RET-US Cohort: Prospective Evaluation of an AI-Ultrasound Model for Detecting RET Gene Alterations and Predicting Lateral Cervical Lymph-Node Metastasis in Papillary Thyroid Carcinoma
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 800
- 试验地点
- 1
- 主要终点
- Area Under the ROC Curve (AUC) for AI-Ultrasound Detection of RET Alterations
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 75 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •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.
排除标准
- •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.
结局指标
主要结局
Area Under the ROC Curve (AUC) for AI-Ultrasound Detection of RET Alterations
时间窗: Date of surgery (assessment completed when gene-panel result is available)
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.
次要结局
- Sensitivity and Specificity of AI-Ultrasound for Detecting RET Alterations(Date of surgery (assessment completed when NGS result is available))
研究者
Bo Wang,MD
Director & Head of Thyroid Surgery, Principal Investigator, Clinical Professor
Fujian Medical University Union Hospital