Cochlear Implant Fitting Methods for Hearing Loss

(CALOS4 Trial)

Recruiting at 4 trial locations

Overseen By Anke Plasmans

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Cochlear

Disqualifiers: Auditory neuropathy, Visual impairment, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

Duration: 4 weeks

17 Participants Needed

Trial Summary

What is the purpose of this trial?

This study aims to collect data in newly implanted cochlear implant-recipients to inform future development of fitting methods to optimally and efficiently program a cochlear implant.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications.

What data supports the effectiveness of the treatment methods used in the Cochlear Implant Fitting Methods for Hearing Loss trial?

Research shows that using personalized and optimized fitting methods for cochlear implants, which include objective data and machine-learning algorithms, can improve speech recognition and hearing outcomes. Additionally, studies indicate that combining behavioral and electrophysiological measures can help predict optimal comfort levels for cochlear implant users, leading to better hearing experiences. ^{1 2 3 4 5}

How does the Categorical Loudness Scaling (CLS) Based Fitting treatment for cochlear implants differ from other treatments?

The Categorical Loudness Scaling (CLS) Based Fitting treatment for cochlear implants is unique because it uses a method to scale loudness perception across different sound levels, allowing for more personalized and accurate adjustments of the implant's settings. This approach focuses on achieving normal loudness perception by defining specific loudness categories, which can be adjusted for each electrode, providing a tailored hearing experience for the user. ^{1 3 6 7 8}

Research Team

Anke Plasmans

Principal Investigator

Cochlear

Eligibility Criteria

This trial is for adults over 18 who became deaf after age 2 and now have a CI600 or CI500 series cochlear implant. Participants must understand the language used in speech tests and agree to follow the study rules.

Inclusion Criteria

Unilaterally implanted with the CI600 Series (CI612, CI622, CI632) or CI500 series (CI512, CI522, CI532) cochlear implant

Willingness to participate in and comply with all requirements of the protocol

Willing and able to provide written informed consent

Exclusion Criteria

Subject who will be programmed with an acoustic component in the implanted ear

Pure tone average (average of unaided thresholds at 0.5, 1, 2 and 4 kHz) less than or equal to 30 dB HL and aided word score of more than 80% in the contralateral ear

Score below 3 on the screening subset of questions from the Mobile Device Proficiency Questionnaire

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Treatment

Participants receive both Categorical Loudness Scaling Based Fitting and Behavioural Fitting with 4 weeks experience of both MAPS

4 weeks

Multiple visits for fitting and testing

Follow-up

Participants are monitored for performance outcomes and further refinement of fitting methods

4 weeks

Follow-up visits for outcome measures

Treatment Details

Interventions

• Behavioural fitting
• Categorical loudness scaling based fitting

Trial Overview The study compares two ways of setting up cochlear implants: one uses behavioral fitting with Custom Sound Suite software, and the other uses loudness scaling with Nexus System. It's to find out which method works best post-activation.

Participant Groups

Group I: Participants receiving both Categorical Loudness Scaling Based Fitting and behavioural fitting. Experimental Treatment 2 Interventions

Participants will receive a categorical loudness scaling based fitting (Interventional) and behavioural fitting with 4 weeks experience of both MAPS

Who Is Running the Clinical Trial?

Cochlear

Lead Sponsor

Trials

96

Recruited

6,300+

Headquarters

Sydney, Australia

Dig Howitt

Cochlear

Chief Executive Officer since 2018

BE (Hons), MBA

Michael del Prado

Cochlear

Chief Medical Officer since 2022

MD, MSc, FRACP, FAAHMS, FAICD

QbD Clinical

Industry Sponsor

Trials

5

Recruited

400+

QbD Clinical

Collaborator

Trials

6

Recruited

460+

Avania

Industry Sponsor

Trials

59

Recruited

10,000+

Findings from Research

The analysis of 39,885 MAPs from 47 cochlear implant recipients revealed distinct comfort level profiles for different electrode arrays, indicating the need for tailored fitting approaches.

The new Custom Sound Pro fitting software allows clinicians to efficiently create accurate comfort level profiles with just nine Neural Response Telemetry thresholds, while 99% of clinical tasks were completed successfully on the first use, enhancing both usability and patient-centered care.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Development of Custom Sound® Pro software utilising big data and its clinical evaluation. Maruthurkkara, S., Bennett, C.[2023]

Cochlear implants (CIs) effectively restore hearing in individuals with total sensorineural hearing loss by converting sound into electrical signals for the auditory nerve, but the current fitting process is often generic and may not optimize individual user outcomes.

To improve speech recognition variability among CI users, the authors propose using objective, patient-specific data and machine-learning algorithms to create personalized fitting procedures that account for individual differences in auditory system function and electrode activation.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Towards personalized and optimized fitting of cochlear implants. Van Opstal, AJ., Noordanus, E.[2023]

Cochlear implant fitting has evolved to include objective electrophysiologic measures and expert knowledge, moving away from solely relying on behavioral responses, which enhances the accuracy of the fitting process.

Recent advancements aim to automate and streamline the fitting process, reducing the time needed for adjustments and allowing for real-time testing of settings, ultimately improving the quality of hearing and speech comprehension for users.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

[Cochlear implant fitting strategies]. Hoppe, U., Liebscher, T., Hornung, J.[2019]

The study involved 10 profoundly hearing impaired children aged 2 to 7 years, and it demonstrated that multi-modal electrophysiological tests can effectively predict optimal comfort levels (M-Levels) for cochlear implant programming, especially in challenging cases where behavioral responses are hard to obtain.

Significant positive correlations were found between electrophysiological thresholds and behavioral comfort levels over the first year of implant use, indicating that this statistical method can reliably assist audiologists in creating effective cochlear implant maps (MAPs) when direct behavioral measurements are difficult.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Electrophysiological Correlates of Behavioral Comfort Levels in Cochlear Implantees: A Prospective Study. Raghunandhan, S., Ravikumar, A., Kameswaran, M., et al.[2020]

The study involved 10 profoundly hearing impaired children aged 2 to 7 years, and it found that multi-modal electrophysiological tests (like NRI, ESRT, and EABR) showed significant positive correlations with behavioral comfort levels (M-levels) over the first year of cochlear implant use.

Predictive formulae derived from these correlations can help audiologists set initial MAPs in 'difficult to MAP' cases, but individual variability means that behavioral measures are still essential for optimizing these settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A clinical study of electrophysiological correlates of behavioural comfort levels in cochlear implantees. Raghunandhan, S., Ravikumar, A., Kameswaran, M., et al.[2014]

Cochlear implant recipients were able to categorize loudness levels of electric and acoustic stimuli, helping to establish a normal loudness perception across the dynamic range of sounds.

The study suggests that individual mapping functions for cochlear implants may need to be flexible and specific to each channel to optimize loudness perception, as one mapping function may not work for all channels.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Indication for the need of flexible and frequency specific mapping functions in cochlear implant speech processors. Hoth, S.[2018]

The study examined the relationship between current levels for cochlear implant sound processor fitting and compound action potential thresholds measured by Neural Response Telemetry (NRT), finding that the correlation between NRT and behavioral measures is weak due to individual variability among implantees.

A proposed model suggested that measuring the effect of interphase gap on NRT amplitude could improve the predictability of NRT thresholds, but this hypothesis was not supported in a small experimental group of eight subjects, indicating the need for further research to enhance the utility of NRT in clinical settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A different approach to using neural response telemetry for automated cochlear implant processor programming. McKay, CM., Fewster, L., Dawson, P.[2019]

The study involving six Nucleus-22 cochlear implant users found that the relationship between loudness and electrical stimulation varies significantly among individuals, indicating a need for personalized mapping of acoustic amplitudes to electric currents.

Loudness growth was influenced by stimulation rate and electrode configuration, with some subjects showing nonlinear loudness responses at lower stimulation rates, suggesting that low-frequency stimulation may be processed differently across electrode locations.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Loudness growth in cochlear implants: effect of stimulation rate and electrode configuration. Fu, QJ.[2007]

References

1. England pubmed.ncbi.nlm.nih.gov

Development of Custom Sound® Pro software utilising big data and its clinical evaluation. [2023]

2. Switzerland pubmed.ncbi.nlm.nih.gov

Towards personalized and optimized fitting of cochlear implants. [2023]

3. Germany pubmed.ncbi.nlm.nih.gov

[Cochlear implant fitting strategies]. [2019]

4. India pubmed.ncbi.nlm.nih.gov

Electrophysiological Correlates of Behavioral Comfort Levels in Cochlear Implantees: A Prospective Study. [2020]

5. England pubmed.ncbi.nlm.nih.gov

A clinical study of electrophysiological correlates of behavioural comfort levels in cochlear implantees. [2014]

6. Germany pubmed.ncbi.nlm.nih.gov

Indication for the need of flexible and frequency specific mapping functions in cochlear implant speech processors. [2018]

7. United States pubmed.ncbi.nlm.nih.gov

A different approach to using neural response telemetry for automated cochlear implant processor programming. [2019]

8. Netherlands pubmed.ncbi.nlm.nih.gov

Loudness growth in cochlear implants: effect of stimulation rate and electrode configuration. [2007]