Abstract

Simple SummaryFrom a prospective series of 480 thyroid nodules, we compared the performances of the American College of Radiology (ACR) and the European Thyroid Association (EU) scoring systems in triaging thyroid nodules for fine-needle aspiration (FNA). FNA was recommended on 46.5% and 51.9% of the nodules using the ACR and EU-TIRADS scores, respectively. The ACR system demonstrated a higher specificity as compared to the EU-TIRADS (59.0% vs. 52.4%, p = 0.0012) in predicting ≥TIR3A/III (SIAPEC/Bethesda) nodules. Moreover, specific radiological features (i.e., echogenic foci and margins), combined with the cytological classes improved the specificity (97.5% vs. 91%, p < 0.0001) and positive predictive value (77.5% vs. 50.7%, p < 0.0001) of the cytology alone, maintaining an excellent sensitivity and negative predictive value.Objective: The American College of Radiology (ACR) and the European Thyroid Association (EU) have proposed two scoring systems for thyroid nodule classification. Here, we compared the ability of the two systems in triaging thyroid nodules for fine-needle aspiration (FNA) and tested the putative role of an approach that combines ultrasound features and cytology for the detection of malignant nodules. Design and Methods: The scores obtained with the ACR and EU Thyroid Imaging Reporting and Data Systems (TIRADS) from a prospective series of 480 thyroid nodules acquired from 435 subjects were compared to assess their performances in FNA triaging on the final cytological diagnosis. The US features that showed the highest contribution in discriminating benign nodules from malignancies were combined with cytology to improve its diagnostic performance. Results: FNA was recommended on 46.5% and 51.9% of the nodules using the ACR and EU-TIRADS scores, respectively. The ACR system demonstrated a higher specificity as compared to the EU-TIRADS (59.0% vs. 52.4%, p = 0.0012) in predicting ≥ TIR3A/III (SIAPEC/Bethesda) nodules. Moreover, specific radiological features (i.e., echogenic foci and margins), combined with the cytological classes improved the specificity (97.5% vs. 91%, p < 0.0001) and positive predictive values (77.5% vs. 50.7%, p < 0.0001) compared to cytology alone, especially in the setting of indeterminate nodules (TIR3A/III and TIR3B/IV), maintaining an excellent sensitivity and negative predictive value. Conclusions: The ACR-TIRADS system showed a higher specificity compared to the EU-TIRADS in triaging thyroid nodules. The use of specific radiological features improved the diagnostic ability of cytology.

Highlights

  • In the international scenario, different alternative ultrasound (US) algorithms have been proposed for characterizing thyroid nodules [1]

  • Defensive medicine, excessive scrupulousness, or limited experience could induce clinicians to perform fine-needle aspiration (FNA) regardless of the Thyroid Imaging Reporting and Data Systems (TIRADS) score, especially in large nodules, still depending on cytology for the final answer regarding the nature of a thyroid lesion and reducing the practical utility of TIRADS [8]

  • We found no improvement in diagnostic accuracy by combining either American College of Radiology (ACR) or European Thyroid Association (EU)-TIRADS and the cytology class

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Summary

Introduction

Different alternative ultrasound (US) algorithms have been proposed for characterizing thyroid nodules [1]. The American College of Radiology (ACR) Thyroid Imaging Reporting and Data Systems (TIRADS) consists of a scale with increasing scores for specific US features of thyroid nodules and is able to stratify lesions with a progressively higher risk of malignancy (ROM) [2,3,4]. On this side of the Atlantic ocean, the European Thyroid Association (EU-TIRADS) proposed in 2017 a US pattern recognition method that combines high-risk criteria, such as nodule composition, echogenicity, margins, shape, and calcifications [5]. The present paper supports the hypothesis that specific US features, coupled with cytological classes, might be better able predict the final malignant nature of a thyroid nodule

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