DCNN Developed for Detection and Assessing the Perfusion of PTG

Development and Improvement of a Deep Convolutional Neural Network for Detection and Assessing the Perfusion of Parathyroid Gland During Endoscopic Thyroidectomy

Since the anatomical location and appearance of the parathyroid gland (PTG) vary, detection of the PTG and preserving the blood supply are among the difficulties encountered during a thyroidectomy procedure. We are planning to train a deep convolutional neural network based on a larger sample of endoscopic images to develop a model to assist surgeons in detection of PTG during endoscopic thyroidectomy. Furthermore, we would like to train a DCNN to predict blood perfusion based on endoscopic images comparing to indocyanine green fluorescence angiography as reference standard, and assess the performance of DCNN in predicting postoperative hypoparathyroidism.

Study Overview

• Status: Recruiting
• Conditions: Thyroidectomy
• Intervention / Treatment: Diagnostic test: a deep convolutional neural network

Detailed Description

Since the anatomical location and appearance of the parathyroid gland (PTG) vary, detection of the PTG and preserving the blood supply are among the difficulties encountered during a thyroidectomy procedure. Resection of the PTG by mistake or interruption of the blood supply may lead to transient or permanent hypoparathyroidism, which would require short-term or lifelong calcium and/or vitamin D supplement. We are planning to train a deep convolutional neural network based on a larger sample of endoscopic images to develop a model to assist surgeons in detection of PTG during endoscopic thyroidectomy. Although several researchers indicated that indocyanine green fluorescence angiography could be used to assess the perfusion of the PTG intraoperatively, it may cause allergic reaction and need repetitive injection. Therefore, we would like to train a DCNN to predict blood perfusion based on endoscopic images comparing to indocyanine green fluorescence angiography as reference standard, and assess the performance of DCNN in predicting postoperative hypoparathyroidism. This research may lead to the development of endoscopic modules in PTG detection and PTG perfusion prediction to reduce postoperative hypoparathyroidism.

• Study Type: Observational
• Enrollment (Estimated): 300

Contacts and Locations

• Study Contact: Name: Peiliang Lin, M.D.; Phone Number: 0086-020-34071439; Email: linpliang3@mail.sysu.edu.cn

Study Locations

• China
  • Guangdong
    • Guangzhou, Guangdong, China, 510000
      • Recruiting
      • Sun Yat-Sen Memorial Hospital
      • Contact: Peiliang Lin, M.D.; Phone Number: +862034071439; Email: linpliang3@mail.sysu.edu.cn

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

The patients, who choose to undergo endoscopic thyroidectomy due to thyroid diseases and have no history of hyperparathyroidism, hypoparathyroidism, neck surgery and cervical radiotherapy, are candidates of our study.

Description

Inclusion Criteria:

• The patients who undergo endoscopic thyroidectomy

Exclusion Criteria:

• hyperparathyroidism
• hypoparathyroidism
• neck surgery history
• cervical radiotherapy history

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Area Under the Receiver Operating Characteristic Curve	Area Under the Receiver Operating Characteristic Curve	3 years

Collaborators and Investigators

• Sponsor: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
• Investigators: Principal Investigator: Peiliang Lin, M.D., Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Study record dates

Study Major Dates

• Study Start (Actual): June 13, 2023
• Primary Completion (Estimated): April 1, 2026
• Study Completion (Estimated): October 1, 2026

Study Registration Dates

• First Submitted: May 11, 2023
• First Submitted That Met QC Criteria: May 11, 2023
• First Posted (Actual): May 22, 2023

Study Record Updates

• Last Update Posted (Estimated): December 3, 2025
• Last Update Submitted That Met QC Criteria: November 25, 2025
• Last Verified: November 1, 2025

More Information

Terms related to this study

• Other Study ID Numbers: SYSKY-2022-177-01

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No