RecruitingNCT07357571

Preoperative Prediction of Lymph Node Metastasis in T1N0M0 Papillary Thyroid Carcinoma by Using Contrast-enhanced Ultrasound

Multicenter Retrospective Study of Dual-mode Contrast-enhanced Ultrasound Predictive Model for Lymph Node Metastasis Burden in T1N0M0 Papillary Thyroid Carcinoma


Sponsor

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Enrollment

600 participants

Start Date

Dec 1, 2025

Study Type

OBSERVATIONAL

Conditions

Summary

Similarly, the burden of central lymph node metastasis affects the individualized management of patients with T1N0M0 papillary thyroid carcinoma (PTC): lymph node metastasis is a contraindication to thermal ablation; low-burden lymph node metastasis is suitable for lobectomy; and high-burden lymph node metastasis recommends total thyroidectomy. However, conventional preoperative imaging examinations have low efficacy in diagnosing central lymph node metastasis. This multicenter retrospective cross-sectional study enrolled 600 patients with T1N0M0 PTC who were admitted to our hospital from June 2018 to June 2025 and confirmed by postoperative pathology. Dynamic contrast-enhanced ultrasound (CEUS) images of the thyroid and lymph nodes before surgery were collected for all patients. Two senior ultrasound physicians unaware of the pathological results independently analyzed the images and extracted qualitative and quantitative CEUS features of lesions and suspicious lymph nodes. Taking postoperative pathological results as the gold standard, patients were divided into the high-burden metastasis group, low-burden metastasis group, and non-metastasis group. Univariate and multivariate Logistic regression analyses were used to screen independent predictors, construct a combined predictive model, and draw receiver operating characteristic (ROC) curves and decision curves to evaluate its diagnostic efficacy and clinical practicality. The primary outcome measure was the area under the curve (AUC), and the secondary outcome measures included sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and net benefit. This project is expected to achieve accurate preoperative prediction of the burden of central lymph node metastasis and realize precise and individualized treatment for patients with T1N0M0 PTC.


Eligibility

Plain Language Summary

Simplified for easier understanding

This study looks at whether a type of ultrasound imaging with a contrast dye can predict before surgery whether thyroid cancer (specifically papillary thyroid cancer at an early stage) has spread to nearby lymph nodes. This is a records-based study using data already collected from patients. **You may be eligible if...** - You were treated for early-stage papillary thyroid cancer (T1N0M0) at one of the participating hospitals between June 2018 and June 2025 - Your cancer diagnosis was confirmed by tissue examination after surgery - You had both standard ultrasound and contrast-enhanced ultrasound done before surgery - You had surgery that included removal of lymph nodes in the neck - Your medical and imaging records are complete and available **You may NOT be eligible if...** - You received radiation, chemotherapy, or other anti-cancer treatment before surgery - You had a different type of thyroid cancer (such as medullary or undifferentiated) - You had previous neck surgery or radiation that could affect lymph node appearance - You had conditions affecting how the contrast ultrasound works (e.g., severe heart failure) - You are allergic to the ultrasound contrast agent - Your records are incomplete Talk to your doctor to see if this trial is right for you.

This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.

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Locations(2)

Sun Yat-sen Memorial Hospital

Guangdong, Guangzhou, China

No. 33 Yingfeng Road, Haizhu District, Guangzhou City, Guangdong Province, Sun Yat-sen Memorial Hospital

Guangzhou, Guangzhou, China

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NCT07357571


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