Electrical vestibular stimulation in humans: a narrative review

Background: In patients with bilateral vestibulopathy, the regular treatment options, such as medication, surgery, and/ or vestibular rehabilitation, do not always suffice. Therefore, the focus in this field of vestibular research shifted to electrical vestibular stimulation (EVS) and the development of a system capable of artificially restoring the vestibular function. Key Message: Currently, three approaches are being investigated: vestibular co-stimulation with a cochlear implant (CI), EVS with a vestibular implant (VI), and galvanic vestibular stimulation (GVS). All three applications show promising results but due to conceptual differences and the experimental state, a consensus on which application is the most ideal for which type of patient is still missing. Summary: Vestibular co-stimulation with a CI is based on “spread of excitation,” which is a phenomenon that occurs when the currents from the CI spread to the surrounding structures and stimulate them. It has been shown that CI activation can indeed result in stimulation of the vestibular structures. Therefore, the question was raised whether vestibular costimulation can be functionally used in patients with bilateral vestibulopathy. A more direct vestibular stimulation method can be accomplished by implantation and activation of a VI. The concept of the VI is based on the technology and principles of the CI. Different VI prototypes are currently being evaluated regarding feasibility and functionality. So far, all of them were capable of activating different types of vestibular reflexes. A third stimulation method is GVS, which requires the use of surface electrodes instead of an implanted electrode array. However, as the currents are sent through the skull from one mastoid to the other, GVS is rather unspecific. It should be mentioned though, that the reported spread of excitation in both CI and VI use also seems to induce a more unspecific stimulation. Although all three applications of EVS were shown to be effective, it has yet to be defined which option is more desirable based on applicability and efficiency. It is possible and even likely that there is a place for all three approaches, given the diversity of the patient population who serves to gain from such technologies

Magnetic resonance imaging in patients with meningitis induced hearing loss

The aim of this multicentre study was to compare T1 with T2 weighted MRI scans of the labyrinth after meningitis and to investigate whether waiting with scanning improved the reliability of diagnosing an ongoing process such as cochlear osteogenesis. Forty-five patients were included who suffered from meningitis induced hearing loss (radiological imaging <1 year after meningitis). Twenty-one gadolinium enhanced T1 and 45 T2 weighted MRI scans were scored by two radiologists regarding the condition of the labyrinth. These radiological observations were compared with the condition of the cochlea as described during cochlear implantation. A higher percentage of agreement with surgery was found for T2 (both radiologists 73%) than for T1 weighted MRI scans (radiologist 1: 62%, radiologist 2: 67%), but this difference is not significant. There was no significant difference between early (0–3 months) and late (>3 months) scanning, showing that radiological imaging soon after meningitis allows early diagnosis without suffering from a lower agreement with surgical findings

Real-world clinical experience with Idebenone in the treatment of Leber hereditary optic neuropathy

Background: Leber hereditary optic neuropathy (LHON) leads to bilateral central vision loss. In a clinical trial setting, idebenone has been shown to be safe and to provide a trend toward improved visual acuity, but long-term evidence of effectiveness in real-world clinical practice is sparse. Methods: Open-label, multicenter, retrospective, noncontrolled analysis of long-term visual acuity and safety in 111 LHON patients treated with idebenone (900 mg/day) in an expanded access program. Eligible patients had a confirmed mitochondrial DNA mutation and had experienced the onset of symptoms (most recent eye) within 1 year before enrollment. Data on visual acuity and adverse events were collected as per normal clinical practice. Efficacy was assessed as the proportion of patients with either a clinically relevant recovery (CRR) or a clinically relevant stabilization (CRS) of visual acuity. In the case of CRR, time to and magnitude of recovery over the course of time were also assessed. Results: At time of analysis, 87 patients had provided longitudinal efficacy data. Average treatment duration was 25.6 months. CRR was observed in 46.0% of patients. Analysis of treatment effect by duration showed that the proportion of patients with recovery and the magnitude of recovery increased with treatment duration. Average gain in best-corrected visual acuity for responders was 0.72 logarithm of the minimal angle of resolution (logMAR), equivalent to more than 7 lines on the Early Treatment Diabetic Retinopathy Study (ETDRS) chart. Furthermore, 50% of patients who had a visual acuity below 1.0 logMAR in at least one eye at initiation of treatment successfully maintained their vision below this threshold by last observation. Idebenone was well tolerated, with most adverse events classified as minor. Conclusions: These data demonstrate the benefit of idebenone treatment in recovering lost vision and maintaining good residual vision in a real-world setting. Together, these findings indicate that idebenone treatment should be initiated early and be maintained more than 24 months to maximize efficacy. Safety results were consistent with the known safety profile of idebenone

Speech enhancement based on neural networks improves speech intelligibility in noise for cochlear implant users

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