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Page 2 of 11 Tamai. Hepatoma Res 2018;4:75 I http://dx.doi.org/10.20517/2394-5079.2018.98

imaging is used not just for its diagnosis, but also for disease surveillance, determination of tumor stage,
evaluation of treatment efficacy, and navigation of local treatments. Importantly, imaging has the ability to
predict histologic differentiations that reflect the malignant potential of HCC.

As the HCC tumor grows larger, it has a stronger tendency to invade the adjacent portal vein or hepatic vein.
HCC with intrahepatic or extrahepatic metastasis derived from vascular invasion is an advanced cancer that
[1]
is difficult to treat radically . However, even if the tumor is solitary on imaging, metastatic recurrences after
curative treatments such as surgical resection or local ablation is not uncommon. These metastatic recur-
rences may result from occult metastasis derived from invisible microvascular invasion (MVI) at the time of
diagnostic imaging before treatment was initiated. Therefore, HCC with MVI can be considered as an ad-
vanced cancer with occult metastasis. However, there is a limitation in the diagnostic imaging of MVI or oc-
cult metastasis. To make an adequate treatment strategy for solitary HCC, the prediction of MVI is crucial.
In this review, the present status of the prediction of MVI of HCC using common imaging modalities such
as ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI) is presented.

FACTORS RELATED TO MVI IN HCC
[2]
HCC develops in a multistep fashion . Therefore, most HCCs consist of heterogenously differentiated com-
ponents. For example, nodule in nodule or mosaic pattern on US imaging represents multistep carcinogene-
[2]
sis . As histologic differentiation advances from well differentiated to poorly differentiated, the prevalence of
[4]
[3]
MVI becomes higher . Poor histologic differentiation is a strong predictor of MVI . A large proportion of
[3]
poorly differentiated HCCs has MVI and intrahepatic metastasis even when the tumor is small . As the tu-
mor size increases, a fibrous capsule forms such that a typical HCC is visualized as a nodule within a fibrous
capsule. Cancer cell infiltration into the fibrous capsule demonstrates a morphologically invasive feature, and
[5]
HCCs with infiltrations to the fibrous capsule tend to be poorly differentiated and to have MVI . Small nodular
HCCs can be macroscopically classified into three types such as single nodular (SN), single nodular with extra-
[6]
nodular growth (SNEG), and contiguous multinodular (CMN) . Both SNEG and CMN types have a stronger
invasive potential, and tend to be more poorly differentiated than the SN type. The prevalence of MVI or micro-
[7-9]
scopic intrahepatic metastasis is also higher in the SNEG and CMN types than in the SN type . Since MVI
is strongly associated with histologic differentiation and the macroscopic type of HCC, the accurate predic-
tion of MVI by imaging will require accurate evaluation of these two parameters.

PREDICTION OF MVI USING US
US has the highest spatial resolution among common imaging modalities, therefore it can potentially pro-
[10]
vide an accurate assessment of the macroscopic morphology of HCC. Moribata et al. reported the correla-
tion between B mode ultrasonogram and histologic differentiation of small HCC. They revealed that most
poorly differentiated small HCCs were visualized as hypoechoic tumor with an irregular or unclear margin
on B mode US. However, sensitivity, specificity, positive predictive value (PPV), negative predictive value
(NPV), and accuracy of diagnosis for poorly differentiated HCC on the basis of their data are 89%, 67%, 19%,
99%, and 69% respectively.

There have been several reports on the prediction of poorly differentiated HCC or MVI using CEUS, based
[11]
on the evaluation of intra-tumoral angioarchitecture. Sugimoto et al. showed the correlation between the
angioarchitecture and histologic differentiation using microflow imaging (MFI) by CEUS. The deadwood
pattern of tumoral blood vessels was visualized clearly, but they gradually tapered off and were interrupted
suddenly. When HCCs with deadwood pattern were assessed as poorly differentiated, the sensitivity, speci-
ficity, positive PPV, NPV, and accuracy of diagnosis for poorly differentiated HCC on the basis of their data
[12]
are 80%, 96%, 86%, 94%, and 92%, respectively. Tanaka et al. implemented the malignant grading system
based on the combined assessment of Kupffer imaging and the maximum intensity projection imaging