ArticleFrontiers in endocrinology2024
Score based on contrast-enhanced ultrasound predict central lymph node metastasis in papillary thyroid cancer.
Article in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Predicting lateral cervical lymph node involvement in papillary thyroid carcinoma patients: development of a nomogram model based on contrast-enhanced ultrasound images.Gland surgery · 2026Article
- Prediction of lymph node metastasis in cN0 papillary thyroid carcinoma using a random forest-based radiomics model integrating contrast-enhanced ultrasound and clinical data.Frontiers in oncology · 2026Article
- Dose-Response Relationship Between BRAF V600E Abundance and Cervical Lymph Node Metastasis in Papillary Thyroid Cancer.Cancers · 2025Article
- A risk stratification model based on ultrasound radiologic features for cervical metastatic lymph nodes in papillary thyroid cancer.World journal of surgical oncology · 2025Article
- Development and validation of a dynamic nomogram for predicting central lymph node metastasis in papillary thyroid carcinoma patients based on clinical and ultrasound features.Quantitative imaging in medicine and surgery · 2025Article
- Construction of a predictive model for cervical lymph node metastasis in papillary thyroid carcinoma.Frontiers in oncology · 2025Article
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Abstract
Objectives: To investigate the association between contrast-enhanced ultrasound (CEUS) features of PTC and central lymph node metastasis (CLNM) and to develop a predictive model for the preoperative identification of CLNM. Methods: This retrospective study evaluated 750 consecutive patients with PTC from August 2020 to April 2023. Conventional ultrasound and qualitative CEUS features were analyzed for the PTC with or without CLNM using univariate and multivariate logistic regression analysis. A nomogram integrating the predictors was constructed to identify CLNM in PTC. The predictive nomogram was validated using a validation cohort. Results: A total of 684 patients were enrolled. The 495 patients in training cohort were divided into two groups according to whether they had CLNM (pCLNM, n= 191) or not (nCLNM, n= 304). There were significant differences in terms of tumor size, shape, echogenic foci, enhancement direction, peak intensity, and score based on CEUS TI-RADS between the two groups. Independent predictive US features included irregular shape, larger tumor size (≥ 1.0cm), and score. Nomogram integrating these predictive features showed good discrimination and calibration in both training and validation cohort with an AUC of 0.72 (95% CI: 0.68, 0.77) and 0.79 (95% CI: 0.72, 0.85), respectively. In the subgroup with larger tumor size, age ≤ 35 years, irregular shape, and score > 6 were independent risk factors for CLNM. Conclusion: The score based on preoperative CEUS features of PTC may help to identify CLNM. The nomogram developed in this study provides a convenient and effective tool for clinicians to determine an optimal treatment regimen for patients with PTC.
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