Magnetic Resonance Imaging Characteristics of Papillary Thyroid Carcinoma for the Prediction of Cervical Central Compartment Lymph Node Metastasis.

Abstract

Cervical lymph node metastasis (LNM) is associated with local recurrence and distant metastasis in papillary thyroid carcinoma (PTC). This study was to assess magnetic resonance imaging (MRI) characteristics for predicting cervical LNM in PTC. A total of 119 patients with 154 PTC examined by MRI were assessed. According to inclusion and exclusion criteria, 78 subjects (78 tumors) were included in the final analysis. Conventional MRI findings and apparent diffusion coefficient were recorded. Descriptive statistics for LNM, sensitivity, specificity, and accuracy of various features were obtained. Multivariate logistic regression was performed for identifying independent variables for predicting LNM. Receiver operating characteristic curves were used to assess the diagnostic performance of the independent variables and model. There were 31 node-positive and 47 node-negative PTCs in this study. Node-positive patients significantly differed from the node-negative group in age (P = 0.039), long/short diameter of lymph nodes (both P < 0.001), lymph nodes cystic change (P = 0.005), tumor size (P < 0.001), poorly defined tumor margin in contrast-enhanced imaging (P < 0.001), and thyroid contour protrusion sign (P < 0.001). Satisfactory interobserver agreement was obtained between the 2 examiners (Cohen κ of 0.871 and 0.872). Thyroid contour protrusion sign and poorly defined tumor margin were identified as independent predictive factors of LNM in PTC (both P < 0.05), with area under the curves of 0.813 and 0.851, and accuracies of 0.810 and 0.838. When the independent factors were combined, the diagnostic performance was improved with an area under the curve of 0.944 and an accuracy of 0.884. Thyroid contour protrusion sign and poorly defined tumor margin in contrast-enhanced imaging could be 2 important predicted findings for cervical LNM in PTC.