Enhancing recurrent laryngeal nerve localization during transoral endoscopic thyroid surgery using augmented reality: a proof-of-concept study.

IF 1.6 4区 医学 Q3 SURGERY
Moon Young Oh, Yeonjin Choi, Taesoo Jang, Eun Kyung Choe, Hyoun-Joong Kong, Young Jun Chai
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Abstract

Purpose: During transoral endoscopic thyroidectomy, preserving the recurrent laryngeal nerve (RLN) is a major challenge because visualization of this nerve is often obstructed by the thyroid itself, increasing the risk of serious complications. This study explores the application of an augmented reality (AR) system to facilitate easier identification of the RLN during transoral endoscopic thyroidectomy.

Methods: Three patients scheduled for transoral endoscopic thyroidectomy were enrolled in this proof-of-concept study. Preoperative computed tomography scans were used to create an AR model that included the thyroid, trachea, veins, arteries, and RLN. The model was overlaid onto real-time endoscopic camera images during live surgeries. Manual registration of the AR model was performed using a customized controller. The model was aligned with surgical landmarks such as the trachea and common carotid artery. Manual registration accuracy was assessed using the Dice similarity coefficient (DSC) to evaluate the alignment between the real RLN and the RLN of the AR model.

Results: The 3 patients included were female (mean age, 33.3 ± 15.7 years), and the mean tumor size was 1.0 ± 0.3 cm. All patients underwent transoral endoscopic thyroidectomy of the right lobe. Final histopathological diagnoses comprised 2 papillary thyroid carcinomas and one follicular adenoma. The manual registration accuracy was 0.60, 0.70, and 0.57 for patients 1, 2, and 3, respectively, with a mean value of 0.6 ± 0.1.

Conclusion: The application of an AR system during transoral endoscopic thyroidectomy proved feasible and demonstrated potential for improving the localization of anatomical structures, particularly the RLN, as indicated by a moderate DSC.

利用增强现实技术加强经口内窥镜甲状腺手术中的喉返神经定位:概念验证研究。
目的:在经口内镜甲状腺切除术中,保留喉返神经(RLN)是一个主要的挑战,因为该神经的可视化经常被甲状腺本身阻塞,增加了严重并发症的风险。本研究探讨了增强现实(AR)系统在经口内镜甲状腺切除术中更容易识别RLN的应用。方法:三名计划经口内窥镜甲状腺切除术的患者加入了这项概念验证研究。术前计算机断层扫描用于创建AR模型,包括甲状腺、气管、静脉、动脉和RLN。该模型在实时手术过程中覆盖在实时内窥镜相机图像上。使用自定义控制器对AR模型进行手动配准。该模型与气管和颈总动脉等手术标志对齐。使用Dice相似系数(DSC)评估人工配准精度,以评估AR模型的真实RLN与RLN之间的对齐程度。结果:3例患者均为女性,平均年龄33.3±15.7岁,平均肿瘤大小1.0±0.3 cm。所有患者均行经口内窥镜右甲状腺切除术。最终病理诊断为2例乳头状甲状腺癌和1例滤泡腺瘤。患者1、2、3的人工配准精度分别为0.60、0.70、0.57,平均值为0.6±0.1。结论:经口内镜甲状腺切除术中应用AR系统被证明是可行的,并且显示出改善解剖结构定位的潜力,特别是RLN,如中等DSC所示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.30
自引率
7.10%
发文量
75
期刊介绍: Manuscripts to the Annals of Surgical Treatment and Research (Ann Surg Treat Res) should be written in English according to the instructions for authors. If the details are not described below, the style should follow the Uniform Requirements for Manuscripts Submitted to Biomedical Journals: Writing and Editing for Biomedical Publications available at International Committee of Medical Journal Editors (ICMJE) website (http://www.icmje.org).
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