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

Background RET rearrangements or point mutations drive a minority of papillary thyroid carcinomas (PTC) yet are associated with aggressive behaviour and may qualify patients for selective RET inhibitors. Because of low prevalence, RET testing is often omitted, resulting in under-recognition. Recent work shows that high-resolution ultrasound contains radiomic signatures linked to tumour genotypes. A deep-learning model (EfficientNet-B3 backbone with dual segmentation + multi-label heads) was trained on 1 000 retrospectively collected cases, including 74 RET-positive tumours augmented with GAN-based synthetic images, achieving an AUC of 0.87 for RET prediction in internal cross-validation.

Objectives Primary: validate the AI model's area under the receiver-operating characteristic curve (AUC) for RET alteration detection in a prospective cohort.

Secondary: (i) sensitivity/specificity for RET; (ii) accuracy for predicting lateral-neck (pN1b) metastasis; (iii) incremental cost per correct RET diagnosis; (iv) concordance between AI probability score and lymph-node burden.

Design Single-arm, prospective observational cohort (n = 800). Consecutive eligible patients will undergo: (1) routine pre-operative thyroid ultrasound; (2) upload of DICOM files to a cloud inference server; (3) rapid 14-gene next-generation sequencing panel on FNA or paraffin tissue (includes RET fusions KIF5B, CCDC6, NCOA4 and point mutations M918T, V804). Surgeons remain blinded to AI output. Surgical specimens provide ground truth for pN staging. Data captured in REDCap; statistical analysis uses DeLong test for AUC and McNemar test for paired accuracy.

Eligibility Adults 18-75 y with radiologically suspected PTC, planned thyroidectomy, and consent for gene testing. Exclusions: re-operative neck, medullary/anaplastic carcinoma, pregnancy, eGFR < 30 mL min-¹ 1.73 m-².

Sample Size With expected RET prevalence 6 % and target AUC ≥ 0.80 vs null 0.50, 800 cases provide 90 % power (α = 0.05).

Ethics & Oversight IRB approved; minimal-risk diagnostic study. Ultrasound and FNA are standard-of-care; AI inference uses de-identified images. Results will be disseminated via peer-reviewed journals and conference presentations.

Inclusion criteria

• 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.

Exclusion criteria

• 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.