To date, over 320,000 hearing impaired individuals have received cochlear implants (CIs) in which an electrode array designed to substitute natural nerve stimulation by electrical stimulation is threaded into the cochlea. While speech understanding outcomes are typically good among CI users, even the best users complain that the fidelity of natural hearing is rarely reproduced. Additionally, a significant minority do poorl. Recently, we have developed a series of image processing algorithms that operate on CT images and permit for the first time to determine precisely the position of individual CI electrodes with respect to the nerves they activate. This will fundamentally change the postoperative management of CI recipients because it permits, also for the first time, the development of custom electrode programing strategies that are informed by objective imaging data. We have developed such an Image-Guided Cochlear Implant Programming (IGCIP) strategy and we have demonstrated that it can substantially and sometime dramatically improve hearing in long term CI users without requiring an additional surgical procedure. The success rate of our approach is also remarkable with the new setting being preferred 77% of the time by the 107 long term recipients who have participated in our ongoing study. To broaden patient access to this technology, we now propose to completely automate our algorithms and to develop software packages that will be useable by clinicians at the time and point of care. We also propose to conduct a large scale clinical validation both at our institution and at collaborating sites to discover factors that affect the performance of our method and further improve it.

Public Health Relevance

Cochlear implants consist of an externally-worn processor, similar in appearance to large hearing aid, and a surgically implanted component which is threaded into the inner ear. We have developed technology where, using CT scans after a patient is implanted; we can improve hearing outcomes with this device. In its current state of development, the technology is available only at Vanderbilt and requires teams of clinicians and engineers. This project will mature it and produce a system that will be clinically deployable, thus increasing the number of recipients who can benefit from our technology.

National Institute of Health (NIH)
National Institute on Deafness and Other Communication Disorders (NIDCD)
Research Project (R01)
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Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Miller, Roger
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Vanderbilt University Medical Center
Engineering (All Types)
Biomed Engr/Col Engr/Engr Sta
United States
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Gifford, René H; Noble, Jack H; Camarata, Stephen M et al. (2018) The Relationship Between Spectral Modulation Detection and Speech Recognition: Adult Versus Pediatric Cochlear Implant Recipients. Trends Hear 22:2331216518771176
Zhang, Dongqing; Zhao, Yiyuan; Noble, Jack H et al. (2018) Selecting electrode configurations for image-guided cochlear implant programming using template matching. J Med Imaging (Bellingham) 5:021202
Koka, Kanthaiah; Riggs, William Jason; Dwyer, Robert et al. (2018) Intra-Cochlear Electrocochleography During Cochear Implant Electrode Insertion Is Predictive of Final Scalar Location. Otol Neurotol 39:e654-e659
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O'Connell, Brendan P; Hunter, Jacob B; Haynes, David S et al. (2017) Insertion depth impacts speech perception and hearing preservation for lateral wall electrodes. Laryngoscope 127:2352-2357
Wang, Jianing; Dawant, Benoit M; Labadie, Robert F et al. (2017) Retrospective Evaluation of a Technique for Patient-Customized Placement of Precurved Cochlear Implant Electrode Arrays. Otolaryngol Head Neck Surg 157:107-112
Chakravorti, Srijata; Bussey, Brian J; Zhao, Yiyuan et al. (2017) Cochlear implant phantom for evaluating computed tomography acquisition parameters. J Med Imaging (Bellingham) 4:045002
Zuniga, M Geraldine; Rivas, Alejandro; Hedley-Williams, Andrea et al. (2017) Tip Fold-over in Cochlear Implantation: Case Series. Otol Neurotol 38:199-206
Rivas, Alejandro; Cakir, Ahmet; Hunter, Jacob B et al. (2017) Automatic Cochlear Duct Length Estimation for Selection of Cochlear Implant Electrode Arrays. Otol Neurotol 38:339-346
Zhang, Dongqing; Liu, Yuan; Noble, Jack H et al. (2017) Localizing landmark sets in head CTs using random forests and a heuristic search algorithm for registration initialization. J Med Imaging (Bellingham) 4:044007

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