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

听力损失更严重的人可以使用人工耳蜗器--一种通过手术植入的设备，电刺激耳蜗神经(听力神经)--来帮助他们再次听力。该装置的一部分是耳蜗(内耳)内的一组电极。人工耳蜗术后良好的语音感知有赖于听力学专家对设备参数的适当调整。对于成年人，最初的试穿通常是基于感知测量，需要患者的口头反馈。当语言反馈不可能时，参数通常是相对于获得可测量的电复合动作电位(ECAP)所需的最低水平来设置的，ECAP是现代人工耳蜗可以记录的所有神经纤维的总和电反应。然而，标准的ECAP方法不能很好地估计知觉阈值，因为使用的刺激率比日常听力使用的刺激率低得多；因此，基于eCAP的拟合是次优的。基于我们以前的动物研究，我们提出了一种新的方法来测量人类的ECAP阈值。这种方法涉及到测量ECAP的可变性，而不是它的平均大小，而且将更加准确和快速。我们将在Selly Oak医院(伯明翰)和House Ear Institute(洛杉矶)的人工耳蜗植入患者身上测试这种方法；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数量，并确定来自每个电极的电流如何在整个耳蜗组织中传播。需要特定于患者的模型来解释研究对象间的实质性差异，例如，潜在的病理、神经存活的程度和手术中电极的放置。该模型将被用来指导装配，并决定哪些电极应该是活跃的。这种生理学和计算机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)的限制：使用eCAP来测量通道相互作用的标准使用，纤维分布和电流扩散的影响无法分离。这种区别在临床上很重要，因为电极不需要单独为低神经存活率而不活动。在项目期间，这些患者特有的模型将被扩展到预测神经活动对更普遍的刺激的反应模式。最初的模型将被修改，以便用我们之前开发的神经模型来模拟神经纤维。将从模型中选择特定于患者的参数来匹配ECAP数据，这将需要开发新的生理学方法来提高数据的可靠性。在项目的后期阶段，该模型将被用来将感知测量与预测的神经活动联系起来，从而使人们能够更好地理解电和声刺激的感觉感知的神经机制。这将导致更好的人工耳蜗术设计。目前由听力学专家进行的配戴是昂贵的，而且不足以对人工耳蜗的参数进行系统的研究。在未来的工作方案中，将使用扩展的特定于患者的模型来快速突出标准策略的潜在有用参数值，例如最佳刺激率，并指导新策略的开发。所有上述ECAP方法和模型都将与可能进行口头反馈的患者进行验证。在这个项目中产生的增强的适配程序预计将提高语音清晰度，并导致更好的生活质量为人工耳蜗术使用者。

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.