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Audiology Research
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Innovations in Cochlear Implant Surgery
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Innovations in Cochlear Implant Surgery

A special issue of Audiology Research (ISSN 2039-4349).

Deadline for manuscript submissions: 30 June 2025 | Viewed by 1871

Special Issue Editors

Prof. Dr. Adrien Eshraghi

E-Mail Website
Guest Editor
Department of Otolaryngology, Neurological Surgery Pediatrics and Biomedical Engineering, University of Miami Leonard M. Miller School of Medicine, Miami, FL, USA
Interests: cochlear implant; hearing preservation; otoprotection; inner ear therapy; stapedectomy
Special Issues, Collections and Topics in MDPI journals
Dr. Emre Ocak

E-Mail Website
Guest Editor
Department of Otolaryngology, Ankara University School of Medicine, Ankara, Turkey
Interests: cochlear implant; auditory brainstem implant; endoscopic ear surgery; lateral skull base surgery; stapes surgery; inner ear drug delivery

Special Issue Information

Dear Colleagues,

Cochlear implants represent a transformative innovation in the field of auditory prosthetics, offering profound benefits to individuals with severe-to-profound hearing loss. This Special Issue explores recent advancements in cochlear implant surgery, focusing on innovations aimed at enhancing auditory performance and improving user experience. Key developments include electrode array designs optimizing neural stimulation, hearing preservation techniques, drug-eluding electrodes, intraoperative electrophysiological monitoring during implant surgery, and minimal invasive surgery. Moreover, innovations in surgical techniques and rehabilitation strategies have contributed to improved outcomes and expanded access to cochlear implants worldwide. This Special Issue highlights how ongoing research and technological advancements continue to redefine the capabilities and outcomes of cochlear implants, promising a future of even greater inclusivity and efficacy for individuals with hearing impairment.

Prof. Dr. Adrien Eshraghi
Dr. Emre Ocak
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Audiology Research is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cochlear implant
  • innovation
  • robotic cochlear implant
  • hearing preservation
  • electrode design
  • cochlear implant candidacy

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

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8 pages, 1647 KiB  
Article
Intraoperative Assessment of Cochlear Nerve Function During Cochlear Implantation Using the Auditory Nerve Test Stimulator
by Karin Hallin and Nadine Schart-Morén
Audiol. Res. 2025, 15(2), 36; https://doi.org/10.3390/audiolres15020036 - 1 Apr 2025
Viewed by 297
Abstract
Background/Objectives: A crucial factor for a successful cochlear implant (CI) outcome is an intact auditory nerve (AN). The integrity of the AN can be tested during implantation by measuring electrical auditory brainstem responses (eABR) via the CI. A method that does not require [...] Read more.
Background/Objectives: A crucial factor for a successful cochlear implant (CI) outcome is an intact auditory nerve (AN). The integrity of the AN can be tested during implantation by measuring electrical auditory brainstem responses (eABR) via the CI. A method that does not require a CI is the use of the auditory nerve test stimulator (ANTS) from MED-EL (Innsbruck, Austria). The aim of the current study was to investigate the cases tested with the ANTS at our clinic and to describe the hearing results following CI for the cases who were implanted with a CI. Methods: All patients underwent preoperative magnetic resonance imaging (MRI) and high-resolution computed tomography (HRCT) to rule out cochlear malformation or retrocochlear pathology. In this study, we described all cases from when we began using the ANTS in 2011. Results: Five patients were tested intraoperatively: three adults with long-term deafness prior to CI and two children with no detectable AN. Three of the five patients were implanted with a CI. All implanted patients in this study could hear with their CIs, even though the speech perception results were limited. Conclusions: The ANTS can be used as a method to assess cochlear nerve function during implantation. The eABR results from the ANTS and the implanted CI were comparable for all cases in our study. Minor changes in waveform latencies were found between ANTS and CI stimulation and may be explained by the insertion depth of the electrode used for stimulation. Full article
(This article belongs to the Special Issue Innovations in Cochlear Implant Surgery)
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11 pages, 1559 KiB  
Article
A Novel Trans-Impedance Matrix (TIM) Abnormality Pattern in Cochlear Implants
by Erica Pizzol, Sara Ghiselli, Patrizia Frontera, Daria Salsi and Domenico Cuda
Audiol. Res. 2025, 15(2), 24; https://doi.org/10.3390/audiolres15020024 - 2 Mar 2025
Viewed by 648
Abstract
In our clinical setting, we have identified a novel pattern of Trans-Impedance Matrix (TIM) measurement that we call “scatter”, a measure characterised by a loss of definition in the heat and line maps. Objective: the aim of this study was to describe the [...] Read more.
In our clinical setting, we have identified a novel pattern of Trans-Impedance Matrix (TIM) measurement that we call “scatter”, a measure characterised by a loss of definition in the heat and line maps. Objective: the aim of this study was to describe the basic characteristics of the anomaly pattern. The secondary purpose is to evaluate correlations between the “scatter” pattern and normal TIM by considering different parameters. Methods: the experimental sample, therefore, consisted of 565 patients (81.1% of people with a checked TIM at follow-up; M: 279, F: 286 and mean age: 27 years (sd 26). The scatter pattern was found in 55 devices (9.7%). We classified this pattern as severe (20 devices) or mild (35 devices) according to the visual extent of the abnormality. We considered the visual extension of the pattern, device lifetime, type of internal part of the CI, and auditory performance (speech audiometry in quiet at 65 dB and in noise—Ita Matrix Sentence Test). We also analysed two quantitive parameters: Shannon entropy and exponential decay. Results: a difference was found in these two quantitative parameters between the severe scatter, mild scatter, and normal TIM groups (p-value < 0.0001). The severe scatter group seems to be related to the type of device (CI24RE and CI512) and long device life (average 133 months); it did not show differences in audiology performances compared to the other groups. Conclusions: this result gives a numerical validation to the more subjective visual inspection approach. The scatter pattern is a novel, previously undescribed abnormality of TIM. It can vary from moderate to severe. A numerical basis to validate the inspection approach is described here. Full article
(This article belongs to the Special Issue Innovations in Cochlear Implant Surgery)
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Review

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29 pages, 851 KiB  
Review
Prediction of Auditory Performance in Cochlear Implants Using Machine Learning Methods: A Systematic Review
by Beyza Demirtaş Yılmaz
Audiol. Res. 2025, 15(3), 56; https://doi.org/10.3390/audiolres15030056 - 8 May 2025
Viewed by 313
Abstract
Background/Objectives: Cochlear implantation is an advantageous procedure for individuals with severe to profound hearing loss in many aspects related to auditory performance, social communication and quality of life. As machine learning applications have been used in the field of Otorhinolaryngology and Audiology in [...] Read more.
Background/Objectives: Cochlear implantation is an advantageous procedure for individuals with severe to profound hearing loss in many aspects related to auditory performance, social communication and quality of life. As machine learning applications have been used in the field of Otorhinolaryngology and Audiology in recent years, signal processing, speech perception and personalised optimisation of cochlear implantation are discussed. Methods: A comprehensive literature review was conducted in accordance with the PRISMA guidelines. PubMed, Scopus, Web of Science, Google Scholar and IEEE databases were searched for studies published between 2010 and 2025. We analyzed 59 articles that met the inclusion criteria. Rayyan AI software was used to classify the studies so that the risk of bias was reduced. Study design, machine learning algorithms, and audiological measurements were evaluated in the data analysis. Results: Machine learning applications were classified as preoperative evaluation, speech perception, and speech understanding in noise and other studies. The success rates of the articles are presented together with the number of articles changing over the years. It was observed that Random Forest, Decision Trees (96%), Bayesian Linear Regression (96.2%) and Extreme machine learning (99%) algorithms reached high accuracy rates. Conclusions: In cochlear implantation applications in the field of audiology, it has been observed that studies have been carried out with a variable number of people and data sets in different subfields. In machine learning applications, it is seen that a high amount of data, data diversity and long training times contribute to achieving high performance. However, more research is needed on deep learning applications in complex problems such as comprehension in noise that require time series processing. Funding and other resources: This study was not funded by any institution or organization. No registration was performed for this study. Full article
(This article belongs to the Special Issue Innovations in Cochlear Implant Surgery)
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