Artificial Intelligent Accelerates the Learning Curve for Mastering Contrast-enhanced Ultrasound of Thyroid Nodules

August 8, 2023 updated by: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Artificial Intelligent Accelerates the Learning Curve for Mastering Thyroid Imaging Reporting and Data System of Contrast-enhanced Ultrasound

The goal of this observational study is to learn about the learning curve for mastering the thyroid imaging reporting and data system of contrast-enhanced ultrasound with the assistance of artificial intelligence in patients with thyroid nodules. The main questions it aims to answer are:

  1. Can we develop a artificial intelligent software to assist doctors in the diagnosis of thyroid nodules using contrast-enhanced ultrasound?
  2. Can artificial intelligent reduce the number of cases and time for doctors to master the contrast-enhanced ultrasound diagnosis of thyroid nodules?

Participants will be asked to undergo contrast-enhanced ultrasound examination and ultrasound-guided fine-needle aspiration of thyroid nodules. Researchers will compare the number of cases and time for doctors with and without artificial intelligent assistance to master the contrast-enhanced ultrasound diagnosis of thyroid nodules to see if artificial intelligent reduce the number of cases and time.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Estimated)

1000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • China
    • Guangdong
      • Guangzhou, Guangdong, China, 510289
        • Recruiting
        • Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University
        • Contact:
        • Principal Investigator:
          • Jingliang Ruan, PhD

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

N/A

Sampling Method

Probability Sample

Study Population

Study population with the same indication for contrast-enhanced ultrasound and fine-needle aspiration biopsy:

  • Planned ablation or surgery;
  • At least one suspicious ultrasound feature, such as hypoechoic/very hypoechoic, irregular/lobulated margin, taller than wide, or punctate echogenic foci.

Description

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.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Training set
Patients with thyroid nodules underwent contrast-enhanced ultrasound and ultrasound-guided fine-needle aspiration during January 2018 and December 2020 in Sun Yat-sen Memorial Hospital Sun Yat-sen University.
Other: Artificial Intelligent
Artificial intelligence assisted radiologists to extract ultrasound features of thyroid nodules.
Internal test set
Patients with thyroid nodules underwent contrast-enhanced ultrasound and ultrasound-guided fine-needle aspiration during January 2021 and May 2023 in Sun Yat-sen Memorial Hospital Sun Yat-sen University.
Other: Artificial Intelligent
Artificial intelligence assisted radiologists to extract ultrasound features of thyroid nodules.
External test set
Patients with thyroid nodules underwent contrast-enhanced ultrasound and ultrasound-guided fine-needle aspiration during January 2022 and June 2023 in Houjie Hospital of Dongguan and Central People's Hospital of Zhanjiang.
Other: Artificial Intelligent
Artificial intelligence assisted radiologists to extract ultrasound features of thyroid nodules.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Area under curve.
Time Frame: At the end of the first (M1), third (M3), and sixth (M6) months of the trainees' rotation.
Receiver operating characteristic curve analysis.
At the end of the first (M1), third (M3), and sixth (M6) months of the trainees' rotation.
The number of cases
Time Frame: At the end of the first (M1), third (M3), and sixth (M6) months of the trainees' rotation.
The faculty responsible for the training program assessed the skills of each resident.
At the end of the first (M1), third (M3), and sixth (M6) months of the trainees' rotation.
The cases time.
Time Frame: At the end of the first (M1), third (M3), and sixth (M6) months of the trainees' rotation.
The faculty responsible for the training program assessed the skills of each resident.
At the end of the first (M1), third (M3), and sixth (M6) months of the trainees' rotation.

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

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

Investigators

  • Principal Investigator: Jingliang Ruan, PhD, Sun Yat-sen Memorial Hospital,Sun Yat-sen University

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

January 3, 2024

Primary Completion (Estimated)

July 30, 2026

Study Completion (Estimated)

December 31, 2026

Study Registration Dates

First Submitted

July 24, 2023

First Submitted That Met QC Criteria

August 8, 2023

First Posted (Actual)

August 9, 2023

Study Record Updates

Last Update Posted (Actual)

August 9, 2023

Last Update Submitted That Met QC Criteria

August 8, 2023

Last Verified

August 1, 2023

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • SYSKY-2023-702-01

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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