Use of Intravoxel Incoherent Motion (IVIM) in Evaluation of Histological Differentiation of Hepatocellular Carcinoma (HCC) in Patients with Hepatitis B Virus Infection
Qungang Shan1, Tianhui Zhang1, Yong Zhang2, Yunhong Shu3, Zhuang Kang1, Bingjun He1, Jingbiao Chen1, Zhenyu Zhou2, and Jin Wang1

1Department of Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China, People's Republic of, 2GE Healthcare China, Beijing, China, People's Republic of, 3Mayo 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 worldwide1. Hepatitis B virus (HBV) infection is one of the leading causes of HCC in Asian countries2, 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 HCCs4-8. 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/mm2). 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

1. Yang J D, Roberts L R. Epidemiology and Management of Hepatocellular Carcinoma[J]. Infectious Disease Clinics of North America,2010,24(4):899-919.

2. de Martel C, Maucort-Boulch D, Plummer M, et al. World-wide relative contribution of hepatitis B and C viruses in hepatocellular carcinoma[J]. Hepatology,2015,62(4):1190-1200.

3. Ashtari S. Hepatocellular carcinoma in Asia: Prevention strategy and planning[J]. World Journal of Hepatology,2015,7(12):1708.

4. Muhi A, Ichikawa T, Motosugi U, et al. High-b-value diffusion-weighted MR imaging of hepatocellular lesions: Estimation of grade of malignancy of hepatocellular carcinoma[J]. Journal of Magnetic Resonance Imaging,2009,30(5):1005-1011.

5. Heo S H, Jeong Y Y, Shin S S, et al. Apparent Diffusion Coefficient Value of Diffusion-Weighted Imaging for Hepatocellular Carcinoma: Correlation with the Histologic Differentiation and the Expression of Vascular Endothelial Growth Factor[J]. Korean Journal of Radiology,2010,11(3):295.

6. Nishie A, Tajima T, Asayama Y, et al. Diagnostic performance of apparent diffusion coefficient for predicting histological grade of hepatocellular carcinoma[J]. European Journal of Radiology,2011,80(2):e29-e33.

7. Nakanishi M, Chuma M, Hige S, et al. Relationship Between Diffusion-Weighted Magnetic Resonance Imaging and Histological Tumor Grading of Hepatocellular Carcinoma[J]. Annals of Surgical Oncology,2012,19(4):1302-1309.

8. Woo S, Lee J M, Yoon J H, et al. Intravoxel incoherent motion diffusion-weighted MR imaging of hepatocellular carcinoma: correlation with enhancement degree and histologic grade[J]. Radiology,2014,270(3):758-767.

Figures

Figure 1: A surgically confirmed HCC of moderately-differentiated in a 31-year-old man. (a)T2WI image, (b-d)arterial, portal venous, delayed phase image, (e)b0 image, and(f-i)ADC, D, D*, f map, respectively. The mean values of ADC, D, D* and f of the tumor were 0.91×10-3mm2/sec, 0.80×10-3mm2/sec, 17.6×10-3mm2/sec, and 21.6%, respectively.

Table 1



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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