Real-Time AI-Based ACR TI-RADS Classification of Thyroid Nodules on the Ultrasound Console: A Prospective Agreement Study in a Region with Historical Iodine Deficiency

Background/Objectives: To assess the agreement between an artificial intelligence (AI)-based decision support system (DS System), applied in real time directly on the ultrasound console, and an expert panel for ACR TI-RADS classification of thyroid nodules (TNs) in a region with a history of iodine deficiency and a consequently high prevalence of TNs.

Methods

A single-center prospective study including 118 consecutive patients (with 276 TNs) referred for thyroid ultrasound between March and May 2024. DS System ultrasound features, ACR TI-RADS classifications (TR1–TR5) and management recommendations were recorded per TN, with and without the ‘AI-Adapter’ (AI-based modification of the TI-RADS score), and compared to the consensus assessment of a TI-RADS expert panel (paired tests of marginal homogeneity, Cohen’s unweighted and weighted κ; all analyses adjusted for clustering of TNs within patients).