Share Email Print
cover

Proceedings Paper

Preoperative prediction of insertion depth of lateral wall cochlear implant electrode arrays
Author(s): Mohammad M. R. Khan; Robert F. Labadie; Jack H. Noble
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Cochlear implants (CI) 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 towards more optimal placement of the array in order to reduce trauma and preserve the residual hearing of the patient. In addition to the electrode array geometry (length and diameter), both the base insertion depth (BID) and the cochlear scale impact the overall array insertion depth. In this paper, we investigated the influence of these parameters on overall insertion depth with the purpose of developing a model which can make preoperative predictions of insertion depth of lateral wall cochlear implant electrode arrays. CT images of 86 lateral wall positioned straight electrode array CI recipients were analyzed. Using previously developed automated algorithms, relative electrode position inside the cochlea as well as the cochlea scale was measured from the CT images. 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 standard deviation of 41 degrees. Surgeons may use this model for patient-customized selection of the electrode array and/or to plan a base insertion depth for a given array that minimizes the likelihood of causing trauma to regions of the cochlea where residual hearing exists.

Paper Details

Date Published: 16 March 2020
PDF: 7 pages
Proc. SPIE 11315, Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling, 113152U (16 March 2020); doi: 10.1117/12.2550577
Show Author Affiliations
Mohammad M. R. Khan, Vanderbilt Univ. (United States)
Robert F. Labadie, Vanderbilt Univ. Medical Ctr. (United States)
Jack H. Noble, Vanderbilt Univ. (United States)


Published in SPIE Proceedings Vol. 11315:
Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

© SPIE. Terms of Use
Back to Top
PREMIUM CONTENT
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?
close_icon_gray