BACKGROUND: The Thyroid Imaging Reporting and Data System (TI-RADS) was proposed based on a scheme similar to Breast Imaging Reporting and Data System (BI-RADS) lexicon used in breast lesions. The purpose of this study was to evaluate its interobserver variability and accuracy. METHODS: We included 498 nodules in 437 patients undergoing thyroidectomy. Two endocrine surgeons and 2 endocrinologists independently reviewed sonographic images. RESULTS: There was moderate to substantial interobserver agreement for final assessment category (kappa = 0.61). The overall sensitivity, specificity, and negative predictive value (NPV) were 94%, 43%, and 96%, respectively. Positive predictive values (PPVs) for categories 4 and 5 were 32% and 60%. The sensitivity was 92%, 99%, 96%, and 89%, whereas the specificity was 25%, 37%, 41%, and 62% for tumor sizes of <2, 2 to 3, 3 to 4, and >4 cm, respectively. CONCLUSION: TI-RADS is a helpful but not optimal reporting tool in characterizing thyroid lesions. Tumor size has a considerable impact on interobserver concordance and diagnostic performance.
BACKGROUND: The Thyroid Imaging Reporting and Data System (TI-RADS) was proposed based on a scheme similar to Breast Imaging Reporting and Data System (BI-RADS) lexicon used in breast lesions. The purpose of this study was to evaluate its interobserver variability and accuracy. METHODS: We included 498 nodules in 437 patients undergoing thyroidectomy. Two endocrine surgeons and 2 endocrinologists independently reviewed sonographic images. RESULTS: There was moderate to substantial interobserver agreement for final assessment category (kappa = 0.61). The overall sensitivity, specificity, and negative predictive value (NPV) were 94%, 43%, and 96%, respectively. Positive predictive values (PPVs) for categories 4 and 5 were 32% and 60%. The sensitivity was 92%, 99%, 96%, and 89%, whereas the specificity was 25%, 37%, 41%, and 62% for tumor sizes of <2, 2 to 3, 3 to 4, and >4 cm, respectively. CONCLUSION: TI-RADS is a helpful but not optimal reporting tool in characterizing thyroid lesions. Tumor size has a considerable impact on interobserver concordance and diagnostic performance.
Authors: Salvatore Gitto; Giorgia Grassi; Chiara De Angelis; Cristian Giuseppe Monaco; Silvana Sdao; Francesco Sardanelli; Luca Maria Sconfienza; Giovanni Mauri Journal: Radiol Med Date: 2018-09-22 Impact factor: 3.469
Authors: Andrew B Rosenkrantz; Luke A Ginocchio; Daniel Cornfeld; Adam T Froemming; Rajan T Gupta; Baris Turkbey; Antonio C Westphalen; James S Babb; Daniel J Margolis Journal: Radiology Date: 2016-04-01 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: D A Krieger; P A Hudgins; G K Nayak; K L Baugnon; A S Corey; M R Patel; J J Beitler; N F Saba; Y Liu; A H Aiken Journal: AJNR Am J Neuroradiol Date: 2017-03-31 Impact factor: 3.825
Authors: Pablo Valderrabano; Donald L Klippenstein; John B Tourtelot; Zhenjun Ma; Zachary J Thompson; Howard S Lilienfeld; Bryan McIver Journal: Thyroid Date: 2016-07-08 Impact factor: 6.568