Intravoxel incoherent motion diffusion-weighted imaging applied in evaluating microcirculation of hepatocellular carcinoma in rat model_West China Medical Journal

Authors：

LI Mou ¹ , ZHENG Xingju ² , HUANG Zixing ¹ ,  SONG Bin ¹

1. Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P. R. China;
2. Department of Radiology, Guizhou Provincial People’s Hospital, Guiyang, Guizhou 550002, P. R. China;

Corresponding author：

SONG Bin, Email: cjr.songbin@vip.163.com

Keywords：

Intravoxel incoherent motion diffusion weighted imaging; Hepatocellular carcinoma; Microvessel density; Microvascular invasion; Rat

DOI：

10.7507/1002-0179.201701065

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

ObjectiveTo assess the feasibility of intravoxel incoherent motion diffusion-weighted imaging (IVIM) in evaluating microvessel density (MVD) and microvascular invasion (MVI) of hepatocellular carcinoma (HCC).MethodsRat models were established to be scanned by IVIM. HCC lesions corresponding to IVIM image were examined pathologically to get data of MVD and MVI. Spearman correlation analysis was used to compare the apparent diffusion coefficient (ADC), D, D*, and f with MVD, independent samples t test was used to compare ADC, D, D*, and f between MVI (+) and MVI (–) groups.ResultsFifty HCC lesions were included finally. ADC and D values both showed a negative correlation with MVD (r=–0.406, P=0.003; r=–0.468, P=0.001), D* and f showed no statistical correlation with MVD (P=0.172, 0.074, respectively). The differences in ADC and all the IVIM parameters (D, D*, and f) between MVI (+) and MVI (–) HCCs were not statistically significant (P=0.393, 0.395, 0.221, 0.550).ConclusionADC and D can be used to evaluate MVD of HCC, but ADC and IVIM parameters were limited in evaluating MVI.

Citation： LI Mou, ZHENG Xingju, HUANG Zixing, SONG Bin. Intravoxel incoherent motion diffusion-weighted imaging applied in evaluating microcirculation of hepatocellular carcinoma in rat model. West China Medical Journal, 2018, 33(4): 411-416. doi: 10.7507/1002-0179.201701065 Copy

1.	Bosetti C, Turati F, La Vecchia C. Hepatocellular carcinoma epidemiology. Best Pract Res Clin Gastroenterol, 2014, 28(5): 753-770.
2.	Hubert, E, Blum. Hepatocellular carcinoma: therapy and prevention. World J Gastroenterol, 2005, 11(47): 7391-7400.
3.	解丽梅, 刘丹丹. 肝细胞癌三维彩色直方图血流定量分析参数与肿瘤微血管密度的相关性研究. 实用医技杂志, 2007, 14(26): 3553-3554.
4.	Hirokawa F, Hayashi M, Asakuma MA, et al. Risk factors and patterns of early recurrence after curative hepatectomy for hepatocellular carcinoma. Surg Oncol, 2016, 25(1): 24-29.
5.	Yang SH, Lin J, Lu F, et al. Evaluation of antiangiogenic and antiproliferative effects of sorafenib by sequential histology and intravoxel incoherent motion diffusion-weighted imaging in an orthotopic hepatocellular carcinoma xenograft model. J Magn Reson Imaging, 2017, 45(1): 270-280.
6.	Taketomi A. Clinical trials of antiangiogenic therapy for hepatocellular carcinoma. Int J Clin Oncol, 2016, 21(2): 213-218.
7.	Berretta M, Rinaldi L, Di Benedetto FA, et al. Angiogenesis inhibitors for the treatment of hepatocellular carcinoma. Front Pharmacol, 2016, 7: 428.
8.	Grąt M, Stypułkowski J, Patkowski W, et al. Limitations of predicting microvascular invasion in patients with hepatocellular cancer prior to liver transplantation. Sci Rep, 2017, 7: 39881.
9.	Yang C, Wang H, Sheng R, et al. Microvascular invasion in hepatocellular carcinoma: is it predictable with a new, preoperative application of diffusion-weighted imaging?. Clin Imaging, 2017, 41: 101-105.
10.	Hou YF, Wei YG, Yang JY, et al. Microvascular invasion patterns affect survival in hepatocellular carcinoma patients after second hepatectomy. J Surg Res, 2016, 200(1): 82-90.
11.	Qin LX, Tang ZY. Recent progress in predictive biomarkers for metastatic recurrence of human hepatocellular carcinoma: a review of the literature. J Cancer Res Clin Oncol, 2004, 130(9): 497-513.
12.	Qin LX, Tang ZY. The prognostic molecular markers in hepatocellular carcinoma. World J Gastroenterol, 2002, 8(3): 385-392.
13.	Vandecaveye V, De Keyzer F, Verslype C, et al. Diffusion-weighted MRI provides additional value to conventional dynamic contrast-enhanced MRI for detection of hepatocellular carcinoma. Eur Radiol, 2009, 19(10): 2456-2466.
14.	Xu PJ, Yan FH, Wang JH, et al. Added value of breathhold diffusion-weighted MRI in detection of small hepatocellular carcinoma lesions compared with dynamic contrast-enhanced MRI alone using receiver operating characteristic curve analysis. J Magn Reson Imaging, 2009, 29(2): 341-349.
15.	Xu PJ, Yan FH, Wang JH, et al. Contribution of diffusion-weighted magnetic resonance imaging in the characterization of hepatocellular carcinomas and dysplastic nodules in cirrhotic liver. J Comput Assist Tomogr, 2010, 34(4): 506-512.
16.	Le Bihan D, Breton E, Lallemand D, et al. Separation of diffusion and perfusion in intravoxel incoherent motion Mr imaging. Radiology, 1988, 168(2): 497-505.
17.	Mannelli L, Nougaret S, Vargas HA, et al. Advances in diffusion-weighted imaging. Radiol Clin North Am, 2015, 53(3): 569-581.
18.	Woo S, Lee JM, Yoon JH, et al. Intravoxel incoherent motion diffusion-weighted Mr imaging of hepatocellular carcinoma: correlation with enhancement degree and histologic grade. Radiology, 2014, 270(3): 758-767.
19.	Zhu AX, Duda DG, Sahani DV, et al. HCC and angiogenesis: possible targets and future directions. Nat Rev Clin Oncol, 2011, 8(5): 292-301.
20.	Cheng SH, Liu JM, Liu QY, et al. Prognostic role of microvessel density in patients with renal cell carcinoma: a meta-analysis. Int J Clin Exp Pathol, 2014, 7(9): 5855-5863.
21.	Lee HJ, Rha SY, Chung YE, et al. Tumor perfusion-related parameter of diffusion-weighted magnetic resonance imaging: correlation with histological microvessel density. Magn Reson Med, 2014, 71(4): 1554-1558.
22.	Kakite S, Dyvorne H, Besa C, et al. Hepatocellular carcinoma: short-term reproducibility of apparent diffusion coefficient and intravoxel incoherent motion parameters at 3.0 T. J Magn Reson Imaging, 2015, 41(1): 149-156.
23.	Shan Y, Zeng MS, Liu K, et al. Comparison of Free-Breathing with navigator-triggered technique in diffusion weighted imaging for evaluation of small hepatocellular carcinoma: effect on image quality and intravoxel incoherent motion parameters. J Comput Assist Tomogr, 2015, 39(5): 709-715.
24.	Suh YJ, Kim MJ, Choi JY, et al. Preoperative prediction of the microvascular invasion of hepatocellular carcinoma with diffusion-weighted imaging. Liver Transpl, 2012, 18(10): 1171-1178.
25.	Xu P, Zeng M, Liu K, et al. Microvascular invasion in small hepatocellular carcinoma: is it predictable with preoperative diffusion-weighted imaging?. J Gastroenterol Hepatol, 2014, 29(2): 330-336.

1. Bosetti C, Turati F, La Vecchia C. Hepatocellular carcinoma epidemiology. Best Pract Res Clin Gastroenterol, 2014, 28(5): 753-770.
2. Hubert, E, Blum. Hepatocellular carcinoma: therapy and prevention. World J Gastroenterol, 2005, 11(47): 7391-7400.
3. 解丽梅, 刘丹丹. 肝细胞癌三维彩色直方图血流定量分析参数与肿瘤微血管密度的相关性研究. 实用医技杂志, 2007, 14(26): 3553-3554.
4. Hirokawa F, Hayashi M, Asakuma MA, et al. Risk factors and patterns of early recurrence after curative hepatectomy for hepatocellular carcinoma. Surg Oncol, 2016, 25(1): 24-29.
5. Yang SH, Lin J, Lu F, et al. Evaluation of antiangiogenic and antiproliferative effects of sorafenib by sequential histology and intravoxel incoherent motion diffusion-weighted imaging in an orthotopic hepatocellular carcinoma xenograft model. J Magn Reson Imaging, 2017, 45(1): 270-280.
6. Taketomi A. Clinical trials of antiangiogenic therapy for hepatocellular carcinoma. Int J Clin Oncol, 2016, 21(2): 213-218.
7. Berretta M, Rinaldi L, Di Benedetto FA, et al. Angiogenesis inhibitors for the treatment of hepatocellular carcinoma. Front Pharmacol, 2016, 7: 428.
8. Grąt M, Stypułkowski J, Patkowski W, et al. Limitations of predicting microvascular invasion in patients with hepatocellular cancer prior to liver transplantation. Sci Rep, 2017, 7: 39881.
9. Yang C, Wang H, Sheng R, et al. Microvascular invasion in hepatocellular carcinoma: is it predictable with a new, preoperative application of diffusion-weighted imaging?. Clin Imaging, 2017, 41: 101-105.
10. Hou YF, Wei YG, Yang JY, et al. Microvascular invasion patterns affect survival in hepatocellular carcinoma patients after second hepatectomy. J Surg Res, 2016, 200(1): 82-90.
11. Qin LX, Tang ZY. Recent progress in predictive biomarkers for metastatic recurrence of human hepatocellular carcinoma: a review of the literature. J Cancer Res Clin Oncol, 2004, 130(9): 497-513.
12. Qin LX, Tang ZY. The prognostic molecular markers in hepatocellular carcinoma. World J Gastroenterol, 2002, 8(3): 385-392.
13. Vandecaveye V, De Keyzer F, Verslype C, et al. Diffusion-weighted MRI provides additional value to conventional dynamic contrast-enhanced MRI for detection of hepatocellular carcinoma. Eur Radiol, 2009, 19(10): 2456-2466.
14. Xu PJ, Yan FH, Wang JH, et al. Added value of breathhold diffusion-weighted MRI in detection of small hepatocellular carcinoma lesions compared with dynamic contrast-enhanced MRI alone using receiver operating characteristic curve analysis. J Magn Reson Imaging, 2009, 29(2): 341-349.
15. Xu PJ, Yan FH, Wang JH, et al. Contribution of diffusion-weighted magnetic resonance imaging in the characterization of hepatocellular carcinomas and dysplastic nodules in cirrhotic liver. J Comput Assist Tomogr, 2010, 34(4): 506-512.
16. Le Bihan D, Breton E, Lallemand D, et al. Separation of diffusion and perfusion in intravoxel incoherent motion Mr imaging. Radiology, 1988, 168(2): 497-505.
17. Mannelli L, Nougaret S, Vargas HA, et al. Advances in diffusion-weighted imaging. Radiol Clin North Am, 2015, 53(3): 569-581.
18. Woo S, Lee JM, Yoon JH, et al. Intravoxel incoherent motion diffusion-weighted Mr imaging of hepatocellular carcinoma: correlation with enhancement degree and histologic grade. Radiology, 2014, 270(3): 758-767.
19. Zhu AX, Duda DG, Sahani DV, et al. HCC and angiogenesis: possible targets and future directions. Nat Rev Clin Oncol, 2011, 8(5): 292-301.
20. Cheng SH, Liu JM, Liu QY, et al. Prognostic role of microvessel density in patients with renal cell carcinoma: a meta-analysis. Int J Clin Exp Pathol, 2014, 7(9): 5855-5863.
21. Lee HJ, Rha SY, Chung YE, et al. Tumor perfusion-related parameter of diffusion-weighted magnetic resonance imaging: correlation with histological microvessel density. Magn Reson Med, 2014, 71(4): 1554-1558.
22. Kakite S, Dyvorne H, Besa C, et al. Hepatocellular carcinoma: short-term reproducibility of apparent diffusion coefficient and intravoxel incoherent motion parameters at 3.0 T. J Magn Reson Imaging, 2015, 41(1): 149-156.
23. Shan Y, Zeng MS, Liu K, et al. Comparison of Free-Breathing with navigator-triggered technique in diffusion weighted imaging for evaluation of small hepatocellular carcinoma: effect on image quality and intravoxel incoherent motion parameters. J Comput Assist Tomogr, 2015, 39(5): 709-715.
24. Suh YJ, Kim MJ, Choi JY, et al. Preoperative prediction of the microvascular invasion of hepatocellular carcinoma with diffusion-weighted imaging. Liver Transpl, 2012, 18(10): 1171-1178.
25. Xu P, Zeng M, Liu K, et al. Microvascular invasion in small hepatocellular carcinoma: is it predictable with preoperative diffusion-weighted imaging?. J Gastroenterol Hepatol, 2014, 29(2): 330-336.

West China Medical Journal

Intravoxel incoherent motion diffusion-weighted imaging applied in evaluating microcirculation of hepatocellular carcinoma in rat model

Abstract Full text Figures/Tables Video References Cited by

Previous Article

Next Article

Format

Content