Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Hannover, Germany.
German Hearing Center, Hannover Medical School, Hannover, Germany.
Sci Rep. 2024 Jan 11;14(1):1115. doi: 10.1038/s41598-023-50632-0.
Cochlear implants can provide an advanced treatment option to restore hearing. In standard pre-implant procedures, many factors are already considered, but it seems that not all underlying factors have been identified yet. One reason is the low quality of the conventional computed tomography images taken before implantation, making it difficult to assess these parameters. A novel method is presented that uses the Pietsch Model, a well-established model of the human cochlea, as well as landmark-based registration to address these challenges. Different landmark numbers and placements are investigated by visually comparing the mean error per landmark and the registrations' results. The landmarks on the first cochlear turn and the apex are difficult to discern on a low-resolution CT scan. It was possible to achieve a mean error markedly smaller than the image resolution while achieving a good visual fit on a cochlear segment and directly in the conventional computed tomography image. The employed cochlear model adjusts image resolution problems, while the effort of setting landmarks is markedly less than the segmentation of the whole cochlea. As a next step, the specific parameters of the patient could be extracted from the adapted model, which enables a more personalized implantation with a presumably better outcome.
人工耳蜗植入可以提供一种先进的治疗选择，以恢复听力。在标准的植入前程序中，已经考虑了许多因素，但似乎尚未确定所有潜在因素。原因之一是植入前拍摄的常规计算机断层扫描图像质量较低，难以评估这些参数。本文提出了一种新方法，该方法使用了 Pietsch 模型，这是一种成熟的人耳蜗模型，以及基于标志点的配准，以解决这些挑战。通过视觉比较每个标志点的平均误差和配准结果，研究了不同的标志点数量和位置。在低分辨率 CT 扫描中，第一耳蜗圈和顶点上的标志点很难辨别。在实现耳蜗段和常规计算机断层扫描图像上良好的视觉匹配的同时，有可能实现明显小于图像分辨率的平均误差。所使用的耳蜗模型解决了图像分辨率问题，而设置标志点的工作量明显小于整个耳蜗的分割。下一步，可以从适配的模型中提取患者的特定参数，从而实现更个性化的植入，预计会有更好的效果。
