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

Prospective Multicenter Model Validation Study of the PTAIR Computer Vision Model for Recognition of Parathyroid Glands and Recurrent Laryngeal Nerves During Endoscopic Thyroid Surgery

Status
Not yet recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT07628543
Acronym
PTAIR
Enrollment
100
Registered
2026-06-05
Start date
2026-06-01
Completion date
2028-05-31
Last updated
2026-06-05

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Thyroid Diseases, Thyroid Neoplasms

Keywords

PTAIR, Computer Vision, Endoscopic Thyroid Surgery, Parathyroid Gland Recognition, Recurrent Laryngeal Nerve Recognition, Model Validation

Brief summary

This study aims to evaluate the performance of the PTAIR computer vision model for recognizing parathyroid glands and recurrent laryngeal nerves during endoscopic thyroid surgery. Multicenter intraoperative endoscopic surgery videos will be prospectively collected. Using the video recorder timeline as the unified time reference, the first recognition time of parathyroid glands and recurrent laryngeal nerves by PTAIR, junior physicians, and senior physicians will be recorded during surgery. The continuous recognition time of parathyroid glands and recurrent laryngeal nerves by PTAIR will also be recorded. This study focuses on the recognition performance of PTAIR in real-world multicenter endoscopic thyroid surgery settings. At this stage, PTAIR will not be used to guide intraoperative surgical decision-making, and the study will not evaluate the effect of PTAIR on clinical outcomes. The collected video data will be used to assess the performance of PTAIR under different centers, surgeons, equipment conditions, and surgical field conditions, and may provide data support for future model optimization.

Detailed description

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.

Interventions

OTHERPTAIR Computer Vision Model Assessment

PTAIR is a computer vision model used to recognize parathyroid glands and recurrent laryngeal nerves in endoscopic thyroid surgery videos. In this observational study, PTAIR will be used to analyze recorder-based intraoperative videos and evaluate first recognition time, continuous recognition time, and recognition performance. PTAIR results will be compared with recognition by junior and senior physicians based on the same intraoperative endoscopic visual field and the same video recording timeline. At this stage, PTAIR will not be used to guide intraoperative surgical decision-making.

Sponsors

Fujian Medical University
Lead SponsorOTHER
Peking University Shenzhen Hospital
CollaboratorOTHER
Cancer Hospital of Guangxi Medical University
CollaboratorOTHER
First Affiliated Hospital of Guangxi Medical University
CollaboratorOTHER
First Hospital of China Medical University
CollaboratorOTHER
The First Affiliated Hospital of Zhengzhou University
CollaboratorOTHER
Peking Union Medical College Hospital
CollaboratorOTHER
United Family Healthcare
CollaboratorUNKNOWN
Longyan First Hospital, Affiliated to Fujian Medical University
CollaboratorUNKNOWN
Mahidol University
CollaboratorOTHER
Rio de Janeiro State University
CollaboratorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Healthy volunteers
No

Inclusion criteria

1. Age 18 years or older. 2. Patients with benign or malignant thyroid disease who are scheduled to undergo endoscopic thyroid surgery. 3. Standardized recorder-based intraoperative video collection is planned during surgery. 4. Patients agree to intraoperative video recording, de-identification, and research use. 5. Basic perioperative clinical data are available. 6. The participating center is able to follow the standardized procedures for video collection, data upload, data security, and annotation quality control.

Exclusion criteria

1. Refusal to provide informed consent. 2. Patients scheduled to undergo conventional open thyroid surgery. 3. Standardized recorder-based intraoperative video collection cannot be performed. 4. Intraoperative video quality is insufficient for model analysis or expert review. 5. Key surgical phases are missing from the video recording. 6. Expert annotation or review of the parathyroid glands or recurrent laryngeal nerves cannot be completed. 7. Video de-identification fails. 8. Severe missing perioperative clinical data. 9. Other conditions judged by the investigators to be unsuitable for study inclusion.

Design outcomes

Primary

MeasureTime frameDescription
First Recognition Time of the Recurrent Laryngeal NerveIntraoperative periodUsing the video recorder timeline as the unified time reference, the first recognition time of the recurrent laryngeal nerve by PTAIR, junior physicians, and senior physicians will be recorded during surgery. All recognitions will be based on the same intraoperative endoscopic visual field.
First Recognition Time of the Parathyroid GlandIntraoperative periodUsing the video recorder timeline as the unified time reference, the first recognition time of the parathyroid gland by PTAIR, junior physicians, and senior physicians will be recorded during surgery. All recognitions will be based on the same intraoperative endoscopic visual field.
Continuous Recognition Time of the Recurrent Laryngeal NerveIntraoperative periodUsing the video recorder timeline as the unified time reference, the continuous recognition time of the recurrent laryngeal nerve by PTAIR will be recorded during surgery.
Continuous Recognition Time of the Parathyroid GlandIntraoperative periodUsing the video recorder timeline as the unified time reference, the continuous recognition time of the parathyroid gland by PTAIR will be recorded during surgery.

Secondary

MeasureTime frameDescription
AP50 for Recurrent Laryngeal Nerve RecognitionFrom completion of intraoperative video collection to completion of expert annotation and model analysisBased on expert-reviewed annotations, AP50 will be calculated for PTAIR recognition of the recurrent laryngeal nerve. AP50 refers to the average precision at an intersection-over-union threshold of 0.50.
AP50 for Parathyroid Gland RecognitionFrom completion of intraoperative video collection to completion of expert annotation and model analysisBased on expert-reviewed annotations, AP50 will be calculated for PTAIR recognition of the parathyroid gland. AP50 refers to the average precision at an intersection-over-union threshold of 0.50.
Comparison of First Recognition Time of the Recurrent Laryngeal Nerve Between PTAIR and PhysiciansIntraoperative periodThe first recognition time of the recurrent laryngeal nerve will be compared among PTAIR, junior physicians, and senior physicians during surgery.
Comparison of First Recognition Time of the Parathyroid Gland Between PTAIR and PhysiciansIntraoperative periodThe first recognition time of the parathyroid gland will be compared among PTAIR, junior physicians, and senior physicians during surgery.
In Situ Recognition Rate of the Parathyroid GlandFrom completion of intraoperative video collection to completion of expert reviewBased on intraoperative videos and expert review, the in situ recognition rate of parathyroid glands by PTAIR will be recorded.
Detection Rate of Parathyroid Glands on the Surgical SpecimenIntraoperative period, before removal of the surgical specimen from the bodyAfter completion of endoscopic dissection and before removal of the surgical specimen from the body, PTAIR will be used within the endoscopic visual field to examine whether parathyroid tissue is attached to or located around the surgical specimen. The detection result will be recorded.

Countries

China

Contacts

CONTACTBo Wang Professor, MD
wangbo@fjmu.edu.cn86+13959123550
PRINCIPAL_INVESTIGATORBo Wang MD, Principal Investigator

Fujian Medical University Union Hospital

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Jun 6, 2026