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The impact of the use of the ACR-TIRADS as a screening tool for thyroid nodules in a cancer center.
- Source :
-
Diagnostic cytopathology [Diagn Cytopathol] 2022 Jan; Vol. 50 (1), pp. 18-23. Date of Electronic Publication: 2021 Nov 19. - Publication Year :
- 2022
-
Abstract
- Background: The Thyroid Imaging Reporting and Data System (TIRADS) was created to assess risk of thyroid nodules through ultrasound. Plenty classifications methods for thyroid nodules have already been created, but none of them have yet achieved global utilization. This study analyzed the performance of the American College of Radiology (ACR) TIRADS, its reproducibility and the impact of its utilization as a screening method in a large Cancer Center cohort.<br />Methods: Thyroid nodules which underwent fine-needle aspiration (FNA) in a 1-year period were selected, with their ultrasound images retrospectively classified according to the ACR TI-RADS. Cytological evaluation of the nodules and final histology (whenever available) was used to assess risk of neoplasm (RON) and risk of malignancy (ROM) associated to each ACR-TIRADS category. Further analyses were also carried out according to recommendation or not of FNA by the ACR-TIRADS and nodule size. Inter-observer agreement for the system was also assessed.<br />Results: A total of 1112 thyroid nodules were included. RON for each category according to final cytological diagnosis was 0% for TR1 and TR2, 2.1% for TR3; 15.6% for TR4 and 68.9% for TR5. No significant difference was observed between the RON of the categories for cases above or below 1.0 cm. Nodules that met the criteria for FNA had 3 times greater chance of a positive outcome. Substantial agreement (kappa 0.77) was seen between two different observers.<br />Conclusions: ACR TI-RADS scoring system has demonstrated to be an accurate method to stratify thyroid nodules in a Cancer Center, with a high reproducibility.<br /> (© 2021 Wiley Periodicals LLC.)
Details
- Language :
- English
- ISSN :
- 1097-0339
- Volume :
- 50
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Diagnostic cytopathology
- Publication Type :
- Academic Journal
- Accession number :
- 34797612
- Full Text :
- https://doi.org/10.1002/dc.24904