Determining the Best Thyroid Imaging Reporting and Data System: A Prospective Study Comparing the Diagnostic Performance of ACR, EU, and K TIRADS in the Evaluation of Thyroid Nodules.
Indian J Radiol Imaging
; 34(2): 220-231, 2024 Apr.
Article
en En
| MEDLINE
| ID: mdl-38549906
ABSTRACT
Background Many different risk stratification systems have been formulated for thyroid nodules, differing in their fine-needle aspiration cytology (FNAC) indication, suggesting a lack of consensus around the world. Purpose This prospective study was conducted to find the best guideline for risk stratification, for a better malignancy yield, and with reduced rates of negative FNACs among three Thyroid Imaging, Reporting, and Data System (TIRADS) guidelines. Materials and Methods A total of 625 thyroid nodules with conclusive FNAC or histopathological diagnosis were included in the study. Various sonographic parameters were recorded. They were classified into categories as per the three guidelines and compared with FNAC diagnosis. The guidelines were evaluated in terms of sensitivity, specificity, predictive values, and diagnostic accuracy. Sensitivity and specificity were compared by McNemar's test. Results American College of Radiology (ACR) TIRADS had the highest diagnostic accuracy (56.8%), specificity (50.75%), positive predictive value (23.92%), lowest rates of negative FNACs (76.08%), and high negative predictive value (97.84 %). Korean (K) TIRADS had the maximum sensitivity (97.75%), highest negative predictive value (98.44%), and gross malignancy yield. European TIRADS was between the two other guidelines in most parameters with specificity like K TIRADS. Conclusion All the three guidelines are very good screening tools, with comparable high sensitivity. ACR TIRADS is better in terms of specificity and reduced rates of negative FNACs. Including the presence of a suspicious cervical lymph node as a criterion and more frequent follow-up might further improve the diagnostic performance of the guideline.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Idioma:
En
Revista:
Indian J Radiol Imaging
Año:
2024
Tipo del documento:
Article
País de afiliación:
India