NCT07296575

Brief Summary

The goal of this observational study is to evaluate the diagnostic accuracy and clinical workflow integration of an ultrasound intelligent agent (UIA) for thyroid disease management in a real-world multicenter setting. The primary research question is: Can the UIA improve diagnostic consistency and efficiency for thyroid nodules (TI-RADS 1-5), Hashimoto's thyroiditis, and cervical lymph node metastasis compared to traditional ultrasound interpretation? Participants will include adults (18-80 years) undergoing thyroid ultrasound at 16 participating hospitals across China. Key inclusion criteria cover patients with suspected thyroid disorders requiring imaging, while exclusion criteria address poor image quality or concurrent clinical trials. Over 2,000 cases (50% thyroid nodules, 30% diffuse lesions, 12.5% non-nodular abnormalities, 7.5% special populations) will be prospectively enrolled. Data collection integrates static/dynamic ultrasound images, laboratory results, and AI-generated reports. Primary endpoints include model performance metrics (AUC, sensitivity/specificity, TI-RADS Kappa ≥0.8), workflow efficiency (report generation time ≤5 minutes), and pediatric/pregnancy-specific reference standards. Secondary analyses will assess inter-rater reliability (Cohen's Kappa) and longitudinal outcomes via 6-12-month follow-up. This study aims to establish evidence-based guidelines for AI-augmented thyroid diagnosis, particularly in underserved regions, while addressing gaps in current AI validation frameworks related to multi-modality data fusion and special population adaptability.

Trial Health

75
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
2,000

participants targeted

Target at P75+ for all trials

Timeline
20mo left

Started Oct 2025

Typical duration for all trials

Geographic Reach
1 country

1 active site

Status
active not recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Progress24%
Oct 2025Dec 2027

Study Start

First participant enrolled

October 1, 2025

Completed
2 months until next milestone

First Submitted

Initial submission to the registry

December 7, 2025

Completed
15 days until next milestone

First Posted

Study publicly available on registry

December 22, 2025

Completed
2 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

December 31, 2027

Expected
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

December 31, 2027

Last Updated

December 22, 2025

Status Verified

December 1, 2025

Enrollment Period

2.2 years

First QC Date

December 7, 2025

Last Update Submit

December 18, 2025

Conditions

ThyroidThyroid CancerThyroid Abnormalities

Keywords

thyroidArtificial IntelligenceUltrasound

Outcome Measures

Primary Outcomes (1)

  • Predictive Performance of Large Models in Ultrasound Thyroid Applications for Thyroid Diseases

    Diagnosing thyroid diseases using a large model in the field of ultrasound thyroid imaging, with histopathological examination results of thyroid lesions as the gold standard, to evaluate the model's sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) for diagnosing thyroid diseases.

    Within 12 months of enrollment for each patient at the time of study completion.

Interventions

No interventionDIAGNOSTIC_TEST

no Intervention

Eligibility Criteria

Sexall
Healthy VolunteersYes
Age GroupsChild (0-17), Adult (18-64), Older Adult (65+)
Sampling MethodProbability Sample
Study Population

Patients with clinically suspected thyroid abnormalities who have been prescribed a thyroid ultrasound examination

You may qualify if:

  • Ages 18-80, clinically suspected thyroid disease (e.g., enlargement, nodules, pain) requiring ultrasound examination;
  • Diffuse lesions must demonstrate both ultrasound characteristics and laboratory evidence;
  • Dynamic video must fully cover the maximum diameter of the nodule without significant probe movement;
  • Voluntary signed informed consent.

You may not qualify if:

  • Poor image quality (severe gas interference, artifacts obscuring structural visualization);
  • Inability to cooperate with examination (consciousness impairment, extreme non-compliance);
  • Prior participation in other thyroid ultrasound-related clinical trials; postoperative thyroid recurrence;
  • Thyroid malformation/ectopia affecting visualization.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Second Affiliated Hospital of Nanchang University

Nanchang, Jiangxi, 330006, China

Location

Related Publications (3)

  • Tessler FN, Middleton WD, Grant EG, Hoang JK, Berland LL, Teefey SA, Cronan JJ, Beland MD, Desser TS, Frates MC, Hammers LW, Hamper UM, Langer JE, Reading CC, Scoutt LM, Stavros AT. ACR Thyroid Imaging, Reporting and Data System (TI-RADS): White Paper of the ACR TI-RADS Committee. J Am Coll Radiol. 2017 May;14(5):587-595. doi: 10.1016/j.jacr.2017.01.046. Epub 2017 Apr 2.

    PMID: 28372962RESULT

  • de Carlos J, Garcia J, Basterra FJ, Pineda JJ, Dolores Ollero M, Toni M, Munarriz P, Anda E. Interobserver variability in thyroid ultrasound. Endocrine. 2024 Aug;85(2):730-736. doi: 10.1007/s12020-024-03731-5. Epub 2024 Feb 19.

    PMID: 38372907RESULT

  • Patel J, Klopper J, Cottrill EE. Molecular diagnostics in the evaluation of thyroid nodules: Current use and prospective opportunities. Front Endocrinol (Lausanne). 2023 Feb 24;14:1101410. doi: 10.3389/fendo.2023.1101410. eCollection 2023.

    PMID: 36909304RESULT

Related Links

MeSH Terms

Conditions

Thyroid DiseasesThyroid Neoplasms

Condition Hierarchy (Ancestors)

Endocrine System DiseasesEndocrine Gland NeoplasmsNeoplasms by SiteNeoplasmsHead and Neck Neoplasms

Study Design

Study Type
observational
Observational Model
OTHER
Time Perspective
CROSS SECTIONAL
Target Duration
12 Months
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Professor

Study Record Dates

First Submitted

December 7, 2025

First Posted

December 22, 2025

Study Start

October 1, 2025

Primary Completion (Estimated)

December 31, 2027

Study Completion (Estimated)

December 31, 2027

Last Updated

December 22, 2025

Record last verified: 2025-12

Data Sharing

IPD Sharing
Will not share

Locations

CN(1)