Abstract
Objectives: Amplitudes of electrically evoked compound action potentials (eCAPs) as a function of the stimulation level constitute the eCAP amplitude growth function (AGF). The slope of the eCAP AGF (i.e., rate of growth of eCAP amplitude as a function of stimulation level), recorded from subjects with cochlear implants (CIs), has
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been widely used as an indicator of survival of cochlear nerve fibers. However, substantial variation in the approach used to calculate the slope of the eCAP AGF makes it difficult to compare results across studies. In this study, we developed an improved slope-fitting method by addressing the limitations of previously used approaches and ensuring its application for the estimation of the maximum slopes of the eCAP AGFs recorded in both animal models and human listeners with various etiologies. Design: The new eCAP AGF fitting method was designed based on sliding window linear regression. Slopes of the eCAP AGF estimated using this new fitting method were calculated and compared with those estimated using four other fitting methods reported in the literature. These four methods were nonlinear regression with a sigmoid function, linear regression, gradient calculation, and boxcar smoothing. The comparison was based on the fitting results of 72 eCAP AGFs recorded from 18 acutely implanted guinea pigs, 46 eCAP AGFs recorded from 23 chronically implanted guinea pigs, and 2094 eCAP AGFs recorded from 200 human CI users from 4 patient populations. The effect of the choice of input units of the eCAP AGF (linear versus logarithmic) on fitting results was also evaluated. Results: The slope of the eCAP AGF was significantly influenced by the slope-fitting method and by the choice of input units. Overall, slopes estimated using all five fitting methods reflected known patterns of neural survival in human patient populations and were significantly correlated with speech perception scores. However, slopes estimated using the newly developed method showed the highest correlation with spiral ganglion neuron density among all five fitting methods for animal models. In addition, this new method could reliably and accurately estimate the slope for 4 human patient populations, while the performance of the other methods was highly influenced by the morphology of the eCAP AGF. Conclusions: The novel slope-fitting method presented in this study addressed the limitations of the other methods reported in the literature and successfully characterized the slope of the eCAP AGF for various animal models and CI patient populations. This method may be useful for researchers in conducting scientific studies and for clinicians in providing clinical care for CI users.
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