RET-US Study - Ultrasound-Based Prediction of RET Alterations and Lateral-Neck Metastasis in Thyroid Cancer

NCT07042984 | Not Yet Recruiting

• 1 other identifier: RET-US
• Study Type: observational
• Target: 800
• Locations: 1 country
• Sites: 1

Brief Summary

Why is this study being done? RET gene alterations occur in only 5-10 % of papillary thyroid cancers, but they can change how surgeons treat the disease. Gene testing is costly and not always performed, so many RET-positive tumours are missed. Researchers have built a computer program (artificial-intelligence or "AI" model) that reads routine thyroid ultrasound images and predicts whether the tumour carries a RET alteration and whether the cancer has already spread to lymph-nodes in the side of the neck. What will happen in this study? About 800 adults who are scheduled for thyroid-cancer surgery will take part. Each participant will:

• have a standard pre-operative ultrasound exam (no extra scanning time),
• give a routine fine-needle sample for a 14-gene panel test (results in 24 h), and
• allow the AI model to analyse the ultrasound images in the background. Doctors making treatment decisions will not see the AI result. After surgery, the research team will compare the AI predictions with the gene-panel result and the final pathology report. Main goal: To find out how accurately the AI model detects RET alterations. Secondary goals: To measure the model's ability to predict lymph-node spread, and to compare costs between ultrasound-only prediction and full gene testing. Benefits and risks: Participants will receive the current standard of care; there is no added risk beyond the usual ultrasound and needle biopsy. The study could lead to faster, less expensive ways to identify high-risk thyroid cancers in the future.

Conditions

Papillary Thyroid Carcinoma; Thyroid Neoplasms; RET Proto-Oncogene Mutation; Lymphatic Metastasis

Keywords

Ultrasound Radiomics; Artificial Intelligence; RET Fusion; BRAF V600E; Lateral Neck Metastasis; Deep Learning Model; 11-Gene Panel

Outcome Measures

Primary Outcomes (1)

• Area Under the ROC Curve (AUC) for AI-Ultrasound Detection of RET Alterations

  The receiver-operating-characteristic area under the curve comparing the AI-generated probability score against the reference 14-gene next-generation sequencing (NGS) result for RET fusion or point mutation. AUC calculated with 95 % confidence interval via DeLong method.

  Date of surgery (assessment completed when gene-panel result is available)

Secondary Outcomes (1)

• Sensitivity and Specificity of AI-Ultrasound for Detecting RET Alterations

  Date of surgery (assessment completed when NGS result is available)

Study Arms (1)

Prospective Thyroid Cancer Cohort

Consecutive adults (18-75 y) with ultrasound-suspected papillary thyroid carcinoma scheduled for surgery. Each participant undergoes standard pre-operative ultrasound, rapid 14-gene next-generation sequencing (NGS) panel, and blinded AI analysis of the ultrasound images. No treatment allocation is made; data are collected prospectively to validate the AI model's ability to detect RET alterations and predict lateral-neck lymph-node metastasis.

Diagnostic Test: AI-Ultrasound RET Prediction

Interventions

AI-Ultrasound RET Prediction DIAGNOSTIC_TEST

Deep-learning algorithm that analyses thyroid ultrasound DICOM images and outputs a probability score for RET gene alteration and lateral-neck lymph-node metastasis; run offline, results blinded to treating surgeons.

Prospective Thyroid Cancer Cohort

Eligibility Criteria

• Age: 18 Years - 75 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Consecutive adults with ultrasound-suspected papillary thyroid carcinoma scheduled for thyroidectomy at participating centers.

You may qualify if:

• Age 18-75 years, able to provide written informed consent.
• Pre-operative ultrasound findings highly suggestive of papillary thyroid carcinoma.
• Planned thyroidectomy (any extent) at a participating institution.
• Willing to undergo rapid 11-gene next-generation sequencing (NGS) panel and allow use of ultrasound DICOM images for AI analysis.

You may not qualify if:

• Prior thyroid or major neck surgery.
• Known medullary thyroid carcinoma, anaplastic carcinoma, or metastatic disease outside the neck.
• Multiple endocrine neoplasia (MEN) syndromes or clinical suspicion of multi-gland disease.
• Pregnant or breastfeeding.
• Severe renal impairment (eGFR \< 30 mL/min/1.73 m²) or other condition that precludes surgery or gene testing.

Sponsors & Collaborators

• Fujian Medical University: lead

Study Sites (1)

Fujian Medical University Union Hospital

Fuzhou, FJ, 350001, China

Location

Biospecimen

Retention: SAMPLES WITH DNA

FNA cytology and paraffin blocks are stored and include DNA extraction for the 11-gene panel.

MeSH Terms

Conditions

Thyroid Cancer, Papillary; Thyroid Neoplasms; Lymphatic Metastasis

Condition Hierarchy (Ancestors)

Adenocarcinoma, Papillary; Adenocarcinoma; Carcinoma; Neoplasms, Glandular and Epithelial; Neoplasms by Histologic Type; Neoplasms; Endocrine Gland Neoplasms; Neoplasms by Site; Head and Neck Neoplasms; Endocrine System Diseases; Thyroid Diseases; Neoplasm Metastasis; Neoplastic Processes; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Central Study Contacts

Bo WANG, MD PhD

CONTACT

+8613959123550; wangbo@fjmu.edu.cn

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Director & Head of Thyroid Surgery, Principal Investigator, Clinical Professor

Study Record Dates

• First Submitted: June 21, 2025
• First Posted: June 29, 2025
• Study Start: July 1, 2025
• Primary Completion (Estimated): July 31, 2029
• Study Completion (Estimated): December 31, 2029
• Last Updated: June 29, 2025

Record last verified: 2025-06

Locations

CN (1)