Purpose: Cochlear implants (CIs) use an array of electrodes surgically threaded into the cochlea to restore hearing sensation. Techniques for predicting the insertion depth of the array into the cochlea could guide surgeons toward more optimal placement of the array to reduce trauma and preserve the residual hearing. In addition to the electrode array geometry, the base insertion depth (BID) and the cochlear size could impact the overall array insertion depth.
Approach: We investigated using these measurements to develop a linear regression model that can make preoperative or intraoperative predictions of the insertion depth of lateral wall CI electrodes. Computed tomography (CT) images of 86 CI recipients were analyzed. Using previously developed automated algorithms, the relative electrode position inside the cochlea was measured from the CT images.
Results: A linear regression model is proposed for insertion depth prediction based on cochlea size, array geometry, and BID. The model is able to accurately predict angular insertion depths with a standard deviation of 41 deg and absolute deviation error of 32 deg.
Conclusions: Surgeons may use this model for patient-customized selection of electrode array and/or to plan a BID for a given array that minimizes the likelihood of causing trauma to regions of the cochlea where residual hearing exists.