Combining ultrasound and cytology whole-slide images to predict cancer risk in indeterminate (Bethesda III) thyroid nodules
Official title: Multimodal Assessment of Malignancy in Atypia of Undetermined Significance in Thyroid Nodules Using Ultrasound and Cytology Whole-Slide Images
Run by Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University · NCT07488325 · Data updated 2026-11-12
This project will test whether a deep learning model that merges ultrasound pictures and cytology whole-slide images can better predict which Bethesda III thyroid nodules are cancerous.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years to 80 Years |
| Sex | All |
| Enrollment | 396 (estimated) |
| Sponsor | Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University Academic / other |
| Locations | 1 site (Guangzhou, Guangzhou) |
| Status | Recruiting |
| Started | March 1, 2026 |
| Main results expected | June 30, 2026 |
| Study ends | July 15, 2026 |
| Registry record updated | April 1, 2026 |
| Trial ID | NCT07488325 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Patients with a Bethesda III (atypia of undetermined significance) cytology result who have at least one preoperative ultrasound image and a definitive postoperative histopathology result or BRAFV600E mutation status are the intended population.
✕Probably not a fit
People without available or usable preoperative ultrasound images, without cytology whole-slide images, or who never undergo surgery or mutation testing would not be eligible and are unlikely to benefit from this model.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This single-center retrospective diagnostic accuracy project builds separate deep learning models using ultrasound images, cytology whole-slide images, and a fusion model that combines both modalities to predict malignancy in Bethesda III thyroid nodules. Consecutive patients with a Bethesda III cytology result who underwent fine-needle aspiration and subsequent thyroid surgery at Sun Yat-sen Memorial Hospital between January 2016 and December 2024 were included if preoperative ultrasound images were available. Postoperative histopathology or BRAFV600E mutation status served as the reference standard, and model performance was measured using receiver operating characteristic curve analysis. Decision curve analysis was used to estimate clinical utility and the study compares diagnostic accuracy of the ultrasound-only, cytology-only, and combined fusion models.
Why it matters
Potential benefit: If successful, this approach could improve preoperative cancer risk estimates and help reduce unnecessary diagnostic surgery for people with indeterminate Bethesda III thyroid nodules.
How similar studies have gone: Prior artificial intelligence work has shown promise using ultrasound or cytology images separately for thyroid nodule classification, but combining ultrasound and whole-slide cytology images is relatively novel and not yet widely validated.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * (a) Patients who underwent fine-needle aspiration of thyroid nodules and received a cytological diagnosis of Bethesda Ⅲ. * (b) Patients who subsequently underwent thyroid surgery with a definitive histopathological diagnosis of benign or malignant lesions,. * (c) Availability of at least one ultrasound image acquired prior to surgery. Exclusion Criteria: * (a) Patients without confirmation by surgical pathology,. * (b) Patients without any available or usable ultrasound images.
Where it's running
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No. 33 Yingfeng Road, Haizhu District, Guangzhou City, Guangdong Province, Sun Yat-sen Memorial Hospital
Guangzhou, Guangzhou, China Recruiting
Study contacts
- Principal investigator: Jingliang Ruan, Ph.D. — Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
- Study coordinator: Jingliang Ruan, Ph.D.
- Email: ruanjl3@mail.sysu.edu.cn
- Phone: +8613694202230
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.