Using artificial intelligence to improve ultrasound diagnosis of thyroid nodules
Artificial Intelligent Accelerates the Learning Curve for Mastering Thyroid Imaging Reporting and Data System of Contrast-enhanced Ultrasound
This study is testing if using artificial intelligence can help doctors learn to diagnose thyroid nodules with ultrasound faster and more accurately.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 1000 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University Academic / other |
| Locations | 1 site (Guangzhou, Guangdong) |
| Trial ID | NCT05982821 on ClinicalTrials.gov |
What this trial studies
This observational study aims to evaluate how artificial intelligence can enhance the learning curve for mastering contrast-enhanced ultrasound in diagnosing thyroid nodules. Participants will undergo contrast-enhanced ultrasound examinations and ultrasound-guided fine-needle aspirations, allowing researchers to compare the efficiency and effectiveness of doctors using AI assistance versus those who do not. The study seeks to determine if AI can reduce the number of cases and the time required for doctors to become proficient in this diagnostic technique.
Who should consider this trial
Good fit: Ideal candidates are patients with thyroid nodules that have a solid component of 5 mm or larger, confirmed by conventional ultrasound.
Not a fit: Patients with certain cytopathology results or those who have undergone thyroid surgery or ablation may not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could significantly streamline the training process for healthcare providers, leading to faster and more accurate diagnoses of thyroid nodules.
How similar studies have performed: While the use of AI in medical imaging is gaining traction, this specific application in mastering contrast-enhanced ultrasound for thyroid nodules is relatively novel.
Eligibility criteria
Show full inclusion / exclusion criteria
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.
Where this trial is running
Guangzhou, Guangdong
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University — Guangzhou, Guangdong, China (Recruiting)
Study contacts
- Principal investigator: Jingliang Ruan, PhD — Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
- Study coordinator: Jingliang Ruan, PhD
- Email: ruanjl3@mail.sysu.edu.cn
- Phone: +8613694202230
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.