Qungang Shan^{1}, Tianhui Zhang^{1}, Yong Zhang^{2}, Yunhong Shu^{3}, Zhuang Kang^{1}, Bingjun He^{1}, Jingbiao Chen^{1}, Zhenyu Zhou^{2}, and Jin Wang^{1}

^{1}Department of Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China, People's Republic of, ^{2}GE Healthcare China, Beijing, China, People's Republic of, ^{3}Mayo Clinic, Rochester, MN, United States

### Synopsis

**Among
the various causes of hepatocellular carcinoma (HCC), hepatitis B virus (HBV)
infection is the most common one in Asian countries including China. We
assessed the correlation of ADC and IVIM parameters with the histological
differentiation of HBV-related HCCs. Our results showed that ADC, D and f
coefficients are significantly correlated with histological differentiation of
HBV-related HCC. According to ROC
analysis, ADC, D and f were useful parameters for the evaluation of histological
differentiation of HCCs. ADC showed better diagnostic performance compared with
D and f IVIM is a promising tool for predicting histological
differentiation of HBV-related HCC.**### Purpose

Hepatocellular
carcinoma (HCC) is the most common primary hepatic malignancy worldwide

^{1}.
Hepatitis B virus (HBV) infection is one of the leading causes of HCC in Asian countries

^{2,
3}. Histological differentiation is an important prognostic factor of HCC.
Previous study has shown that apparent
diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM)-derived
parameters could be used to differentiate high- and low-grade
HCCs

^{4-8}. To our knowledge, IVIM studies that focus on HCC groups
with HBV infection have not been reported. This study aimed to evaluate the correlation
of ADC and IVIM-derived parameters with the histological differentiation of
HBV-related HCCs.

### Methods

The study was approved by the institutional review board and written
informed consents were obtained from each recruited patient. 96 patients who
underwent surgery after MR examination and were diagnosed as HCC pathologically
were included initially. 22 of them were excluded according to the following
exclusion criteria: (a) no history of HBV infection, (b) treated by
transarterial chemoembolization (TACE), radiofrequency ablation (RFA), (c)
distinct motion artifacts or slice misregistration, (d) no lesion more
than 1 cm in diameter. In total, 74 chronic HBV patients (64 males and 10 females;
age range, 25-78 years; mean, 50.4 years) with 75 pathologically confirmed HCCs
were enrolled in our study. The lesions were classified into three groups according
to pathological results as follows: well-differentiated (n=14),
moderately-differentiated (n=47) and poorly-differentiated (n=14). All subjects
underwent conventional MRI and IVIM scans using a 3.0T MR system (Discovery
MR750, GE Healthcare, Milwaukee, WI). Respiratory-triggered diffusion-weighted
imaging (DWI) were performed using 11 b values (b=0, 30, 50, 100, 150, 200,
300, 500, 800, 1000, 1500 sec/mm

^{2}). The scanning parameters were:
TR, 9231ms; TE, 56ms; flip angle, 90º; matrix size, 128×128; field of view,
38×30 cm; bandwidth, 250 kHz; slice thickness, 5 mm; intersection gap, 1mm; and
acquisition time, 3 min 52 sec. Regions of interests (ROIs) were placed on the
axial images to encompass as much lesion body as possible while staying 5 mm
away from the margin of the lesion. Necrosis and hemorrhage were avoided. ROIs
were placed on the diffusion-weighted images with a b-value of 0 and were
copied to all IVIM-derived maps for measurement. Mean ADC, D
(diffusion coefficient), D* (pseudodiffusion coefficient) and f (perfusion
fraction) values of the HCCs were measured. The values of different
histologically differentiated groups were analyzed with ANOVA or Kruskal-Wallis
test depending on the statistical distribution of the data. The Spearman rank
correlation was used to assess the statistical dependence among the HCCs with
various histological differentiations. Receiver operating characteristic (ROC)
analysis was performed to evaluate diagnostic performance of these
parameters in differentiating among HCCs with the three histological
grades.

### Results

The
mean values of ADC, D, D* and f for the well-, moderately- and
poorly-differentiated HCCs are shown in Table 1. ADC, D and f values were
significantly different among well-differentiated, moderately-differentiated and
poorly-differentiated HCCs. All these three values increased with the degrees
of histological differentiation. ADC, D, and f were significantly correlated
with histological differentiation: r = 0.579 (

*P* < .001), r = 0.413(

*P*<
.001) and r=0.326(

*P*= .003), respectively. The area under the ROC
curve(AUC-ROC) of ADC, D and f for diagnosing well-differentiated HCCs was
0.859, 0.773, 0.775, respectively, and the AUC-ROC of the above parameters for
diagnosing poorly-differentiated HCCs was 0.828, 0.742, 0.670, respectively. Significant
differences were found between the AUC-ROC of ADC and D or f for diagnosing
well- and poorly-differentiated HCC (

*P*< .05). On the other hand, there were
no correlation between the histologic grades and the D* values.

### Discussion

Our study showed that ADC, D and f values derived
from IVIM theory were significantly different among HBV-related HCCs
with different histological grades. The above parameters have the potentials to
reflect the pathological grades of HBV-related HCCs. According to ROC analysis,
ADC, D and f yielded high AUC-ROC and were useful parameters for the evaluation
of histological differentiation of HCCs. Among all the parameters, ADC showed
better diagnostic performance compared with D and f, which may be related to the
characteristics of HBV-related HCCs.

### Conclusion

In summary, ADC and IVIM parameters could be useful
for evaluating histological differentiation of HBV-related HCCs and they may
provide complementary information for prognosis before surgery.

### Acknowledgements

No acknowledgement found.### References

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