Hepatocellular carcinoma (HCC) is heterogeneous in terms of its biological nature. Various factors related to its biological nature, including size, multifocality, macroscopic morphology, grade of differentiation, macro/microvascular invasion, bile duct invasion, intra-tumoral fat and molecular factors, and their value as prognostic imaging biomarkers have been reported. And recently, genome-based molecular HCC classification correlated with clinical outcome has been elucidated. The imaging biomarkers suggesting a less aggressive nature of HCC are smaller size, solitary tumor, smooth margin suggesting small nodular type with indistinct margin and simple nodular type with distinct margin, capsule, imaging biomarkers predicting early or well-differentiated grade, intra-tumoral fat detection, and low fluorodeoxyglucose (FDG) accumulation. The imaging biomarkers suggesting an aggressive HCC nature are larger size, multifocality, non-smooth margin suggesting simple nodular type with extranodular growth, confluent multinodular, and infiltrative type, imaging biomarkers predicting poor differentiation, macrovascular tumor thrombus, predicting microvascular invasion imaging biomarkers, bile duct dilatation or tumor thrombus, and high FDG accumulation. In the genome-based molecular classification, CTNNB-1 mutated HCC shows a less aggressive nature, while CK19/EpCAM positive HCC and macrotrabecular massive HCC show an aggressive one. Better understanding of these imaging biomarkers can contribute to devising more appropriate treatment plans for HCC.
Hepatocellular carcinoma (HCC) is heterogeneous in terms of its biological behavior. The biological properties of HCC correlate well with prognosis. In other words, some HCCs have less aggressive biological natures with better prognosis, while others have aggressive biological natures with worse prognosis. Because the diagnosis of HCC is often made solely by imaging in the clinical setting, imaging plays an important role in the diagnosis of HCC and is also useful for predicting the biological properties of HCC.
Various factors related to the biological nature of HCC, such as size , multifocality , macroscopic morphology [2,3,4], grade of differentiation of cancer cells [5, 6], macro/microvascular invasion [7,8,9], bile duct invasion , intra-tumoral fat  and molecular factors [12, 13], and their value as prognostic imaging biomarkers have been reported. Table 1 shows the various factors related to the biological nature of HCC and their imaging biomarkers. Information about the biological nature of HCC is important to determine the optimal therapeutic strategy. Therefore, an understanding of the imaging biomarkers predicting the biological nature of HCC is essential.
Recently, a genome-based HCC classification [14,15,16] has been elucidated and proven to be correlated with the clinical outcome. In addition, distinct histological variants are associated with specific molecular subclasses [15, 16]. This classification has the possibility of contributing to future target therapy and personalized care.
In this review, we discuss the various imaging biomarkers predicting the biological nature of HCC and review the genome-based HCC classification correlated with imaging and its possibility as an imaging biomarker for future perspective.
The size of HCC is an important prognostic factor . In patients with large HCC, long-term prognosis is generally poor. Larger HCCs (> 5 cm) have a higher incidence of macro/microscopic vascular invasion, and more advanced histologic grade . On the other hand, small HCCs (< 2 cm) consist of two subtypes: early HCC and classic small HCC . Early HCC has the following pathological characteristics: consists of well-differentiated tumor cells , shows stromal invasion , grows by replacing the surrounding liver parenchyma  and presents an indistinct margin. Radiologically, this early HCC tends to show an atypical enhancement pattern of HCC with a lack of arterial hyper enhancement  (Fig. 1). Decreased intra-nodular portal supply, hyperintensity on T1-weighted images (T1WI) of magnetic resonance imaging (MRI), and isointensity or hypointensity on T2-weighted images (T2WI) are also imaging features of early HCC (Fig. 1). On the other hand, classic small HCC shows moderate differentiation (about 80%), both well- and moderately differentiated components (20%) with a distinct margin (expanding growth) , frequent nodule in nodule pattern and the absence of portal tracts within the tumor. A previous study documented portal vein invasion (27%) and intrahepatic metastasis (10%) in classic small HCC . Radiologically classic small HCC tends to show a typical enhancement pattern of HCC such as arterial hypervascularity and corona pattern of enhancement  (Fig. 2). Therefore, even in small HCCs less than 2 cm, early HCC shows a more favorable biological behavior and prognosis than small classic HCC showing hyperenhancement on arterial dominant phase with distinct margin. On the other hand, poorly differentiated HCC demonstrates an invasive nature with different imaging features as described below even when smaller (Fig. 3).
The number of tumors is another important prognostic factor . The number of HCCs was reported to correlate positively with microvascular invasion . There are two types of multifocal HCCs, namely, multicentric HCC and intrahepatic metastases from a primary HCC (including satellite nodules).
Intrahepatic metastases from HCC tend to show a worse prognosis compared with multicentric HCC . Although it is difficult to strictly distinguish between them radiologically, they have the respective characteristics noted below. Multicentric HCC has various histological grades. And a nodule in nodule appearance or well-differentiated HCC should be regarded as multicentric HCC. Intrahepatic metastases (IM) resemble the primary lesion with advanced tumor grade.
Macroscopic morphology/gross classification
The gross classification of HCC is an important prognostic factor . Eggel’s gross classification of HCC (nodular, massive, and diffuse) was introduced in 1901 based on autopsy reports . According to the classification proposed by the Liver Study Group of Japan, Eggel’s nodular type is further subclassified into the following five types: small nodular type with indistinct margin (SN-IM), simple nodular type (with distinct margin) (SN-DM), simple nodular type with extranodular growth (SN-EG), confluent multinodular type (CMN) and infiltrative type (Fig. 4) . Of them, the non-simple nodular types (SN-EG, CMN and infiltrative) generally demonstrate a poor prognosis. The microvascular invasion rate of SN-EG, CMN and infiltrative type was reported to be significantly higher than that of SN-DM [2, 26, 27].
Radiologically, the post-vascular phase of sonazoid-enhanced ultrasonography has been reported as useful in predicting the macroscopic findings . And the hepatobiliary phase (HB phase) of gadoxetic acid-enhanced MRI could predict the macroscopic pathological findings except for SN-IM . The shape and tumor margins on imaging reflect well the gross classification of HCC.
Macroscopic morphology/fibrous capsule
A fibrous capsule surrounding HCC is a favorable prognostic factor [3, 4]. 15–76% of HCCs have been reported as having a fibrous capsule [30, 31]. A fibrous capsule is composed of two layers histologically. The inner layer has a rich fibrous component and outer layer has various numbers of small vessels and newly formed bile ducts [32, 33]. A fibrous capsule is not a common pathological feature of early HCC, dysplastic nodules (DNs), or regenerative nodules . Radiologically, on dynamic CT and MRI an enhancing rim surrounding an HCC on portal venous phase or delayed phase suggests the presence of a fibrous capsule . On MR imaging sequence, the fibrous capsule shows a thin rim of hypointensity on T1WI and hypointensity or hyperintensity on T2WI. Pseudocapsule represents compressed fibrous tissue surrounding regenerative nodules but it has been not well defined [32, 34], and the precise discrimination between capsule and pseudocapsule is often difficult even histologically. The so-called pseudocapsule is thin as compared with fibrous capsule, but both show similar imaging features. HCCs with pseudocapsule formation are also associated with a more favorable prognosis [32, 34].
Grade of differentiation of HCC
The histological grade of differentiation in HCC cells is one of the important prognostic factors determining recurrence and survival rates after surgical resection and liver transplantation [5, 6]. The grade of differentiation in HCC can be predicted by the following imaging biomarkers: (1) intra-tumoral blood supply, (2) gadoxetic acid uptake, (3) Kupffer cell imaging, (4) signal intensity on T1, T2-weighted imaging and the value of apparent diffusion coefficient (ADC) on diffusion weighted imaging (DWI), and (5) accumulation of fluorodeoxyglucose (FDG) uptake.
Intra-tumoral blood supply
Estimation of the intra-nodular arterial and portal blood supply is useful to predict the grade of differentiation of HCC. In the course of hepatocarcinogenesis, first both the portal blood supply and hepatic arterial supply decrease (due to a decrease in the number of portal tracts) in parallel with increasing grade of malignancy, after which the number of newly formed abnormal arteries increases. In moderately differentiated HCC (classic HCC), the portal blood supply vanishes with only abnormal arteries supplying the lesion [35, 36]. In the late stage of HCC development (poorly differentiated HCC), arterial vascularity decreases again , probably due to increased anaerobic metabolism, and it is often shown as a hypovascular tumor compared with background liver (Fig. 3).
Gadoxetic acid uptake
The expression of organic anion-transporting polypeptide (OATP)1B3 (thought to be main uptake transporter of gadoxetic acid in HCC cells) is significantly decreased in accordance with increasing grade of malignancy of the nodules (Fig. 5), and around 80% of early HCCs already demonstrate decreased but not absent OATP1B3 expression relative to the surrounding liver parenchyma, resulting in slight hypointensity on the hepatobiliary phase of gadoxetic acid MRI (Fig. 1). All poorly differentiated HCCs show absent or markedly decreased expression with definite hypointensity on HB phase (Fig. 3). Well and moderately differentiated HCCs demonstrate an intermediate grade of OATP1B3 expression between early HCC and poorly differentiated HCCs (Fig. 2), but around 10% of them show equivalent or increased expression relative to the surrounding liver  (Fig. 5). Signal intensity of HB phase is useful for predicting the grade of differentiation of HCC (Figs. 1, 2, 3).
Kupffer cell imaging (SPIO-MRI or Sonazoid US)
Superparamagnetic iron oxide (SPIO)-MRI and gaseous perfluorobutane (Sonazoid, GE Healthcare) can be used for Kupffer cell imaging. Kupffer cell imaging is useful for estimation of the histological grade of HCCs, although there is some difficulty in the differentiation between dysplastic nodules and well-differentiated HCCs. The number of Kupffer cells decreases in parallel with increasing grade of differentiation of HCCs and most well-differentiated HCCs show a similar number of Kupffer cells in the tumors to that in surrounding non-tumor tissues . Signal intensity of HCC relative to the surrounding liver on SPIO enhanced T2WI increases as the degree of differentiation of HCCs declines. However, considerable overlap has been noted between the SPIO intensity of dysplastic nodules and that of well-differentiated HCCs . Contrast-enhanced ultrasound (US) using Sonazoid is also a useful tool for estimating the histologic grade of HCC . The proportion of hypoechoic tumors during the Kupffer phase is increased from well-differentiated to moderately and poorly differentiated HCCs.
Signal intensity on T1WI and T2WI and the value of ADC
About 65% of well-differentiated HCC show hyperintensity on T1WI . Hyperintensity on T1WI of HCC gradually decreases in parallel with increasing histological grade . Therefore, HCCs with T1WI hyperintensity tend to have a better tumor histologic grade, while HCCs with T1WI hypointensity tend to be more poorly differentiated [41, 42]. In addition, T1WI hyperintense HCCs without T2WI hyperintensity or arterial hypervascularity usually show a benign clinical course .
Quantitative measurement of ADC on DWI of HCC is a predictor of histological grade [44, 45] and early recurrence before treatment . ADC value of HCC significantly decreases in parallel with increasing histological grade. Poorly differentiated HCC shows lower ADC values compared with all other histological grades.
Fluorodeoxyglucose (FDG) uptake
18F-fluorodeoxyglucose positron emission tomography (FDG-PET) has a low sensitivity for detecting well to moderately differentiated HCCs , because of lower expression of HK (hexokinase) and GLUT1 (glucose transporter 1) and higher expression of G6Pase (glucose-6-phosphatase) in well to moderately differentiated HCCs. High FDG accumulation in poorly differentiated HCC indicates increased GLUT1 and decreased G6Pase . FDG accumulates similarly in highly differentiated HCC and normal liver, with the signal strength of FDG being relatively weak, making FDG uptake a predictor of the grade of HCC differentiation. Therefore, FDG uptake can serve as one of the predictors of the grade of HCC differentiation.
In summary, the grade of differentiation of HCC during multistep hepatocarcinogenesis can be well predicted by the combination of the imaging biomarkers including intra-tumoral blood flow, signal intensity of HB phase, SPIO uptake, signal intensity of T1WI and T2WI, ADC value of DWI, and FDG uptake (Fig. 6).
There are two types of vascular invasion, macro and microvascular invasion, depending on the level of involved vascular structures. Both macro and microvascular invasion are associated with a poor prognosis because they provide the route for tumor cells to access the portal or systemic circulation. HCCs with vascular invasion have frequent intrahepatic metastasis and a higher recurrence rate after hepatic resection, ablation therapy, or liver transplantation [7, 8]. Therefore, surgical resection or liver transplantation is usually contraindicated in HCCs with macrovascular invasion .
The presence of microvascular invasion has been reported to be one of the most important risk factors related to post-surgery tumor recurrence . Despite its significance in HCC assessment, the diagnosis of microvascular invasion is usually made by the postoperative pathological diagnosis. However, the presence of microvascular invasion may be predicted by the following imaging biomarkers: (1) tumor margin (non-smooth margin), (2) peritumoral enhancement (irregular circumferential), (3) peritumoral hypointensity on HB phase of gadoxetic acid-enhanced MRI, (4) ADC, (5) tumor size, (6) arterial rim enhancement, (7) FDG uptake, (8) disruption of the capsule and (9) multifocality.
Tumor margin (non-smooth margin)
Non-smooth tumor margins (simple nodular type with extranodular growth, and confluent multinodular type), detected on multiphasic CT, have been found to correlate with the pathologic presence and location of microvascular invasion . Ariizumi et al.  reported that non-smooth tumor margin on the HB phase of gadoxetic acid-enhanced MRI can be used as a preoperative predictor of microvascular invasion (Fig. 7a).
Peritumoral enhancement (irregular circumference)
Kim et al.  categorized the pattern of peritumoral enhancement as wedge-shaped and irregular circumferential enhancement. The wedge-shaped enhancement was not a statistically significant risk factor for microvascular invasion, while irregular circumferential peritumoral enhancement could be a preoperative predictor of microvascular invasion (Fig. 7b). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of irregular circumferential peritumoral enhancement for prediction of microvascular invasion were reported to be 74.3, 82.9, 81.3 and 76.3%, respectively. Nishie et al.  reported that the area of peritumoral hemodynamic change might be larger in the microvascular invasion group, particularly in small HCCs (≤ 3 cm).
Peritumoral hypointensity on the HB phase
Peritumoral hypointensity on the HB phase of gadoxetic acid-enhanced-MRI may also be a predictive factor of microvascular invasion (Fig. 7c). Kim et al. observed peritumoral hypointensity on HB phase in 26 (25.0%) of 104 HCCs, with 23 (88.5%) of them showing microvascular invasion. The sensitivity, specificity, PPV, and NPV for predicting microvascular invasion by the presence of peritumoral hypointensity were reported as 38.3, 93.2, 88.5 and 53.6%, respectively. The probable cause of peritumoral hypointensity was considered to be decreased expression of OATPs because of hemodynamic alterations related to tumor obstruction of minute portal veins . Nishie et al. reported similar finding as peritumoral decreased uptake area of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) (POUAE). Based on this study, the presence of PDUAE can be an indicator of microscopic vascular invasion with a sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of 72, 80.6, 77, 72 and 80.6%, respectively .
Suh et al.  showed that lower ADC values can be a useful predictor of microvascular invasion (Fig. 7 d), with a sensitivity and specificity of 93.5% and 72.2%, respectively, and a cut off ADC value of 1.11 × 10−3mm2/second.
Tumor size shows a statistically significant association with the presence of microvascular invasion [57, 58]. Significant tumor size cutoffs for positive microvascular invasion were reported as > 5 cm (P = 0.001) by Ahn et al. , and ≥ 3 cm (P = 0.0013) by Hirokawa et al. .
Arterial rim enhancement
An et al.  reported that arterial rim enhancement on arterial phase of dynamic MRI is associated with microvascular invasion (Fig. 7e). The arterial rim enhancement pattern in HCC has also been reported to indicate rapid progression and poorer differentiation [60, 61].
Kornberg et al.  reported that preoperative 18F-FDG uptake on PET was a reliable predictor of microvascular invasion (Fig. 7f). Ahn et al.  reported that a ratio of tumor maximum standardized uptake values (SUV) to normal liver mean SUV (TSUVmax/L SUVmean) of 1.2 or more had a statistically significant association with microvascular invasion (P < 0.001).
Disruption of the capsule
Lim et al.  reported that the disruption of the capsule on CT to be correlated with microvascular invasion (P < 0.001), and the presence of an intact HCC capsule on CT was closely correlated with the absence of microvascular invasion (Fig. 7g). However, in a different study, no significant correlation was noted between microvascular invasion and the presence of a capsule . The correlation between presence of a capsule and microvascular invasion thus remains unclear.
Chandarana et al. reported that the presence of three or more tumors on MRI and four or more at pathologic examination had high specificity (88.2% and 91.2%, respectively) for the prediction of microvascular invasion . However, a recent study documented that multifocality was not associated with microvascular invasion . These discordant results may be attributable to differences between intrahepatic metastasis and multicentric hepatocarcinogenesis. In this way, tumor multifocality remains a controversial parameter for prediction of microvascular invasion in HCC.
As mentioned above, imaging biomarkers predicting the presence or absence of microvascular invasion in HCC are non-smooth tumor margin, irregular circumferential peritumoral enhancement, lower ADC value, increased tumor size, arterial rim enhancement and increased FDG uptake, capsule disruption and multifocal tumor. Microvascular invasion can be predicted to some extent by these imaging findings. Interestingly, a recent study revealed that the combination of two or more MR imaging biomarkers such as arterial peritumoral enhancement, non-smooth tumor margin, and peritumoral hypointensity on HBP can be used as a preoperative imaging biomarker for predicting microvascular invasion with a high specificity (90%) and an association with early recurrence after curative resection of single HCC .
Bile duct invasion
Around 1.2–9% of HCCs show bile duct invasion . HCC patients with bile duct invasion are thought to have a poorer prognosis than those without it . The reasons for the poor prognosis of HCC patients with bile duct invasion include the following. HCC with bile duct invasion is often accompanied by obstructive jaundice, cholangitis and hemobilia that are also immediate threats to survival, HCC with bile duct invasion is frequently accompanied by portal vein invasion, while HCC with bile duct invasion has been shown to have a more advanced tumor stage HCC with adverse histological features including higher rates of microvascular invasion, lymphovascular invasion and poor differentiation . The long-term outcomes after surgical treatment for HCC with bile duct invasion are still controversial. Some previous studies reported poorer surgical outcomes in these patients than in those without bile duct invasion . However, others have reported that some patients with obstructive jaundice can be treated by hepatic resection, with favorable long-term results .
The presence of intra-tumoral fat has been documented in 19.6% of HCCs on light microscopy  or up to 10% of HCCs on opposed-phase of MRI . Patients with fat-containing HCC may have a better clinical outcome than patients without it . Diffuse fatty metamorphosis is considered to be one of the characteristics of early-stage HCC and well-differentiated HCC . Approximately 6% of moderately differentiated HCCs have fatty change, in contrast to poorly differentiated HCCs in which it is rarely seen . On the other hand, Asayama et al. reported that a fat component was significantly more frequent in poorly differentiated HCC compared to the moderately differentiated HCC and proposed a possible mechanism of fatty change in relation to decreased arterial blood supply . There is a controversial point regarding the amount of fat component in poorly differentiated HCC. Min et al.  reported lower rates of microvascular invasion in fat-containing HCCs (27.3%), than non-fat-containing HCCs (39.1%), although this difference was not statistically significant (P = 0.07). In addition, diffuse-fat-containing HCCs showed a lower tendency for microvascular invasion (21.1%) compared to that of focal-fat-containing HCCs (35.7%) or non-fat-containing HCCs (36.8%). HCC with intra-tumoral fat may have a more favorable prognosis, but the clinical value of this finding remains uncertain.
A meta-analysis showed both high Tsuv/Lsuv ratio and high Tsuv value to be associated with a poor prognosis in HCC patients. Therefore, pretreatment 18F-FDG PET is a useful tool in predicting the prognosis of HCC patients .
HB phase hyperintense HCC
Around 10% of hypervascular classic HCCs [71, 72] show hyperintensity (HB phase hyperintense HCC) on HB phase of gadoxetic acid-enhanced MRI (Fig. 8). Compared with hypervascular HCC showing hypointensity on HB phase, HB phase hyperintense HCC (OATP1B3 overexpressed HCC) shows a biologically less aggressive nature with a good prognosis, higher frequency of well to moderate differentiation and rarer portal vein invasion , lower expression of α-fetoprotein (AFP), AFP L3 and protein induced by vitamin K absence or antagonists-II (PIVKA-II) , lower recurrence rate and better prognosis , beta-catenin, glutamine synthetase (which is a target of Wnt/β-catenin signaling), Hep-Par1 (hepatocyte marker) and hepatocyte nuclear factor 4α (HNF4α) by immunohistochemical analysis [73, 74] and weaker expression of stem cell markers [epithelial cell adhesion molecule (EpCAM), cytokeratin 19 (CK19)] by immunohistochemical analysis .
Hyperintense HCC is a molecular/genetical subtype of HCC with activation of mature hepatocyte-related genes/pathways and hepatocyte nuclear factor 4α overexpression . HNF4α suppresses hepatocyte proliferation and experimental HCC growth, and its decrease is linked to hepatocarcinogenesis . Of note, a recent study reported that the inhibitory effect of HNF4α on HCC development might be caused by suppression of hepatocyte epithelial–mesenchymal transformation (EMT) and cancer stem cell generation .
Genome-based molecular classification of HCC
In the past decade, molecular-based HCC classification has been elucidated [14, 15]. Recently, Calderano et al.  also proposed six subclasses (G1–G6) of HCC molecular-based classification associated with clinical and histological features (Fig. 9). Groups G1–G3 are characterized by high cell proliferation and chromosomal instability with enrichment in TP53 (G1-3), RPS6KA3 (G1), AXIN1 and ATM (G1-2), and FGF19 and TSC1/TSC2 (G3) genetic alterations. And G1–G3 have the following clinical features: HBV infection (G1–2), high AFP serum levels (G1–3), female gender (G1) and haemochromatosis (G3). Histologically, G1–3 HCCs were poorly differentiated (G1–3) with frequent macrovascular invasion (G3) foci of clear cells (G1), sarcomatous changes (G1G2), areas of compact (G3) and macrotrabecular (G3) histological patterns. The G1 subtype showed a progenitor phenotype with both CK19 and EpCAM expression. On the other hand, groups G4–G6 are characterized by chromosomal stability. G5G6 subclasses strongly associated with catenin beta 1(CTNNB1) mutations (G5G6) and G4 HCCs have the genetic feature without CTNNB1 and TP53 mutations. G4–G6 HCCs have the following histological features: good differentiation (G4–6), steatohepatitic subtype (G4), microtrabecular pattern of growth (G5G6), the presence of tumor cholestasis and a lack of inflammatory infiltrates (G5G6).
CK19 positive HCC
CK19 has been considered as a marker for the biliary phenotype and stem or progenitor cell. CK19 positive HCC has TP53 inactivation mutations. CK19 positive HCC has been shown to have a high metastatic potential, which is associated with a poor prognosis .
Radiologically hypovascular HCCs have been significantly associated with positive CK19 expression  (Fig. 10). A recent study revealed that on gadoxetic acid-enhanced MRI irregular margin, arterial rim enhancement, lower tumor-to liver ADC ratio, and lower tumor to liver SI ration at HB phase may be useful to predict CK19-positive HCC with early recurrence after surgery .
EpCAM positive HCC
EpCAM positive HCC shows an aggressive biological behavior and poor prognosis with stem cell features. It is established that EpCAM is a biomarker for normal hepatic stem cells and cancer stem cells (CSC) in HCC . EpCAM positive HCC associated with worse histological grade and high serum AFP level , and displayed a distinct molecular signature with features of hepatic stem cell/progenitor markers such as CK19 and c-kit and activated with Wnt-beta-catenin signaling . Therefore, CK19 positive HCC and EPCAM positive HCC seem to overlap to some extent. The imaging features of EpCAM positive HCC are still unclear.
Macrotrabecular massive HCC (MTM-HCC)
MTM-HCC has clinical and biological relevance. MTM-HCC has poor survival, and 10% of HCCs are classified as MTM-HCC subtype . MTM-HCC is associated with TP53 inactivation, ATM mutations, HBV infection, angiogenesis activation, high AFP serum level, satellite nodules and macro and microvascular invasion with early relapse and poor survival, and frequently demonstrated progenitor phenotype. Thick trabeculae surrounded by vascular spaces (> 50%) are a characteristic pathological feature. The imaging features of MTM-HCC have not yet been described.
Steatohepatitic HCC (SH-HCC)
13.5–35.5% of HCCs have been reported to be of the steatohepatitic subtype . This subset of HCCs is associated with metabolic conditions and the presence of steatosis or steatohepatitis in the background liver. Lack of WNT/beta-catenin pathway activation is one of the genomic features. Pathological features of SH-HCC include large droplet steatosis, ballooning of malignant hepatocytes, Mallory–Denk bodies, pericellular fibrosis and intra-tumoral inflammatory cell infiltration.
The biological nature of SH-HCC is still controversial. Goossens et al. reported SH-HCC as being associated with S1 subclass with more aggressive tumor behavior. On the other hand, Calderaro et al.  pointed out that SH-HCC is not related to specific clinical features, but displays a less aggressive phenotype with a lack of satellite nodules and microvascular invasion. Further investigation regarding this issue is needed. One of the characteristic imaging features of SH-HCC is fat deposition, although the details of the imaging features of SH-HCC remain to be clarified (Fig. 11).
CTNNB-1 mutated HCC
CTNNB-1 (which encodes beta catenin) mutated HCC was estimated to account for about 30–40% of all HCCs . CTNNB-1 mutated HCC is characterized by well-differentiated tumors with cholestasis, microtrabecular and pseudoglandular patterns, lack of inflammatory infiltrates, low AFP expression  and a relatively favorable prognosis .
CTNNB-1 mutated HCC showed higher enhancement ratios on HB phase of gadoxetic acid-enhanced MRI with overexpression of OATP1B3 and a high ADC on DWI radiologically  (Fig. 8). Most CTNNB-1 mutated HCCs with a better prognosis are suspected to correspond to HB phase hyperintense HCC as mentioned above.
As outlined above, there are various factors and their imaging biomarkers are predictive of the biological nature of HCC. Imaging biomarkers suggesting less aggressive (better prognosis) or aggressive (worse prognosis) of HCC are summarized in Table 2.
The imaging biomarkers suggesting a less aggressive HCC nature are smaller size, solitary tumor, smooth margin suggesting small nodular type with indistinct margin (SN-IM) and simple nodular type with distinct margin (SN-DM), fibrous capsule or pseudocapsule, imaging biomarkers predicting early or well-differentiated grade, intra-tumoral-fat detection and low accumulation of fluorodeoxyglucose (FDG). On the other hand, the imaging biomarkers suggesting an aggressive HCC nature are larger size, multifocality, non-smooth margin suggesting simple nodular type with extranodular growth (SN-EG), confluent multinodular (CMN), and infiltrative type, imaging biomarkers predicting poor differentiation, macrovascular thrombus, predictive of microvascular invasion imaging biomarkers, bile duct dilatation or thrombus, and high accumulation of FDG. In the genome-based molecular classification, CTNNB-1 mutated HCC shows a less aggressive biological nature, whereas CK19/EpCAM positive HCC and MTM-HCC show an aggressive biological nature.
The biological nature of HCC is not a simple issue that can be predicted with a single imaging biomarker, and it is thought that various imaging biomarkers are related. Currently, it is still difficult to comprehensively evaluate these imaging biomarkers and predict biological characteristics in total. In addition, there are other clinical biomarkers such as tumor markers that predict biological properties. Therefore, it will be necessary in the future to establish a comprehensive evaluation system of the biological characteristics of HCC including various biomarkers predicting the prognosis so as to select the most appropriate treatment for individual HCC patient.
In conclusion, the biological nature of HCC is correlated with various factors, and an understanding of their imaging biomarkers can contribute to determining the most appropriate treatment plan of HCC. Genome-based molecular HCC classification has the possibility of contributing to future target therapy and personalized care. In the genome-based molecular HCC classification, the establishment of imaging biomarkers is not yet sufficient, although it is anticipated that this will be achieved in the near future.
- T1WI :
T1 weighted image
- MRI :
Magnetic resonance imaging
T2 weighted image
Small nodular type with indistinct margin
Simple nodular type with distinct margin
Simple nodular type with extranodular growth
Confluent multinodular type
- HB phase:
Apparent diffusion coefficient
Diffusion weighted image
- FDG PET:
Fluorodeoxyglucose positron emission tomography
Organic anion-transporting polypeptide
Superparamagnetic iron oxide
Glucose transporter 1
Positive predictive value
Negative predictive value
Standardized uptake values
Protein induced by Vitamin K absence or antagonists-II
Hepatocyte nuclear factor (HNF)
Epithelial cell adhesion molecule
- CTNNB1 :
Catenin beta 1
Macrotrabecular massive HCC
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Yoneda, N., Matsui, O., Kobayashi, S. et al. Current status of imaging biomarkers predicting the biological nature of hepatocellular carcinoma. Jpn J Radiol 37, 191–208 (2019). https://doi.org/10.1007/s11604-019-00817-3
- Hepatocellular carcinoma
- Biological nature
- Imaging biomarkers
- Genome-based molecular HCC classification