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虚拟现实耳蜗植入术用于深度听力损失的个性化康复。

Virtual cochlear implantation for personalized rehabilitation of profound hearing loss.

机构信息

Institute of AudioNeuroTechnology & Department of Experimental Otology, ENT Department, Hannover Medical School, Hannover, Germany; MED-EL Research Center, Hannover, Germany.

OtoJig GmbH, Hannover, Germany.

出版信息

Hear Res. 2023 Mar 1;429:108687. doi: 10.1016/j.heares.2022.108687. Epub 2022 Dec 27.

Abstract

In cochlear implantation, current preoperative planning procedures allow for estimating how far a specific implant will reach into the inner ear of the patient, which is important to optimize hearing preservation and speech perception outcomes. Here we report on the development of a methodology that goes beyond current planning approaches: the proposed model does not only estimate specific outcome parameters but allows for entire, three-dimensional virtual implantations of patient-specific cochlear anatomies with different types of electrode arrays. The model was trained based on imaging datasets of 186 human cochleae, which contained 171 clinical computer tomographies (CTs) of actual cochlear implant patients as well as 15 high-resolution micro-CTs of cadaver cochleae to also reconstruct the refined intracochlear structures not visible in clinical imaging. The model was validated on an independent dataset of 141 preoperative and postoperative clinical CTs of cochlear implant recipients and outperformed all currently available planning approaches, not only in terms of accuracy but also regarding the amount of information that is available prior to the actual implantation.

摘要

在人工耳蜗植入中,当前的术前规划程序可以估计特定植入物将深入患者内耳的程度,这对于优化听力保护和言语感知效果非常重要。在这里,我们报告了一种超越当前规划方法的方法的发展:所提出的模型不仅估计特定的结果参数,而且还允许使用不同类型的电极阵列对患者特定的耳蜗解剖结构进行整个三维虚拟植入。该模型是基于 186 个人耳蜗的成像数据集进行训练的,其中包含 171 例实际人工耳蜗植入患者的临床计算机断层扫描(CT)以及 15 例尸体耳蜗的高分辨率微 CT,以重建在临床成像中不可见的精细耳蜗内结构。该模型在 141 例接受人工耳蜗植入的患者的术前和术后临床 CT 的独立数据集上进行了验证,并且不仅在准确性方面,而且在实际植入前可用信息量方面都优于所有当前可用的规划方法。

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