A Broadly Applicable Method for Characterizing the Slope of the Electrically Evoked Compound Action Potential Amplitude Growth Function.
A Broadly Applicable Method for Characterizing the Slope of the Electrically Evoked Compound Action Potential Amplitude Growth Function.
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DOI：
10.1097/aud.0000000000001084
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发表时间：
2022
期刊：
影响因子：
3.7
通讯作者：
He S
中科院分区：
文献类型：
--
作者：
Skidmore J;Ramekers D;Colesa DJ;Schvartz-Leyzac KC;Pfingst BE;He S
电诱发复合动作电位（eCAP）振幅作为刺激水平的函数构成了eCAP振幅生长函数（AGF）。植入人工耳蜗（CIs）的受试者记录的eCAP AGF斜率（即eCAP振幅随刺激水平的增长速率）已被广泛用作耳蜗神经纤维存活的指标。然而，用于计算eCAP AGF斜率的方法存在很大差异，这使得很难比较不同研究的结果。在这项研究中，我们开发了一种改进的斜率拟合方法，解决了以前使用的方法的局限性，并确保其适用于估计动物模型和各种病因的人类听者记录的eCAP agf的最大斜率。设计了基于滑动窗口线性回归的eCAP AGF拟合新方法。计算了使用这种新拟合方法估计的eCAP AGF的斜率，并与文献中报道的其他四种拟合方法估计的斜率进行了比较。这四种方法分别是s型函数非线性回归、线性回归、梯度计算和箱车平滑。比较基于18只急性植入豚鼠记录的72个eCAP agf， 23只慢性植入豚鼠记录的46个eCAP agf，以及来自4个患者群体的200名人类CI使用者记录的2094个eCAP agf的拟合结果。对eCAP AGF（线性vs对数）输入单元的选择对拟合结果的影响也进行了评估。斜率拟合方法和输入单元的选择对eCAP AGF的斜率有显著影响。总体而言，使用所有五种拟合方法估计的斜率反映了人类患者群体中已知的神经存活模式，并与语音感知评分显著相关。然而，在所有五种动物模型拟合方法中，使用新开发的方法估计的斜率与螺旋神经节神经元密度的相关性最高。此外，该方法可以可靠准确地估计四种患者群体的斜率，而其他方法的性能受到eCAP AGF形态的高度影响。本研究提出的新的斜率拟合方法解决了文献中报道的其他方法的局限性，并成功地表征了各种动物模型和CI患者群体的eCAP AGF斜率。这种方法可能对研究人员进行科学研究和临床医生为CI用户提供临床护理有用。
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 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. 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 to 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 2,094 eCAP AGFs recorded from 200 human CI users from four patient populations. The effect of the choice of input units of the eCAP AGF (linear vs logarithmic) on fitting results was also evaluated. 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 four human patient populations, while the performance of the other methods was highly influenced by the morphology of the eCAP AGF. 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.