Page 23 - Read Online

Page 8 of 10 Fowler et al. Hepatoma Res 2020;6:19 I http://dx.doi.org/10.20517/2394-5079.2020.21

doubt about whether CEUS washout is marked or mild, it should be classified as marked. Likewise, if in
doubt about rim APHE vs. nonrim APHE, we should call it rim APHE. These rules help direct individuals
in the application of the LI-RADS algorithm, but do not necessarily address inter-reader variability, which is
invariably encountered in clinical practice. While the literature suggests that agreement is good to excellent
for LR-M vs. LR-5 categorization [4,49] , its reliability in routine practice is not well known and this remains an
area of continued research and improvement for LI-RADS.

FUTURE DIRECTIONS
The prognostic value of LR features and categories is an area of active research with opportunities to
investigate relationships of features with molecular profiles, immune landscapes, and histological subtypes of
HCC that may inform individualized therapy.

As radiology continues to evolve toward big data and natural language processing applications, the LI-RADS
categorical approach may be replaced or augmented by radiomics or deep learning models that have the
potential to provide a more granular probability of diagnosing iCCA, cHCC-CCA, and HCC.

CEUS LI-RADS currently only addresses contrast agents that are FDA approved in the United States. Future
versions may incorporate hepatocyte specific agents.

CONCLUSION
LI-RADS LR-M category is intended to capture all non-HCC malignancies. The criteria differs depending on
modality. On CT/MRI, targetoid dynamic enhancement, diffusion weight, and hepatobiliary phase imaging
are the primary features of LR-M. On CEUS, the presence of rim APHE and marked or early washout are the
primary features of LR-M. When applied, LR-M criteria accurately capture almost all non-HCC malignancies
and some atypical HCCs.

DECLARATIONS
Authors’ contributions
Made substantial contributions to the conception and design of the study and performed data analysis and
interpretation: Fowler KJ, Cunha GM, Kim TK

Availability of data and materials
Not applicable.

Financial support and sponsorship
None.

Conflicts of interest
Dr. Fowler KJ receives research support from Bayer and General Electric (GE healthcare) and from Innovis,
Medscape and Bayer for consulting. Dr. Cunha GM and Dr. Kim TK declared that there are no conflict of
interest with regard to this manuscript.

Ethical approval and consent to participate
Not applicable.

Consent for publication
Not applicable.