TY - JOUR
T1 - Objective evaluation of intracochlear electrocochleography
T2 - repeatability, thresholds, and tonotopic patterns
AU - Schuerch, Klaus
AU - Wimmer, Wilhelm
AU - Rummel, Christian
AU - Caversaccio, Marco Domenico
AU - Weder, Stefan
N1 - Publisher Copyright:
Copyright © 2023 Schuerch, Wimmer, Rummel, Caversaccio and Weder.
PY - 2023
Y1 - 2023
N2 - Introduction: Intracochlear electrocochleography (ECochG) is increasingly being used to measure residual inner ear function in cochlear implant (CI) recipients. ECochG signals reflect the state of the inner ear and can be measured during implantation and post-operatively. The aim of our study was to apply an objective deep learning (DL)-based algorithm to assess the reproducibility of longitudinally recorded ECochG signals, compare them with audiometric hearing thresholds, and identify signal patterns and tonotopic behavior. Methods: We used a previously published objective DL-based algorithm to evaluate post-operative intracochlear ECochG signals collected from 21 ears. The same measurement protocol was repeated three times over 3 months. Additionally, we measured the pure-tone thresholds and subjective loudness estimates for correlation with the objectively detected ECochG signals. Recordings were made on at least four electrodes at three intensity levels. We extracted the electrode positions from computed tomography (CT) scans and used this information to evaluate the tonotopic characteristics of the ECochG responses. Results: The objectively detected ECochG signals exhibited substantial repeatability over a 3-month period (bias-adjusted kappa, 0.68; accuracy 83.8%). Additionally, we observed a moderate-to-strong dependence of the ECochG thresholds on audiometric and subjective hearing levels. Using radiographically determined tonotopic measurement positions, we observed a tendency for tonotopic allocation with a large variance. Furthermore, maximum ECochG amplitudes exhibited a substantial basal shift. Regarding maximal amplitude patterns, most subjects exhibited a flat pattern with amplitudes evenly distributed over the electrode carrier. At higher stimulation frequencies, we observed a shift in the maximum amplitudes toward the basal turn of the cochlea. Conclusions: We successfully implemented an objective DL-based algorithm for evaluating post-operative intracochlear ECochG recordings. We can only evaluate and compare ECochG recordings systematically and independently from experts with an objective analysis. Our results help to identify signal patterns and create a better understanding of the inner ear function with the electrode in place. In the next step, the algorithm can be applied to intra-operative measurements.
AB - Introduction: Intracochlear electrocochleography (ECochG) is increasingly being used to measure residual inner ear function in cochlear implant (CI) recipients. ECochG signals reflect the state of the inner ear and can be measured during implantation and post-operatively. The aim of our study was to apply an objective deep learning (DL)-based algorithm to assess the reproducibility of longitudinally recorded ECochG signals, compare them with audiometric hearing thresholds, and identify signal patterns and tonotopic behavior. Methods: We used a previously published objective DL-based algorithm to evaluate post-operative intracochlear ECochG signals collected from 21 ears. The same measurement protocol was repeated three times over 3 months. Additionally, we measured the pure-tone thresholds and subjective loudness estimates for correlation with the objectively detected ECochG signals. Recordings were made on at least four electrodes at three intensity levels. We extracted the electrode positions from computed tomography (CT) scans and used this information to evaluate the tonotopic characteristics of the ECochG responses. Results: The objectively detected ECochG signals exhibited substantial repeatability over a 3-month period (bias-adjusted kappa, 0.68; accuracy 83.8%). Additionally, we observed a moderate-to-strong dependence of the ECochG thresholds on audiometric and subjective hearing levels. Using radiographically determined tonotopic measurement positions, we observed a tendency for tonotopic allocation with a large variance. Furthermore, maximum ECochG amplitudes exhibited a substantial basal shift. Regarding maximal amplitude patterns, most subjects exhibited a flat pattern with amplitudes evenly distributed over the electrode carrier. At higher stimulation frequencies, we observed a shift in the maximum amplitudes toward the basal turn of the cochlea. Conclusions: We successfully implemented an objective DL-based algorithm for evaluating post-operative intracochlear ECochG recordings. We can only evaluate and compare ECochG recordings systematically and independently from experts with an objective analysis. Our results help to identify signal patterns and create a better understanding of the inner ear function with the electrode in place. In the next step, the algorithm can be applied to intra-operative measurements.
KW - ECochG
KW - cochlear implants
KW - deep learning
KW - electric acoustic stimulation
KW - electrophysiology
KW - hearing loss
KW - hearing preservation
KW - signal processing
UR - http://www.scopus.com/inward/record.url?scp=85168661782&partnerID=8YFLogxK
U2 - 10.3389/fneur.2023.1181539
DO - 10.3389/fneur.2023.1181539
M3 - Article
AN - SCOPUS:85168661782
SN - 1664-2295
VL - 14
JO - Frontiers in Neurology
JF - Frontiers in Neurology
M1 - 1181539
ER -