Abstract
Introduction and aims: CEUS LI-RADS scheme categorizes liver nodules in high-risk patients according to their degree of risk to be HCC. CEUS LI-RADS algorithm classifies nodules in various groups (LR-1 – LR-5, M) according to their enhancement in comparison with surrounding liver parenchyma in different vascular phases and is currently based on the operator's visual impression. We additionally used a prototype of software to quantify the enhancement during the CEUS acquisition. The study aimed to estimate intra-operator, inter-operator and software-operator agreement in classifying the nodules into LI-RADS classes.
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