Enhancing Electrode Location Assessment in Cochlear Implantation via Computed Tomography Image Fusion

Summary

This protocol demonstrates a method for fusing pre-operative and post-operative computed tomography images for cochlear implant recipients. The approach may enhance the measurement accuracy of insertion depth and the center frequency of electrode array contacts. Additionally, this method has potential applications in anatomy-based fitting, an emerging area within the cochlear implant field.

Abstract

This study aimed to determine whether fusing pre- and post-operative computed tomography (CT) images could help in assessing electrode placement and center frequency (CF) in cochlear implant (CI) recipients. A secondary objective was to compare automatic fusion with manual methods for measuring cochlear parameters. The study included twenty ears with CIs that underwent both pre- and post-operative CT scans. Manual measurements of cochlear parameters were initially taken from the post-operative CT images, followed by automatic detection using fused pre- and post-operative CT images with otological software (OTOPLAN). Angular insertion depth (AID) and CF of each electrode contact were calculated using both methods, and error differences were assessed. The analysis showed significant differences between the two methods for cochlear width (B-value) and cochlear duct length (CDL); however, these differences were not clinically significant. Furthermore, there was no statistically significant difference in cochlear diameter (A-value). The mean differences were 0.04 mm for the A-value, 0.21 mm for the B-value, and 0.73 mm for the CDL. The comparison of AID and CF revealed non-significant differences between manual and automatic fusion methods across all electrode contacts, except for electrode number five. According to this study, fusing pre- and post-operative CT images can be used to determine electrode positions in CI recipients. Automatic fused images can potentially measure cochlear parameters, AID, and CF with reduced human interference. Therefore, this method may serve as another basis for creating anatomy-based fitting.

Introduction

Cochlear implant (CI) surgery is a transformative treatment for individuals with severe-to-profound sensorineural hearing loss, offering substantial improvements in auditory function and quality of life¹. A critical factor for the success of CI surgery is the accurate placement of the electrode array within the correct cochlear compartment, specifically the scala tympani, as optimal electrode positioning, is consistently linked to superior hearing outcomes². Thus, careful pre-operative planning and assessment of cochlear anatomy are essential to ensure the electrode array is positioned appropriately. Ensuring that the el....

Protocol

This study received approval from the principal Institutional Review Board (E-21-5737) and was conducted following the ethical principles outlined in the Declaration of Helsinki. Data were retrospectively collected from medical records at our tertiary CI center. Due to the anonymized nature of data analysis, informed consent was not required. The study included 20 ears from patients across various age groups.

Inclusion criteria were as follows: patients with normal inner ear anatomy who receiv.......

Discussion

The findings of the present study revealed comparable measurements between Manual and Automatic Fusion methods for most cochlear parameters and frequencies. While Manual measurements exhibited marginally higher values for certain parameters, such as the B value and CDL, no clinically significant differences were observed overall. This discrepancy could be attributed to artifacts in the post-operative CT, which may affect measurement accuracy. Furthermore, this study builds upon prior research by specifically evaluating A.......

Materials

Name	Company	Catalog Number	Comments
CI devices	MED-EL, Innsbruck, Austria
OTOPLAN software	CASCINATION, MED-EL, Innsbruck, Austria	version 4 (3.0.0)	Otology Planning Software
R software	R Foundation for Statistical Computing, Vienna, Austria	version 4.2.2	Language and Environment for Statistical Computing