Fat-containing hepatocellular carcinoma in patients with cirrhosis: proposal of a diagnostic modification regarding enhancement characteristics

ObjectivesThe aim of this study was to develop and validate an algorithm for the non-invasive diagnosis of these fat-containing HCCs.MethodsEighty-four cirrhotic patients with 77 fat-containing HCCs and 11 non-HCC fat-containing nodules were retrospectively included. All MRIs were reviewed; nodule characteristics, European Association for the Study of the Liver (EASL) and LI-RADS classifications, and survival were collected. One of the major features of LI-RADS v2018 (non-rim-like arterial phase hyperenhancement [APHE]) was changed to include different enhancing patterns at arterial phase and a new fat-LI-RADS algorithm was created for fat-containing nodules in cirrhosis. Its diagnostic performance was evaluated in both a derivation and external validation cohort (external cohort including 58 fat-containing HCCs and 10 non-HCC fat nodules). Reproducibility of this new algorithm was assessed.ResultsIn the derivation cohort, 54/77 (70.1%) fat-containing HCCs had APHE, 62/77 (80.5%) had enhancement compared to the nodule itself at arterial phase (APE), 43/77 (55.8%) had washout, and 20/77 (26.0%) had an enhancing capsule. EASL and LI-RADS had a sensitivity of 37.7% (29/77) and 36.4% (28/77), respectively, for the diagnosis of fat-containing HCC and both had a specificity of 100% (11/11). The new fat-LI-RADS algorithm increased sensitivity to 50.6% (39/77) without decreasing the specificity of 100% (11/11). The validation cohort confirmed the increased sensitivity, with a slight decrease in specificity. The concordance for the diagnosis of HCC for fat-LR5 was 85.3% (58/68).ConclusionThe new fat-LI-RADS algorithm proposed here significantly improves the performance of the non-invasive diagnosis of fat-containing HCC and thus could reduce the number of biopsies conducted for fat-containing HCCs.Clinical relevance statementThe European Association for the Study of the Liver and LI-RADS guidelines are poorly sensitive for the diagnosis of fat-containing HCC, mainly because of the low rate of arterial phase hyperenhancement (APHE) displayed by fat-containing HCC. Using all types of enhancement instead of APHE improves sensitivity of LI-RADS.Key Points center dot Fat-containing HCCs on MRI account for 7.5% of HCCs and have different imaging characteristics from non-fatty HCCs.center dot The European Association for the Study of the Liver and LI-RADS algorithms for the non-invasive diagnosis of HCC have low sensitivity for the diagnosis of fat-containing HCC with MRI (37.7% and 36.4%, respectively).center dot The new fat-LI-RADS, which includes a slight modification of the arterial enhancement criterion, improves the sensitivity for the diagnosis of fat-containing HCC using MRI, without degrading the specificity.Key Points center dot Fat-containing HCCs on MRI account for 7.5% of HCCs and have different imaging characteristics from non-fatty HCCs.center dot The European Association for the Study of the Liver and LI-RADS algorithms for the non-invasive diagnosis of HCC have low sensitivity for the diagnosis of fat-containing HCC with MRI (37.7% and 36.4%, respectively).center dot The new fat-LI-RADS, which includes a slight modification of the arterial enhancement criterion, improves the sensitivity for the diagnosis of fat-containing HCC using MRI, without degrading the specificity.Key Points center dot Fat-containing HCCs on MRI account for 7.5% of HCCs and have different imaging characteristics from non-fatty HCCs. center dot The European Association for the Study of the Liver and LI-RADS algorithms for the non-invasive diagnosis of HCC have low sensitivity for the diagnosis of fat-containing HCC with MRI (37.7% and 36.4%, respectively).center dot The new fat-LI-RADS, which includes a slight modification of the arterial enhancement criterion, improves the sensitivity for the diagnosis of fat-containing HCC using MRI, without degrading the specificity.

Automated summary

This study developed and validated a new fat-LI-RADS algorithm for the non-invasive diagnosis of fat-containing HCC, which significantly improves diagnostic sensitivity without compromising specificity. It has the potential to reduce unnecessary biopsies for fat-containing HCCs.