Detection of Extracochlear Electrodes Using Stimulation-Current- Induced Non-Stimulating Electrode Voltage Recordings...

Area of Science:

• Biomedical Engineering
• Otolaryngology
• Medical Devices

Background:

• Extracochlear electrodes (EEs) occur in 9-13% of cochlear implantations and can negatively impact speech outcomes.
• SCINSEVs have previously shown effectiveness in detecting EEs with one manufacturer's devices.
• The generalizability of SCINSEVs to other cochlear implant manufacturers requires investigation.

Purpose of the Study:

• To evaluate the generalizability of SCINSEVs for detecting extracochlear electrodes (EEs) in cochlear implant (CI) devices from different manufacturers.
• To assess the performance of SCINSEVs across varying electrode array designs and measurement software.

Main Methods:

• Human cadaveric heads were implanted with Cochlear Ltd. (CI-A) and MED-EL (CI-B) electrodes.
• Contact impedances and SCINSEVs were measured using manufacturer-specific software for both full insertion and EEs in different simulated environments (air, saline, soft tissue).
• An automated detection tool was optimized and tested, and intra-operative SCINSEVs were collected from six patients.

Main Results:

• SCINSEVs demonstrated altered patterns at the transition zone from intracochlear to extracochlear electrodes.
• Automated detection achieved high sensitivity and specificity (91% for CI-A, 100% for CI-B) in cadaveric specimens with EEs.
• Quantification of EEs showed significant correlations between estimated and actual EEs (r=0.69 for CI-A, r=0.76 for CI-B).

Conclusions:

• SCINSEVs are applicable for detecting extracochlear electrodes across different cochlear implant companies.
• The technique's effectiveness is demonstrated despite variations in electrode array design and measurement software.
• SCINSEVs offer a promising method for identifying extracochlear electrode placement in various CI systems.