HCC within LR-M on CEUS LI-RADS: Analysis of Washout Timing & Intensity

Abstract Purpose: LR-M nodules > 1cm, are probably or definitely malignant, but not specific for hepatocellular carcinoma (HCC). HCC is found within LR-M category in 44%. We identify CEUS imaging features within the LR-M category predictive of the presence of HCC. Methods: This single-center retrospective study reviewed 100 CEUS examinations of LR-M nodules in at-risk livers performed between March 2019 and January 2025. CEUS arterial phase enhancement and washout features were documented and classified according to the CEUS LI-RADS v2017 algorithm. Reference standards for HCC diagnosis included biopsy, surgical pathology, or concordant findings on CT/MR. Sensitivity, specificity, and positive predictive value (PPV) were calculated for each CEUS feature. Results: Within LR-M, rapid onset of weak washout persisting as weak to 5 minutes showed the best diagnostic performance for identifying HCC within LR-M. This feature was present in 38/49 (78%) of HCCs and achieved a sensitivity of 78%, specificity of 65%, and PPV of 68%. When combined with non-rim arterial phase hyperenhancement (APHE), rapid onset of weak washout increased specificity to 80% and reduced sensitivity to 61%, with a PPV of 75%. Rim APHE with late weak washout was observed in only 4/49 (8%) of HCCs and did not reach statistical significance. Other washout patterns in LR-M nodules proven to be HCC, including rapid marked and late weak washout, were infrequently encountered and demonstrated limited diagnostic value. Conclusion: Rapid onset of weak washout prior to 1 minute and sustained as weak to 5 minutes, particularly in combination with non-rim APHE, represents the most reliable CEUS feature for prediction of HCC within LR-M. Recognition of this pattern may provide clinicians with greater diagnostic confidence while preserving the high specificity of the LR-5 category. Incorporating this anticipated result into routine interpretation and multidisciplinary discussion can streamline clinical decision-making and optimize management of patients with liver malignancy.