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神经自发荧光与人工智能组织识别软件引导下的甲状腺手术

Thyroid surgery under nerve auto-fluorescence & artificial intelligence tissue identification software guidance.

作者信息

Dip Fernando, Aleman Rene, Rancati Alberto, Eiben Gustavo, Rosenthal Raul J, Sinagra Diego

机构信息

Department of General Surgery, Sanatorio Otamendi & Miroli (Otamendi & Miroli Hospital), University of Buenos Aires, Buenos Aires, Argentina.

出版信息

Langenbecks Arch Surg. 2025 Jan 4;410(1):23. doi: 10.1007/s00423-024-03597-1.

Abstract

Thyroid cancer is a common malignancy that requires comprehensive clinical evaluation prior to adequate surgical management. Over the last three decades thyroid surgery has tripled and is considered one of the most commonly performed procedures in general surgery. These procedures are associated with potential postoperative complications with significant deterioration in the patient's quality of life. While the current rates of recurrent laryngeal nerve injury following thyroidectomy have decreased secondary to intraoperative neuromonitoring, thyroid surgery remains the leading cause of iatrogenic injury. The authors herein present a case of a thyroid nodule with cervical lymph node involvement undergoing total thyroidectomy guided by near-ultraviolet (NUV) imaging nerve auto-fluorescent technology to visualize, identify and protect vital structures.

摘要

甲状腺癌是一种常见的恶性肿瘤,在进行充分的手术治疗之前需要进行全面的临床评估。在过去三十年中,甲状腺手术量增加了两倍,被认为是普通外科中最常进行的手术之一。这些手术可能会引发术后并发症,严重降低患者的生活质量。虽然由于术中神经监测,目前甲状腺切除术后喉返神经损伤的发生率有所下降,但甲状腺手术仍然是医源性损伤的主要原因。本文作者介绍了一例甲状腺结节伴颈部淋巴结受累的病例,该病例在近紫外(NUV)成像神经自发荧光技术的引导下进行了全甲状腺切除术,以可视化、识别和保护重要结构。

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