• Young Jun Choi, Jung Hwan Baek, Seung Hee Baek, Woo Hyun Shim, Kang Dae Lee, Hyoung Shin Lee, Young Kee Shong, Eun Ju Ha, and Jeong Hyun Lee.
• 1 Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine , Seoul, Korea.
• Thyroid. 2015 Dec 1; 25 (12): 1306-12.

BackgroundTo establish a practical and simplified method for analyzing thyroid nodules in a clinical setting, the development of a new practical prediction model was required. This study aimed to construct and validate a simple and reliable web-based predictive model using the ultrasonography characteristics of thyroid nodules to stratify the risk of malignancy.MethodsTo analyze ultrasonography images, radiologists were asked to assess thyroid nodules according to the following criteria: internal content, echogenicity of the solid portion, shape, margin, and calcifications. Multivariate logistic regression was performed to predict whether nodules were diagnosed as malignant or benign. The developmental data set included 849 nodules (January-June 2003). The validation set included different data (n = 453, June 2008-February 2009).ResultsUltrasonography features, including solid content, taller-than-wide shape, spiculated margin, ill-defined margin, hypoechogenicity, marked hypoechogenicity, microcalicifications, and rim calcifications, were selected as predictors for malignant nodules in the development set. A 14-point risk scoring system was developed. Malignancy risk ranged from 3.8% to 97.4%, and the risk of malignancy was positively associated with increases in risk scores. The areas under the receiver operating characteristic curve of the development and validation sets were 0.903 and 0.897, respectively.ConclusionA simple and reliable web-based predictive model was designed using ultrasonography characteristics to stratify thyroid nodules according to the probability of malignancy.

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