The value of computer-aided diagnosis (CAD) and computer-assisted techniques equipped with different TIRADS remains ambiguous. Parallel diagnosis performances of computer-assisted subjective assessments and CAD were compared based on AACE, ATA, EU, and KSThR TIRADS. CAD software computed the diagnosis of 162 thyroid nodule sonograms. Two raters (R and R) independently rated the sonographic features of the nodules using an online risk calculator while blinded to pathology results. Diagnostic efficiency measures were calculated based on the final pathology results. R had higher diagnostic performance outcomes than CAD with similarities between KSThR (SEN: 90.3% vs. 83.9%, = 0.57; SPEC: 46% vs. 51%, = 0.21; AUROC: 0.76 vs. 0.67, = 0.02), and EU (SEN: 85.5% vs. 79%, = 0.82; SPEC: 62% vs. 55%, = 0.27; AUROC: 0.74 vs. 0.67, = 0.06). Similarly, R had higher AUROC and specificity but lower sensitivity than CAD (KSThR-AUROC: 0.74 vs. 0.67, = 0.13; SPEC: 61% vs. 46%, = 0.02 and SEN: 75.8% vs. 83.9%, = 0.31, and EU-AUROC: 0.69 vs. 0.67, = 0.57, SPEC: 64% vs. 55%, = 0.19, and SEN: 71% vs. 79%, = 0.51, respectively). CAD had higher sensitivity but lower specificity than both R and R with AACE for 114 specified nodules (SEN: 92.5% vs. 88.7%, = 0.50; 92.5% vs. 79.3%, = 0.02, and SPEC: 26.2% vs. 54.1%, = 0.001; 26.2% vs. 62.3%, < 0.001, respectively). All diagnostic performance outcomes were comparable for ATA with 96 specified nodules. Computer-assisted subjective interpretation using KSThR is more ideal for ruling out papillary thyroid carcinomas than CAD. Future larger multi-center and multi-rater prospective studies with a diverse representation of thyroid cancers are necessary to validate these findings.
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http://dx.doi.org/10.3390/life11111148 | DOI Listing |
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