Image Reporting and Characterization System for Ultrasound Features of Thyroid Nodules: Multicentric Korean Retrospective Study.
10.3348/kjr.2013.14.1.110
- Author:
Jin Young KWAK
1
;
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
Author Information
1. Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul 120-752, Korea.
- Publication Type:Multicenter Study ; Original Article
- Keywords:
Thyroid;
Ultrasound;
Thyroid cancer
- MeSH:
Female;
Humans;
*Image Interpretation, Computer-Assisted;
Korea;
Male;
Middle Aged;
Predictive Value of Tests;
ROC Curve;
Regression Analysis;
Retrospective Studies;
Risk;
Thyroid Nodule/*ultrasonography
- From:Korean Journal of Radiology
2013;14(1):110-117
- CountryRepublic of Korea
- Language:English
-
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.
