Comparison in New Cochlear Implanted Subjects of a Tonotopy-based Fitting With or Without Fine Structure Coding

Comparison of Speech Understanding and Melodic Perception of Two Tonotopic Fitting Modalities With or Without Fine Structure in Newly Implanted Cochlear Patients: Randomized Double-blind Crossover Study.

Brief Summary:

Main objective:

Comparison of a tonotopy based fitting strategy (TFS) with fine structure coding to a tonotopy based fitting strategy without fine structure coding (TnoFS) for speech perception in noise.

Secondary objectives:

Comparison of TFS to TnoFS for the perception of musical elements (contour test).

Comparison of TFS to TnoFS for speech perception in quiet

Comparison of TFS to TnoFS for the qualitative preference for the listening of musical pieces.

Comparison of TFS to TnoFS for the melodic recognition

Study Overview

• Status: Completed
• Conditions: Sensorineural Hearing Loss, Bilateral
• Intervention / Treatment: Device: TnoFs then TFS (Cochlear implant); Device: TFS then TnoFS (Cochlear implant)

Detailed Description

Introduction: Cochlear implantation allows the rehabilitation of profound bilateral deafness, restoring speech perception and verbal communication when the traditional hearing aid no longer provides satisfactory hearing gain (Nimmons et al.).

A cochlear implant includes an electrode array and its functioning is based on the principle of cochlear tonotopy: each electrode encodes a frequency spectrum according to its position in the cochlea (high frequencies are assigned to the basal electrodes and low frequencies to the apical electrodes). The cochlear implant thus breaks down the frequency spectrum into a number of frequency bands via bandpass filters corresponding to the number of electrodes in the implant. During the fitting these bands can be modified by the audiologist.

The fitting software developed by the manufacturers proposed a default fitting with a lower limit between 100 and 250 Hz according to the brands and an upper limit of about 8500 Hz. The frequency bands assigned to each electrode follow a logarithmic scale with the high frequencies for the basal electrodes and the low frequencies for the apical electrodes. This distribution takes into account the number of active electrodes but does not take into account the anatomy and the natural cochlear tonotopy specific to each patient.

Several studies have analyzed the anatomical variations of the cochlear dimensions: size of the cochlea and the ratio between the contact surfaces of the electrodes with the cochlea are variable from one patient to another (Stakhovskaya O et al., P. Pelliccia et al.).

The insertion depth during surgery is also variable due to parameters related to the patients as well as to the operator, which seems to impact the understanding of speech in noise (Deep electrode insertion and sound coding in cochlear implants - Ingeborg Hochmair et al.).

Mathematical algorithms have recently been developed to estimate the cochlear tonotopy of each patient from a CT scan assessment (Jiam et al., Sridhar et al.). CT imaging of the implanted ear combined with 3D reconstruction software, provides cochlear length measurements (Cochlear length determination using Cone Beam Computed Tomography in a clinical setting - Würfel et al .). Using this approach it is possible to measure the position of each electrode relative to the cochlear apex. These measurements are applied to the modified Greenwood equation to obtain the tonotopic frequency for each electrode and to determine for each patient a fitting based on the tonotopy of each electrode.

Conventional stimulation strategies in cochlear implants (e.g. advanced combination encoder (ACE), continuous interleaved sampling (CIS)) use the place of the electrode to code the frequency by sending low frequency information on the apical electrodes and high frequency information on the basal electrodes. The stimulation rate of the electrodes is constant. The pitch is only partially transmitted by these conventional strategies which would explain the poor results of cochlear implants in the perception of music. In the FineHearing strategy of the MED-EL implant, the rate of stimulation on the low-frequency electrodes is related to the frequency of the sound and makes it possible to code the frequency information temporally.

Rader & al. 2016 have studied the contribution of adding to the tonotopic coding of the frequency (classical strategy) a temporal coding of the information by varying the stimulation rate. The results obtained show that providing this frequency information by time coding makes it possible to obtain perceived pitch much closer to the expected pitch (of normal-hearing) and less variability, especially at low frequencies. With fixed stimulation rate (classical strategy) low frequencies are poorly coded, whereas with the variable stimulation rate they are better coded. In addition, Landsberger et al. [2018] studied in six subjects with a MED-EL implant the perception of a temporal coding according to the position of the electrodes with a long insertion: middle or apical position. The results seem to show that the temporal coding of the frequency would be more reliable than the spatial coding (related to the position of the electrode) at the apex, and the reverse on the electrodes in the middle position. Studies have shown that the FineHearing strategy can provide benefits over the classic High-Definition Continuous Interleaved Sampling (HDCIS) strategy in tasks involving the fundamental F0 such as speech recognition in noise (after a certain learning time) [Kleine Punte & al. 2014 ; Vermeire & al. 2010], the perception of music [Roy & al. 2015 ; Roy & al. 2016] or the perceived quality of pitch [Müller & al. 2012].

MED-EL's FineHearing coding strategy with a tonotopic-based fitting could therefore allow better transmission of pitch and in particular improve the speech recognition in noise compared to the same tonotopic-based fitting without FineHearing coding.

Main objective:

Comparison of a tonotopy based fitting strategy (TFS) with fine structure coding to a tonotopy based fitting strategy without fine structure coding (TnoFS) for speech perception in noise.

Secondary objectives:

Comparison of TFS to TnoFS for the perception of musical elements (contour test).

Comparison of TFS to TnoFS for speech perception in quiet

Comparison of TFS to TnoFS for the qualitative preference for the listening of musical pieces.

Comparison of TFS to TnoFS for the melodic recognition

Plan of the study:

It is a prospective open monocentric randomized crossover study: measures will be done on the patient at 6 weeks and 12 weeks post-activation.

• Study Type: Interventional
• Enrollment (Actual): 21
• Phase: Not Applicable

Contacts and Locations

Study Locations

• France
  • Rennes, France, 35000
    • Chu Rennes

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• Adult patient (>= 18 years old) speaking French
• Patient who fulfils the criteria for cochlear implantation
• Total hearing loss for less than 5 years

Exclusion Criteria:

• retro-cochlear pathology: auditory neuropathy, vestibular schwannoma
• patient with residual hearing < 60 dB HL at 250 Hz and < 80 dB HL at 500 Hz

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Other
• Allocation: Randomized
• Interventional Model: Crossover Assignment
• Masking: Double

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Active Comparator: TnoFS then TFS; Cochlear Implant with TnoFS first during 6 weeks then with TFS during 6 weeks	Device: TnoFs then TFS (Cochlear implant); Cochlear implant with tonotopy-based fitting without fine structure coding then with fine structure coding
Active Comparator: TFS then TnoFS; Cochlear Implant with TFS first during 6 weeks then with TnoFS during 6 weeks	Device: TFS then TnoFS (Cochlear implant); Cochlear implant with tonotopy-based fitting with fine structure coding then without fine structure coding

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Speech recognition in noise	The speech recognition in noise is evaluated with syllabic list of 40 phonemes. The patient has to recognize 20 syllables. The phonemes are scored: each good answer is scored 1 yielding a total between 0 and 1 (or 0% and 100%). Signal-noise-ratios of 9, 6, 3 and 0 dB will be tested with speech at 65 dB SPL.	at 6 weeks post-activation
Speech recognition in noise	The speech recognition in noise is evaluated with syllabic list of 40 phonemes. The patient has to recognize 20 syllables. The phonemes are scored: each good answer is scored 1 yielding a total between 0 and 1 (or 0% and 100%). Signal-noise-ratios of 9, 6, 3 and 0 dB will be tested with speech at 65 dB SPL.	at 12 weeks post-activation

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Melodic contour test	The test stimuli of the melodic contour test (Galvin et al. 2007) are melodic contours composed of 5 notes of equal duration whose frequencies correspond to musical intervals. Nine distinct musical patterns have to be identified by the patient. Each good answer is scored 1 yielding a total between 0 and 1 (or 0% and 100%).	at 6 weeks post-activation
Melodic contour test	The test stimuli of the melodic contour test (Galvin et al. 2007) are melodic contours composed of 5 notes of equal duration whose frequencies correspond to musical intervals. Nine distinct musical patterns have to be identified by the patient. Each good answer is scored 1 yielding a total between 0 and 1 (or 0% and 100%).	at 12 weeks post-activation
Speech recognition in quiet	The speech recognition in quiet is evaluated with syllabic list of 40 phonemes. The patient has to recognize 20 syllables. The phonemes are scored: each good answer is scored 1 yielding a total between 0 and 1 (or 0% and The speech recognition in quiet is evaluated with syllabic list of 40 phonemes. The patient has to recognize 20 syllables. The phonemes are scored: each good answer is scored 1 yielding a total between 0 and 1 (or 0% and 100%).	at 6 weeks post-activation
Speech recognition in quiet	The speech recognition in quiet is evaluated with syllabic list of 40 phonemes. The patient has to recognize 20 syllables. The phonemes are scored: each good answer is scored 1 yielding a total between 0 and 1 (or 0% and The speech recognition in quiet is evaluated with syllabic list of 40 phonemes. The patient has to recognize 20 syllables. The phonemes are scored: each good answer is scored 1 yielding a total between 0 and 1 (or 0% and 100%).	at 12 weeks post-activation
Qualitative measure of music	The Gabrielsson scale (1988) is used to evaluate perceived sound quality as a multidimensional phenomenon, that is composed of a number of separate perceptual dimensions. Eight perceptual dimensions are evaluated: clarity, fullness, brightness vs dullness, hardness/sharpness vs softness, spaciousness, nearness, extraneous sound, loudness.	at 6 weeks post-activation
Qualitative measure of music	The Gabrielsson scale (1988) is used to evaluate perceived sound quality as a multidimensional phenomenon, that is composed of a number of separate perceptual dimensions. Eight perceptual dimensions are evaluated: clarity, fullness, brightness vs dullness, hardness/sharpness vs softness, spaciousness, nearness, extraneous sound, loudness.	at 12 weeks post-activation
Melodic recognition	Each participant had to choose, among ten pieces (List in Figure 6), two pieces of which he knew the melody well. The songs were each played twice for 40 seconds. After each listening, the participant had to indicate on a visual analogical scale the level of recognition of the melody. The minimum, score 0, means that the music sample was not recognized at all. The maximum, score 10, means that the extract has been fully recognized.	at 6 weeks post-activation
Melodic recognition	Each participant had to choose, among ten pieces (List in Figure 6), two pieces of which he knew the melody well. The songs were each played twice for 40 seconds. After each listening, the participant had to indicate on a visual analogical scale the level of recognition of the melody. The minimum, score 0, means that the music sample was not recognized at all. The maximum, score 10, means that the extract has been fully recognized.	at 12 weeks post-activation

Collaborators and Investigators

• Sponsor: MED-EL Elektromedizinische Geräte GesmbH
• Investigators: Principal Investigator: Gwenaelle Creff, Dr, Rennes University Hospital

Study record dates

Study Major Dates

• Study Start (Actual): April 15, 2023
• Primary Completion (Actual): December 1, 2024
• Study Completion (Actual): April 1, 2025

Study Registration Dates

• First Submitted: February 22, 2023
• First Submitted That Met QC Criteria: March 3, 2023
• First Posted (Actual): March 6, 2023

Study Record Updates

• Last Update Posted (Actual): April 8, 2025
• Last Update Submitted That Met QC Criteria: April 7, 2025
• Last Verified: April 1, 2025

More Information

Terms related to this study

• Keywords: cochlear implant strategy; tonotopy-based fitting; fine structure coding
• Additional Relevant MeSH Terms: Neurologic Manifestations; Nervous System Diseases; Otorhinolaryngologic Diseases; Sensation Disorders; Ear Diseases; Hearing Disorders; Seizures; Hearing Loss; Hearing Loss, Sensorineural; Hearing Loss, Bilateral
• Other Study ID Numbers: MED_EL_COFRET_Rennes_study

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No