In silico study on in vitro experiments to determine the electric membrane properties of a realistic cochlear model for electric field simulations on cochlear implants

To further develop and optimise the design of cochlear implants, a numerical model with precise material properties and authentic geometry is required. Since simulation results strongly depend on the accuracy of the estimates of the electrical properties of cochlear membranes, it is important to have a reliable in vivo method for measuring electrical impedance changes in the cochlear compartments. This work is a preliminary attempt to model, simulate and analyse the behaviour of a novel in-vitro experimental system for conducting plausible in-vivo measurements on mammalian cochlea membranes.Zur Weiterentwicklung und Optimierung des Designs von Cochlea-Implantaten ist ein detailliertes numerisches Modell der Cochlea erforderlich. Da die Simulationsergebnisse stark von den elektrischen Eigenschaften der Cochlea-Membranen abhängen, ist es wichtig, ein zuverlässiges In-vivo-Verfahren zur Messung des elektrischen Impedanzverlaufs zu haben. Diese Arbeit ist eine vorbereitende Studie, das Verhalten eines neuartigen In-vitro-Versuchssystems zur Durchführung plausibler In-vivo-Messungen an Cochlea-Membranen von Säugetieren zu modellieren, zu simulieren und zu analysieren

High Fidelity Bioelectric Modelling of the Implanted Cochlea

Cochlear implants are medical devices that can restore sound perception in individuals with sensorineural hearing loss (SHL). Since their inception, improvements in performance have largely been driven by advances in signal processing, but progress has plateaued for almost a decade. This suggests that there is a bottleneck at the electrode-tissue interface, which is responsible for enacting the biophysical changes that govern neuronal recruitment. Understanding this interface is difficult because the cochlea is small, intricate, and difficult to access. As such, researchers have turned to modelling techniques to provide new insights. The state-of-the-art involves calculating the electric field using a volume conduction model of the implanted cochlea and coupling it with a neural excitation model to predict the response. However, many models are unable to predict patient outcomes consistently. This thesis aims to improve the reliability of these models by creating high fidelity reconstructions of the inner ear and critically assessing the validity of the underlying and hitherto untested assumptions. Regarding boundary conditions, the evidence suggests that the unmodelled monopolar return path should be accounted for, perhaps by applying a voltage offset at a boundary surface. Regarding vasculature, the models show that large modiolar vessels like the vein of the scala tympani have a strong local effect near the stimulating electrode. Finally, it appears that the oft-cited quasi-static assumption is not valid due to the high permittivity of neural tissue. It is hoped that the study improves the trustworthiness of all bioelectric models of the cochlea, either by validating the claims of existing models, or by prompting improvements in future work. Developing our understanding of the underlying physics will pave the way for advancing future electrode array designs as well as patient-specific simulations, ultimately improving the quality of life for those with SHL

Qualitative effect of tissue heterogeneity and modiolus porosity on the transmembrane potential of type-1 spiral ganglion neurons in the human cochlea: a simulation study

Electric stimulation of auditory nerve by cochlear implants has been a successful clinical intervention to treat the sensorineural deafness. However, various micro-anatomical factors have not been considered in the state of the art models while studying the interaction between the applied electric field and the auditory nerve. The present finite element modeling study suggests that the modiolus porosity and tissue heterogeneity significantly alter the electric field distribution in the Rosenthal’s canal and thereby affect the cochlear implant functionality

Electrochemical Safety Studies of Cochlear Implant Electrodes Using the Finite Element Method

Cochlear implants, amongst other neural prostheses, utilise platinum electrodes as an interface between the synthetic implant and the biological tissue environment. If excessive electrical charge is injected via these electrodes, injury to the tissue may result. Empirically derived stimulation limits have been defined to prevent tissue damage, however the injurious mechanisms are still unclear. Evidence suggests that the non-uniform distribution of charge on electrodes influences the electrochemical generation of toxic by-products. However, in vivo and in vitro techniques are limited in their ability to systematically explore the factors and mechanisms that contribute to stimulation-induced tissue injury. To this end, an in silico approach was used to develop a time-domain model of cochlear implant stimulation electrodes. A constant phase angle impedance was used to model the reversible processes on the electrode surface, and Butler-Volmer reaction kinetics were used to define the behaviour of the water window irreversible electrochemical reactions. The resulting model provided time-domain responses of the current density distributions, and net charge consumed by the hydrolysis reactions. This model was then used to perform systematic evaluations of various electrode geometries and stimulation parameters. The modelling results showed the current associated with irreversible reactions was non-uniform and tended towards the periphery of the electrode. A comparison of electrode geometries revealed interactions between electrode size, shape and recess depth. Stimulation mode, electrode position, and electrolyte conductivity were found to impact the shape of the electric field and the extent of irreversible reactions. This emphasised the influence of the physiological environment on the stimulation safety. In vitro experiments were conducted to validate the model. The implications of the results described in this thesis can be used to inform the design of safer electrodes

Model-based prediction of optogenetic sound encoding in the human cochlea by future optical cochlear implants

When hearing fails, electrical cochlear implants (eCIs) partially restore hearing by direct stimulation of spiral ganglion neurons (SGNs). As light can be better confined in space than electrical current, optical CIs (oCIs) provide more spectral information promising a fundamental improvement of hearing restoration by cochlear implants. Here, we turned to computer modelling for predicting the outcome of optogenetic hearing restoration by future oCIs in humans. We combined three-dimensional reconstruction of the human cochlea with ray-tracing simulation of emission from LED or laser-coupled waveguide emitters of the oCI. Irradiance was read out at the somata of SGNs. The irradiance values reached with waveguides were about 14 times higher than with LEDs, at the same radiant flux of the emitter. Moreover, waveguides outperformed LEDs regarding spectral selectivity. oCIs with either emitter type showed greater spectral selectivity when compared to eCI. In addition, modeling the effects of the source-to-SGN distance, orientation of the sources and impact of scar tissue further informs the development of optogenetic hearing restoration

Proceedings of the Conference on Progress in Electrically Active Implants - Tissue and Functional Regeneration (ELAINE 2020)

The conference on Progress in Electrically Active Implants - Tissue and Functional Regeneration (ELAINE 2020) focused on novel methods in the electric stimulation of bio-material compounds of living cells and implantable electric stimulation devices. ELAINE 2020 provided international scientists a virtual platform to discuss the latest achievements in the form of invited presentations, selected talks from abstract submissions, and virtual poster sessions. In addition, we particularly invited critical reviews and contributions with negative results or unsuccessful replications to foster the scientific discussion and explicitly encourage young scientists to contribute and submit their work

Occupational exposure to electromagnetic fields in magnetic resonance environment: an update on regulation, exposure assessment techniques, health risk evaluation, and surveillance

Magnetic resonance imaging (MRI) is one of the most-used diagnostic imaging methods worldwide. There are ∼50,000 MRI scanners worldwide each of which involves a minimum of five workers from different disciplines who spend their working days around MRI scanners. This review analyzes the state of the art of literature about the several aspects of the occupational exposure to electromagnetic fields (EMF) in MRI: regulations, literature studies on biological effects, and health surveillance are addressed here in detail, along with a summary of the main approaches for exposure assessment. The original research papers published from 2013 to 2021 in international peer-reviewed journals, in the English language, are analyzed, together with documents published by legislative bodies. The key points for each topic are identified and described together with useful tips for precise safeguarding of MRI operators, in terms of exposure assessment, studies on biological effects, and health surveillance. Graphical abstract: [Figure not available: see fulltext.

Computational evaluation of cochlear implant surgery outcomes accounting for uncertainty and parameter variability

Cochlear implantation (CI) is a complex surgical procedure that restores hearing in patients with severe deafness. The successful outcome of the implanted device relies on a group of factors, some of them unpredictable or difficult to control. Uncertainties on the electrode array position and the electrical properties of the bone make it difficult to accurately compute the current propagation delivered by the implant and the resulting neural activation. In this context, we use uncertainty quantification methods to explore how these uncertainties propagate through all the stages of CI computational simulations. To this end, we employ an automatic framework, encompassing from the finite element generation of CI models to the assessment of the neural response induced by the implant stimulation. To estimate the confidence intervals of the simulated neural response, we propose two approaches. First, we encode the variability of the cochlear morphology among the population through a statistical shape model. This allows us to generate a population of virtual patients using Monte Carlo sampling and to assign to each of them a set of parameter values according to a statistical distribution. The framework is implemented and parallelized in a High Throughput Computing environment that enables to maximize the available computing resources. Secondly, we perform a patient-specific study to evaluate the computed neural response to seek the optimal post-implantation stimulus levels. Considering a single cochlear morphology, the uncertainty in tissue electrical resistivity and surgical insertion parameters is propagated using the Probabilistic Collocation method, which reduces the number of samples to evaluate. Results show that bone resistivity has the highest influence on CI outcomes. In conjunction with the variability of the cochlear length, worst outcomes are obtained for small cochleae with high resistivity values. However, the effect of the surgical insertion length on the CI outcomes could not be clearly observed, since its impact may be concealed by the other considered parameters. Whereas the Monte Carlo approach implies a high computational cost, Probabilistic Collocation presents a suitable trade-off between precision and computational time. Results suggest that the proposed framework has a great potential to help in both surgical planning decisions and in the audiological setting process