ArticleFrontiers in endocrinology2026
Development and validation of an intra-tumoral and peri-tumoral radiomics model based on dynamic contrast-enhanced ultrasound for predicting lymph node metastasis in type 2 diabetic patients with thyroid cancer.
Article in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objectives: This study aimed to develop and validate intra-tumoral and peri-tumoral radiomics models based on dynamic contrast-enhanced ultrasound (CEUS) to preoperatively predict lymph node metastasis (LNM) in thyroid cancer patients with type 2 diabetes. Materials and methods: A total of 203 pathologically confirmed diabetic thyroid cancer patients from three centers were retrospectively included and divided into a training cohort and two external validation cohorts. Radiomics features were extracted from CEUS parameters-time to enhancement (TTE), time to half-peak (TTHP), time to peak (TTP), and washout time (WT). Feature dimensionality reduction was performed using Variance Threshold, SelectKBest, and LASSO regression. Key LNM-related features were screened in the training cohort, and the optimal peri-tumoral region (1 mm vs 2 mm) was determined. Intra-tumoral and peri-tumoral radiomics scores were constructed and integrated into a multivariate logistic regression model. Model performance, calibration, and clinical utility were evaluated across all cohorts. Results: The 2 mm peri-tumoral region yielded a higher AUC than the 1 mm region in all cohorts, with statistical significance in the training cohort and a consistent trend in the external validation cohorts. The combined radiomics model achieved AUCs of 0.930 (95% CI: 0.876-0.964), 0.907 (95% CI: 0.796-0.968), and 0.865 (95% CI: 0.739-0.941) in the training and external validation cohorts. Calibration curves showed good agreement between predicted and actual outcomes, and decision curve analysis demonstrated substantial clinical benefit. Conclusions: The CEUS-based combined radiomics model using intra-tumoral and 2 mm peri-tumoral features provides an effective tool for preoperative LNM prediction in thyroid cancer patients with type 2 diabetes.
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