SpeedCAP: An Efficient Method for Estimating Neural Activation Patterns Using Electrically Evoked Compound Action-Potentials in Cochlear Implant Users.
SpeedCAP: An Efficient Method for Estimating Neural Activation Patterns Using Electrically Evoked Compound Action-Potentials in Cochlear Implant Users.
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DOI：
10.1097/aud.0000000000001305
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发表时间：
2023-05-01
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影响因子：
3.7
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电诱发复合动作电位 (ECAP) 可以使用人工耳蜗 (CI) 中的电极进行记录，并代表电刺激听觉神经的同步反应。 ECAP 可以使用前向掩蔽方法获得，该方法分别或组合测量对探针和掩蔽电极的神经反应。全景 ECAP (PECAP) 分析使用掩蔽电极和探针电极的多种组合获得的测量 ECAP，并使用非线性优化算法来估计每个电极的电流分布和沿耳蜗的神经健康状况。然而，在临床中使用多种电极组合来测量 ECAP 过于耗时。在这里，我们提出并评估了 SpeedCAP，这是一种获取 PECAP 测量的快速方法，通过利用多个 ECAP 测量之间的冗余来最大限度地减少记录时间。在第一项研究中，Cochlear Ltd. CI 的 11 名用户参与了研究。根据标准 PECAP 记录范例，对于用户 MAP 中所有有源电极的掩蔽器和探针电极的每种组合，使用前向掩蔽伪影消除技术以最舒适的响度级别 (MCL) 记录 ECAP。然后使用相同的电流水平和记录参数通过 SpeedCAP 方法收集相同用户的 ECAP。然后比较两种条件之间的 ECAP 幅度，以及使用 Garcia 等人先前描述的 PECAP 方法计算的神经健康状况和电流分布的相应估计。第二项研究在 8 名 CI 患者术中测量了 SpeedCAP，所有掩蔽器和探针均处于相同的电流水平，以评估可行性。将掩蔽器和探针出现在同一电极上的条件子集的 ECAP 与使用标准临床软件所利用的较慢方法获得的 ECAP 进行比较。数据收集时间从约 45 分钟减少到约 8 分钟。术后 PECAP 和 SpeedCAP 数据的归一化均方根误差 (RMSE) 重复性指标以及 PECAP 和 SpeedCAP 数据之间计算的 RMSE 之间没有显着差异。该比较实现了 80% 的功效来检测低至 8.2% RMSE 的效应大小。当消除参与者之间的差异后，所有电极的 SpeedCAP 和 PECAP 条件之间的神经健康 (r = 0.73) 和电流扩散 (r = 0.65) 估计值均显着相关 (p < 0.0001，df = 218)，并且显示 RMSE 误差分别为 12.7±±4.7% 和 16.8±±8.8%（其中± 边际代表 95% 置信区间）。在第二项研究中，所有患者均获得了有效的 ECAP，证明了 SpeedCAP 术中的可行性。术后和术中 ECAP 测量之间的 RMSE 没有检测到显着差异，比较达到 80% 的功效来检测低至 13.3% RMSE 的效应大小。 SpeedCAP 效率的提高可节省时间，促进常规临床实践中的多电极 ECAP 记录。 SpeedCAP 数据收集速度足够快，足以在术中进行记录，并且 ECAP 幅度的误差不超过 8.2%。此后，此类测量结果可以提交给 PECAP 等模型，以提供患者特定的神经激活模式，从而为临床 MAP 的编程提供信息，并确定 CI 用户的电极-神经界面表现不佳的原因。这些测量的速度和准确性也引发了一系列需要解决的其他研究问题。
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) analyses measured ECAPs obtained 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. Here, we propose and evaluate SpeedCAP, a speedy method for obtaining the PECAP measurements that minimizes recording time by exploiting redundancies between multiple ECAP measures. In the first study, 11 users of Cochlear Ltd. CIs took part. ECAPs were recorded using the forward-masking artifact-cancelation 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 previously described by Garcia et al. The second study measured SpeedCAP intraoperatively 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 with those obtained using the slower approach leveraged by the standard clinical software. Data collection time was reduced from ≈45 to ≈8 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. The comparison achieved 80% power to detect effect sizes down to 8.2% RMSE. 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, and showed RMSE errors of 12.7 ± 4.7% and 16.8 ± 8.8%, respectively (with the ± margins representing 95% confidence intervals). Valid ECAPs were obtained in all patients in the second study, demonstrating intraoperative feasibility of SpeedCAP. No significant differences in RMSEs were detectable between post- and intra-operative ECAP measurements, with the comparison achieving 80% power to detect effect sizes down to 13.3% RMSE. The improved efficiency of SpeedCAP provides time savings facilitating multi-electrode ECAP recordings in routine clinical practice. SpeedCAP data collection is sufficiently quick to record intraoperatively, and adds no more than 8.2% 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 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.