Insertion Guidance Based on Impedance Measurements of a Cochlear Electrode Array

Abstract

The cochlear implantable neuromodulator provides substantial auditory perception to those with severe or profound impaired hearing. Correct electrode array positioning in the cochlea is one of the important factors for quality hearing, and misplacement may lead to additional injury to the cochlea. Visual inspection of the progress of electrode insertion is limited and mainly relies on the surgeon's tactile skills, and there is a need to detect in real-time the electrode array position in the cochlea during insertion. The available clinical measurement presently provides very limited information. Impedance measurement may be used to assist with the insertion of the electrode array. Using computational modeling of the cochlea, and its local tissue layers merging with the associated neuromodulator electrode array parameters, the impedance variations at different insertion depths and the proximities to the cochlea walls have been analyzed. In this study, an anatomical computational model of the temporal region of a patient is used to derive the relationship between impedance variations and the electrode proximity to the cochlea wall and electrode insertion depth. The aim was to examine whether the use of electrode impedance variations can be an effective marker of electrode proximity and electrode insertion depth. The proposed anatomical model simulates the quasi-static electrode impedance variations at different selected points but at considerable computation cost. A much less computationally intensive geometric model (~1/30) provided comparative impedance measurements with differences of <2%. Both use finite element analysis over the entire cross-section area of the scala tympani. It is shown that the magnitude of the impedance varies with both electrode insertion depth and electrode proximity to the adjacent anatomical layers (e.g., cochlea wall). In particular, there is a 1,400% increase when the electrode array is moved very close to the cochlea wall. This may help the surgeon to find the optimal electrode position within the scala tympani by observation of such impedance characteristics. The misplacement of the electrode array within the scala tympani may be eliminated by using the impedance variation metric during electrode array insertion if the results are validated with an experimental study.

Human cochlear microstructures at risk of electrode insertion trauma, elucidated in 3D with contrast-enhanced microCT

“…Contrary to standard microCT imaging 28 , 31 , CECT enables clear visualization of cochlear soft tissues structures in their original shape, without the need for removal of the intracochlear fluid, which enables more accurate assessment of soft-tissue electrode insertion trauma. In addition, CECT imaging of the human cochlea has the potential to enable highly accurate modelling and testing of novel techniques for atraumatic electrode insertion, such as impedance measurements 82 , 83 and robotics-assisted insertion 31 . Finally, CECT holds a great promise for nondestructive, quantitative 3D study of cochlear pathologies, underlying hearing loss, which are currently mainly being investigated with classical histology 84 .…”

Models of Cochlea Used in Cochlear Implant Research: A Review

“…These have gradually increased in complexity from simpler parametric representations of the cochlear spiral to microCT-based models that also incorporate the trajectories of auditory neurons [11,55,115]. As well as understanding the electrical properties of the cochlea, these finite element models have also been utilised for impedance-guided insertion to determine the CI positioning within the cochlea from electrical measurements [127]. These finite element models can be coupled to multi-physics simulations such as thermal safety analyses of intracochlear heating with magnetically steered CIs [39].…”

Human Head Transcranial Magnetic Stimulation Using Finite Element Method

“…Such methods are implemented using finite elements (FE) and models (FEM). It consists of a volume conductor model that represents different structures and the electrodes according to their conductivities and appropriate boundary conditions [14]- [16]. Current commercial FEM software packages (e.g., COMSOL Multiphysics, ANSYS) allow calculating electrical magnetic induction in the computational models.…”