Ultrasound Large-scale Model in Thyroid Field: A Multi-center Study on Medical-Engineering Integration

N/AActive Not RecruitingNCT07296575

Second Affiliated Hospital of Nanchang University2,000 enrolled

Overview

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.

Study Type

OBSERVATIONAL

Enrollment

2,000

Conditions

Thyroid Abnormalities Thyroid Thyroid Cancer

Eligibility

Sex: ALLHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: * 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. Exclusion Criteria: * 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.

Outcomes

Primary Outcomes

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.

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