Vision-based tracking system for augmented reality to localize recurrent laryngeal nerve during robotic thyroid surgery

Dongheon Lee, Hyeong Won Yu, Seunglee Kim, Jin Yoon, Keunchul Lee, Young Jun Chai, June Young Choi, Hyoun Joong Kong, Kyu Eun Lee, Hwan Seong Cho, Hee Chan Kim

Research output: Contribution to journalArticle

Abstract

We adopted a vision-based tracking system for augmented reality (AR), and evaluated whether it helped surgeons to localize the recurrent laryngeal nerve (RLN) during robotic thyroid surgery. We constructed an AR image of the trachea, common carotid artery, and RLN using CT images. During surgery, an AR image of the trachea and common carotid artery were overlaid on the physical structures after they were exposed. The vision-based tracking system was activated so that the AR image of the RLN followed the camera movement. After identifying the RLN, the distance between the AR image of the RLN and the actual RLN was measured. Eleven RLNs (9 right, 4 left) were tested. The mean distance between the RLN AR image and the actual RLN was 1.9 ± 1.5 mm (range 0.5 to 3.7). RLN localization using AR and vision-based tracking system was successfully applied during robotic thyroidectomy. There were no cases of RLN palsy. This technique may allow surgeons to identify hidden anatomical structures during robotic surgery.

Original languageEnglish
Article number8437
JournalScientific Reports
Volume10
Issue number1
DOIs
StatePublished - 1 Dec 2020

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