Artificial Intelligence-assisted Contrast-enhanced Ultrasound Diagnosis of Thyroid Nodules

The goal of this intervention study is to learn about the diagnostic performance of artificial intelligence to assist the contrast-enhanced ultrasound diagnosis of thyroid nodules. The main questions it aims to answer are:

1. Can we develop an artificial intelligence model to assist the contrast-enhanced ultrasound diagnosis of thyroid nodules? 2. Can artificial intelligent reduce the unnecessary biopsy of thyroid nodules?

Participants will be asked to undergo contrast-enhanced ultrasound examination and ultrasound-guided fine-needle aspiration of thyroid nodules. Researchers will calculate the diagnostic performance of the contrast-enhanced ultrasound diagnosis of thyroid nodules with and without artificial intelligent assistance.

Completed

Looking for future studies?

Notify Me

Key information

Conditions

Thyroid Nodule Disease Endocrine Gland Neoplasms Endocrine System Diseases Head and Neck Neoplasms Neoplasms Neoplasms by Site Pathologic Processes Pathological Conditions, Signs and Symptoms Thyroid Diseases Thyroid Neoplasms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Sun Yat-sen Memorial Hospital, Sun Yat-sen University

Guangzhou, Guangdong, 510289, China

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

Patients with thyroid nodules with a solid component ≥5 mm confirmed by conventional ultrasound;
Patients who underwent conventional ultrasound, contrast-enhanced ultrasound, and fine-needle aspiration biopsy;
Patients with a final benign or malignant pathological results.

Exclusion criteria

Patients with cytopathology of Bethesda I, III, or IV and without final benign or malignant pathology；
Patients with a history of thyroid ablation or surgery;
Patients with low-quality ultrasound images.

Treatment and study plan

Artificial intelligence

Other

Artificial intelligence assisted contrast-enhanced ultrasound diagnosis of thyroid nodules.

Primary outcomes

Diagnostic performance

Time frame: First week after primary completion date.

Sensitivity, specificity, positive predictive value, negative predictive value, accuracy, area under the curve
The necessity of biopsy

Time frame: First week after primary completion date.

Unnecessary biopsy rate

Sponsors and collaborators

Lead sponsor

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

Other

Registry information

Official study title

A Multicenter Study of Artificial Intelligence-assisted Contrast-enhanced Ultrasound Diagnosis of Thyroid Nodules

Acronym: AIA-CEUD-TN

Important dates

Study start: 2023
Primary completion: 2026
Study completion: 2026
First posted: Aug 9, 2023
Registry last updated: Mar 25, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

Recruiting