Intracochlear Electrocochleography and Speech Perception Scores in Cochlear Implant Recipients

Predicting Postoperative Speech Perception and Audiometric Thresholds Using Intracochlear Electrocochleography in Cochlear Implant Recipients

OBJECTIVES

Electrocochleography (ECochG) appears to offer the most accurate prediction of post-cochlear implant hearing outcomes. This may be related to its capacity to interrogate the health of underlying cochlear tissue. The four major components of ECochG (cochlear microphonic [CM], summating potential [SP], compound action potential [CAP], and auditory nerve neurophonic [ANN]) are generated by different cochlear tissue components. Analyzing characteristics of these components can reveal the state of hair and neural cell in a cochlea. There is limited evidence on the characteristics of intracochlear (IC) ECochG recordings measured across the array postinsertion but compared with extracochlear recordings has better signal to noise ratio and spatial specificity. The present study aimed to examine the relationship between ECochG components recorded from an IC approach and postoperative speech perception or audiometric thresholds.

DESIGN

In 113 human subjects, responses to 500 Hz tone bursts were recorded at 11 IC electrodes across a 22-electrode cochlear implant array immediately following insertion. Responses to condensation and rarefaction stimuli were then subtracted from one another to emphasize the CM and added to one another to emphasize the SP, ANN, and CAP. Maximum amplitudes and extracochlear electrode locations were recorded for each of these ECochG components. These were added stepwise to a multi-factor generalized additive model to develop a best-fit model predictive model for pure-tone audiometric thresholds (PTA) and speech perception scores (speech recognition threshold [SRT] and consonant-vowel-consonant phoneme [CVC-P]) at 3- and 12-month postoperative timepoints. This best-fit model was tested against a generalized additive model using clinical factors alone (preoperative score, age, and gender) as a null model proxy.

RESULTS

ECochG-factor models were superior to clinical factor models in predicting postoperative PTA, CVC-P, and SRT outcomes at both timepoints. Clinical factor models explained a moderate amount of PTA variance ( r2 = 45.9% at 3-month, 31.8% at 12-month, both p < 0.001) and smaller variances of CVC-P and SRT ( r2 range = 6 to 13.7%, p = 0.008 to 0.113). Age was not a significant predictive factor. ECochG models explained more variance at the 12-month timepoint ( r2 for PTA = 52.9%, CVC-P = 39.6%, SRT = 36.4%) compared with the 3-month one timepoint ( r2 for PTA = 49.4%, CVC-P = 26.5%, SRT = 22.3%). The ECochG model was based on three factors: maximum SP deflection amplitude, and electrode position of CM and SP peaks. Adding neural (ANN and/or CAP) factors to the model did not improve variance explanation. Large negative SP deflection was associated with poorer outcomes and a large positive SP deflection with better postoperative outcomes. Mid-array peaks of SP and CM were both associated with poorer outcomes.

CONCLUSIONS

Postinsertion IC-ECochG recordings across the array can explain a moderate amount of postoperative speech perception and audiometric thresholds. Maximum SP deflection and its location across the array appear to have a significant predictive value which may reflect the underlying state of cochlear health.

A Guinea Pig Model Suggests That Objective Assessment of Acoustic Hearing Preservation in Human Ears With Cochlear Implants Is Confounded by Shifts in the Spatial Origin of Acoustically Evoked Potential Measurements Along the Cochlear Length

OBJECTIVES

Our recent empirical findings have shown that the auditory nerve compound action potential (CAP) evoked by a low-level tone burst originates from a narrow cochlear region tuned to the tone burst frequency. At moderate to high sound levels, the origins shift to the most sensitive audiometric regions rather than the extended high-frequency regions of the cochlear base. This means that measurements evoked from extended high-frequency sound stimuli can shift toward the apex with increasing level. Here we translate this study to understand the spatial origin of acoustically evoked responses from ears that receive cochlear implants, an emerging area of research and clinical practice that is not completely understood. An essential step is to first understand the influence of the cochlear implant in otherwise naive ears. Our objective was to understand how function of the high-frequency cochlear base, which can be excited by the intense low-frequency sounds that are frequently used for objective intra- and postoperative monitoring, can be influenced by the presence of the cochlear implant.

DESIGN

We acoustically evoked responses and made measurements with an electrode placed near the guinea pig round window. The cochlear implant was not utilized for either electrical stimulation or recording purposes. With the cochlear implant in situ, CAPs were acoustically evoked from 2 to 16 kHz tone bursts of various levels while utilizing the slow perfusion of a kainic acid solution from the cochlear apex to the cochlear aqueduct in the base, which sequentially reduced neural responses from finely spaced cochlear frequency regions. This cochlear perfusion technique reveals the spatial origin of evoked potential measurements and provides insight on what influence the presence of an implant has on acoustical hearing.

RESULTS

Threshold measurements at 3 to 11 kHz were elevated by implantation. In an individual ear, thresholds were elevated and lowered as cochlear implant was respectively inserted and removed, indicative of "conductive hearing loss" induced by the implant. The maximum threshold elevation occurred at most sensitive region of the naive guinea pig ear (33.66 dB at 8 kHz), making 11 kHz the most sensitive region to acoustic sounds for guinea pig ears with cochlear implants. Conversely, the acute implantation did not affect the low-frequency, 500 Hz thresholds and suprathreshold function, as shown by the auditory nerve overlapped waveform. As the sound pressure level of the tone bursts increased, mean data show that the spatial origin of CAPs along the cochlear length shifted toward the most sensitive cochlear region of implanted ears, not the extended high-frequency cochlear regions. However, data from individual ears showed that after implantation, measurements from moderate to high sound pressure levels originate in places that are unique to each ear.

CONCLUSIONS

Alterations to function of the cochlear base from the in situ cochlear implant may influence objective measurements of implanted ears that are frequently made with intense low-frequency sound stimuli. Our results from guinea pigs advance the interpretation of measurements used to understand how and when residual acoustic hearing is lost in human ears receiving a cochlear implant.

Self-assessment of cochlear health by cochlear implant recipients

Recent technological advances in cochlear implant (CI) telemetry have enabled, for the first time, CI users to perform cochlear health (CH) measurements through self-assessment for prolonged periods of time. This is important to better understand the influence of CH on CI outcomes, and to assess the safety and efficacy of future novel treatments for deafness that will be administered as adjunctive therapies to cochlear implantation. We evaluated the feasibility of using a CI to assess CH and examined patterns of electrode impedances, electrically-evoked compound action potentials (eCAPs) and electrocochleography (ECochGs), over time, in a group of adult CI recipients. Fifteen subjects were trained to use the Active Insertion Monitoring tablet by Advanced Bionics, at home for 12 weeks to independently record impedances twice daily, eCAPs once weekly and ECochGs daily in the first week, and weekly thereafter. Participants also completed behavioral hearing and speech assessments. Group level measurement compliance was 98.9% for impedances, 100% for eCAPs and 99.6% for ECochGs. Electrode impedances remained stable over time, with only minimal variation observed. Morning impedances were significantly higher than evening measurements, and impedances increased toward the base of the cochlea. eCAP thresholds were also highly repeatable, with all subjects showing 100% measurement consistency at, at least one electrode. Just over half of all subjects showed consistently absent thresholds at one or more electrodes, potentially suggesting the existence of cochlear dead regions. All subjects met UK NICE guidelines for cochlear implantation, so were expected to have little residual hearing. ECochG thresholds were, unsurprisingly, highly erratic and did not correlate with audiometric thresholds, though lower ECochG thresholds showed more repeatability over time than higher thresholds. We conclude that it is feasible for CI users to independently record CH measurements using their CI, and electrode impedances and eCAPs are promising measurements for objectively assessing CH.

Electrocochleography and cognition are important predictors of speech perception outcomes in noise for cochlear implant recipients

Although significant progress has been made in understanding outcomes following cochlear implantation, predicting performance remains a challenge. Duration of hearing loss, age at implantation, and electrode positioning within the cochlea together explain ~ 25% of the variability in speech-perception scores in quiet using the cochlear implant (CI). Electrocochleography (ECochG) responses, prior to implantation, account for 47% of the variance in the same speech-perception measures. No study to date has explored CI performance in noise, a more realistic measure of natural listening. This study aimed to (1) validate ECochG total response (ECochG-TR) as a predictor of performance in quiet and (2) evaluate whether ECochG-TR explained variability in noise performance. Thirty-five adult CI recipients were enrolled with outcomes assessed at 3-months post-implantation. The results confirm previous studies showing a strong correlation of ECochG-TR with speech-perception in quiet (r = 0.77). ECochG-TR independently explained 34% of the variability in noise performance. Multivariate modeling using ECochG-TR and Montreal Cognitive Assessment (MoCA) scores explained 60% of the variability in speech-perception in noise. Thus, ECochG-TR, a measure of the cochlear substrate prior to implantation, is necessary but not sufficient for explaining performance in noise. Rather, a cognitive measure is also needed to improve prediction of noise performance.