Increasing the reliability of real-time electrocochleography during cochlear implantation: a standardized guideline

ZH-ECochG Bode Plot: A Novel Approach to Visualize Electrocochleographic Data in Cochlear Implant Users

Background: Various representations exist in the literature to visualize electrocochleography (ECochG) recordings along the basilar membrane (BM). This lack of generalization complicates comparisons within and between cochlear implant (CI) users, as well as between publications. This study synthesized the visual representations available in the literature via a systematic review and provides a novel approach to visualize ECochG data in CI users. Methods: A systematic review was conducted within PubMed and EMBASE to evaluate studies investigating ECochG and CI. Figures that visualized ECochG responses were selected and analyzed. A novel visualization of individual ECochG data, the ZH-ECochG Bode plot (ZH = Zurich), was devised, and the recordings from three CI recipients were used to demonstrate and assess the new framework. Results: Within the database search, 74 articles with a total of 115 figures met the inclusion criteria. Analysis revealed various types of representations using different axes; their advantages were incorporated into the novel visualization framework. The ZH-ECochG Bode plot visualizes the amplitude and phase of the ECochG recordings along the different tonotopic regions and angular insertion depths of the recording sites. The graph includes the pre- and postoperative audiograms to enable a comparison of ECochG responses with the audiometric profile, and allows different measurements to be shown in the same graph. Conclusions: The ZH-ECochG Bode plot provides a generalized visual representation of ECochG data, using well-defined axes. This will facilitate the investigation of the complex ECochG potentials generated along the BM and allows for better comparisons of ECochG recordings within and among CI users and publications. The scripts used to construct the ZH-ECochG Bode plot are provided by the authors.

[Application of extra- and intracochlear electrocochleography during and after cochlear implantation]

Electrocochleography (ECochG) represents a promising approach for monitoring cochlear function during cochlear implantation and for investigating the causes of residual cochlear function loss after implantation. This paper provides an overview of the current research and application status of ECochG, both during and after cochlear implantation. Intraoperative ECochG can be conducted either via the implant itself or an extracochlear measuring electrode. Postoperative ECochG recordings are also feasible via the implant. Various studies have demonstrated that a significant decrease in ECochG amplitude during electrode insertion correlates with an increased risk of losing residual cochlear function, with critical cochlear events occurring primarily towards the end of the insertion. Postoperative data suggest that the loss of cochlear function mainly occurs in the early postoperative phase. Future research directions include the automation and objectification of signal analysis, as well as a more in-depth investigation into the underlying mechanisms of these signal changes.

Evaluation of an impedance-based method to monitor the insertion of the electrode array during cochlear implantation

PURPOSE

Cochlear implantation is a prevalent remedy for severe-to-profound hearing loss. Optimising outcomes and hearing preservation, and minimising insertion trauma, require precise electrode placement. Objective monitoring during the insertion process can provide valuable insights and enhance surgical precision. This study assesses the feasibility and performance of an impedance-based method for monitoring electrode insertion, compared to the surgeon's feedback.

METHODS

The study utilised the Insertion Monitoring Tool (IMT) research software, allowing for real-time measurement of impedance and evoked compound action potential (eCAP) during electrode insertion in 20 patient implantations. This enabled an impedance-based method to continuously assess the status of each electrode during the insertion process. The feasibility and performance was evaluated and compared to the surgeon's feedback approach. eCAP measurements focused merely on feasibility without searching specific responses.

RESULTS

The IMT demonstrated feasibility in measuring real-time impedances and eCAP during the insertion of the electrode array. The impedance-based method exhibited potential for accurately monitoring the insertion depth with a high success rate. However, further development is needed to improve the number of usable contacts.

CONCLUSIONS

Objective monitoring with the impedance-based method shows promise as a valuable tool to enhance the precision of cochlear implant electrode insertion respecting insertion distance estimation. The IMT research software proved feasible in recording real-time impedances and eCAP during electrode insertion. While this impedance-based method exhibits high success rates, further improvements are required to optimise the number of usable contacts. This study highlights the potential of objective monitoring techniques to enhance cochlear implantation outcomes.

Uncovering Vulnerable Phases in Cochlear Implant Electrode Array Insertion: Insights from an In Vitro Model

OBJECTIVES

The aim of this study is to improve our understanding of the mechanics involved in the insertion of lateral wall cochlear implant electrode arrays.

DESIGN

A series of 30 insertion experiments were conducted by three experienced surgeons. The experiments were carried out in a previously validated artificial temporal bone model according to established soft surgery guidelines. The use of an in vitro setup enabled us to comprehensively evaluate relevant parameters, such as insertion force, intracochlear pressure, and exact electrode array position in a controlled and repeatable environment.

RESULTS

Our findings reveal that strong intracochlear pressure transients are more frequently caused during the second half of the insertion, and that regrasping the electrode array is a significant factor in this phenomenon. For choosing an optimal insertion speed, we show that it is crucial to balance slow movement to limit intracochlear stress with short duration to limit tremor-induced pressure spikes, challenging the common assumption that a slower insertion is inherently better. Furthermore, we found that intracochlear stress is affected by the order of execution of postinsertion steps, namely sealing the round window and posterior tympanotomy with autologous tissue and routing of the excess cable into the mastoid cavity. Finally, surgeons' subjective estimates of physical parameters such as speed, smoothness, and resistance did not correlate with objectively assessed measures, highlighting that a thorough understanding of intracochlear mechanics is essential for an atraumatic implantation.

CONCLUSION

The results presented in this article allow us to formulate evidence-based surgical recommendations that may ultimately help to improve surgical outcome and hearing preservation in cochlear implant patients.

Real-Time Feature Extraction From Electrocochleography With Impedance Measurements During Cochlear Implantation Using Linear State-Space Models

Electrocochleography (ECochG) is increasingly used to monitor the inner ear function of cochlear implant (CI) patients during surgery. Current ECochG-based trauma detection shows low sensitivity and specificity and depends on visual analysis by experts. Trauma detection could be improved by including electric impedance data recorded simultaneously with the ECochG. However, combined recordings are rarely used because the impedance measurements produce artifacts in the ECochG. In this study, we propose a framework for automated real-time analysis of intraoperative ECochG signals using Autonomous Linear State-Space Models (ALSSMs). We developed ALSSM based algorithms for noise reduction, artifact removal, and feature extraction in ECochG. Feature extraction includes local amplitude and phase estimations and a confidence metric over the presence of a physiological response in a recording. We tested the algorithms in a controlled sensitivity analysis using simulations and validated them with real patient data recorded during surgeries. The results from simulation data show that the ALSSM method provides improved accuracy in the amplitude estimation together with a more robust confidence metric of ECochG signals compared to the state-of-the-art methods based on the fast Fourier transform (FFT). Tests with patient data showed promising clinical applicability and consistency with the findings from the simulations. We showed that ALSSMs are a valid tool for real-time analysis of ECochG recordings. Removal of artifacts using ALSSMs enables simultaneous recording of ECochG and impedance data. The proposed feature extraction method provides the means to automate the assessment of ECochG. Further validation of the algorithms in clinical data is needed.

Objective evaluation of intracochlear electrocochleography: repeatability, thresholds, and tonotopic patterns

Introduction

Intracochlear electrocochleography (ECochG) is increasingly being used to measure residual inner ear function in cochlear implant (CI) recipients. ECochG signals reflect the state of the inner ear and can be measured during implantation and post-operatively. The aim of our study was to apply an objective deep learning (DL)-based algorithm to assess the reproducibility of longitudinally recorded ECochG signals, compare them with audiometric hearing thresholds, and identify signal patterns and tonotopic behavior.

Methods

We used a previously published objective DL-based algorithm to evaluate post-operative intracochlear ECochG signals collected from 21 ears. The same measurement protocol was repeated three times over 3 months. Additionally, we measured the pure-tone thresholds and subjective loudness estimates for correlation with the objectively detected ECochG signals. Recordings were made on at least four electrodes at three intensity levels. We extracted the electrode positions from computed tomography (CT) scans and used this information to evaluate the tonotopic characteristics of the ECochG responses.

Results

The objectively detected ECochG signals exhibited substantial repeatability over a 3-month period (bias-adjusted kappa, 0.68; accuracy 83.8%). Additionally, we observed a moderate-to-strong dependence of the ECochG thresholds on audiometric and subjective hearing levels. Using radiographically determined tonotopic measurement positions, we observed a tendency for tonotopic allocation with a large variance. Furthermore, maximum ECochG amplitudes exhibited a substantial basal shift. Regarding maximal amplitude patterns, most subjects exhibited a flat pattern with amplitudes evenly distributed over the electrode carrier. At higher stimulation frequencies, we observed a shift in the maximum amplitudes toward the basal turn of the cochlea.

Conclusions

We successfully implemented an objective DL-based algorithm for evaluating post-operative intracochlear ECochG recordings. We can only evaluate and compare ECochG recordings systematically and independently from experts with an objective analysis. Our results help to identify signal patterns and create a better understanding of the inner ear function with the electrode in place. In the next step, the algorithm can be applied to intra-operative measurements.

An intracochlear electrocochleography dataset - from raw data to objective analysis using deep learning

Electrocochleography (ECochG) measures electrophysiological inner ear potentials in response to acoustic stimulation. These potentials reflect the state of the inner ear and provide important information about its residual function. For cochlear implant (CI) recipients, we can measure ECochG signals directly within the cochlea using the implant electrode. We are able to perform these recordings during and at any point after implantation. However, the analysis and interpretation of ECochG signals are not trivial. To assist the scientific community, we provide our intracochlear ECochG data set, which consists of 4,924 signals recorded from 46 ears with a cochlear implant. We collected data either immediately after electrode insertion or postoperatively in subjects with residual acoustic hearing. This data descriptor aims to provide the research community access to our comprehensive electrophysiological data set and algorithms. It includes all steps from raw data acquisition to signal processing and objective analysis using Deep Learning. In addition, we collected subject demographic data, hearing thresholds, subjective loudness levels, impedance telemetry, radiographic findings, and classification of ECochG signals.

Objectification of intracochlear electrocochleography using machine learning

Introduction

Electrocochleography (ECochG) measures inner ear potentials in response to acoustic stimulation. In patients with cochlear implant (CI), the technique is increasingly used to monitor residual inner ear function. So far, when analyzing ECochG potentials, the visual assessment has been the gold standard. However, visual assessment requires a high level of experience to interpret the signals. Furthermore, expert-dependent assessment leads to inconsistency and a lack of reproducibility. The aim of this study was to automate and objectify the analysis of cochlear microphonic (CM) signals in ECochG recordings.

Methods

Prospective cohort study including 41 implanted ears with residual hearing. We measured ECochG potentials at four different electrodes and only at stable electrode positions (after full insertion or postoperatively). When stimulating acoustically, depending on the individual residual hearing, we used three different intensity levels of pure tones (i.e., supra-, near-, and sub-threshold stimulation; 250–2,000 Hz). Our aim was to obtain ECochG potentials with differing SNRs. To objectify the detection of CM signals, we compared three different methods: correlation analysis, Hotelling's T² test, and deep learning. We benchmarked these methods against the visual analysis of three ECochG experts.

Results

For the visual analysis of ECochG recordings, the Fleiss' kappa value demonstrated a substantial to almost perfect agreement among the three examiners. We used the labels as ground truth to train our objectification methods. Thereby, the deep learning algorithm performed best (area under curve = 0.97, accuracy = 0.92), closely followed by Hotelling's T² test. The correlation method slightly underperformed due to its susceptibility to noise interference.

Conclusions

Objectification of ECochG signals is possible with the presented methods. Deep learning and Hotelling's T² methods achieved excellent discrimination performance. Objective automatic analysis of CM signals enables standardized, fast, accurate, and examiner-independent evaluation of ECochG measurements.

Cochlear Implant Electrode Impedance as Potential Biomarker for Residual Hearing

Introduction and Objectives

Among cochlear implant candidates, an increasing number of patients are presenting with residual acoustic hearing. To monitor the postoperative course of structural and functional preservation of the cochlea, a reliable objective biomarker would be desirable. Recently, impedance telemetry has gained increasing attention in this field. The aim of this study was to investigate the postoperative course of the residual acoustic hearing and clinical impedance in patients with long electrode arrays and to explore the applicability of impedance telemetry for monitoring residual hearing.

Methods

We retrospectively analyzed records of 42 cochlear implant recipients with residual hearing covering a median postoperative follow-up of 25 months with repeated simultaneous pure tone audiometry and impedance telemetry. We used a linear mixed-effects model to estimate the relation between clinical electrode impedance and residual hearing. Besides the clinical impedance, the follow-up time, side of implantation, gender, and age at implantation were included as fixed effects. An interaction term between impedance and follow-up time, as well as subject-level random intercepts and slopes, were included.

Results

Loss of residual hearing occurred either during surgery or within the first 6 post-operative months. Electrode contacts inserted further apically (i.e., deeper) had higher impedances, independent of residual hearing. The highest impedances were measured 1 month postoperatively and gradually decreased over time. Basal electrodes were more likely to maintain higher impedance. Follow-up time was significantly associated with residual hearing. Regardless of the time, we found that a 1 kΩ increase in clinical impedance was associated with a 4.4 dB deterioration of residual hearing (p < 0.001).

Conclusion

Pure tone audiometry is the current gold standard for monitoring postoperative residual hearing. However, the association of clinical impedances with residual hearing thresholds found in our study could potentially be exploited for objective monitoring using impedance telemetry. Further analysis including near-field related impedance components could be performed for improved specificity to local immune responses.