Image-Guided Cochlear Implant Programming Techniques

描述（由申请人提供）：本研究的目标是开发和评价新的患者定制的图像引导的髋关节植入物编程（IGCIP）策略。 全世界有超过320，000名接受者，人工耳蜗植入物（CI）被认为是严重到极深的感觉性听力损失的标准治疗。 听力学家在临床上使用的编程过程是限制结果的一个因素，因为虽然现有设备允许操纵许多可能导致更好性能的设置，但没有客观的线索可以指示什么设置变化将导致更好的性能。 任何加速收敛到更接近自然保真度的设置的进步都可能对CI接受者，临床医生和听力学中心产生重大影响。 该项目的目标是开发和评估新的IGCIP策略，这些策略可以为编程过程提供对象信息，并导致更好地近似自然保真度的程序。 在自然听觉中，当声音中存在其特征频率（CF）时，每个神经纤维（约30，000个）都会被激活。 对于CI，由于电极数量少（12至22个）、它们相对于单个神经的尺寸大以及它们的宽电流分布，有限的光谱分辨率是可实现的，因此每个电极刺激对应于宽范围的CF的神经。 由于这在传统编程中通常不被考虑，因此通常选择次优设置，其导致交互通道，从而导致频谱拖尾伪影。 此外，由于电极的刺激模式是 未知，由每个电极刺激的CF是未知的。 因此，分配给每个电极的声音频率通常不对应于其刺激的神经的CF，导致频率失配伪影。 这些限制因素对成果产生了负面影响，虽然众所周知，但一直难以解决。 本研究的假设是，通过分析患者CT图像可以获得更客观、更重要的信息，并可用于定制CI设置以改善听力性能。 将测试的IGCIP策略将涉及使用成像来检测频谱拖尾和频率失配发生的位置，并通过选择患者定制的程序设置（包括频率表设置、电流引导设置和电流聚焦设置）来最大限度地减少这些伪影。 为了支持IGCIP策略的设计，还将开发一种使用患者CT图像来创建患者特定的电流和CI神经激活模式的综合模型的方法。 由于IGCIP策略仅需要简单更改CI设置，因此它们与现有器械技术配合使用，不需要进一步手术，并且是可逆的。 如果成功的话，一套IGCIP技术，可以客观地指导编程的CI朝着优化的设置和改善听力恢复的新的和现有的CI收件人将在这个项目中开发。

DESCRIPTION (provided by applicant): The goals of this research are to develop and evaluate new patient-customized, Image-Guided Cochlear Implant Programming (IGCIP) strategies. With over 320,000 recipients worldwide, cochlear implants (CIs) are considered standard of care treatment for severe-to-profound sensory-based hearing loss. The programming process that audiologists use clinically is one factor that limits outcomes because, while existing devices permit manipulation of very many settings that could lead to better performance, there are no objective cues available to indicate what setting changes will lead to better performance. Any advancement that accelerates convergence to settings that better approximate natural fidelity could have significant impact for CI recipients, clinicians, and audiology centers. The goal of this project is to develop and evaluate new IGCIP strategies that could provide object information to the programming process and lead to programs that better approximate natural fidelity. In natural hearing, each neural fiber (out of ~30,000) is activated when its characteristic frequency (CF) is present in a sound. With a CI, due to the small number of electrodes (12 to 22), their large size relative to the individual nerves, and their wide curren spread, limited spectral resolution has been achievable, thus each electrode stimulates nerves corresponding to a wide range of CFs. Since this is generally not accounted for in traditional programming, sub-optimal settings are typically chosen that result in interacting channels, causing spectral smearing artifacts. Further, since the stimulation patterns of the electrodes are unknown, the CFs stimulated by each electrode are unknown. Thus the sound frequencies assigned to each electrode do not generally correspond to the CFs of the nerves it stimulates, resulting in frequency mismatch artifacts. These limitations negatively affect outcomes and, while known, have been difficult to address. The hypothesis of this study is that more objective, important information can be obtained through analysis of patient CT images and can be used to customize CI settings for improved hearing performance. The IGCIP strategies that will be tested will involve using imaging to detect where spectral smearing and frequency mismatching is occurring and to minimize these artifacts through selection of patient-customized program settings, including frequency table settings, current steering settings, and current focusing settings. To support the design of IGCIP strategies, an approach for using patient CT images to create patient-specific, comprehensive models of electrical current flow and the CI's neural activation patterns will also be developed. Since IGCIP strategies require only simple changes of CI settings, they work with existing device technology, do not require further surgery, and are reversible. If successful, a suite of IGCIP techniques that can objectively guide the programming of CIs towards optimized settings and improve hearing restoration for new and existing CI recipients will be developed in this project.