Development of a \(\upmu \)CT-based Patient-Specific Model of the Electrically Stimulated Cochlea

Cochlear implants (CIs) are neural prosthetics that are used to treat sensory-based hearing loss. There are over 320,000 recipients worldwide. After implantation, each CI recipient goes through a sequence of programming sessions where audiologists determine several CI processor settings to attempt to optimize hearing outcomes. However, this process is difficult because there are no objective measures available to indicate what setting changes will lead to better hearing outcomes. It has been shown that a simplified model of electrically induced neural activation patterns within the cochlea can be created using patient CT images, and that audiologists can use this information to determine settings that lead to better hearing performance. A more comprehensive physics-based patient-specific model of neural activation has the potential to lead to even greater improvement in outcomes. In this paper, we propose a method to create such customized electro-anatomical models of the electrically stimulated cochlea. We compare the accuracy of our patient-specific models to the accuracy of generic models. Our results show that the patient-specific models are on average more accurate than the generic models, which motivates the use of a patient-specific modeling approach for cochlear implant patients.