Evaluation of Thyroid Nodules by a Scoring and Categorizing Method Based on Sonographic Features.
OBJECTIVE
To assess sonographic features of thyroid nodules associated with malignancy and to establish a scoring and categorizing method based on sonographic features.


METHODS
A total of 2445 patients with 2445 thyroid nodules were included and divided into 2 groups: benign (1493 cases) and malignant (952 cases). First, 10 sonographic features, including shape, border, margin, internal content, echogenicity, microcalcifications, posterior echo, halo, vascularization distribution, and vascularization degree, were defined, and all nodules were retrospectively evaluated. Second, the features associated with malignancy were selected by statistical analysis and were assigned weightings according to their odds ratios. Third, a total score for each nodule was obtained after the assigned weightings of the suspicious features were summed. Fourth, the malignancy rate of each total score was calculated. Then a modified version of the Thyroid Imaging Reporting and Data System (TI-RADS) was established with reference to the American College of Radiology's Breast Imaging Reporting and Data System.


RESULTS
Seven independent features associated with malignancy were a taller-than-wide shape, an obscure border, an irregular margin, solid internal content, marked hypoechogenicity and hypoechogenicity, microcalcifications, and an internal vascularization distribution. The TI-RADS included 5 categories with different malignancy rates: category 3 (<2%), 4A (2%-5%), 4B (5%-50%), 4C (50%-90%), and 5 (≥ 90%).


CONCLUSIONS
A modified version of TI-RADS was established on the basis of the sonographic features with different weightings according to the relative risk of malignancy. This system could be of great use in predicting the nature of thyroid nodules in a quantified and standardized way and also helping clinicians decide on the clinical management.
From the Department of Ultrasonography, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Shang-Yan
SY
Xu
From the Department of Ultrasonography, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Wei-Wei
WW
Zhan
From the Department of Ultrasonography, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. xushangyan@126.com.
Wen-Han
WH
Wang
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D002648:Child; D002681:China / Q000453:epidemiology; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D015995:Prevalence; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods; D012680:Sensitivity and Specificity; D016606:Thyroid Nodule / Q000145:classification / Q000000981:diagnostic imaging* / Q000453:epidemiology*; D014463:Ultrasonography; D055815:Young Adult
categorizing; head and neck ultrasound; sonography; thyroid nodule