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DCNN Developed for Detection and Assessing the Perfusion of PTG

Sponsor
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University (Other)
Overall Status
Recruiting
CT.gov ID
NCT05869058
Collaborator
(none)
300
Enrollment
1
Location
41
Anticipated Duration (Months)
7.3
Patients Per Site Per Month

Study Details

Study Description

Brief 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.

Condition or Disease Intervention/Treatment Phase
  • 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 Design

Study Type:
Observational
Anticipated Enrollment :
300 participants
Observational Model:
Cohort
Time Perspective:
Prospective
Official Title:
Development and Improvement of a Deep Convolutional Neural Network for Detection and Assessing the Perfusion of Parathyroid Gland During Endoscopic Thyroidectomy
Anticipated Study Start Date :
May 1, 2023
Anticipated Primary Completion Date :
Apr 1, 2026
Anticipated Study Completion Date :
Oct 1, 2026

Outcome Measures

Primary Outcome Measures

  1. Area Under the Receiver Operating Characteristic Curve [3 years]

    Area Under the Receiver Operating Characteristic Curve

Eligibility Criteria

Criteria

Ages Eligible for Study:
18 Years to 70 Years
Sexes Eligible for Study:
All
Accepts Healthy Volunteers:
No
Inclusion Criteria:
  • The patients who undergo endoscopic thyroidectomy
Exclusion Criteria:

  • hyperparathyroidism

  • hypoparathyroidism

  • neck surgery history

  • cervical radiotherapy history

Contacts and Locations

Locations

Site City State Country Postal Code
1 Sun Yat-sen Memorial Hospital Guangzhou Guangdong China 510000

Sponsors and Collaborators

  • 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 Documents (Full-Text)

None provided.

More Information

Publications

None provided.
Responsible Party:
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
ClinicalTrials.gov Identifier:
NCT05869058
Other Study ID Numbers:
  • SYSKY-2022-177-01
First Posted:
May 22, 2023
Last Update Posted:
May 22, 2023
Last Verified:
May 1, 2023
Studies a U.S. FDA-regulated Drug Product:
No
Studies a U.S. FDA-regulated Device Product:
No

Study Results

No Results Posted as of May 22, 2023