Title:Evaluating Diagnostic Efficiency of Thyroid Imaging Reporting and Data
Systems proposed by the American College of Radiology in Surgically Resected
Thyroid Nodules
Volume: 20
Author(s): Izadmehr Ahmadinejad, Kimia Ghanbari Mardasi, Yasmina Ahmadinejad, Mohammad Saeed Kahrizi, Ali Soltanian, Pooriya Ghanbari Merdasi and Mojtaba Ahmadinejad*
Affiliation:
- Department of Surgery, School of Medicine, Alborz University of Medical Sciences, Karaj, Iran
Keywords:
ACR-TIRADS, Thyroid, Imaging, Malignancy, Nodules, Ultrasound.
Abstract:
Aim:
Thyroid nodules are one of the most common clinical findings, with a prevalence of 68% in adults. Thyroid cancer is the fifth most common cancer
in women.
Introduction:
The purpose of this study is to evaluate the diagnostic efficacy of Thyroid Imaging Reporting and Data Systems proposed by the American College
of Radiology (ACR-TIRADS) for the diagnosis of malignancy in surgically resected thyroid nodules.
Methods:
In this retrospective study, patients who underwent thyroid nodules resected surgically from 2018-2020 were included. Before resection, an
ultrasound was performed for TIRADS scores, and after resection histopathology, thyroid mass was obtained. The outcomes of the two systems
were statistically compared.
Results:
The mean age of the 146 included patients was 47.6 ± 14.08 years, of which 109 (74.7%) were female. Based on TIRADS, 47 patients (32.2%)
were in TI-RADS TR3, 36 patients (24.7%) were in TIRADS TR2, 34 (23.3%) in TIRADS 4, 24 (16.4%) in TIRADS TR5 and 5 patients (3.4%)
were in TIRADS TR1. The overall sensitivity was 79.9% when ACR-TIRADS TR4 was set as a diagnostic cutoff value. Considering the total of
TIRADS TR4 and TIRADS TR5 as predictors of thyroid malignancy, the sensitivity was 74.5% and the specificity was 76.8%. The positive and
negative predictive value was 60.3% and 76.8%.
Conclusion:
ACR-TIRADS 4 and 5 can be considered good predictors of malignancy in thyroid nodules. More studies, including larger samples, are required to
obtain a better conclusion.
