PurposeThere is still a clinical-radiologic discrepancy in patients with Menière’s disease (MD). Therefore, the purpose of this study was to investigate the reliability of current MRI endolymphatic hydrops (EH) criteria according to Baráth in a larger study population and the clinical utility of new imaging signs such as a supplementary fourth low-grade vestibular EH and the degree of perilymphatic enhancement (PE) in patients with Menière’s disease (MD).MethodsThis retrospective study included 148 patients with probable or definite MD according to the 2015 American Academy of Otolaryngology, Head and Neck Surgery criteria who underwent a 4-h delayed intravenous Gd-enhanced 3D-FLAIR MRI between January 2015 and December 2016. Vestibular EH, vestibular PE, cochlear EH, and cochlear PE were reviewed twice by three experienced readers. Cohen’s Kappa and multivariate logistic regression were used for analysis.ResultsThe intra- and inter-reader reliability for the grading of vestibular-cochlear EH and PE was excellent (0.7 < kappa < 0.9). The two most distinctive characteristics to identify MD are cochlear PE and vestibular EH which combined gave a sensitivity and specificity of 79.5 and 93.6%. By addition of a lower grade vestibular EH, the sensitivity improved to 84.6% without losing specificity (92.3%). Cochlear EH nor vestibular PE showed added-value.ConclusionsMRI using vestibular-cochlear EH and PE grading system is a reliable technique. A four-stage vestibular EH grading system in combination with cochlear PE assessment gives the best diagnostic accuracy to detect MD.

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Speech understanding in noisy environments is still one of the major challenges for cochlear implant (CI) users in everyday life. We evaluated a speech enhancement algorithm based on neural networks (NNSE) for improving speech intelligibility in noise for CI users. The algorithm decomposes the noisy speech signal into time-frequency units, extracts a set of auditory-inspired features and feeds them to the neural network to produce an estimation of which frequency channels contain more perceptually important information (higher signal-to-noise ratio, SNR). This estimate is used to attenuate noise-dominated and retain speech-dominated CI channels for electrical stimulation, as in traditional n-of-m CI coding strategies. The proposed algorithm was evaluated by measuring the speech-in-noise performance of 14 CI users using three types of background noise. Two NNSE algorithms were compared: a speaker-dependent algorithm, that was trained on the target speaker used for testing, and a speaker-independent algorithm, that was trained on different speakers. Significant improvements in the intelligibility of speech in stationary and fluctuating noises were found relative to the unprocessed condition for the speaker-dependent algorithm in all noise types and for the speaker-independent algorithm in 2 out of 3 noise types. The NNSE algorithms used noise-specific neural networks that generalized to novel segments of the same noise type and worked over a range of SNRs. The proposed algorithm has the potential to improve the intelligibility of speech in noise for CI users while meeting the requirements of low computational complexity and processing delay for application in CI devices.

Those suffering from a severe to profound sensorineural hearing loss can obtain substantial benefit from a cochlear implant prosthesis. An electrode array implanted in the inner ear stimulates auditory nerve fibers by direct injection of electrical current. A major limitation of today's technology is the imprecise control of intracochlear current flow, particularly the relatively wide spread of neural excitation. A better understanding of the intracochlear electrical fields is, therefore, required. This paper analyzes the structure of intracochlear potential measurements in relation to both the subject's anatomy and to the properties of the electrode array. An electrically equivalent network is proposed, composed of small lumped circuits for the interface impedance and for the cochlear tissues. The numerical methods required to estimate the model parameters from high-quality electrical potential recordings are developed. Finally, some models are presented for subjects wearing a Clarion CII device with a HiFocus electrode and discussed in terms of model reliability.

1) Significant differences in the audiometric thresholds and the speech understanding scores were found between the preoperative test conditions and the final postoperative result. 2) Audiometric results obtained with the headband and the testband are comparable; therefore, the more comfortable headband is also suitable for the preoperative audiologic evaluation. 3) The magnitude of the skin damping must be accounted for when referring to the audiometric results obtained with the BAHA attached to the testband or headband.