepsis, aspiration, and pneumonia, including that caused by SARS coronavirus and human influenza viruses. The main pathophysiological mechanism of ARDS is a systemic inflammatory response. Vagus nerve stimulation (VNS) can limit cytokine production in the spleen and thereby dampen any systemic inflammation and inflammation-induced tissue damage in the lungs and other organs. However, the effects of increased parasympathetic outflow to the lungs when non-selective VNS is applied may result in bronchoconstriction, increased mucus secretion and enhance local pulmonary inflammatory activity; this may outweigh the beneficial systemic anti-inflammatory action of VNS. Organ/function-specific therapy can be achieved by imaging of localized fascicle activity within the vagus nerve and selective stimulation of identified organ-specific fascicles. This may be able to provide selective neuromodulation of different pathways within the vagus nerve and offer a novel means to improve outcome in ARDS. This has motivated this review in which we discuss the mechanisms of anti-inflammatory effects of VNS, progress in selective VNS techniques, and a possible application for ARDS.

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

Intracranial EEG is the current gold standard technique for localizing seizures for surgery, but it can be insensitive to tangential dipole or distant sources. Electrical Impedance Tomography (EIT) offers a novel method to improve coverage and seizure onset localization. The feasibility of EIT has been previously assessed in a computer simulation, which revealed an improved accuracy of seizure detection with EIT compared to intracranial EEG. In this study, slow impedance changes, evoked by cell swelling occurring over seconds, were reconstructed in real time by frequency division multiplexing EIT using depth and subdural electrodes in a swine model of epilepsy. EIT allowed to generate repetitive images of ictal events at similar time course to fMRI but without its significant limitations. EIT was recorded with a system consisting of 32 parallel current sources and 64 voltage recorders. Seizures triggered with intracranial injection of benzylpenicillin (BPN) in five pigs caused a repetitive peak impedance increase of 3.4 ± 1.5 mV and 9.5 ± 3% (N =205 seizures); the impedance signal change was seen already after a single, first seizure. EIT enabled reconstruction of the seizure onset 9 ± 1.5 mm from the BPN cannula and 7.5 ± 1.1 mm from the closest SEEG contact (p<0.05, n =37 focal seizures in three pigs) and it could address problems with sampling error in intracranial EEG. The amplitude of the impedance change correlated with the spread of the seizure on the SEEG (p <<0.001, n =37). The results presented here suggest that combining a parallel EIT system with intracranial EEG monitoring has a potential to improve the diagnostic yield in epileptic patients and become a vital tool in improving our understanding of epilepsy.

Model-based geometrical optimisation and in vivo validation of a spatially selective multielectrode cuff array for vagus nerve neuromodulation

BACKGROUND

Neuromodulation by electrical stimulation of the human cervical vagus nerve may be limited by adverse side effects due to stimulation of off-target organs. It may be possible to overcome this by spatially selective stimulation of peripheral nerves. Preliminary studies have shown this is possible using a cylindrical multielectrode human-sized nerve cuff in vagus nerve selective neuromodulation.

NEW METHOD

The model-based optimisation method for multi-electrode geometric design is presented. The method was applied for vagus nerve cuff array and suggested two rings of 14 electrodes, 3 mm apart, with 0.4 mm electrode width and separation and length 0.5-3 mm, with stimulation through a pair in the same radial position on the two rings. The electrodes were fabricated using PDMS-embedded stainless steel foil and PEDOT: pTS coating.

RESULTS

In the cervical vagus nerve in anaesthetised sheep, it was possible to selectively reduce the respiratory breath rate (RBR) by 85 ± 5% without affecting heart rate, or selectively reduce heart rate (HR) by 20 ± 7% without affecting respiratory rate. The cardiac- and pulmonary-specific sites on the nerve cross-sectional perimeter were localised with a radial separation of 105 ± 5 degrees (P < 0.01, N = 24 in 12 sheep).

CONCLUSIONS

Results suggest organotopic or function-specific organisation of neural fibres in the cervical vagus nerve. The optimised electrode array demonstrated selective electrical neuromodulation without adverse side effects. It may be possible to translate this to improved treatment by electrical autonomic neuromodulation for currently intractable conditions.

Imaging fascicular organization of rat sciatic nerves with fast neural electrical impedance tomography

Imaging compound action potentials (CAPs) in peripheral nerves could help avoid side effects in neuromodulation by selective stimulation of identified fascicles. Existing methods have low resolution, limited imaging depth, or are invasive. Fast neural electrical impedance tomography (EIT) allows fascicular CAP imaging with a resolution of <200 µm, <1 ms using a non-penetrating flexible nerve cuff electrode array. Here, we validate EIT imaging in rat sciatic nerve by comparison to micro-computed tomography (microCT) and histology with fluorescent dextran tracers. With EIT, there are reproducible localized changes in tissue impedance in response to stimulation of individual fascicles (tibial, peroneal and sural). The reconstructed EIT images correspond to microCT scans and histology, with significant separation between the fascicles (p < 0.01). The mean fascicle position is identified with an accuracy of 6% of nerve diameter. This suggests fast neural EIT can reliably image the functional fascicular anatomy of the nerves and so aid selective neuromodulation.

A 10 nV/rt Hz noise level 32-channel neural impedance sensing ASIC for local activation imaging on nerve section

A 10 nV/rt Hz noise level 32-channel neural impedance sensing ASIC is presented for the application of local activation imaging in nerve section. It is increasingly known that the monitoring and control of nerve signals can improve physical and mental health. Major nerves, such as the vagus nerve and the sciatic nerve, consist of a bundle of fascicles. Therefore, to accurately control a particular application without any side effects, we need to know exactly which fascicle was activated. The only way to find locally activated fascicle is to use electrical impedance tomography (EIT). The ASIC to be introduced is designed for neural EIT applications. A neural impedance sensing ASIC was implemented using CMOS 180-nm process technology. The integrated input referred noise was calculated to be 0.46 μVrms (noise floor 10.3 nVrms/rt Hz) in the measured noise spectrum. At an input of 80 mV, the squared correlation coefficient for linear regression was 0.99998. The amplification gain uniformity of 32 channels was in the range of + 0.23% and - 0.29%. Using the resistor phantom, the simplest model of nerve, it was verified that a single readout channel could detect a signal-to- noise ratio of 75.6 dB or more. Through the reservoir phantom, real-time EIT images were reconstructed at a rate of 8.3 frames per second. The developed ASIC has been applied to in vivo experiments with rat sciatic nerves, and signal processing is currently underway to obtain activated nerve cross-sectional images. The developed ASIC was also applied to in-vivo experiments with rat sciatic nerves, and signal processing is currently underway to obtain locally activated nerve cross-sectional images.

MicroCT optimisation for imaging fascicular anatomy in peripheral nerves

BACKGROUND

Due to the lack of understanding of the fascicular organisation, vagus nerve stimulation (VNS) leads to unwanted off-target effects. Micro-computed tomography (microCT) can be used to trace fascicles from periphery and image fascicular anatomy.

NEW METHOD

In this study, we present a simple and reproducible method for imaging fascicles in peripheral nerves with iodine staining and microCT for the determination of fascicular anatomy and organisation.

RESULTS

At the determined optimal pre-processing steps and scanning parameters, the microCT protocol allowed for segmentation and tracking of fascicles within the nerves. This was achieved after 24 hours and 120 hours of staining with Lugol's solution (1% total iodine) for rat sciatic and pig vagus nerves, respectively, and the following scanning parameters: 4 μm voxel size, 35 kVp energy, 114 μA current, 4 W power, 0.25 fps in 4 s exposure time, 3176 projections and a molybdenum target.

COMPARISON WITH EXISTING METHOD(S)

This optimised method for imaging fascicles provides high-resolution, three-dimensional images and full imaging penetration depth not obtainable with methods typically used such as histology, magnetic resonance imaging and optical coherence tomography whilst obviating time-consuming pre-processing methods, the amount of memory required, destruction of the samples and the cost associated with current microCT methods.

CONCLUSION

The optimised microCT protocol facilitates segmentation and tracking of the fascicles within the nerve. The resulting segmentation map of the functional anatomical organisation of the vagus nerve will enable selective VNS ultimately allowing for the avoidance of the off-target effects and improving its therapeutic efficacy.

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.

Avoiding off-target effects in electrical stimulation of the cervical vagus nerve: Neuroanatomical tracing techniques to study fascicular anatomy of the vagus nerve

Vagus nerve stimulation (VNS) is a promising therapy for treatment of various conditions that are resistant to standard medication, such as heart failure, epilepsy, and depression. The vagus nerve is a complex nerve providing afferent and efferent innervation of the pharynx, larynx, heart, tracheobronchial tree and lungs, oesophagus, stomach, liver, pancreas, small intestine and proximal colon. It is therefore a prime target for intervention for VNS. Surprisingly, the fascicular organisation of the vagus nerve at the cervical level is still not well understood. This, along with the current stimulation techniques, results in the entire nerve being stimulated, which leads to unwanted off-target effects. Neuronal tracing is a promising method to delineate the organ-specific innervation by the vagus nerve, thereby providing valuable insight into the fascicular anatomy. In this review we discuss the current knowledge of vagus nerve anatomy and neuronal tracers used for mapping of its organ-specific projections in various species. Efferent vagal projections are a chain of two neurones (pre- and postganglionic), while afferent projections consist of only one pseudounipolar neurone with one branch terminating in the target organ/tissue directly and another in the brainstem. It would be feasible to retrogradely trace the afferent fibres from their respective visceral targets and identify them at the cervical level using non-transsynaptic neuronal tracers. Using this to create a map of the functional anatomical organisation of the vagus nerve will enable selective VNS ultimately allowing for the avoidance of the off-target effects and improving overall efficacy.

Electrode fabrication and interface optimization for imaging of evoked peripheral nervous system activity with electrical impedance tomography (EIT)

OBJECTIVE

Non-invasive imaging techniques are undoubtedly the ideal methods for continuous monitoring of neural activity. One such method, fast neural electrical impedance tomography (EIT) has been developed over the past decade in order to image neural action potentials with non-penetrating electrode arrays.

APPROACH

The goal of this study is two-fold. First, we present a detailed fabrication method for silicone-based multiple electrode arrays which can be used for epicortical or neural cuff applications. Secondly, we optimize electrode material coatings in order to achieve the best accuracy in EIT reconstructions.

MAIN RESULTS

The testing of nanostructured electrode interface materials consisting of platinum, iridium oxide, and PEDOT:pTS in saline tank experiments demonstrated that the PEDOT:pTS coating used in this study leads to more accurate reconstruction dimensions along with reduced phase separation between recording channels. The PEDOT:pTS electrodes were then used in vivo to successfully image and localize the evoked activity of the recurrent laryngeal fascicle from within the cervical vagus nerve.

SIGNIFICANCE

These results alongside the simple fabrication method presented here position EIT as an effective method to image neural activity.

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

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

Multi-frequency electrical impedance tomography and neuroimaging data in stroke patients

Electrical Impedance Tomography (EIT) is a non-invasive imaging technique, which has the potential to expedite the differentiation of ischaemic or haemorrhagic stroke, decreasing the time to treatment. Whilst demonstrated in simulation, there are currently no suitable imaging or classification methods which can be successfully applied to human stroke data. Development of these complex methods is hindered by a lack of quality Multi-Frequency EIT (MFEIT) data. To address this, MFEIT data were collected from 23 stroke patients, and 10 healthy volunteers, as part of a clinical trial in collaboration with the Hyper Acute Stroke Unit (HASU) at University College London Hospital (UCLH). Data were collected at 17 frequencies between 5 Hz and 2 kHz, with 31 current injections, yielding 930 measurements at each frequency. This dataset is the most comprehensive of its kind and enables combined analysis of MFEIT, Electroencephalography (EEG) and Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) data in stroke patients, which can form the basis of future research into stroke classification.

Model of Impedance Changes in Unmyelinated Nerve Fibers

OBJECTIVE

Currently, there is no imaging method that is able to distinguish the functional activity inside nerves. Such a method would be essential for understanding peripheral nerve physiology and would allow precise neuromodulation of organs these nerves supply. Electrical impedance tomography (EIT) is a method that produces images of electrical impedance change (dZ) of an object by injecting alternating current and recording surface voltages. It has been shown to be able to image fast activity in the brain and large peripheral nerves. To image inside small autonomic nerves, mostly containing unmyelinated fibers, it is necessary to maximize SNR and optimize the EIT parameters. An accurate model of the nerve is required to identify these optimal parameters as well as to validate data obtained in the experiments.

METHODS

In this study, we developed two three-dimensional models of unmyelinated fibers: Hodgkin-Huxley (HH) squid giant axon (single and multiple) and mammalian C-nociceptor. A coupling feedback system was incorporated into the models to simulate direct and alternating current application and simultaneously record external field during action potential propagation.

RESULTS

Parameters of the developed models were varied to study their influence on the recorded impedance changes; the optimal parameters were identified. The negative dZ was found to monotonically decrease with frequency for both HH and C fiber models, in accordance with the experimental data.

CONCLUSION AND SIGNIFICANCE

The accurate realistic model of unmyelinated nerve allows the optimization of EIT parameters and matches literature and experimental results.

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.

Feasibility study of imaging fast neural activity in retinal tissue using Electrical Impedance Tomography

Electrical Impedance Tomography has been recently applied to image fast neural activity in the somatosensory cerebral cortex. This non-invasive imaging modality has the unique advantage of high spatial-temporal resolution in millimeters over milliseconds. This work was designed to test an existing 32-channel EIT system, a modified UCL ScouseTom, and to discuss the feasibility of imaging neural activity in retinal tissue through computer simulation. The finite element method was used to model a retinal slice with a realistic conductivity-depth profile of the macaque eye. The conductivity perturbation was simulated in five different layers of the model. 5μV_RMS white noise was added to boundary voltages. Simulation results showed that it is feasible to apply EIT in retinal tissue but the injection current is near threshold of unwanted phosphenes induction. Therefore the suggested future work are validating threshold current through animal experiments, developing electrodes with low contact impedance and mitigating noise through averaging.

Reproducible 3D printed head tanks for electrical impedance tomography with realistic shape and conductivity distribution

OBJECTIVE

Electrical impedance tomography (EIT) has many promising applications in brain injury monitoring. To evaluate both instrumentation and reconstruction algorithms, experiments are first performed in head tanks. Existing methods, whilst accurate, produce a discontinuous conductivity, and are often made by hand, making it hard for other researchers to replicate.

APPROACH

We have developed a method for constructing head tanks directly in a 3D printer. Conductivity was controlled through perforations in the skull surface, which allow for saline to pass through. Varying the diameter of the holes allowed for the conductivity to be controlled with 3% error for the target conductivity range. Taking CT and MRI segmentations as a basis, this method was employed to create an adult tank with a continuous conductivity distribution, and a neonatal tank with fontanelles.

MAIN RESULTS

Using 3D scanning a geometric accuracy of 0.21 mm was recorded, equal to that of the precision of the 3D printer used. Differences of 6.1%  ±  6.4% (n  =  11 in 4 tanks) compared to simulations were recorded in c. 800 boundary voltages. This may be attributed to the morphology of the skulls increasing tortuosity effects and hole misalignment. Despite significant differences in errors between three repetitions of the neonatal tank, images of a realistic perturbation could still be reconstructed with different tanks used for the baseline and perturbation datasets.

SIGNIFICANCE

These phantoms can be reproduced by any researcher with access to a 'hobbyist' 3D printer in a matter of days. All design files have been released using an open source license to encourage reproduction and modification.

A Versatile and Reproducible Multi-Frequency Electrical Impedance Tomography System

A highly versatile Electrical Impedance Tomography (EIT) system, nicknamed the ScouseTom, has been developed. The system allows control over current amplitude, frequency, number of electrodes, injection protocol and data processing. Current is injected using a Keithley 6221 current source, and voltages are recorded with a 24-bit EEG system with minimum bandwidth of 3.2 kHz. Custom PCBs interface with a PC to control the measurement process, electrode addressing and triggering of external stimuli. The performance of the system was characterised using resistor phantoms to represent human scalp recordings, with an SNR of 77.5 dB, stable across a four hour recording and 20 Hz to 20 kHz. In studies of both haeomorrhage using scalp electrodes, and evoked activity using epicortical electrode mats in rats, it was possible to reconstruct images matching established literature at known areas of onset. Data collected using scalp electrode in humans matched known tissue impedance spectra and was stable over frequency. The experimental procedure is software controlled and is readily adaptable to new paradigms. Where possible, commercial or open-source components were used, to minimise the complexity in reproduction. The hardware designs and software for the system have been released under an open source licence, encouraging contributions and allowing for rapid replication.

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.

Correction of electrode modelling errors in multi-frequency EIT imaging

The differentiation of haemorrhagic from ischaemic stroke using electrical impedance tomography (EIT) requires measurements at multiple frequencies, since the general lack of healthy measurements on the same patient excludes time-difference imaging methods. It has previously been shown that the inaccurate modelling of electrodes constitutes one of the largest sources of image artefacts in non-linear multi-frequency EIT applications. To address this issue, we augmented the conductivity Jacobian matrix with a Jacobian matrix with respect to electrode movement. Using this new algorithm, simulated ischaemic and haemorrhagic strokes in a realistic head model were reconstructed for varying degrees of electrode position errors. The simultaneous recovery of conductivity spectra and electrode positions removed most artefacts caused by inaccurately modelled electrodes. Reconstructions were stable for electrode position errors of up to 1.5 mm standard deviation along both surface dimensions. We conclude that this method can be used for electrode model correction in multi-frequency EIT.

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.

Correcting electrode modelling errors in EIT on realistic 3D head models

Electrical impedance tomography (EIT) is a promising medical imaging technique which could aid differentiation of haemorrhagic from ischaemic stroke in an ambulance. One challenge in EIT is the ill-posed nature of the image reconstruction, i.e., that small measurement or modelling errors can result in large image artefacts. It is therefore important that reconstruction algorithms are improved with regard to stability to modelling errors. We identify that wrongly modelled electrode positions constitute one of the biggest sources of image artefacts in head EIT. Therefore, the use of the Fréchet derivative on the electrode boundaries in a realistic three-dimensional head model is investigated, in order to reconstruct electrode movements simultaneously to conductivity changes. We show a fast implementation and analyse the performance of electrode position reconstructions in time-difference and absolute imaging for simulated and experimental voltages. Reconstructing the electrode positions and conductivities simultaneously increased the image quality significantly in the presence of electrode movement.

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 CPU's 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.

Multifrequency electrical impedance tomography with total variation regularization

Multifrequency electrical impedance tomography (MFEIT) reconstructs the distribution of conductivity by exploiting the dependence of tissue conductivity on frequency. MFEIT can be performed on a single instance of data, making it promising for applications such as stroke and cancer imaging, where it is not possible to obtain a 'baseline' measurement of healthy tissue. A nonlinear MFEIT algorithm able to reconstruct the volume fraction distribution of tissue rather than conductivities has been developed previously. For each volume, the fraction of a certain tissue should be either 1 or 0; this implies that the sharp changes of the fractions, representing the boundaries of tissue, contain all the relevant information. However, these boundaries are blurred by traditional regularization methods using [Formula: see text] norm. The total variation (TV) regularization can overcome this problem, but it is difficult to solve due to its non-differentiability. Because the fraction must be between 0 and 1, this imposes a constraint on the MFEIT method based on the fraction model. Therefore, a constrained optimization method capable of dealing with non-differentiable problems is required. Based on the primal and dual interior point method, we propose a new constrained TV regularized method to solve the fraction reconstruction problem. The noise performance of the new MFEIT method is analysed using simulations on a 2D cylindrical mesh. Convergence performance is also analysed through experiments using a cylindrical tank. Finally, simulations on an anatomically realistic head-shaped mesh are demonstrated. The proposed MFEIT method with TV regularization shows higher spatial resolution, particularly at the edges of the perturbation, and stronger noise robustness, and its image noise and shape error are 20% to 30% lower than the traditional fraction method.