title: [Exploration on an ultrasonographic imaging reporting and data system in malignancy grading of thyroid nodules].
abstract: OBJECTIVE
  To explore the values of ultrasonographic features in differentially diagnosing benign and malignant thyroid nodules, and attempt to establish a quantitative ultrasound classification system.
  
  
  METHODS
  We retrospectively analyzed 20 ultrasound features of 926 thyroid nodules in 527 patients. Using logistic regression analysis, we obtained the probability function for predicting the malignancy in thyroid nodules and established a preliminary ultrasound classification system.
  
  
  RESULTS
  The ages of patients with thyroid nodules was older than that of the patients with thyroid carcinoma (t = 6.496, P < 0.001). The correctness rate of ultrasonic diagnosis was 80.1%. The logistic multivariate regression analysis showed that among all ultrasonographic features, aspect ratio ≥ 1, obscure boundary, irregular margin, significant internal hypoecho, internal hypoecho, internal micro-calcifications, posterior echo attenuation, thyroid capsule invasion, abnormal adjacent lymph nodes, and ultrasonic elastography 5-point evaluation scores > 3 were contributing factors for thyroid carcinoma. The equation was P (us) = 1 /[1+e(-)Z], where z is the logit of malignant thyroid nodule, and taking P (us) > 0.50 as boundary value, the prediction accuracy rate was 84.1%. Using this model, 92.2% of the thyroid nodules were predicted as nodular goiter, and 69.4% of the thyroid carcinomas were correctly predicted. P (us) was stratified into four levels: Level 1: 0-16% malignancy; Level 2: 17%-50% malignancy; Level 3: 51%-70% malignancy; and level 4: 71%-100% malignancy.
  
  
  CONCLUSIONS
  The quantitative thyroid imaging reporting and data system developed in this study makes ultrasound reports more objective, normalized and standardized. It can be used to evaluate the malignancy risk of thyroid nodules and help to make right decision in clinics.
authors.affiliation: Department of Ultrasound, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China.
authors.forename: Chen
authors.initials: C
authors.lastname: Yang
authors.forename: Chun
authors.initials: C
authors.lastname: Han
authors.forename: Li-ping
authors.initials: LP
authors.lastname: Wang
authors.forename: Na
authors.initials: N
authors.lastname: Feng
authors.forename: Yi-fan
authors.initials: YF
authors.lastname: Wang
authors.affiliation: Email: xdyou@sina.com.
authors.forename: Xiang-dong
authors.initials: XD
authors.lastname: You
mesh_terms: D000328:Adult; D002114:Calcinosis / Q000000981:diagnostic imaging / Q000473:pathology; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D012189:Retrospective Studies; D013961:Thyroid Gland / Q000000981:diagnostic imaging* / Q000473:pathology; D013964:Thyroid Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D016606:Thyroid Nodule / Q000000981:diagnostic imaging* / Q000473:pathology; D014463:Ultrasonography