The goals of this research are to develop and assess the clinical utility of an approach for determining the position of implanted cochlear implant (CI) electrodes relative to stimulation targets (the nerves of the Spiral Ganglion (SG)) for CI tuning assistance. It is widely believed that the best hearing restoration outcome can be achieved by stimulating, for a particular sound, the nerves that naturally correspond to the spectrum of that sound. However, this is not currently possible due to several technical limitations. One such issue is that the positions of the implanted electrodes are unknown. Thus, the audiologist adjusts the signal characteristics assigned to each electrode based solely on patient response. The majority of potentially adjustable parameters are left at the default settings determined by the CI manufacturer. Because of this one-size-fits-all approach, the tuning process may not result in optimal hearing restoration for all recipients. Each electrode is positioned at variable depths and perimodiolar distances. Electrode depth discrepancies result in a frequency shift artifact, i.e., each electrode stimulates nerves that do not correspond to the frequencies of the detected sound. A larger distance to the SG leads to wider current spread from each electrode, decreasing the spectral resolution, i.e., each electrode stimulates many nerves corresponding to a wide range of frequencies. In future work, we would like to test a range of advanced tuning techniques that rely on knowing the position of implanted electrodes relative to tonotopically mapped SG nerves. These techniques have the potential to improve hearing outcomes achieved with existing CIs. However, there has been no technology developed that allows accurate assessment of electrode position relative to stimulation targets in vivo. In this research, we will develop this technology and test a simple tuning scheme to assess its clinical utility. If successful, we will have developed an easy to use software package that has the potential to increase the effectiveness of existing cochlear implant technology and improve the quality of hearing restoration for implantees. To identify electrode position, existing techniques for identifying Cochlear Contour Advance electrode arrays in post-operative CT will be expanded for application to other types of electrodes. To identify stimulation targets (the SG), advanced active shape modeling techniques will be explored. These are powerful image processing methods that identify structures in images while constraining the shape of the results to be consistent with typical anatomical variations. The SG region will be tonotopically mapped using known heuristic equations that describe this frequency relationship. A simple tuning scheme will then be tested on implantees to evaluate the utility of this approach. Tuning parameters will include deciding which electrodes are on and off, determining the relative power of each electrode, and determining an electrode frequency allocation table. Positive results will demonstrate that these techniques will lead to more effective implant tuning and better hearing restoration.

Public Health Relevance

The proposed project involves exploring algorithmic methods that will lead to performance optimizations of cochlear implant electrode arrays. Thus, the results of this project can potentially improve the quality of hearing restoration for cochlear implant users and improve efficiency of the tuning process.

Agency
National Institute of Health (NIH)
Institute
National Institute on Deafness and Other Communication Disorders (NIDCD)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21DC012620-02
Application #
8500228
Study Section
Special Emphasis Panel (BNVT)
Program Officer
Miller, Roger
Project Start
2012-07-01
Project End
2014-06-30
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
2
Fiscal Year
2013
Total Cost
$216,632
Indirect Cost
$74,132
Name
Vanderbilt University Medical Center
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
004413456
City
Nashville
State
TN
Country
United States
Zip Code
37212
Zhao, Yiyuan; Dawant, Benoit M; Labadie, Robert F et al. (2014) Automatic localization of cochlear implant electrodes in CT. Med Image Comput Comput Assist Interv 17:331-8
Reda, Fitsum A; Noble, Jack H; Labadie, Robert F et al. (2014) An artifact-robust, shape library-based algorithm for automatic segmentation of inner ear anatomy in post-cochlear-implantation CT. Proc SPIE Int Soc Opt Eng 9034:90342V
Noble, Jack H; Gifford, René H; Hedley-Williams, Andrea J et al. (2014) Clinical evaluation of an image-guided cochlear implant programming strategy. Audiol Neurootol 19:400-11
Reda, Fitsum A; McRackan, Theodore R; Labadie, Robert F et al. (2014) Automatic segmentation of intra-cochlear anatomy in post-implantation CT of unilateral cochlear implant recipients. Med Image Anal 18:605-15
Noble, Jack H; Labadie, Robert F; Gifford, Rene H et al. (2013) Image-guidance enables new methods for customizing cochlear implant stimulation strategies. IEEE Trans Neural Syst Rehabil Eng 21:820-9