JianQiao Zhou1, YanYan Song2, WeiWei Zhan3, Xi Wei4, Sheng Zhang4, RuiFang Zhang5, Ying Gu6, Xia Chen6, Liying Shi6, XiaoMao Luo7, LiChun Yang7, QiaoYing Li8, BaoYan Bai9, XinHua Ye10, Hong Zhai11, Hua Zhang12, XiaoHong Jia13, YiJie Dong13, JingWen Zhang13, ZhiFang Yang13, HuiTing Zhang13, Yi Zheng13, WenWen Xu13, LiMei Lai13, LiXue Yin14. 1. Department of Ultrasound, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, 200025, China. zhousu30@126.com. 2. Department of Biostatistics, Institute of Medical Sciences, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China. syyssmu@126.com. 3. Department of Ultrasound, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, 200025, China. shanghairuijinus@163.com. 4. Department of Diagnostic and Therapeutic Ultrasound, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, 300060, China. 5. Department of Ultrasound, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, 450052, China. 6. Department of Ultrasound, Affiliated Hospital of Guizhou Medical University, Guiyang, 550001, China. 7. Department of Ultrasound, The Third Affiliated Hospital Of Kunming Medical University, Yunnan Cancer Hospital, Kunming, 650031, China. 8. Department of Ultrasound Diagnostics, Tangdu Hospital, Fourth Military Medical University, Xi'an, 710038, China. 9. Department of Ultrasound, Affiliated Hospital of Yan'an University, School of Medicine, Yan'an University, Shanxi, 716000, China. 10. Department of Ultrasound, the first affiliated Hospital of Nanjing Medical University, NanJing, 210029, China. 11. Department of Abdominal Ultrasound, The fourth Clinical Medical Collegen, Xinjiang Medical University, Urumqi, 830000, China. 12. Department of ultrasound, Anyang tumor hospital, The Fourth Affiliated Hospital of Henan University of Science and Technology, Anyang, 455000, China. 13. Department of Ultrasound, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, 200025, China. 14. Institute of Ultrasound in Medicine, The Affiliated Sichuan Provincial People's Hospital of Electronic Science and Technology University of China, Chengdu, 610071, China.
Abstract
PURPOSE: To establish a practical and simplified Chinese thyroid imaging reporting and data system (C-TIRADS) based on the Chinese patient database. METHODS: A total of 2141 thyroid nodules that were neither cystic nor spongy were used in the current study. These specimens were derived from 2141 patients in 131 alliance hospitals of the Chinese Artificial Intelligence Alliance for Thyroid and Breast Ultrasound. The ultrasound features, including location, orientation, margin, halo, composition, echogenicity, echotexture, echogenic foci and posterior features were assessed. Univariate and multivariate analyses were performed to investigate the association between ultrasound features and malignancy. The regression equation, the weighting, and the counting methods were used to determine the malignant risk of the thyroid nodules. The areas under the receiver operating characteristic curve (Az values) were calculated. RESULTS: Of the 2141 thyroid nodules, 1572 were benign, 565 were malignant, and 4 were borderline. Vertical orientation, ill-defined, or irregular margin (including extrathyroidal extension), microcalcifications, solid, and markedly hypoechoic were positively associated with malignancy, while comet-tail artifacts were negatively associated with malignancy. The logistic regression equation yielded the highest Az value of 0.913, which was significantly higher than that obtained using the weighting method (0.893) and the counting method (0.890); however, no significant difference was found between the latter two. The C-TIRADS, based on the counting method, was designed following the principle of balancing the diagnostic performance and sensitivity of the risk stratification with the ease of use. CONCLUSIONS: A relatively simple C-TIRADS was established using the counting value of positive and negative ultrasound features.
PURPOSE: To establish a practical and simplified Chinese thyroid imaging reporting and data system (C-TIRADS) based on the Chinese patient database. METHODS: A total of 2141 thyroid nodules that were neither cystic nor spongy were used in the current study. These specimens were derived from 2141 patients in 131 alliance hospitals of the Chinese Artificial Intelligence Alliance for Thyroid and Breast Ultrasound. The ultrasound features, including location, orientation, margin, halo, composition, echogenicity, echotexture, echogenic foci and posterior features were assessed. Univariate and multivariate analyses were performed to investigate the association between ultrasound features and malignancy. The regression equation, the weighting, and the counting methods were used to determine the malignant risk of the thyroid nodules. The areas under the receiver operating characteristic curve (Az values) were calculated. RESULTS: Of the 2141 thyroid nodules, 1572 were benign, 565 were malignant, and 4 were borderline. Vertical orientation, ill-defined, or irregular margin (including extrathyroidal extension), microcalcifications, solid, and markedly hypoechoic were positively associated with malignancy, while comet-tail artifacts were negatively associated with malignancy. The logistic regression equation yielded the highest Az value of 0.913, which was significantly higher than that obtained using the weighting method (0.893) and the counting method (0.890); however, no significant difference was found between the latter two. The C-TIRADS, based on the counting method, was designed following the principle of balancing the diagnostic performance and sensitivity of the risk stratification with the ease of use. CONCLUSIONS: A relatively simple C-TIRADS was established using the counting value of positive and negative ultrasound features.
Authors: Mary C Frates; Carol B Benson; J William Charboneau; Edmund S Cibas; Orlo H Clark; Beverly G Coleman; John J Cronan; Peter M Doubilet; Douglas B Evans; John R Goellner; Ian D Hay; Barbara S Hertzberg; Charles M Intenzo; R Brooke Jeffrey; Jill E Langer; P Reed Larsen; Susan J Mandel; William D Middleton; Carl C Reading; Steven I Sherman; Franklin N Tessler Journal: Radiology Date: 2005-12 Impact factor: 11.105
Authors: Bryan R Haugen; Erik K Alexander; Keith C Bible; Gerard M Doherty; Susan J Mandel; Yuri E Nikiforov; Furio Pacini; Gregory W Randolph; Anna M Sawka; Martin Schlumberger; Kathryn G Schuff; Steven I Sherman; Julie Ann Sosa; David L Steward; R Michael Tuttle; Leonard Wartofsky Journal: Thyroid Date: 2016-01 Impact factor: 6.568
Authors: Jin Young Kwak; Kyung Hwa Han; Jung Hyun Yoon; Hee Jung Moon; Eun Ju Son; So Hee Park; Hyun Kyung Jung; Ji Soo Choi; Bo Mi Kim; Eun-Kyung Kim Journal: Radiology Date: 2011-07-19 Impact factor: 11.105