Neuroimaging: Head and NeckIncidental Thyroid Nodule on Chest Computed Tomography: Application of Computed Tomography Texture Analysis in Prediction of Ultrasound ClassificationJo, Jung In MD∗; Kim, Jung Im MD∗; Ryu, Jung Kyu MD∗; Lee, Han Na MD∗ Author Information From the ∗Department of Radiology, Kyung Hee University Hospital at Gangdong, Seoul, Republic of Korea. Received for publication July 1, 2021; accepted October 6, 2021. Correspondence to: Jung Im Kim, MD, Department of Radiology, Kyung Hee University Hospital at Gangdong, College of Medicine, Kyung Hee University, 892 Dongnam-Ro, Gangdong-Gu, Seoul 05278, Republic of Korea (e-mail: [email protected]). This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. 2021R1F1A1056487). The authors declare no conflict of interest. Journal of Computer Assisted Tomography: 5/6 2022 - Volume 46 - Issue 3 - p 480-486 doi: 10.1097/RCT.0000000000001286 Buy Metrics Abstract Objective The aim of the study was to evaluate the value of computed tomography (CT) texture analysis (CTTA) in predicting ultrasound (US) classification of incidentally detected thyroid nodule (ITN) on chest CT. Methods A total of 117 ITNs (≥1 cm in the longest diameter) on chest CT scan of 107 patients was divided into 4 categories according to the Korean Thyroid Imaging Reporting and Data System (K-TIRADS) classification on recent thyroid US within 3 months. Computed tomography texture features were extracted with or without filtration using commercial software. The texture features were compared between the benign (K-TIRADS 2; n = 21) and the suspicious (K-TIRADS 3, 4, 5; n = 96) nodules. Multivariate regression and area under the receiver operating characteristic curve analysis were performed to determine significant prediction factors of the suspicious nodules. Results The mean value of positive pixels was significantly higher in the suspicious nodules except the unfiltered image (P < 0.05). Entropy of the suspicious nodules was significantly higher with unfiltered and fine filters (P < 0.05), and kurtosis of the suspicious nodules was significantly higher with medium and coarse filters (P < 0.05). A logistic regression model incorporating mean value of positive pixels and kurtosis with a medium filter using volumetric analysis demonstrated the best performance to predict the suspicious nodules with an area under the receiver operating characteristic curve of 0.842 (P < 0.001, sensitivity 82.3%, and specificity 81.0%). Conclusions Computed tomography texture analysis for ITN larger than 1 cm showed significant correlation with systematic thyroid US classification and presented excellent performance to predict the suspicious nodules. Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.