RT Journal Article
SR Electronic
T1 Computer-Aided Diagnostic System for Thyroid Nodules on Ultrasonography: Diagnostic Performance Based on the Thyroid Imaging Reporting and Data System Classification and Dichotomous Outcomes
JF American Journal of Neuroradiology
JO Am. J. Neuroradiol.
FD American Society of Neuroradiology
SP 559
OP 565
DO 10.3174/ajnr.A6922
VO 42
IS 3
A1 Han, M.
A1 Ha, E.J.
A1 Park, J.H.
YR 2021
UL http://www.ajnr.org/content/42/3/559.abstract
AB BACKGROUND AND PURPOSE: Artificial intelligence-based computer-aided diagnostic systems have been introduced for thyroid cancer diagnosis. Our aim was to compare the diagnostic performance of a commercially available computer-aided diagnostic system and radiologist-based assessment for the detection of thyroid cancer based on the Thyroid Imaging Reporting and Data Systems (TIRADS) and dichotomous outcomes.MATERIALS AND METHODS: In total, 372 consecutive patients with 454 thyroid nodules were enrolled. The computer-aided diagnostic system was set up to render a possible diagnosis in 2 formats, the Korean Society of Thyroid Radiology (K)-TIRADS and the American Thyroid Association (ATA)-TIRADS-classifications, and dichotomous outcomes (possibly benign or possibly malignant).RESULTS: The diagnostic sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the computer-aided diagnostic system for thyroid cancer were, respectively, 97.6%, 21.6%, 42.0%, 93.9%, and 49.6% for K-TIRADS; 94.6%, 29.6%, 43.9%, 90.4%, and 53.5% for ATA-TIRADS; and 81.4%, 81.9%, 72.3%, 88.3%, and 81.7% for dichotomous outcomes. The sensitivities of the computer-aided diagnostic system did not differ significantly from those of the radiologist (all P > .05); the specificities and accuracies were significantly lower than those of the radiologist (all P < .001). Unnecessary fine-needle aspiration rates were lower for the dichotomous outcome characterizations, particularly for those performed by the radiologist. The interobserver agreement for the description of K-TIRADS and ATA-TIRADS classifications was fair-to-moderate, but the dichotomous outcomes were in substantial agreement.CONCLUSIONS: The diagnostic performance of the computer-aided diagnostic system varies in terms of TIRADS classification and dichotomous outcomes and relative to radiologist-based assessments. Clinicians should know about the strengths and weaknesses associated with the diagnosis of thyroid cancer using computer-aided diagnostic systems.AIartificial intelligenceATAAmerican Thyroid AssociationCADcomputer-aided diagnosisFNAfine-needle aspirationKKoreanTIRADSThyroid Imaging Reporting and Data SystemUSultrasonography