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

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 2x14-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±56µm (-26±94µm 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

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

OBJECTIVE: Fast neural Electrical Impedance Tomography (FnEIT) 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 EIT 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 FEM-based statistical model of temporal dispersion in porcine subdiaphragmatic nerve was developed and experimentally validated ex-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 (SNR) 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 minutes. 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

Imaging fascicular organisation in mammalian vagus nerve for selective VNS

Nerves contain a large number of nerve fibres, or axons, organised into bundles known as fascicles. Despite the somatic nervous system being well understood, the organisation of the fascicles within the nerves of the autonomic nervous system remains almost completely unknown. The new field of bioelectronics medicine, Electroceuticals, involves the electrical stimulation of nerves to treat diseases instead of administering drugs or performing complex surgical procedures. Of particular interest is the vagus nerve, a prime target for intervention due to its afferent and efferent innervation to the heart, lungs and majority of the visceral organs. Vagus nerve stimulation (VNS) is a promising therapy for treatment of various conditions resistant to standard therapeutics. However, due to the unknown anatomy, the whole nerve is stimulated which leads to unwanted off-target effects. Electrical Impedance Tomography (EIT) is a non-invasive medical imaging technique in which the impedance of a part of the body is inferred from electrode measurements and used to form a tomographic image of that part. Micro-computed tomography (microCT) is an ex vivo method that has the potential to allow for imaging and tracing of fascicles within experimental models and facilitate the development of a fascicular map. Additionally, it could validate the in vivo technique of EIT. The aim of this thesis was to develop and optimise the microCT imaging method for imaging the fascicles within the nerve and to determine the fascicular organisation of the vagus nerve, ultimately allowing for selective VNS. Understanding and imaging the fascicular anatomy of nerves will not only allow for selective VNS and the improvement of its therapeutic efficacy but could also be integrated into the study on all peripheral nerves for peripheral nerve repair, microsurgery and improving the implementation of nerve guidance conduits. Chapter 1 provides an introduction to vagus nerve anatomy and the principles of microCT, neuronal tracing and EIT. Chapter 2 describes the optimisation of microCT for imaging the fascicular anatomy of peripheral nerves in the experimental rat sciatic and pig vagus nerve models, including the development of pre-processing methods and scanning parameters. Cross-validation of this optimised microCT method, neuronal tracing and EIT in the rat sciatic nerve was detailed in Chapter 3. Chapter 4 describes the study with microCT with tracing, EIT and selective stimulation in pigs, a model for human nerves. The microCT tracing approach was then extended into the subdiaphragmatic branches of the vagus nerves, detailed in Chapter 5. The ultimate goal of human vagus nerve tracing was preliminarily performed and described in Chapter 6. Chapter 7 concludes the work and describes future work. Lastly, Appendix 1 (Chapter 8) is a mini review on the application of selective vagus nerve stimulation to treat acute respiratory distress syndrome and Appendix 2 is morphological data corresponding to Chapter 4

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

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 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