DCNN Developed for Detection and Assessing the Perfusion of PTG

Sun Yat-sen University

Status

Enrolling

Conditions

Thyroidectomy

Treatments

Diagnostic Test: a deep convolutional neural network

Study type

Observational

Funder types

Other

Identifiers

NCT05869058

SYSKY-2022-177-01

Details and patient eligibility

About

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.

Full 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.

Enrollment

300 estimated patients

Sex

All

Ages

18 to 70 years old

Volunteers

No Healthy Volunteers

Inclusion criteria