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DCNN Developed for Detection and Assessing the Perfusion of PTG

NCT05869058 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 300

Last updated 2025-12-03

No results posted yet for this study

Summary

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.

Conditions

  • Thyroidectomy

Interventions

DIAGNOSTIC_TEST

a deep convolutional neural network

a deep convolutional neural network developed for detection and assessing the perfusion of parathyroid gland during endoscopic thyroidectomy

Sponsors & Collaborators

  • Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

    lead OTHER

Principal Investigators

  • Peiliang Lin, M.D. · Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Eligibility

Min Age
18 Years
Max Age
70 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-06-13
Primary Completion
2026-04-30
Completion
2026-10-31

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05869058 on ClinicalTrials.gov