Suppr超能文献

一种图像引导的人工耳蜗编程策略的临床评估

Clinical evaluation of an image-guided cochlear implant programming strategy.

作者信息

Noble Jack H, Gifford René H, Hedley-Williams Andrea J, Dawant Benoit M, Labadie Robert F

机构信息

Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tenn., USA.

出版信息

Audiol Neurootol. 2014;19(6):400-11. doi: 10.1159/000365273. Epub 2014 Nov 7.

Abstract

The cochlear implant (CI) has been labeled the most successful neural prosthesis. Despite this success, a significant number of CI recipients experience poor speech understanding, and, even among the best performers, restoration to normal auditory fidelity is rare. While significant research efforts have been devoted to improving stimulation strategies, few developments have led to significant hearing improvement over the past two decades. We have recently introduced image processing techniques that open a new direction for advancement in this field by making it possible, for the first time, to determine the position of implanted CI electrodes relative to the nerves they stimulate using computed tomography images. In this article, we present results of an image-guided, patient-customized approach to stimulation that utilizes the electrode position information our image processing techniques provide. This approach allows us to identify electrodes that cause overlapping stimulation patterns and to deactivate them from a patient's map. This individualized mapping strategy yields significant improvement in speech understanding in both quiet and noise as well as improved spectral resolution in the 68 adult CI recipients studied to date. Our results indicate that image guidance can improve hearing outcomes for many existing CI recipients without requiring additional surgery or the use of 'experimental' stimulation strategies, hardware or software.

摘要

人工耳蜗(CI)被誉为最成功的神经假体。尽管取得了这样的成功,但仍有相当数量的人工耳蜗植入者言语理解能力较差,而且即使在表现最佳的人群中,恢复到正常听觉保真度的情况也很少见。虽然在改进刺激策略方面投入了大量研究工作,但在过去二十年里,很少有进展能带来显著的听力改善。我们最近引入了图像处理技术,通过首次利用计算机断层扫描图像确定植入的人工耳蜗电极相对于它们所刺激神经的位置,为该领域的发展开辟了一个新方向。在本文中,我们展示了一种图像引导、针对患者定制的刺激方法的结果,该方法利用了我们图像处理技术提供的电极位置信息。这种方法使我们能够识别导致重叠刺激模式的电极,并从患者的图谱中停用它们。这种个性化映射策略在迄今研究的68名成年人工耳蜗植入者中,在安静和嘈杂环境下的言语理解以及频谱分辨率方面都产生了显著改善。我们的结果表明,图像引导可以改善许多现有人工耳蜗植入者的听力结果,而无需额外的手术或使用“实验性”刺激策略、硬件或软件。

相似文献

3
4
Implementation of Image-Guided Cochlear Implant Programming at a Distant Site.远程站点的图像引导人工耳蜗编程实施
Otolaryngol Head Neck Surg. 2017 May;156(5):933-937. doi: 10.1177/0194599817698435. Epub 2017 Apr 4.
8
The multi-channel cochlear implant and the relief of severe-to-profound deafness.多通道人工耳蜗与重度至极重度耳聋的缓解
Cochlear Implants Int. 2012 May;13(2):69-85. doi: 10.1179/1754762811Y.0000000019. Epub 2011 Sep 29.

引用本文的文献

7
Cochlear Implant Electrode Placement and Music Perception.人工耳蜗电极植入与音乐感知
JAMA Otolaryngol Head Neck Surg. 2025 Mar 1;151(3):220-227. doi: 10.1001/jamaoto.2024.4761.
9
Super-resolution segmentation network for inner-ear tissue segmentation.用于内耳组织分割的超分辨率分割网络。
Simul Synth Med Imaging. 2023 Oct;14288:11-20. doi: 10.1007/978-3-031-44689-4_2. Epub 2023 Oct 7.
10
A Unified Deep-Learning-Based Framework for Cochlear Implant Electrode Array Localization.一种基于深度学习的人工耳蜗电极阵列定位统一框架。
Med Image Comput Comput Assist Interv. 2023 Oct;14228:376-385. doi: 10.1007/978-3-031-43996-4_36. Epub 2023 Oct 1.

本文引用的文献

1
The NAL-NL2 Prescription Procedure.NAL-NL2处方程序。
Audiol Res. 2011 Mar 23;1(1):e24. doi: 10.4081/audiores.2011.e24. eCollection 2011 May 10.
5
9
Development and validation of the AzBio sentence lists.发展和验证 AzBio 句子列表。
Ear Hear. 2012 Jan-Feb;33(1):112-7. doi: 10.1097/AUD.0b013e31822c2549.
10
Spectral cues for understanding speech in quiet and in noise.用于在安静和嘈杂环境中理解语音的频谱线索。
Cochlear Implants Int. 2011 May;12 Suppl 1:S66-9. doi: 10.1179/146701011X13001035753056.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验