Computer Vision-Based Recognition of Parathyroid Glands and Recurrent Laryngeal Nerves in Endoscopic Surgery

Identification of the parathyroid glands and recurrent laryngeal nerves is an important component of safe thyroid surgery. Parathyroid glands are small and may resemble surrounding fat, lymph nodes, or soft tissue. The recurrent laryngeal nerve has a complex anatomical course and may be partially covered by fascia or insufficiently exposed in some cases, which may increase the difficulty of intraoperative recognition. Computer vision-based artificial intelligence models may help recognize these structures in endoscopic surgical images, but their performance in multicenter real-world surgical settings requires further validation.

Previous PTAIR studies mainly focused on parathyroid gland recognition in endoscopic thyroid surgery videos. Based on these prior studies, the present study will further evaluate the PTAIR model in a prospective multicenter setting, with a focus on recognition of parathyroid glands and recurrent laryngeal nerves. This stage of the study is designed as a model performance validation study and will not evaluate whether PTAIR changes intraoperative surgical decisions, parathyroid management, or postoperative clinical outcomes.

During endoscopic thyroid surgery, PTAIR, junior physicians, and senior physicians will identify parathyroid glands and recurrent laryngeal nerves based on the same intraoperative endoscopic visual field. All time-related outcomes will use the video recorder timeline as the unified reference. The study will record the first recognition time of the recurrent laryngeal nerve and parathyroid gland by PTAIR, junior physicians, and senior physicians, as well as the continuous recognition time of these structures by PTAIR. Expert-reviewed annotations will be used as the reference for subsequent model performance evaluation and confirmation of recognition results.

The study will also evaluate PTAIR performance under different exposure conditions, including cases with fascial coverage, incomplete exposure, or complex surgical field conditions. Multicenter video data will be used to assess model performance across different centers, surgeons, equipment settings, and operative field conditions, and may provide data for future model improvement and iteration.

Inclusion criteria

• Age 18 years or older.
• Patients with benign or malignant thyroid disease who are scheduled to undergo endoscopic thyroid surgery.
• Standardized recorder-based intraoperative video collection is planned during surgery.
• Patients agree to intraoperative video recording, de-identification, and research use.
• Basic perioperative clinical data are available.
• The participating center is able to follow the standardized procedures for video collection, data upload, data security, and annotation quality control.

Exclusion criteria

• Refusal to provide informed consent.
• Patients scheduled to undergo conventional open thyroid surgery.
• Standardized recorder-based intraoperative video collection cannot be performed.
• Intraoperative video quality is insufficient for model analysis or expert review.
• Key surgical phases are missing from the video recording.
• Expert annotation or review of the parathyroid glands or recurrent laryngeal nerves cannot be completed.
• Video de-identification fails.
• Severe missing perioperative clinical data.
• Other conditions judged by the investigators to be unsuitable for study inclusion.