The use of enhanced neural response imaging to get better cochlear implant fitting for children and adults

使用增强神经反应成像为儿童和成人提供更好的人工耳蜗植入

• 批准号: EP/H000682/1
• 负责人: Robert Morse
• 金额: $ 49.26万
• 依托单位: Aston University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2009
• 资助国家: 英国
• 起止时间: 2009 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FH000682%2F1
• 关键词: use; enhanced; neural; response; imaging

People with more severe hearing loss can be helped to hear again using a cochlear implant - a surgically implanted device that electrically stimulates the cochlear nerve (the nerve of hearing). Part of the device is a set of electrodes within the cochlea (the inner ear). Good speech perception with cochlear implants depends on appropriate adjustment of device parameters, the fitting , by an audiologist. With adults, the initial fitting is usually based on perceptual measurements that require verbal feedback from the patient. When verbal feedback is not possible, the parameters are typically set relative to the minimum level required to get a measurable electrical compound action potential (ECAP) - the summed electrical response from all the nerve fibres that can be recorded by modern cochlear implants. Standard ECAP methods, however, do not lead to a good estimate of perceptual threshold because the rate of stimulation used is much lower than that used for everyday listening; fitting based on ECAPs is therefore suboptimal. Based on our previous animal studies, we are proposing a new method to measure the ECAP threshold in humans. This method involves measuring the variability of an ECAP rather than its average size and will be both more accurate and faster. We will test the approach with cochlear implants patients from Selly Oak Hospital (Birmingham) and the House Ear Institute (Los Angeles); all tests will be in collaboration with Advanced Bionics SARL who will provide the hardware required to test patients.We will combine this method with a computer model to predict the number of cochlear nerve fibres in different regions of the patient's cochlea and determine how the current from each electrode spreads throughout the cochlea. Patient-specific models are required to account for the substantial intersubject variability arising, for example, from underlying pathology, the degree of nerve survival, and electrode placement during surgery. The model will be used to guide fitting and decide, for example, which electrodes should be active. This combination of physiological and computational techniques will overcome the limitation of using ECAPs alone to determine channel interaction (how the nerve activity generated by different electrodes overlap): With the standard use of ECAPs to gauge channel interaction, the effect of fibre distribution and current spread cannot be separated. Such a distinction is clinically important because electrodes need not be made inactive for low nerve survival alone.During the project, these patient-specific models will be extended to predict the pattern of nerve activity in response to more general stimuli. The initial model will be modified so that nerve fibres are simulated by a nerve model we have previously developed. The patient-specific parameters from the model will be selected to match ECAP data, which will require the development of novel physiological methods to improve the reliability of the data. In the later stages of the project, the model will be used to relate perceptual measures to the predicted nerve activity and therefore enable a greater understanding of neural mechanisms underlying the sensory perception of electrical and acoustic stimulation. This will lead to better cochlear implant design. Contemporary fitting by an audiologist is expensive and insufficient to enable a systematic investigation of cochlear implant parameters. In future programmes of work, extended patient-specific models will be used to quickly highlight potentially useful parameter values for standard strategies, e.g. the optimum stimulation rate, and to guide the development of novel strategies. All the above ECAP methods and models will be validated with patients with whom verbal feedback is possible. The enhanced fitting procedures derived in this project are expected to increase speech intelligibility and lead to a better quality-of-life for cochlear implant users.

听力损失较严重的人可以通过人工耳蜗重新听到声音。人工耳蜗是一种通过外科手术植入的装置，通过电刺激耳蜗神经（听觉神经）。该装置的一部分是耳蜗（内耳）内的一组电极。良好的语音感知与人工耳蜗植入取决于设备参数的适当调整，拟合，听力学家。对于成人，最初的拟合通常是基于知觉测量，需要患者的口头反馈。当口头反馈不可能时，这些参数通常被设定为获得可测量的复合动作电位（ECAP）所需的最低水平，ECAP是现代人工耳蜗可以记录的所有神经纤维的总电反应。然而，标准的ECAP方法并不能很好地估计感知阈值，因为使用的刺激率远低于日常听力使用的刺激率；因此，基于ecap的拟合是次优的。基于我们之前的动物研究，我们提出了一种新的方法来测量人类的ECAP阈值。这种方法涉及测量ECAP的可变性，而不是其平均大小，将更准确和更快。我们将在Selly Oak医院（伯明翰）和House耳研究所（洛杉矶）的人工耳蜗患者中测试这种方法；所有测试都将与Advanced Bionics SARL合作，后者将提供测试患者所需的硬件。我们将把这种方法与计算机模型结合起来，预测患者耳蜗不同区域的耳蜗神经纤维的数量，并确定来自每个电极的电流如何在整个耳蜗中传播。患者特异性模型需要考虑受试者之间的差异，例如，潜在病理、神经存活程度和手术期间电极放置。该模型将用于指导拟合和决定，例如，哪些电极应该是活跃的。这种生理和计算技术的结合将克服单独使用ecap来确定通道相互作用（不同电极产生的神经活动如何重叠）的局限性：通过标准使用ecap来测量通道相互作用，纤维分布和电流传播的影响无法分离。这样的区别在临床上是很重要的，因为电极不需要仅仅为低神经存活而失效。在这个项目中，这些针对病人的模型将被扩展到预测神经活动对更一般刺激的反应模式。我们将对最初的模型进行修改，以便用我们之前开发的神经模型来模拟神经纤维。将选择模型中的患者特定参数来匹配ECAP数据，这将需要开发新的生理方法来提高数据的可靠性。在项目的后期阶段，该模型将用于将感知测量与预测的神经活动联系起来，从而能够更好地理解电刺激和声刺激的感觉知觉背后的神经机制。这将导致更好的人工耳蜗设计。由听力学家进行的当代装配是昂贵的，而且不足以对人工耳蜗参数进行系统的调查。在未来的工作规划中，将使用扩展的患者特异性模型来快速突出标准策略的潜在有用参数值，例如最佳刺激速率，并指导新策略的开发。以上所有ECAP方法和模型都将在有可能进行口头反馈的患者中进行验证。在这个项目中得到的增强的装配程序有望提高语音清晰度，并为人工耳蜗使用者带来更好的生活质量。

项目成果

Noise helps cochlear implant listeners to categorize vowels.

噪音有助于人工耳蜗听者对元音进行分类。

• DOI: 10.1121/10.0010071
• 发表时间: 2022
• 期刊: JASA express letters
• 影响因子: 1
• 作者: Morse RP