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Recruiting Observational

DCNN Developed for Detection and Assessing the Perfusion of PTG

NCT05869058 · tracked via the Priya Life Science China tracker
Phase
Observational
Started
2023-06-13
Last updated
2025-12-03

Condition(s) studied

Thyroidectomy

Investigational drug(s) / intervention(s)

a deep convolutional neural network

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

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.

Eligibility

Sex
ALL
Min age
18 Years
Max age
70 Years
Healthy volunteers
No
Inclusion Criteria: * The patients who undergo endoscopic thyroidectomy Exclusion Criteria: * hyperparathyroidism * hypoparathyroidism * neck surgery history * cervical radiotherapy history

Primary outcome measure(s)

  • Area Under the Receiver Operating Characteristic Curve — 3 years
    Area Under the Receiver Operating Characteristic Curve

Trial sites (1)

FacilityCityRegionStatus
Sun Yat-sen Memorial Hospital Guangzhou Guangdong Recruiting
Official registry record

This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.

View NCT05869058 on ClinicalTrials.gov ↗ ← All trials in China