S-Detect Software vs. EU-TIRADS Classification: A Dual-Center Validation of Diagnostic Performance in Differentiation of Thyroid Nodules

Abstract

Computer-aided diagnosis (CAD) and other risk stratification systems may improve ultrasound image interpretation. This prospective study aimed to compare the diagnostic performance of CAD and the European Thyroid Imaging Reporting and Data System (EU-TIRADS) classification applied by physicians with S-Detect 2 software CAD based on Korean Thyroid Imaging Reporting and Data System (K-TIRADS) and combinations of both methods (MODELs 1 to 5). In all, 133 nodules from 88 patients referred to thyroidectomy with available histopathology or with unambiguous results of cytology were included. The S-Detect system, EU-TIRADS, and mixed MODELs 1–5 for the diagnosis of thyroid cancer showed a sensitivity of 89.4%, 90.9%, 84.9%, 95.5%, 93.9%, 78.9% and 93.9%; a specificity of 80.6%, 61.2%, 88.1%, 53.7%, 73.1%, 89.6% and 80.6%; a positive predictive value of 81.9%, 69.8%, 87.5%, 67%, 77.5%, 88.1% and 82.7%; a negative predictive value of 88.5%, 87.2%, 85.5%, 92.3%, 92.5%, 81.1% and 93.1%; and an accuracy of 85%, 75.9%, 86.5%, 74.4%, 83.5%, 84.2%, and 87.2%, respectively. Comparison showed superiority of the similar MODELs 1 and 5 over other mixed models as well as EU-TIRADS and S-Detect used alone (p-value < 0.05). S-Detect software is characterized with high sensitivity and good specificity, whereas EU-TIRADS has high sensitivity, but rather low specificity. The best diagnostic performance in malignant thyroid nodule (TN) risk stratification was obtained for the combined model of S-Detect (“possibly malignant” nodule) and simultaneously obtaining 4 or 5 points (MODEL 1) or exactly 5 points (MODEL 5) on the EU-TIRADS scale.

Assessment of perinodular stiffness in differentiating malignant from benign thyroid nodules

“…Although the combinations of RSS with different US technologies have been applied to improve the accuracy of diagnosis of benign and malignant TNs, they only focused on a single RSS version ( 13 , 14 , 15 , 16 , 17 , 18 , 19 , 22 , 38 , 39 ). Thus, we combined multiple RSSs versions with the perinodular stiffness index, which would be easier to generalize due to its broad applicability.…”

A Computer-Aided Diagnosis System and Thyroid Imaging Reporting and Data System for Dual Validation of Ultrasound-Guided Fine-Needle Aspiration of Indeterminate Thyroid Nodules

“…Ultrasound (US) is widely used as a noninvasive and effective screening modality for the detection of thyroid nodules. However, although various diagnostic standards and guidelines are available, the diagnostic specificity remains unsatisfactory (3). Since first proposed in 2009, the Thyroid Imaging Reporting and Data System (TI-RADS) has become among the most widely applied approaches for US-based diagnosis of thyroid diseases, as this system allows the physician to analyze the composition, echogenicity, shape, orientation, margin, calcification, presence of a halo, and type of vascularization for more accurate diagnosis and treatment (4).…”

The European Institute of Oncology Thyroid Imaging Reporting and Data System for Classification of Thyroid Nodules: A Prospective Study

“…A new generation of US machines, computer-aided diagnosis (CAD) and other stratification systems can improve US image evaluation. New US software has been developed to automatically assess the US features and evaluate the TN in terms of the degree of risk of malignancy after the identification of a TN by the operator [ 16 ]. One of these pieces of software, “S-Detect”, is used to evaluate the risk of malignancy of TNs, and automatically assesses the following US features: composition, margins, echogenicity, orientation, spongiform appearance, shape, and calcifications.…”