SpeedCAP: An Efficient Method for Estimating Neural Activation Patterns Using Electrically-Evoked Compound Action-Potentials in Cochlear Implant Users

Objectives: Electrically-Evoked Compound Action-Potentials (ECAPs) can be recorded using the electrodes in a cochlear implant (CI) and represent the synchronous responses of the electrically-stimulated auditory-nerve. ECAPs can be obtained using a forward-masking method that measures the neural response to a probe and masker electrode separately and in combination. The Panoramic ECAP (PECAP) method measures ECAPs using multiple combinations of masker and probe electrodes and uses a nonlinear optimization algorithm to estimate current spread from each electrode and neural health along the cochlea. However, the measurement of ECAPs from multiple combinations of electrodes is too time-consuming for use in clinics. This study proposes and evaluates a fast version of the PECAP measurements, SpeedCAP, that minimises recording time by exploiting redundancies between multiple ECAP measures, and that can be applied to methods where multiple ECAPs are required. Design: In the first study, 11 users of Cochlear Limited CIs took part. ECAPs were recorded using the forward-masking artefact-cancellation technique at the most comfortable loudness level (MCL) for every combination of masker and probe electrodes for all active electrodes in the users’ MAPs, as per the standard PECAP recording paradigm. The same current levels and recording parameters were then used to collect ECAPs in the same users with the SpeedCAP method. The ECAP amplitudes were then compared between the two conditions, as were the corresponding estimates of neural health and current spread calculated using the PECAP method described by Garcia et al (2021). The second study measured SpeedCAP intra-operatively in 8 CI patients and with all maskers and probes presented at the same current level to assess feasibility. ECAPs for the subset of conditions where the masker and probe were presented on the same electrode were compared to those obtained using the slower approach leveraged by the standard clinical software. Results: Data collection time was reduced from 45 (PECAP) to 8 (SpeedCAP) minutes. There were no significant differences between normalized root mean squared error (RMSE) repeatability metrics for post-operative PECAP and SpeedCAP data, nor for the RMSEs calculated between PECAP and SpeedCAP data. When between-participant differences were removed, both the neural health (r = 0.73) and current spread (r = 0.65) estimates were significantly correlated (p < 0.0001, df = 218) between SpeedCAP and PECAP conditions across all electrodes. Valid ECAPs were obtained in all patients in the second study, demonstrating intra-operative feasibility of SpeedCAP. No significant differences in RMSEs were detectable between post- and intra-operative ECAP measurements. Conclusions: The improved efficiency of SpeedCAP provides time savings facilitating multi-electrode ECAP recordings in routine clinical practice. The SpeedCAP data collection is sufficiently quick to record intra-operatively, and adds no significant error to the ECAP amplitudes. Such measurements could thereafter be submitted to models such as PECAP to provide patient-specific patterns of neural activation to inform programming of clinical MAPs and/or identify causes of poor performance at the electrode-nerve interface of CI users. The speed and accuracy of these measurements also opens up a wide range of additional research questions to be addressed.