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Image Reporting and Characterization System for Ultrasound Features of Thyroid Nodules: Multicentric Korean Retrospective Study

Authors
 Jin Young Kwak  ;  Inkyung Jung  ;  Jung Hwan Baek  ;  Seon Mi Baek  ;  Nami Choi  ;  Yoon Jung Choi  ;  So Lyung Jung  ;  Eun-Kyung Kim  ;  Jeong-Ah Kim  ;  Ji-hoon Kim  ;  Kyu Sun Kim  ;  Jeong Hyun Lee  ;  Joon Hyung Lee  ;  Hee Jung Moon  ;  Won-Jin Moon  ;  Jeong Seon Park  ;  Ji Hwa Ryu  ;  Jung Hee Shin  ;  Eun Ju Son  ;  Jin Yong Sung  ;  Dong Gyu Na 
Citation
 KOREAN JOURNAL OF RADIOLOGY, Vol.14(1) : 110-117, 2013 
Journal Title
 KOREAN JOURNAL OF RADIOLOGY 
ISSN
 1229-6929 
Issue Date
2013
MeSH
Female ; Humans ; Image Interpretation, Computer-Assisted* ; Korea ; Male ; Middle Aged ; Predictive Value of Tests ; ROC Curve ; Regression Analysis ; Retrospective Studies ; Risk ; Thyroid Nodule/diagnostic imaging* ; Ultrasonography
Keywords
Thyroid ; Thyroid cancer ; Ultrasound
Abstract
OBJECTIVE: The objective of this retrospective study was to develop and validate a simple diagnostic prediction model by using ultrasound (US) features of thyroid nodules obtained from multicenter retrospective data. MATERIALS AND METHODS: Patient data were collected from 20 different institutions and the data included 2000 thyroid nodules from 1796 patients. For developing a diagnostic prediction model to estimate the malignant risk of thyroid nodules using suspicious malignant US features, we developed a training model in a subset of 1402 nodules from 1260 patients. Several suspicious malignant US features were evaluated to create the prediction model using a scoring tool. The scores for such US features were estimated by calculating odds ratios, and the risk score of malignancy for each thyroid nodule was defined as the sum of these individual scores. Later, we verified the usefulness of developed scoring system by applying into the remaining 598 nodules from 536 patients. RESULTS: Among 2000 tumors, 1268 were benign and 732 were malignant. In our multiple regression analysis models, the following US features were statistically significant for malignant nodules when using the training data set: hypoechogenicity, marked hypoechogenicity, non-parallel orientation, microlobulated or spiculated margin, ill-defined margins, and microcalcifications. The malignancy rate was 7.3% in thyroid nodules that did not have suspicious-malignant features on US. Area under the receiver operating characteristic (ROC) curve was 0.867, which shows that the US risk score help predict thyroid malignancy well. In the test data set, the malignancy rates were 6.2% in thyroid nodules without malignant features on US. Area under the ROC curve of the test set was 0.872 when using the prediction model. CONCLUSION: The predictor model using suspicious malignant US features may be helpful in risk stratification of thyroid nodules.
Files in This Item:
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DOI
10.3348/kjr.2013.14.1.110
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers
Yonsei Authors
Kwak, Jin Young(곽진영) ORCID logo https://orcid.org/0000-0002-6212-1495
Kim, Eun-Kyung(김은경) ORCID logo https://orcid.org/0000-0002-3368-5013
Kim, Jeong Ah(김정아) ORCID logo https://orcid.org/0000-0003-4949-4913
Moon, Hee Jung(문희정) ORCID logo https://orcid.org/0000-0002-5643-5885
Son, Eun Ju(손은주) ORCID logo https://orcid.org/0000-0002-7895-0335
Jung, Inkyung(정인경) ORCID logo https://orcid.org/0000-0003-3780-3213
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/86207
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