Use of patient-specific models for computer-assisted cochlear implant programming

Abstract

Sensorineural hearing loss affects over 10% of the U.S. population and is most commonly caused by damage to the hair cells that transduce sound into action potentials in the afferent neurons of the auditory nerve fibers. Direct electrical stimulation of the spiral ganglion cell bodies using a surgically implanted neuroprosthetic device known as a cochlear implant (CI) bypasses damaged hair cells and effectively restores hearing sensation for individuals experiencing severe-to-profound hearing loss. Although these devices have been remarkably successful at restoring hearing, it is rare to achieve natural fidelity, and many patients experience poor outcomes. The selection of appropriately sized electrode array is one of the factors that limits outcomes. An ideal electrode covers the entire frequency spectrum of the cochlea without causing cochlear trauma. Another factor is the post-implantation programming process that audiologists clinically use because, while existing devices permit manipulation of many settings that could lead to better performance, there are no objective cues available to indicate what setting changes will lead to better performance. Thus, the adjustment process often converges to sub-optimal settings and may require dozens of programming sessions. In this dissertation, several approaches are proposed to estimate subject-specific cochlear length, which can be used to select appropriately sized electrode arrays, and neural activation patterns (NAPs) that contain information on which group of nerve fibers are activated by each intra-cochlear electrode. NAPs are predicted via physics-based computational models of electrically stimulated cochlea coupled with auditory nerve fiber activation models that are parameterized by neural health. These models can potentially guide CI programming as we have shown that NAPs can be used to determine channel interaction artefacts which negatively affect hearing outcomes. We have also clinically validated the in-vivo estimations of subject specific health of auditory nerve fiber populations in different regions of the inner ear as regions of dead or degenerated nerve fibers in the inner ear are common among individuals experiencing hearing loss and are a major contributor to the high variability in hearing outcomes with CIs.