Dual-energy CT iodine mapping and lymph node characteristic parameters for distinguishing metastatic lymph nodes in papillary thyroid carcinoma

Background : To evaluate the predictive value of dual-energy computed tomography (DECT) iodine quantification combined with lymph node morphological characteristics for identifying metastatic lymph nodes in patients with papillary thyroid carcinoma (PTC). Methods : This retrospective study included 123 histologically confirmed PTC patients who underwent DECT between 2021 and 2023 as the derivation cohort. Among them, 78 patients were randomly selected for internal validation. An additional 47 patients scanned between 2023 and 2024 composed the external validation cohort. Univariate and multivariate logistic regression analyses were conducted to identify independent predictors of lymph node metastasis(LNM). A predictive model was then developed and validated using both internal and external datasets. Results : Multivariate analysis revealed that the arterial phase iodine concentration (≥ 2.6 mg/mL), marked arterial enhancement, heterogeneous enhancement pattern, irregular shape, indistinct margins, and incomplete capsule of the primary thyroid nodule were independent predictors of LNM. A nomogram incorporating DECT-derived iodine metrics and CT-based morphological features was developed. In the internal validation cohort, the model achieved an area under the curve (AUC) of 0.992 (95% CI: 0.956–0.984), with a cutoff value of 0.2, sensitivity of 98%, and specificity of 95%. In the external validation cohort, the AUC was 0.950 (95% CI: 0.893–0.884), with a cutoff value of 0.486, sensitivity of 89%, and specificity of 88%. Conclusion : A predictive model combining DECT iodine concentration with CT-based morphological features provides high diagnostic accuracy for preoperative identification of metastatic lymph nodes in patients with PTC.