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Effects of Stimulus Repetition Rate on Electrically Evoked Auditory Brainstem Potentials in Postlingually Deafened Adult Cochlear Implant Recipients

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18 October 2023

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19 October 2023

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Abstract
Background: By using outcome prediction scores, it is possible to distinguish between good and poor performers with cochlear implants (CI) after CI implantation. The reasons for poor performance, despite good basic conditions, can be manifold. On the one hand, the postoperative fitting may be inadequate; on the other, neurophysiological disease processes may impair speech understanding with a CI. These disease processes are not yet fully understood. In acoustics, it is known that the auditory brainstem responses (ABR) and their latencies and amplitudes allow differential diagnosis based on reference values for normal-hearing individuals. The aim of this study was to provide reference values for electrically evoked brainstem responses (EABRs) in terms of rate-dependent latencies and amplitudes. Methods: 20 experienced adult CI recipients with a predicted and measured good postoperative word recognition score were recruited from the clinic’s patient pool. In the same stimulation mode and intensity we measured latencies and interpeak-latencies of EABRs and electrically evoked compound action potentials (ECAPs). With a defined supra-threshold stimulation intensity above the individual ECAP threshold, we applied stimulation at several rates between 11 and 91 stimuli per second. Results: We found rate dependences for EABR latency t3 and t5 in the order of 0.19 ms and 0.37 ms respectively, while ECAP was not affected by rate. Correspondingly, the interpeak intervalls’ rate dependences for t5-t1, t5-t3 and t3-t1 were of the order of 0.37 ms, 0.18 ms and 0.19 ms. Comparing the EABR amplitudes between the stimulation rates 11/s and 81/s, we found that at 81/s the amplitudes were significantly reduced down: to 73% for A3 and 81% for A5. These rate dependences of latency and amplitude in EABR have characteristics comparable to those of acoustic ABR. Conclusions: These data may serve to provide reference values for EABR and ECAP latencies, interpeak intervals and amplitudes with respect to stimulation rate. Altered response patterns of ECAPs and EABRs to normalised stimulation modes could be used in the future to describe and classify neuropathological processes in a better-differentiated way.
Keywords: 
Subject: Medicine and Pharmacology  -   Otolaryngology

1. Introduction

Cochlear implantation is an established therapy for sensorineural hearing loss if hearing aids and other solutions fail to restore speech recognition [1,2]. Recent studies reported on successful CI provision for patients with hearing losses from 50 to 80 dB [3,4,5,6]. However, even in these patients, with good preconditions for postoperative word recognition – and even more in the established patient population with no preoperative word recognition [6] – some challenges still remain. Recent studies and opinions [3,7,8,9,10] indicate a lack of audiological differential diagnosis in these patients and highlight the observation that “the broad array of factors that contribute to speech recognition performance in adult CI users suggests the potential both for novel diagnostic assessment batteries to explain poor performance, and also new rehabilitation strategies for patients who exhibit poor outcomes” [7].
To our knowledge there is no generally agreed classification of CI recipients with respect to performance or to speech perception in general. A prediction model recently introduced by Hoppe et al. [3] for the expected postoperative word recognition score at conversation level, WRS65(CI), after six months of CI use would allow such a classification. Thus, failure to reach this goal can easily be assessed by routine clinical audiometry [3,6]. “Unexplained poor performance” may be defined as applying to CI recipients whose WRS65(CI) does not meet the predicted score according to this model. Such cases can be observed with an incidence of around five percent in a population with residual preoperative WRS [6] on the basis of a 20-pp difference (WRSGAP) between prediction and measurement in monosyllable test scores. Users who reach the predicted score later than six months after implantation (e.g., twelve months later) would not be covered by this definition [6]. More recently, in a study by Dziemba et al. [11] such a definition was applied in order to identify systematic differences in postoperative fitting of CI systems in a group of well and poorly performing CI recipients, namely, the differences in audibility and the loudness growth function measured by categorical loudness scaling. An additional application of the prediction model [3] could be the interpretation of electrophysiological measurements based on prior classification of groups of recipients in respect of the WRSGAP. Other recent work [8,12,13,14,15] led to the proposal and use of a setting for EABR mimicking the established acoustic broadband click. Reference values for latencies were assessed by including only CI recipients with WRS65CI of 50% or more [13]. This approach led to improved differential diagnosis for CI recipients and improved intraoperative assessment [13,15,16].
Some characteristics of CI recipients, such as rate dependence of electrophysiological measurements, indicate a potential for improvement in differential diagnostics. In the acoustic modality, rate effects in ABR are already well described [17,18]. Jiang et al. [18] reported age-dependent latencies and interpeak intervals in children as consequences of developmental effects. In our opinion this measure of auditory synaptic efficacy [18] can be transferred to differential diagnostics in CI recipients to provide further explanation of unexpectedly poor WRS65CI values. We expect that certain damage mechanisms in hearing-impaired subjects and CI recipients may have a similar effect on rate dependence of EABRs.
Consequently, the goal of this study was to provide reference values for rate-dependent EABR in CI recipients. By including only CI users who met the predicted values of WRS65CI we aimed to open a window for differential diagnostics in CI recipients with unexpected and unexplained poor postoperative WRS65CI.

2. Materials and Methods

2.1. Research Subjects

This prospective investigation included five subjects in the pilot phase and thereafter a further 20 subjects according to a power calculation based on the results of the pilot phase.
The study was approved by the local ethics committee on 10th August 2021 (BB 120/21), and all procedures were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
The study was registered in the German Clinical Trials Register (DRKS00026195).
Participants were recruited from the clinic’s patient population.
Inclusion criteria were:
  • Adulthood (minimum age 18 years) at implantation,
  • Implant type: CI24RE, CI400 series, CI500 series, or CI600 series (Cochlear™ Limited, Sydney, Australia),
  • Implant in specification according to European Consensus Statement on Cochlear Implant Failures and Explantations [19],
  • WRS65(CI) in the upper three quartiles according to classification of Hoppe et al. [20] and
  • Willingness and ability to participate in the study.
Exclusion criteria were:
  • Known mental handicap,
  • Known central hearing disorders and
  • Short cut or open circuit of intracochlear electrodes 11 and/or 18.
Demographic information for these patients is provided in Table 1. Bilateral implantation was not an exclusion criterion; in those two cases, both ears were included in the analysis separately (#098/#107 and #271/#275).

2.2. Electrophysiological Measurements

To measure rate dependences of latencies and inter-peak latencies of EABRs, a quasi-simultaneous measurement of ECAPs and EABRs is needed. Here, it is essential to use the same stimulation mode and the same stimulation intensity for both assessments, to ensure compatibility of the data. Therefore, Dziemba et al. [12] introduced an intracochlear stimulation mode for the Nucleus® CI system (EABRCIStim). They used electrode 11 as a stimulation-active and electrode 18 as a stimulation-indifferent electrode, with a pulse width of 100 µs. This EABRCIStim facilitates an electrical excitation covering a median length of about 80% of the length of the implanted CI electrode array.
In order to avoid possible intensity-dependent effects, a defined supra-threshold stimulation intensity of 20 CL above the individual ECAP threshold, measured with the EABRCIStim, was set. The measurements in all subjects followed the same procedure, as described below.

2.2.1. ECAP Measurements

For the unconditional avoidance of uncomfortable loud stimulation the LAPL using the EABRCIStim was estimated subjectively in a first step.
The second step was the identification of the most appropriate recording-active electrode according to Dziemba et al. [12]. Therefore, ECAP was measured at LAPL by stimulating all intra-cochlear electrodes, except electrodes 11 and 18, sequentially by using the extracochlear electrode (plate) MP2 as recording-indifferent electrode. The electrode with the largest ECAP amplitude at LAPL was selected as the best recording-active electrode.
In the third step, an ECAP amplitude-growth function was measured up to LAPL with the values found previously. The visual ECAP threshold was read out, taking into account a minimum signal-to-noise ratio for ECAP measurements according to Hey et al. [21].
Finally, the rate-dependent ECAPs were measured by using a stimulation intensity of 20 CL above the previously found threshold at stimulation rates of 11, 41, 81 and 91 stimuli per second.

2.2.2. EABR Measurements

All EABR measurement series were performed in the same stimulation mode as for the rate-dependent ECAP. The Eclipse system (Interacoustics, Middelfart, Denmark) was used to record the rate-dependent EABRs. Synchronisation between the CI system and the EABR device was achieved through a TTL-compatible trigger signal. This was sent via a commercially available cable (3.5 mm jack) from the programming interface of the CI system to the EABR recording system. The marking and labelling of all the measured potentials (ECAP and EABR) was performed according to Atcherson and Stoody [22]. To avoid ambivalence in picking peaks, they recommended that the rightmost sample be used for marking the positive peaks and the leftmost sample be used for marking the negative peaks.

2.3. Statistical Analysis

We used boxplots for the graphical representation of the measured values.
For each user, the set of measurement data is a connected, non-normally distributed sample. Furthermore, there is no variance homogeneity of the data. Therefore, a non-parametric test must be used; we chose the Friedman rank sum test as being the most appropriate.
All statistical tests and figures were condicted with R [23] and RStudio [24].

3. Results

3.1. Latencies

The latencies t1, t3 and t5 of rate-dependent ECAP and EABR are shown in Figure 1. While for the ECAP no rate effect on latency t1 was seen ( p = 0.07 ), we found significant mean rate effects for latency t3 (0.19 ms) and t5 (0.37 ms) The post-hoc analyses of the rate effects of t3 and t5 are summarised in Table 2 and Table 3.

3.2. Interpeak Intervals

The interpeak intervals t 5 − t 1 , t 5 − t 3 and t 3 − t 1 of rate-dependent ECAPs and EABRs are shown in Figure 2. We found significant rate effects for all the interpeak intervals analysed. The interpeak interval t 5 − t 1 shows a rate effect of 0.37 ms, while the interpeak interval t 5 − t 3 is shows a rate effect of 0.18 ms. The mean rate effect on interpeak interval t 3 − t 1 is 0.19 ms. The analyses are summarised in Table 4, Table 5 and Table 6.

3.3. Amplitudes

The amplitudes A1, A3 and A5 of rate-dependent ECAPs and EABRs are shown in Figure 3. While for ECAP there is no rate effect on A1 ( p = 0.26 ), we found significant detrimental rate effects, for A3 and A5, with respective mean reductions of 73% and 81%. The post-hoc analyses of the rate effects of A3 and A5 are summarised in Table 7 and Table 8.

4. Discussion

In accordance with the study’s goals we investigated the rate dependences in our population of CI recipients, all of whom had monosyllabic word recognition within the upper three quartiles according to the classification put forward by Hoppe et al. [20]. We found rate dependences for EABR latency t3 and t5 in the order of 0.19 ms and 0.37 ms respectively, while ECAPs were not affected by rate. Correspondingly, the interpeak intervals’ rate dependences for t 5 − t 1 , t 5 − t 3 and t 3 − t 1 were found to be in the order of 0.37 ms, 0.18 ms and 0.19 ms. Jiang et al. [18] described the change of rate dependence in acoustic ABR as an effect of the maturing auditory pathway in children of various ages. In adults the latency changes with rate are probably related to synaptic adaptation [17]. With respect to the amplitudes, Campbell et al. [25] have stated that the change in wave V of acoustic ABR does not decrease at 81/s by more than 28% compared with the amplitude at 11/s. However, in our population we found significant detrimental rate effects: a reduction down to 73% for A3 and down to 81% for A5. This is within the range for rate-dependent changes found for wave V in acoustic ABR [25]. To summarise, these reference values for EABR and ECAP latencies, interpeak intervals and amplitudes provide a basis for possible differential diagnoses after cochlear implantation.
We hypothesize that in postlingually deafened adults with CI larger changes of amplitudes and latencies due to rate (in comparison with references values) can be interpreted as pathological effects. The values shown above can be regarded as reference values. Pathologies may then be revealed in significant deviations from them. For example, in patients with auditory neuropathy spectrum disorder the dyssynchronous neural activity may affect temporal encoding of electrical stimulation from a cochlear implant [26]. Even though Fulmer et al. [26] investigated the recovery function of ECAP, one may reasonably assume that EABR measurements and their rate dependences will be affected by these pathological mechanisms as well. Continuing this line of thought, we would ardue that, compared with ECAP, EABR assesses the higher levels of the auditory pathway as well and therefore appears to offer a valuable complement within differential diagnostics. However, while ECAP can be considered to provide tonotopic information, the EABR as applied in this study will provide integrated information about the status of the auditory pathway. This differential diagnostic pattern is especially important for the most recent CI population [3,4,5,6] with higher preoperative speech recognition scores. In this patient population a highly predictive outcome was observed [3,6] compared with the established patient population with no preoperative speech perception [6,27].
Consequently, if in the patient population with good audiometric preoperative conditions [6] the prediction cannot be achieved, an underlying pathology of the auditory pathway may be suspected. Moreover, approaches utilising advanced measurements of ECAPs [8,28,29,30,31] and the assessment of EABR and its rate dependences might be suitable in analogy to the findings in acoustic ABR. With values up to 0.28 ms the standard deviation for the interpeak interval t 5 − t 1 seems to be slightly higher than the 0.23 ms found by Campbell et al. [25]. A more thorough analysis will be needed in future studies.
Assuming a higher standard deviation (which still has to be confirmed) this may have its root cause in the inclusion criteria of the CI population. For acoustic stimulation, normative values, and the population in which to assess them, are easy to define as one has by definition to include normal-hearing subjects. In the case of CI recipients the definition of a reference group is far more challenging. There are no generally agreed criteria for the derivation of a reference group. Consequently, the reference values provided by this study can potentially be improved by better outcome prediction models and, based on this, a narrower patient selection.
Recently, Hoppe et al. [6] applied the criterion “unexpectedly poor speech perception” defined as monosyllabic speech recognition ≥ 20 pp lower than predicted after six months, in order to discuss the time course of such cases. The six months were derived from study which found that 90% of the final score is achieved after 6.9 months. Even if in that study [6] the majority of subjects who were poor perfomer after six months nonetheless reached the target value after a longer time period, there remain 5% of cases in which the prediction is not reached in the long run. The aim of differential diagnostics using EABR would be to differentiate between a patient’s intrinsic root causes for unexpectedly poor speech perception (pathologies) or causes in which the fitting of CI system also plays a part [11]. Future studies with a focus on the time course of postoperative speech recognition with respect to different pathologies (once these are confirmed) will be needed to refine the diagnostics using EABR.

5. Conclusions

The rate-dependences of latency and amplitude in EABR have characteristics comparable to those of acoustic ABR. Consequently, EABR may potentially support differential diagnosis in CI recipients with an outcome below expectation. The results of this study may serve to provide reference values. Pathological issues of the peripheral auditory pathway hindering a postoperative increase in speech perception and CI outcome in general can be excluded or confirmed.

Author Contributions

Conceptualization, O.D.; methodology, O.D., T.H. and F.I.; software, O.D.; validation, O.D.; formal analysis, O.D.; investigation, O.D.; resources, O.D., T.B., T.H. and F.I.; data curation, O.D.; writing—original draft preparation, O.D. and T.H.; writing—review and editing, O.D., F.I. and T.B.; visualization, O.D.; supervision, F.I.; project administration, O.D. and T.H.; funding acquisition, O.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Cochlear™ Research an Development Limited grant number IIR-2311.

Institutional Review Board Statement

Ethical approval: BB 120/21, This study was registered in German Clinical Trials Register under DRKS-ID: DRKS00026195.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Not applicable.

Acknowledgments

No Acknowledgements.

Conflicts of Interest

O.D. received funding in other projects and travel money. T.H. is employee of Cochlear Deutschland GmbH & Co. KG. T.B. and F.I. declare no conflict of interest.

Abbreviations

ABR auditory brainstem responses
CL current level
CI cochlear implant
EABR electrically evoked auditory brainstem responses
ECAP electrically evoked compound action potentials
EABRCIStim EABR stimulation mode according to [12]
IQR interquartile range
LAPL loudest acceptable presentation level
pp percentage-points
WRS word recognition score
WRS65(CI) word recognition score with cochlear implant at 65 dB

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Figure 1. Latencies of all measured potentials. The boxes show medians and quartiles; the whiskers show the maximum value within 1.5 IQR (1.5 times the interquartile range). Filled circles show the outliers.
Figure 1. Latencies of all measured potentials. The boxes show medians and quartiles; the whiskers show the maximum value within 1.5 IQR (1.5 times the interquartile range). Filled circles show the outliers.
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Figure 2. Interpeak intervals of all measured potentials. The boxes show medians and quartiles; the whiskers show the maximum value within 1.5 IQR. Filled circles show the outliers.
Figure 2. Interpeak intervals of all measured potentials. The boxes show medians and quartiles; the whiskers show the maximum value within 1.5 IQR. Filled circles show the outliers.
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Figure 3. Amplitudes of all measured potentials. The boxes show medians and quartiles; the whiskers show the maximum value within 1.5 IQR. Filled circles show the outliers.
Figure 3. Amplitudes of all measured potentials. The boxes show medians and quartiles; the whiskers show the maximum value within 1.5 IQR. Filled circles show the outliers.
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Table 1. Biographical data of participants. ‘Age’ is the recipient’s age at the time of inclusion in the study. Side is coded right (r) or left (l) for ear receiving the implant. Recipient’s sex is indicated, (f) or (m). Electrode types were: Contour Advance® (CA), Slim Modiolar (SM), and Slim Straight (SS).
Table 1. Biographical data of participants. ‘Age’ is the recipient’s age at the time of inclusion in the study. Side is coded right (r) or left (l) for ear receiving the implant. Recipient’s sex is indicated, (f) or (m). Electrode types were: Contour Advance® (CA), Slim Modiolar (SM), and Slim Straight (SS).
ID Age (years) Usage of CI (months) Side Gender Implant type Electrode type WRS65(CI) (%)
#098 62 146 r f CI512 CA 75.0
#107 62 140 l f CI512 CA 85.0
#140 59 104 r f CI24RE CA 92.5
#160 65 97 r f CI24RE CA 67.5
#193 58 81 r f CI422 SS 75.0
#234 57 71 l m CI522 SS 55.0
#242 53 26 l f CI522 SS 87.5
#247 53 25 r m CI532 SM 85.0
#251 72 52 l f CI532 SM 75.0
#262 45 61 l f CI512 CA 75.0
#269 55 13 l f CI512 CA 77.5
#271 73 8 l m CI532 SM 80.0
#275 73 3 r m CI532 SM 60.0
#279 62 28 r f CI532 SM 82.5
#281 56 27 r f CI532 SM 87.5
#288 57 19 r f CI622 SS 82.5
#315 38 7 r f CI622 SS 75.0
#341 64 3 r m CI622 SS 87.5
#348 74 116 l f CI612 CA 82.5
#350 59 1 l f CI622 SS 60.0
Table 2. Friedman rank sum test of t3 latency ( p = 2 · 10 − 10 ), post-hoc analysis.
Table 2. Friedman rank sum test of t3 latency ( p = 2 · 10 − 10 ), post-hoc analysis.
obs.diff critical diff stat signif p
11-41 13.5 21.5 FALSE 0.98
11-81 30.5 21.5 TRUE 0.001
11-91 52.0 21.5 TRUE 2 · 10 − 9
41-81 17.0 21.5 FALSE 0.37
41-91 38.5 21.5 TRUE 2 · 10 − 5
81-91 21.5 21.5 FALSE 0.08
Table 3. Friedman rank sum test of t5 latency ( p = 3 · 10 − 10 ), post-hoc analysis.
Table 3. Friedman rank sum test of t5 latency ( p = 3 · 10 − 10 ), post-hoc analysis.
obs.diff critical diff stat signif p
11-41 4.0 21.5 FALSE 1.0
11-81 29.5 21.5 TRUE 0.003
11-91 48.5 21.5 TRUE 3 · 10 − 8
41-81 25.5 21.5 TRUE 0.02
41-91 44.5 21.5 TRUE 5 · 10 − 7
81-91 19.0 21.5 FALSE 0.19
Table 4. Friedman rank sum test of t5-t1 interpeak interval ( p = 3 · 10 − 10 ), post-hoc analysis.
Table 4. Friedman rank sum test of t5-t1 interpeak interval ( p = 3 · 10 − 10 ), post-hoc analysis.
obs.diff critical diff stat signif p
11-41 4.0 21.5 FALSE 1.0
11-81 29.5 21.5 TRUE 0.003
11-91 48.5 21.5 TRUE 3 · 10 − 8
41-81 25.5 21.5 TRUE 0.02
41-91 44.5 21.5 TRUE 5 · 10 − 7
81-91 19.0 21.5 FALSE 0.20
Table 5. Friedman rank sum test of t5-t3 interpeak interval ( p = 1 · 10 − 8 ), post-hoc analysis.
Table 5. Friedman rank sum test of t5-t3 interpeak interval ( p = 1 · 10 − 8 ), post-hoc analysis.
obs.diff critical diff stat signif p
11-41 3.5 21.5 FALSE 1.0
11-81 29.5 21.5 TRUE 0.003
11-91 38.0 21.5 TRUE 3 · 10 − 5
41-81 33.0 21.5 TRUE 5 · 10 − 4
41-91 41.5 21.5 TRUE 4 · 10 − 6
81-91 8.5 21.5 FALSE 1.0
Table 6. Friedman rank sum test of t3-t1 interpeak interval ( p = 2 · 10 − 10 ), post-hoc analysis.
Table 6. Friedman rank sum test of t3-t1 interpeak interval ( p = 2 · 10 − 10 ), post-hoc analysis.
obs.diff critical diff stat signif p
11-41 13.5 21.5 FALSE 0.99
11-81 30.5 21.5 TRUE 0.002
11-91 52.0 21.5 TRUE 2 · 10 − 9
41-81 17.0 21.5 FALSE 0.37
41-91 38.5 21.5 TRUE 2 · 10 − 5
81-91 21.5 21.5 FALSE 0.08
Table 7. Friedman rank sum test of amplitude A3 ( p = 9 · 10 − 5 ), post-hoc analysis.
Table 7. Friedman rank sum test of amplitude A3 ( p = 9 · 10 − 5 ), post-hoc analysis.
obs.diff critical diff stat signif p
11-41 2.0 21.5 FALSE 1.0
11-81 21.0 21.5 FALSE 0.10
11-91 29.0 21.5 TRUE 0.004
41-81 23.0 21.5 TRUE 0.048
41-91 31.0 21.5 TRUE 0.001
81-91 8.0 21.5 FALSE 1.0
Table 8. Friedman rank sum test of amplitude A5 ( p = 2 · 10 − 5 ), post-hoc analysis.
Table 8. Friedman rank sum test of amplitude A5 ( p = 2 · 10 − 5 ), post-hoc analysis.
obs.diff critical diff stat signif p
11-41 16.0 21.5 FALSE 0.50
11-81 17.0 21.5 FALSE 0.37
11-91 19.0 21.5 FALSE 0.20
41-81 33.0 21.5 TRUE 5 · 10 − 4
41-91 35.0 21.5 TRUE 2 · 10 − 4
81-91 2.0 21.5 FALSE 1.0
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