Results of Postoperative, CT-based, Electrode Deactivation on Hearing in Prelingually Deafened Adult Cochlear Implant Recipients

Cochlear Implant Electrode Placement and Music Perception

Importance

Cochlear implants enable improvements in speech perception, but music perception outcomes remain variable. Image-guided cochlear implant programming has emerged as a potential programming strategy for increasing the quality of spectral information delivered through the cochlear implant to improve outcomes.

Objectives

To perform 2 experiments, the first of which modeled the variance in music perception scores as a function of electrode positioning factors, and the second of which evaluated image-guided cochlear implant programming as a strategy to improve music perception with a cochlear implant.

Design, Setting, and Participants

This single-center, prospective study recruited 50 adult patients with at least 6 months of cochlear implant listening experience and normal cochlear anatomy to participate in experiment 1 from 2013 to 2023. Data analysis was conducted from January to February 2024. Thirty-four of the 50 patients from experiment 1 also completed experiment 2.

Interventions

Cochlear implant programming using a computed tomography-guided electrode selection strategy.

Main Outcomes and Measures

University of Washington Clinical Assessment of Music score, including subtests of pitch discrimination thresholds, isochronous familiar melody recognition, and timbre recognition.

Results

Of 50 participants, 20 (40%) were female, and the mean (SD) age was 57.7 (16.4) years. Experiment 1 suggested that better music perception abilities in the 50 participants were associated with patients who were younger and had a postlingual onset of deafness, as well as electrode arrays with a full scala tympani insertion, higher modiolar distance, and shallower insertion depth. Experiment 2 suggested improvements in melody recognition in the 34 participants using the image-guided cochlear implant programming strategy. Patients with apical electrodes that were deactivated were more likely to demonstrate an improvement in their pitch perception thresholds with the image-guided strategy, likely due to the low-frequency stimuli used in the University of Washington Clinical Assessment of Music.

Conclusions and Relevance

This study identified patient and device factors that were associated with music perception outcomes with a cochlear implant. These findings suggest that a personalized, image-guided approach to programming may improve music perception abilities for patients with cochlear implants.

The relationship between channel interaction, electrode placement, and speech perception in adult cochlear implant users

This study (1) characterized the effects of channel interaction using spectral blurring, (2) evaluated an image-guided electrode selection (IGES) method aiming to reduce channel interaction, and (3) investigated the impact of electrode placement factors on the change in performance by condition. Twelve adult MED-EL (Innsbruck, Austria) cochlear implant recipients participated. Performance was compared across six conditions: baseline (no blurring), all blurred, apical blurred, middle blurred, basal blurred, and IGES. Electrode placement information was calculated from post-insertion computerized tomography (CT) imaging. Each condition tested measures of speech recognition and subjective ratings. Results showed poorer performance when spectral blurring was applied to all channels compared to baseline, suggesting an increase in channel interaction was achieved. Vowel recognition was more sensitive to apical and middle blurring while consonant recognition was more sensitive to basal blurring, indicating that phoneme identification may be useful for assessing channel interaction clinically. IGES did not significantly improve group performance, and electrode placement factors did not impact results. However, participants who were more affected by spectral blurring tended to benefit more from IGES. These findings indicate that spectral blurring can help identify areas most affected by channel interaction to help optimize electrode selection.

Variability in Manual Segmentation of Temporal Bone Structures in Cone Beam CT Images

PURPOSE

Manual segmentation of anatomical structures is the accepted "gold standard" for labeling structures in clinical images. However, the variability in manual segmentation of temporal bone structures in CBCT images of the temporal bone has not been systematically evaluated using multiple reviewers. Therefore, we evaluated the intravariability and intervariability of manual segmentation of inner ear structures in CBCT images of the temporal bone.

METHODS

Preoperative CBCTs scans of the inner ear were obtained from 10 patients who had undergone cochlear implant surgery. The cochlea, facial nerve, chorda tympani, mid-modiolar (MM) axis, and round window (RW) were manually segmented by five reviewers in two separate sessions that were at least 1 month apart. Interreviewer and intrareviewer variabilities were assessed using the Dice coefficient (DICE), volume similarity, mean Hausdorff Distance metrics, and visual review.

RESULTS

Manual segmentation of the cochlea was the most consistent within and across reviewers with a mean DICE of 0.91 (SD = 0.02) and 0.89 (SD = 0.01) respectively, followed by the facial nerve with a mean DICE of 0.83 (SD = 0.02) and 0.80 (SD = 0.03), respectively. The chorda tympani had the greatest amount of reviewer variability due to its thin size, and the location of the centroid of the RW and the MM axis were also quite variable between and within reviewers.

CONCLUSIONS

We observed significant variability in manual segmentation of some of the temporal bone structures across reviewers. This variability needs to be considered when interpreting the results in studies using one manual reviewer.

Survey of selective electrode deactivation attitudes and practices by cochlear implant audiologists

OBJECTIVES

The purpose of this study was to explore clinician attitudes regarding selective electrode deactivation and to investigate the primary methodology used to identify poorly encoded electrodes, deactivate identified electrodes, and measure outcomes.

METHODS

An online survey consisting of 32 questions was administered to certified clinical and research cochlear implant (CI) audiologists. Questions asked participants about their demographic information, device programming patterns, and attitudes regarding selective electrode deactivation.

RESULTS

Fifty-four audiologists completed the survey. When asked whether they believed selectively deactivating poorly encoded electrodes could improve speech perception outcomes, 43% of respondents selected 'Probably Yes,' 39% selected 'Definitely Yes,' and 18% selected 'Might or Might Not.' Of those who reported deactivating electrodes as part of CI programming, various methodology was reported to identify and deactivate poorly encoding electrodes and evaluate effectiveness of deactivation. General reasons against deactivation were also reported.

DISCUSSION

CI audiologists generally believed selective electrode deactivation could be used to improve speech perception outcomes for patients; however, few reported implementing selective electrode deactivation in practice. Among those who do perform selective electrode deactivation, the reported methodology was highly variable.

CONCLUSION

These findings support the need for clinical practice guidelines to assist audiologists in performing selective electrode deactivation.

Evaluation of a clinical method for selective electrode deactivation in cochlear implant programming

Background

Cochlear implants are a neural prosthesis used to restore the perception of hearing in individuals with severe-to-profound hearing loss by stimulating the auditory nerve with electrical current through a surgically implanted electrode array. The integrity of the interface between the implanted electrode array and the auditory nerve contributes to the variability in outcomes experienced by cochlear implant users. Strategies to identify and eliminate poorly encoding electrodes have been found to be effective in improving outcomes with the device, but application is limited in a clinical setting.

Objective

The purpose of this study was to evaluate a clinical method used to identify and selectively deactivate cochlear implants (CI) electrodes related to poor electrode-neural interface.

Methods

Thirteen adult CI users participated in a pitch ranking task to identify indiscriminate electrode pairs. Electrodes associated with indiscriminate pairs were selectively deactivated, creating an individualized experimental program. Speech perception was evaluated in the baseline condition and with the experimental program before and after an acclimation period. Participant preference responses were recorded at each visit.

Results

Statistically significant improvements using the experimental program were found in at least one measure of speech perception at the individual level in four out of 13 participants when tested before acclimation. Following an acclimation period, ten out of 13 participants demonstrated statistically significant improvements in at least one measure of speech perception. Statistically significant improvements were found with the experimental program at the group level for both monosyllabic words (p = 0.006) and sentences in noise (p = 0.020). Additionally, ten participants preferred the experimental program prior to the acclimation period and eleven preferred the experimental program following the acclimation period.

Conclusion

Results from this study suggest that electrode deactivation may yield improvement in speech perception following an acclimation period. A majority of CI users in our study reported a preference for the experimental program. This method proved to be a suitable clinical strategy for identifying and deactivating poorly encoding electrodes in adult CI users.

Image-Guided Cochlear Implant Programming: A Systematic Review and Meta-analysis

OBJECTIVE

To review studies evaluating clinically implemented image-guided cochlear implant programing (IGCIP) and to determine its effect on cochlear implant (CI) performance.

DATA SOURCES

PubMed, EMBASE, and Google Scholar were searched for English language publications from inception to August 1, 2021.

STUDY SELECTION

Included studies prospectively compared intraindividual CI performance between an image-guided experimental map and a patient's preferred traditional map. Non-English studies, cadaveric studies, and studies where imaging did not directly inform programming were excluded.

DATA EXTRACTION

Seven studies were identified for review, and five reported comparable components of audiological testing and follow-up times appropriate for meta-analysis. Demographic, speech, spectral modulation, pitch accuracy, and quality-of-life survey data were collected. Aggregate data were used when individual data were unavailable.

DATA SYNTHESIS

Audiological test outcomes were evaluated as standardized mean change (95% confidence interval) using random-effects meta-analysis with raw score standardization. Improvements in speech and quality-of-life measures using the IGCIP map demonstrated nominal effect sizes: consonant-nucleus-consonant words, 0.15 (-0.12 to 0.42); AzBio quiet, 0.09 (-0.05 to 0.22); AzBio +10 dB signal-noise ratio, 0.14 (-0.01 to 0.30); Bamford-Kowel-Bench sentence in noise, -0.11 (-0.35 to 0.12); Abbreviated Profile of Hearing Aid Benefit, -0.14 (-0.28 to 0.00); and Speech Spatial and Qualities of Hearing Scale, 0.13 (-0.02 to 0.28). Nevertheless, 79% of patients allowed to keep their IGCIP map opted for continued use after the investigational period.

CONCLUSION

IGCIP has potential to precisely guide CI programming. Nominal effect sizes for objective outcome measures fail to reflect subjective benefits fully given discordance with the percentage of patients who prefer to maintain their IGCIP map.

Conversations in Cochlear Implantation: The Inner Ear Therapy of Today

As biomolecular approaches for hearing restoration in profound sensorineural hearing loss evolve, they will be applied in conjunction with or instead of cochlear implants. An understanding of the current state-of-the-art of this technology, including its advantages, disadvantages, and its potential for delivering and interacting with biomolecular hearing restoration approaches, is helpful for designing modern hearing-restoration strategies. Cochlear implants (CI) have evolved over the last four decades to restore hearing more effectively, in more people, with diverse indications. This evolution has been driven by advances in technology, surgery, and healthcare delivery. Here, we offer a practical treatise on the state of cochlear implantation directed towards developing the next generation of inner ear therapeutics. We aim to capture and distill conversations ongoing in CI research, development, and clinical management. In this review, we discuss successes and physiological constraints of hearing with an implant, common surgical approaches and electrode arrays, new indications and outcome measures for implantation, and barriers to CI utilization. Additionally, we compare cochlear implantation with biomolecular and pharmacological approaches, consider strategies to combine these approaches, and identify unmet medical needs with cochlear implants. The strengths and weaknesses of modern implantation highlighted here can mark opportunities for continued progress or improvement in the design and delivery of the next generation of inner ear therapeutics.

Automated Calculation of Cochlear Implant Electrode Insertion Parameters in Clinical Cone-Beam CT

HYPOTHESIS

Automated processing of postoperative clinical cone-beam CT (CBCT) of cochlear implant (CI) patients can be used to accurately determine electrode contacts and integrated with an atlas-based mapping of cochlear microstructures to calculate modiolar distance, angular insertion distance, and scalar location of electrode contacts.

BACKGROUND

Hearing outcomes after CI surgery are dependent on electrode placement. CBCT is increasingly used for in-office temporal bone imaging and might be routinely used for pre- and post-surgical evaluation.

METHODS

Thirty-six matched pairs of pre- and postimplant CBCT scans were obtained. These were registered with an atlas to model cochlear microstructures in each dataset. Electrode contact center points were automatically determined using thresholding and electrode insertion parameters were calculated. Automated localization and calculation were compared with manual segmentation of contact center points as well as manufacturer specifications.

RESULTS

Automated electrode contact detection aligned with manufacturer specifications of spacing and our algorithms worked for both distantly- and closely spaced arrays. The average difference between the manual and the automated selection was 0.15 mm, corresponding to a 1.875 voxel difference in each plane at the scan resolution. For each case, we determined modiolar distance, angular insertion depth, and scalar location. These calculations also resulted in similar insertion values using manual and automated contact points as well as aligning with electrode properties.

CONCLUSION

Automated processing of implanted high-resolution CBCT images can provide the clinician with key information on electrode placement. This is one step toward routine use of clinical CBCT after CI surgery to inform and guide postoperative treatment.

Cochlear Implant Research and Development in the Twenty-first Century: A Critical Update

Cochlear implants (CIs) are the world's most successful sensory prosthesis and have been the subject of intense research and development in recent decades. We critically review the progress in CI research, and its success in improving patient outcomes, from the turn of the century to the present day. The review focuses on the processing, stimulation, and audiological methods that have been used to try to improve speech perception by human CI listeners, and on fundamental new insights in the response of the auditory system to electrical stimulation. The introduction of directional microphones and of new noise reduction and pre-processing algorithms has produced robust and sometimes substantial improvements. Novel speech-processing algorithms, the use of current-focusing methods, and individualised (patient-by-patient) deactivation of subsets of electrodes have produced more modest improvements. We argue that incremental advances have and will continue to be made, that collectively these may substantially improve patient outcomes, but that the modest size of each individual advance will require greater attention to experimental design and power. We also briefly discuss the potential and limitations of promising technologies that are currently being developed in animal models, and suggest strategies for researchers to collectively maximise the potential of CIs to improve hearing in a wide range of listening situations.

Effects of Spectral Resolution and Frequency Mismatch on Speech Understanding and Spatial Release From Masking in Simulated Bilateral Cochlear Implants

OBJECTIVES

Due to interaural frequency mismatch, bilateral cochlear-implant (CI) users may be less able to take advantage of binaural cues that normal-hearing (NH) listeners use for spatial hearing, such as interaural time differences and interaural level differences. As such, bilateral CI users have difficulty segregating competing speech even when the target and competing talkers are spatially separated. The goal of this study was to evaluate the effects of spectral resolution, tonotopic mismatch (the frequency mismatch between the acoustic center frequency assigned to CI electrode within an implanted ear relative to the expected spiral ganglion characteristic frequency), and interaural mismatch (differences in the degree of tonotopic mismatch in each ear) on speech understanding and spatial release from masking (SRM) in the presence of competing talkers in NH subjects listening to bilateral vocoder simulations.

DESIGN

During testing, both target and masker speech were presented in five-word sentences that had the same syntax but were not necessarily meaningful. The sentences were composed of five categories in fixed order (Name, Verb, Number, Color, and Clothes), each of which had 10 items, such that multiple sentences could be generated by randomly selecting a word from each category. Speech reception thresholds (SRTs) for the target sentence presented in competing speech maskers were measured. The target speech was delivered to both ears and the two speech maskers were delivered to (1) both ears (diotic masker), or (2) different ears (dichotic masker: one delivered to the left ear and the other delivered to the right ear). Stimuli included the unprocessed speech and four 16-channel sine-vocoder simulations with different interaural mismatch (0, 1, and 2 mm). SRM was calculated as the difference between the diotic and dichotic listening conditions.

RESULTS

With unprocessed speech, SRTs were 0.3 and -18.0 dB for the diotic and dichotic maskers, respectively. For the spectrally degraded speech with mild tonotopic mismatch and no interaural mismatch, SRTs were 5.6 and -2.0 dB for the diotic and dichotic maskers, respectively. When the tonotopic mismatch increased in both ears, SRTs worsened to 8.9 and 2.4 dB for the diotic and dichotic maskers, respectively. When the two ears had different tonotopic mismatch (e.g., there was interaural mismatch), the performance drop in SRTs was much larger for the dichotic than for the diotic masker. The largest SRM was observed with unprocessed speech (18.3 dB). With the CI simulations, SRM was significantly reduced to 7.6 dB even with mild tonotopic mismatch but no interaural mismatch; SRM was further reduced with increasing interaural mismatch.

CONCLUSIONS

The results demonstrate that frequency resolution, tonotopic mismatch, and interaural mismatch have differential effects on speech understanding and SRM in simulation of bilateral CIs. Minimizing interaural mismatch may be critical to optimize binaural benefits and improve CI performance for competing speech, a typical listening environment. SRM (the difference in SRTs between diotic and dichotic maskers) may be a useful clinical tool to assess interaural frequency mismatch in bilateral CI users and to evaluate the benefits of optimization methods that minimize interaural mismatch.

Assessment of Inter- and Intra-Rater Reliability of Tablet-Based Software to Measure Cochlear Duct Length

OBJECTIVE

The objective of this study is to build upon previous work validating a tablet-based software to measure cochlear duct length (CDL). Here, we do so by greatly expanding the number of cochleae (n = 166) analyzed, and examined whether computed tomography (CT) slice thickness influences reliability of CDL measurements.

STUDY DESIGN

Retrospective chart review study.

SETTING

Tertiary referral center.

PATIENTS

Eighty-three adult cochlear implant recipients were included in the study. Both cochleae were measured for each patient (n = 166).

INTERVENTIONS

Three raters analyzed the scans of 166 cochleae at 2 different time points. Each rater individually identified anatomical landmarks that delineated the basal turn diameter and width. These coordinates were applied to the elliptic approximation method (ECA) to estimate CDL. The effect of CT scan slice thickness on the measurements was explored.

MAIN OUTCOME MEASURES

The primary outcome measure is the strength of the inter- and intra-rater reliability.

RESULTS

The mean CDL measured was 32.84 ± 2.03 mm, with a range of 29.03 to 38.07 mm. We observed no significant relationship between slice thickness and CDL measurement (F1,164 = 3.04; p = 0.08). The mean absolute difference in CDL estimations between raters was 1.76 ± 1.24 mm and within raters was 0.263 ± 0.200 mm. The intra-class correlation coefficient (ICC) between raters was 0.54 and ranged from 0.63 to 0.83 within raters.

CONCLUSIONS

This software produces reliable measurements of CDL between and within raters, regardless of CT scan thickness.

Effects of noise on integration of acoustic and electric hearing within and across ears

In bimodal listening, cochlear implant (CI) users combine electric hearing (EH) in one ear and acoustic hearing (AH) in the other ear. In electric-acoustic stimulation (EAS), CI users combine EH and AH in the same ear. In quiet, integration of EH and AH has been shown to be better with EAS, but with greater sensitivity to tonotopic mismatch in EH. The goal of the present study was to evaluate how external noise might affect integration of AH and EH within or across ears. Recognition of monosyllabic words was measured for normal-hearing subjects listening to simulations of unimodal (AH or EH alone), EAS, and bimodal listening in quiet and in speech-shaped steady noise (10 dB, 0 dB signal-to-noise ratio). The input/output frequency range for AH was 0.1–0.6 kHz. EH was simulated using an 8-channel noise vocoder. The output frequency range was 1.2–8.0 kHz to simulate a shallow insertion depth. The input frequency range was either matched (1.2–8.0 kHz) or mismatched (0.6–8.0 kHz) to the output frequency range; the mismatched input range maximized the amount of speech information, while the matched input resulted in some speech information loss. In quiet, tonotopic mismatch differently affected EAS and bimodal performance. In noise, EAS and bimodal performance was similarly affected by tonotopic mismatch. The data suggest that tonotopic mismatch may differently affect integration of EH and AH in quiet and in noise.

Auditory performance of post-lingually deafened adult cochlear implant recipients using electrode deactivation based on postoperative cone beam CT images

PURPOSE

The use of image processing techniques to estimate the position of intra-cochlear electrodes has enabled the creation of personalized maps to meet the individual stimulation needs of cochlear implant (CI) recipients. The aim of this study was to evaluate a novel technique of electrode deactivation based on postoperative cone beam computed tomography (CBCT) images in post-lingually deafened adult CI recipients.

METHODS

Based on postoperative CBCT images, the positioning of the electrodes was estimated in relation to the modiolus in 14 ears of 13 post-lingually deafened adult CI recipients. The electrodes sub-optimally positioned or involved in kinking and tip fold-over were deactivated. Speech perception scores in silence and in noise were obtained from subjects using the standard map and were followed up 4 weeks after image-based electrode deactivation reprogramming technique (IBEDRT). The participants selected their preferred map after 4 weeks of IBEDRT use.

RESULTS

There were statistically significant improvements in the speech recognition tests in silence and noise when comparing IBEDRT performance to the standard map. All participants elected the IBEDRT as their new preferred map.

CONCLUSIONS

IBEDRT is a promising technique for fitting CI recipients and minimizing channel interaction increased by the positioning of the electrodes sub-optimally placed, thereby improving their auditory performance. We propose a novel electrode deactivation technique based on postoperative CBCT imaging, with a limited number of deactivated electrodes and a low-dosing scanning which could be applied for clinical routine.

Longitudinal effect of deactivating stimulation sites based on low-rate thresholds on speech recognition in cochlear implant users

Objective: The objective of the current study was to examine the longitudinal effect of deactivating stimulation sites estimated to produce broad neural excitation on speech recognition. Design: Spatial patterns of neural excitation were estimated based on a previously established psychophysical measure, that is, detection threshold for low-rate pulse trains. Stimulation sites with relatively poor thresholds were deactivated in an experimental map. The acute effect was evaluated, in quiet and in noise, immediately after the experimental map was created (baseline), after the subjects practiced with the experimental map for two months (treatment), and after the subjects' daily map was switched back again to the clinical map for another two months (withdrawal). Study sample: Eight Cochlear Nucleus device users participated in the study. Results: For both listening in noise and in quiet, the greatest effect of deactivation was observed after the subjects were given time to adapt to the new frequency allocations. The effect was comparable for listening in fluctuating and steady-state noises. All subjects benefited from deactivation for listening in noise, but subjects with greater variability in thresholds were more likely to benefit from deactivation for listening in quiet. Conclusion: The benefit of electrode deactivation for speech recognition can increase with practice.

The Relationship Between Spectral Modulation Detection and Speech Recognition: Adult Versus Pediatric Cochlear Implant Recipients

Adult cochlear implant (CI) recipients demonstrate a reliable relationship between spectral modulation detection and speech understanding. Prior studies documenting this relationship have focused on postlingually deafened adult CI recipients—leaving an open question regarding the relationship between spectral resolution and speech understanding for adults and children with prelingual onset of deafness. Here, we report CI performance on the measures of speech recognition and spectral modulation detection for 578 CI recipients including 477 postlingual adults, 65 prelingual adults, and 36 prelingual pediatric CI users. The results demonstrated a significant correlation between spectral modulation detection and various measures of speech understanding for 542 adult CI recipients. For 36 pediatric CI recipients, however, there was no significant correlation between spectral modulation detection and speech understanding in quiet or in noise nor was spectral modulation detection significantly correlated with listener age or age at implantation. These findings suggest that pediatric CI recipients might not depend upon spectral resolution for speech understanding in the same manner as adult CI recipients. It is possible that pediatric CI users are making use of different cues, such as those contained within the temporal envelope, to achieve high levels of speech understanding. Further investigation is warranted to investigate the relationship between spectral and temporal resolution and speech recognition to describe the underlying mechanisms driving peripheral auditory processing in pediatric CI users.

Two-level Training of a 3d U-Net for Accurate Segmentation of the Intra-cochlear Anatomy in Head CTs with Limited Ground Truth Training Data

Cochlear implants (CIs) use electrode arrays that are surgically inserted into the cochlea to treat patients with hearing loss. For CI recipients, sound bypasses the natural transduction mechanism and directly stimulates the neural regions, thus creating a sense of hearing. Post-operatively, CIs need to be programmed. Traditionally, this is done by an audiologist who is blind to the positions of the electrodes relative to the cochlea and only relies on the subjective response of the patient. Multiple programming sessions are usually needed, which can take a frustratingly long time. We have developed an image-guided cochlear implant programming (IGCIP) system to facilitate the process. In IGCIP, we segment the intra-cochlear anatomy and localize the electrode arrays in the patient's head CT image. By utilizing their spatial relationship, we can suggest programming settings that can significantly improve hearing outcomes. To segment the intra-cochlear anatomy, we use an active shape model (ASM)-based method. Though it produces satisfactory results in most cases, sub-optimal segmentation still happens. As an alternative, herein we explore using a deep learning method to perform the segmentation task. Large image sets with accurate ground truth (in our case manual delineation) are typically needed to train a deep learning model for segmentation but such a dataset does not exist for our application. To tackle this problem, we use segmentations generated by the ASM-based method to pre-train the model and fine-tune it on a small image set for which accurate manual delineation is available. Using this method, we achieve better results than the ASM-based method.

Deactivating cochlear implant electrodes to improve speech perception: A computational approach

A potential bottleneck to improving speech perception performance in cochlear implant (CI) users is that some of their electrodes may poorly encode speech information. Several studies have examined the effect of deactivating poorly encoding electrodes on speech perception with mixed results. Many of these studies focused on identifying poorly encoding electrodes by some measure (e.g. electrode discrimination, pitch ordering, threshold, CT-guided, masked modulation detection), but provide inconsistent criteria about which electrodes, and how many, should be deactivated, and without considering how speech information becomes distributed across the electrode array. The present simulation study addresses this issue using computational approaches. Previously validated models were used to generate predictions of speech scores as a function of all possible combinations of active electrodes in a 22-electrode array in three groups of hypothetical subjects representative of relatively better, moderate, and poorer performing CI users. Using high-performance computing, over 500 million predictions were generated. Although deactivation of the poorest encoding electrodes sometimes resulted in predicted benefit, this benefit was significantly less relative to predictions resulting from model-optimized deactivations. This trend persisted when using novel stimuli (i.e. other than those used for optimization) and when using different processing strategies. Optimum electrode deactivation patterns produced an average predicted increase in word scores of 10% with some scores increasing by more than 20%. Optimum electrode deactivation patterns typically included 11 to 19 (out of 22) active electrodes, depending on the performance group. Optimal active electrode combinations were those that maximized discrimination of speech cues, maintaining 80%-100% of the physical span of the array. The present study demonstrates the potential for further improving CI users' speech scores with appropriate selection of active electrodes.

Temporal Modulation Detection Depends on Sharpness of Spatial Tuning

Prior research has shown that in electrical hearing, cochlear implant (CI) users' speech recognition performance is related in part to their ability to detect temporal modulation (i.e., modulation sensitivity). Previous studies have also shown better speech recognition when selectively stimulating sites with good modulation sensitivity rather than all stimulation sites. Site selection based on channel interaction measures, such as those using imaging or psychophysical estimates of spread of neural excitation, has also been shown to improve speech recognition. This led to the question of whether temporal modulation sensitivity and spatial selectivity of neural excitation are two related variables. In the present study, CI users' modulation sensitivity was compared for sites with relatively broad or narrow neural excitation patterns. This was achieved by measuring temporal modulation detection thresholds (MDTs) at stimulation sites that were significantly different in their sharpness of the psychophysical spatial tuning curves (PTCs) and measuring MDTs at the same sites in monopolar (MP) and bipolar (BP) stimulation modes. Nine postlingually deafened subjects implanted with Cochlear Nucleus® device took part in the study. Results showed a significant correlation between the sharpness of PTCs and MDTs, indicating that modulation detection benefits from a more spatially restricted neural activation pattern. There was a significant interaction between stimulation site and mode. That is, using BP stimulation only improved MDTs at stimulation sites with broad PTCs but had no effect or sometimes a detrimental effect on MDTs at stimulation sites with sharp PTCs. This interaction could suggest that a criterion number of nerve fibers is needed to achieve optimal temporal resolution, and, to achieve optimized speech recognition outcomes, individualized selection of site-specific current focusing strategies may be necessary. These results also suggest that the removal of stimulation sites measured with poor MDTs might improve both temporal and spectral resolution.

Automatic Detection of the Inner Ears in Head CT Images Using Deep Convolutional Neural Networks

Cochlear implants (CIs) use electrode arrays that are surgically inserted into the cochlea to stimulate nerve endings to replace the natural electro-mechanical transduction mechanism and restore hearing for patients with profound hearing loss. Post-operatively, the CI needs to be programmed. Traditionally, this is done by an audiologist who is blind to the positions of the electrodes relative to the cochlea and relies on the patient's subjective response to stimuli. This is a trial-and-error process that can be frustratingly long (dozens of programming sessions are not unusual). To assist audiologists, we have proposed what we call IGCIP for image-guided cochlear implant programming. In IGCIP, we use image processing algorithms to segment the intra-cochlear anatomy in pre-operative CT images and to localize the electrode arrays in post-operative CTs. We have shown that programming strategies informed by image-derived information significantly improve hearing outcomes for both adults and pediatric populations. We are now aiming at deploying these techniques clinically, which requires full automation. One challenge we face is the lack of standard image acquisition protocols. The content of the image volumes we need to process thus varies greatly and visual inspection and labelling is currently required to initialize processing pipelines. In this work we propose a deep learning-based approach to automatically detect if a head CT volume contains two ears, one ear, or no ear. Our approach has been tested on a data set that contains over 2,000 CT volumes from 153 patients and we achieve an overall 95.97% classification accuracy.

The cochlear implant and possibilities for narrowing the remaining gaps between prosthetic and normal hearing

Background

The cochlear implant has become the standard of care for severe or worse losses in hearing and indeed has produced the first substantial restoration of a lost or absent human sense using a medical intervention. However, the devices are not perfect and many efforts to narrow the remaining gaps between prosthetic and normal hearing are underway.

Objective

To assess the present status of cochlear implants and to describe possibilities for improving them.

Results

The present-day devices work well in quiet conditions for the great majority of users. However, not all users have high levels of speech reception in quiet and nearly all users struggle with speech reception in typically noisy acoustic environments. In addition, perception of sounds more complex than speech, such as most music, is generally poor unless residual hearing at low frequencies can be stimulated acoustically in conjunction with the electrical stimuli provided by the implant. Possibilities for improving the present devices include increasing the spatial specificity of neural excitation by reducing masking effects or with new stimulus modes; prudent pruning of interfering or otherwise detrimental electrodes from the stimulation map; a further relaxation in the criteria for implant candidacy, based on recent evidence from persons with high levels of residual hearing and to allow many more people to benefit from cochlear implants; and “top down” or “brain centric” approaches to implant designs and applications.

Conclusions

Progress in the development of the cochlear implant and related treatments has been remarkable but room remains for improvements. The future looks bright as there are multiple promising possibilities for improvements and many talented teams are pursuing them.

Selecting electrode configurations for image-guided cochlear implant programming using template matching

Cochlear implants (CIs) are neural prostheses that restore hearing using an electrode array implanted in the cochlea. After implantation, the CI processor is programmed by an audiologist. One factor that negatively impacts outcomes and can be addressed by programming is cross-electrode neural stimulation overlap (NSO). We have proposed a system to assist the audiologist in programming the CI that we call image-guided CI programming (IGCIP). IGCIP permits using CT images to detect NSO and recommend deactivation of a subset of electrodes to avoid NSO. We have shown that IGCIP significantly improves hearing outcomes. Most of the IGCIP steps are robustly automated but electrode configuration selection still sometimes requires manual intervention. With expertise, distance-versus-frequency curves, which are a way to visualize the spatial relationship learned from CT between the electrodes and the nerves they stimulate, can be used to select the electrode configuration. We propose an automated technique for electrode configuration selection. A comparison between this approach and one we have previously proposed shows that our method produces results that are as good as those obtained with our previous method while being generic and requiring fewer parameters.

Measuring Cochlear Duct Length - a historical analysis of methods and results

Background

Cochlear Duct Length (CDL) has been an important measure for the development and advancement of cochlear implants. Emerging literature has shown CDL can be used in preoperative settings to select the proper sized electrode and develop customized frequency maps. In order to improve post-operative outcomes, and develop new electrode technologies, methods of measuring CDL must be validated to allow usage in the clinic.

Purpose

The purpose of this review is to assess the various techniques used to calculate CDL and provide the reader with enough information to make an informed decision on how to conduct future studies measuring the CDL.

Results

The methods to measure CDL, the modality used to capture images, and the location of the measurement have all changed as technology evolved. With recent popularity and advancement in computed tomography (CT) imaging in place of histologic sections, measurements of CDL have been focused at the lateral wall (LW) instead of the organ of Corti (OC), due to the inability of CT to view intracochlear structures. After analyzing results from methods such as directly measuring CDL from histology, indirectly reconstructing the shape of the cochlea, and determining CDL based on spiral coefficients, it was determined the three dimensional (3D) reconstruction method is the most reliable method to measure CDL. 3D reconstruction provides excellent visualization of the cochlea and avoids errors evident in other methods. Due to the number of varying methods with varying accuracies, certain guidelines must be followed in the future to allow direct comparison of CDL values between studies.

Conclusion

After summarizing and analyzing the interesting history of CDL measurements, the use of standardized guidelines and the importance of CDL for future cochlear implant developments is emphasized for future studies.

Deactivating stimulation sites based on low-rate thresholds improves spectral ripple and speech reception thresholds in cochlear implant users

The study examined whether the benefit of deactivating stimulation sites estimated to have broad neural excitation was attributed to improved spectral resolution in cochlear implant users. The subjects' spatial neural excitation pattern was estimated by measuring low-rate detection thresholds across the array [see Zhou (2016). PLoS One 11, e0165476]. Spectral resolution, as assessed by spectral-ripple discrimination thresholds, significantly improved after deactivation of five high-threshold sites. The magnitude of improvement in spectral-ripple discrimination thresholds predicted the magnitude of improvement in speech reception thresholds after deactivation. Results suggested that a smaller number of relatively independent channels provide a better outcome than using all channels that might interact.

Monopolar Detection Thresholds Predict Spatial Selectivity of Neural Excitation in Cochlear Implants: Implications for Speech Recognition

The objectives of the study were to (1) investigate the potential of using monopolar psychophysical detection thresholds for estimating spatial selectivity of neural excitation with cochlear implants and to (2) examine the effect of site removal on speech recognition based on the threshold measure. Detection thresholds were measured in Cochlear Nucleus® device users using monopolar stimulation for pulse trains that were of (a) low rate and long duration, (b) high rate and short duration, and (c) high rate and long duration. Spatial selectivity of neural excitation was estimated by a forward-masking paradigm, where the probe threshold elevation in the presence of a forward masker was measured as a function of masker-probe separation. The strength of the correlation between the monopolar thresholds and the slopes of the masking patterns systematically reduced as neural response of the threshold stimulus involved interpulse interactions (refractoriness and sub-threshold adaptation), and spike-rate adaptation. Detection threshold for the low-rate stimulus most strongly correlated with the spread of forward masking patterns and the correlation reduced for long and high rate pulse trains. The low-rate thresholds were then measured for all electrodes across the array for each subject. Subsequently, speech recognition was tested with experimental maps that deactivated five stimulation sites with the highest thresholds and five randomly chosen ones. Performance with deactivating the high-threshold sites was better than performance with the subjects' clinical map used every day with all electrodes active, in both quiet and background noise. Performance with random deactivation was on average poorer than that with the clinical map but the difference was not significant. These results suggested that the monopolar low-rate thresholds are related to the spatial neural excitation patterns in cochlear implant users and can be used to select sites for more optimal speech recognition performance.