Skip to main content

Advertisement

Log in

Quantitative free-breathing dynamic contrast-enhanced MRI in hepatocellular carcinoma using gadoxetic acid: correlations with Ki67 proliferation status, histological grades, and microvascular density

  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

Purpose

To validate a free-breathing dynamic contrast-enhanced-MRI (DCE-MRI) in hepatocellular carcinoma (HCC) patients using gadoxetic acid, and to determine the relationship between DCE-MRI parameters and histological results.

Methods

Thirty-four HCC patients were included in this prospective study. Free-breathing DCE-MRI data was acquired preoperatively on a 3.0 Tesla scanner. Perfusion parameters (K trans, K ep, V e and the semi-quantitative parameter of initial area under the gadolinium concentration–time curve, iAUC) were calculated and compared with tumor enhancement at contrast-enhanced CT. The relationship between DCE-MRI parameters and Ki67 indices, histological grades and microvascular density (MVD) was determined by correlation analysis. Differences of perfusion parameters between different histopathological groups were compared. Receiver operation characteristic (ROC) analysis of discriminating high-grades (grade III and IV) from low-grades (grade I and II) HCC was performed for perfusion parameters.

Results

Significant relationship was found between DCE-MRI and CT results. The DCE-MRI derived K trans were significantly negatively correlated with Ki-67 indices (rho = − 0.408, P = 0.017) and the histological grades (rho = − 0.444, P = 0.009) of HCC, and K ep and V e were significantly related with tumor MVD (rho = − 0.405, P = 0.017 for K ep; and rho = 0.385, P = 0.024 for V e). K trans, K ep, and iAUC demonstrated moderate diagnostic performance (iAUC = 0.78, 0.77 and 0.80, respectively) for discriminating high-grades from low-grades HCC without significant differences.

Conclusions

The DCE-MRI derived parameters demonstrated weak but significant correlations with tumor proliferation status, histological grades or microvascular density, respectively. This free-breathing DCE-MRI is technically feasible and offers a potential avenue toward non-invasive evaluation of HCC malignancy.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Siegel RL, Miller KD, Jemal A (2015) Cancer statistics, 2015. CA Cancer J Clin 65:5–29

    Article  PubMed  Google Scholar 

  2. Jonas S, Bechstein WO, Steinmuller T, et al. (2001) Vascular invasion and histopathologic grading determine outcome after liver transplantation for hepatocellular carcinoma in cirrhosis. Hepatology 33:1080–1086

    Article  CAS  PubMed  Google Scholar 

  3. Perez-Saborido B, De Los Galanes SJ, Meneu-Diaz JC, et al. (2007) Tumor recurrence after liver transplantation for hepatocellular carcinoma: recurrence pathway and prognostic factors. Transplant Proc 39:2304–2307

    Article  CAS  PubMed  Google Scholar 

  4. Zhou L, Rui JA, Wang SB, Chen SG, Qu Q (2015) Clinicopathological predictors of poor survival and recurrence after curative resection in hepatocellular carcinoma without portal vein tumor thrombosis. Pathol Oncol Res 21:131–138

    Article  CAS  PubMed  Google Scholar 

  5. D’Errico A, Grigioni WF, Fiorentino M, et al. (1994) Overexpression of p53 protein and Ki67 proliferative index in hepatocellular carcinoma: an immunohistochemical study on 109 Italian patients. Pathol Int 44:682–687

    Article  PubMed  Google Scholar 

  6. Hsu HC, Tseng HJ, Lai PL, Lee PH, Peng SY (1993) Expression of p53 gene in 184 unifocal hepatocellular carcinomas: association with tumor growth and invasiveness. Cancer Res 53:4691–4694

    CAS  PubMed  Google Scholar 

  7. Nigro JM, Baker SJ, Preisinger AC, et al. (1989) Mutations in the p53 gene occur in diverse human tumour types. Nature 342:705–708

    Article  CAS  PubMed  Google Scholar 

  8. Stroescu C, Dragnea A, Ivanov B, et al. (2008) Expression of p53, Bcl-2, VEGF, Ki67 and PCNA and prognostic significance in hepatocellular carcinoma. J Gastrointestin Liver Dis 17:411–417

    PubMed  Google Scholar 

  9. Yamaguchi R, Yano H, Iemura A, et al. (1998) Expression of vascular endothelial growth factor in human hepatocellular carcinoma. Hepatology 28:68–77

    Article  CAS  PubMed  Google Scholar 

  10. Zhang W, Kim R, Quintini C, et al. (2015) Prognostic role of plasma vascular endothelial growth factor in patients with hepatocellular carcinoma undergoing liver transplantation. Liver Transpl 21:101–111

    Article  CAS  PubMed  Google Scholar 

  11. Mann CD, Neal CP, Garcea G, et al. (2007) Prognostic molecular markers in hepatocellular carcinoma: a systematic review. Eur J Cancer 43:979–992

    Article  CAS  PubMed  Google Scholar 

  12. Murakami K, Kasajima A, Kawagishi N, Ohuchi N, Sasano H (2015) Microvessel density in hepatocellular carcinoma: Prognostic significance and review of the previous published work. Hepatol Res 45:1185–1194

    Article  CAS  PubMed  Google Scholar 

  13. Li Y, Ma X, Zhang J, Liu X, Liu L (2014) Prognostic value of microvessel density in hepatocellular carcinoma patients: a meta-analysis. Int J Biol Markers 29:e279–e287

    Article  PubMed  Google Scholar 

  14. Tofts PS, Brix G, Buckley DL, et al. (1999) Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusible tracer: standardized quantities and symbols. J Magn Reson Imaging 10:223–232

    Article  CAS  PubMed  Google Scholar 

  15. Yang X, Knopp MV (2011) Quantifying tumor vascular heterogeneity with dynamic contrast-enhanced magnetic resonance imaging: a review. J Biomed Biotechnol 2011:732848

    PubMed  PubMed Central  Google Scholar 

  16. Rao SX, Chen CZ, Liu H, Zeng MS, Qu XD (2013) Three-dimensional whole-liver perfusion magnetic resonance imaging in patients with hepatocellular carcinomas and colorectal hepatic metastases. BMC Gastroenterol 13:53

    Article  PubMed  PubMed Central  Google Scholar 

  17. Huh J, Choi Y, Woo DC, et al. (2016) Feasibility of test-bolus DCE-MRI using CAIPIRINHA-VIBE for the evaluation of pancreatic malignancies. Eur Radiol . doi:10.1007/s00330-016-4209-6

    Google Scholar 

  18. Hao W, Zhao B, Wang G, Wang C, Liu H (2015) Influence of scan duration on the estimation of pharmacokinetic parameters for breast lesions: a study based on CAIPIRINHA-Dixon-TWIST-VIBE technique. Eur Radiol 25:1162–1171

    Article  PubMed  Google Scholar 

  19. Chen BB, Shih TT (2014) DCE-MRI in hepatocellular carcinoma-clinical and therapeutic image biomarker. World J Gastroenterol 20:3125–3134

    Article  PubMed  PubMed Central  Google Scholar 

  20. Braren R, Curcic J, Remmele S, et al. (2011) Free-breathing quantitative dynamic contrast-enhanced magnetic resonance imaging in a rat liver tumor model using dynamic radial T(1) mapping. Invest Radiol 46:624–631

    Article  PubMed  Google Scholar 

  21. FritzHansen T, Rostrup E, Larsson HBW, et al. (1996) Measurement of the arterial concentration of Gd-DTPA using MRI: a step toward quantitative perfusion imaging. Magn Reson Med 36:225–231

    Article  CAS  Google Scholar 

  22. Wagner M, Doblas S, Daire JL, et al. (2012) Diffusion-weighted MR imaging for the regional characterization of liver tumors. Radiology 264:464–472

    Article  PubMed  Google Scholar 

  23. Shinriki S, Jono H, Ota K, et al. (2009) Humanized anti-interleukin-6 receptor antibody suppresses tumor angiogenesis and in vivo growth of human oral squamous cell carcinoma. Clin Cancer Res 15:5426–5434

    Article  CAS  PubMed  Google Scholar 

  24. Song KD, Choi D, Lee JH, et al. (2014) Evaluation of tumor microvascular response to brivanib by dynamic contrast-enhanced 7-T MRI in an orthotopic xenograft model of hepatocellular carcinoma. AJR Am J Roentgenol 202:W559–W566

    Article  PubMed  Google Scholar 

  25. DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44:837–845

    Article  CAS  PubMed  Google Scholar 

  26. Zwick S, Brix G, Tofts PS, et al. (2010) Simulation-based comparison of two approaches frequently used for dynamic contrast-enhanced MRI. Eur Radiol 20:432–442

    Article  PubMed  Google Scholar 

  27. Padhani AR, Khan AA (2010) Diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for monitoring anticancer therapy. Target Oncol 5:39–52

    Article  PubMed  Google Scholar 

  28. Shen FU, Lu J, Chen L, Wang Z, Chen Y (2016) Diagnostic value of dynamic contrast-enhanced magnetic resonance imaging in rectal cancer and its correlation with tumor differentiation. Mol Clin Oncol 4:500–506

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Wegner CS, Gaustad JV, Andersen LM, Simonsen TG, Rofstad EK (2016) Diffusion-weighted and dynamic contrast-enhanced MRI of pancreatic adenocarcinoma xenografts: associations with tumor differentiation and collagen content. J Transl Med 14:161

    Article  PubMed  PubMed Central  Google Scholar 

  30. Kim KA, Park MS, Ji HJ, et al. (2014) Diffusion and perfusion MRI prediction of progression-free survival in patients with hepatocellular carcinoma treated with concurrent chemoradiotherapy. J Magn Reson Imaging 39:286–292

    Article  PubMed  Google Scholar 

  31. Shin JK, Kim JY (2017) Dynamic contrast-enhanced and diffusion-weighted MRI of estrogen receptor-positive invasive breast cancers: Associations between quantitative MR parameters and Ki-67 proliferation status. J Magn Reson Imaging 45:94–102

    Article  PubMed  Google Scholar 

  32. Flaherty KT, Rosen MA, Heitjan DF, et al. (2008) Pilot study of DCE-MRI to predict progression-free survival with sorafenib therapy in renal cell carcinoma. Cancer Biol Ther 7:496–501

    Article  CAS  PubMed  Google Scholar 

  33. Barnes SL, Whisenant JG, Loveless ME, Yankeelov TE (2012) Practical dynamic contrast enhanced MRI in small animal models of cancer: data acquisition, data analysis, and interpretation. Pharmaceutics 4:442–478

    Article  PubMed  PubMed Central  Google Scholar 

  34. Kim YE, Lim JS, Choi J, et al. (2013) Perfusion parameters of dynamic contrast-enhanced magnetic resonance imaging in patients with rectal cancer: correlation with microvascular density and vascular endothelial growth factor expression. Korean J Radiol 14:878–885

    Article  PubMed  PubMed Central  Google Scholar 

  35. Li L, Wang K, Sun X, et al. (2015) Parameters of dynamic contrast-enhanced MRI as imaging markers for angiogenesis and proliferation in human breast cancer. Med Sci Monit 21:376–382

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Jia ZZ, Gu HM, Zhou XJ, et al. (2015) The assessment of immature microvascular density in brain gliomas with dynamic contrast-enhanced magnetic resonance imaging. Eur J Radiol 84:1805–1809

    Article  PubMed  Google Scholar 

  37. Chen J, Qian T, Zhang H, et al. (2016) Combining dynamic contrast enhanced magnetic resonance imaging and microvessel density to assess the angiogenesis after PEI in a rabbit VX2 liver tumor model. Magn Reson Imaging 34:177–182

    Article  CAS  PubMed  Google Scholar 

  38. Bali MA, Metens T, Denolin V, et al. (2011) Tumoral and nontumoral pancreas: correlation between quantitative dynamic contrast-enhanced MR imaging and histopathologic parameters. Radiology 261:456–466

    Article  PubMed  Google Scholar 

  39. Mayr NA, Hawighorst H, Yuh WT, et al. (1999) MR microcirculation assessment in cervical cancer: correlations with histomorphological tumor markers and clinical outcome. J Magn Reson Imaging 10:267–276

    Article  CAS  PubMed  Google Scholar 

  40. Cheng HL, Wallis C, Shou Z, Farhat WA (2007) Quantifying angiogenesis in VEGF-enhanced tissue-engineered bladder constructs by dynamic contrast-enhanced MRI using contrast agents of different molecular weights. J Magn Reson Imaging 25:137–145

    Article  CAS  PubMed  Google Scholar 

  41. Kim BK, Han KH, Park YN, et al. (2008) Prediction of microvascular invasion before curative resection of hepatocellular carcinoma. J Surg Oncol 97:246–252

    Article  PubMed  Google Scholar 

  42. Oishi K, Itamoto T, Amano H, et al. (2007) Clinicopathologic features of poorly differentiated hepatocellular carcinoma. J Surg Oncol 95:311–316

    Article  PubMed  Google Scholar 

  43. Qian T, Chen M, Gao F, et al. (2014) Diffusion-weighted magnetic resonance imaging to evaluate microvascular density after transarterial embolization ablation in a rabbit VX2 liver tumor model. Magn Reson Imaging 32:1052–1057

    Article  PubMed  Google Scholar 

  44. An C, Park MS, Jeon HM, et al. (2012) Prediction of the histopathological grade of hepatocellular carcinoma using qualitative diffusion-weighted, dynamic, and hepatobiliary phase MRI. Eur Radiol 22:1701–1708

    Article  PubMed  Google Scholar 

  45. Chang WC, Chen RC, Chou CT, et al. (2014) Histological grade of hepatocellular carcinoma correlates with arterial enhancement on gadoxetic acid-enhanced and diffusion-weighted MR images. Abdom Imaging 39:1202–1212

    Article  PubMed  Google Scholar 

  46. Choi YS, Rhee H, Choi JY, et al. (2013) Histological characteristics of small hepatocellular carcinomas showing atypical enhancement patterns on gadoxetic acid-enhanced MR imaging. J Magn Reson Imaging 37:1384–1391

    Article  PubMed  Google Scholar 

  47. Kogita S, Imai Y, Okada M, et al. (2010) Gd-EOB-DTPA-enhanced magnetic resonance images of hepatocellular carcinoma: correlation with histological grading and portal blood flow. Eur Radiol 20:2405–2413

    Article  PubMed  Google Scholar 

  48. Tahir B, Sandrasegaran K, Ramaswamy R, et al. (2011) Does the hepatocellular phase of gadobenate dimeglumine help to differentiate hepatocellular carcinoma in cirrhotic patients according to histological grade? Clin Radiol 66:845–852

    Article  CAS  PubMed  Google Scholar 

  49. Thompson SM, Wang J, Chandan VS, et al. (2017) MR elastography of hepatocellular carcinoma: Correlation of tumor stiffness with histopathology features-Preliminary findings. Magn Reson Imaging 37:41–45

    Article  PubMed  Google Scholar 

  50. Matsui O, Kobayashi S, Sanada J, et al. (2011) Hepatocelluar nodules in liver cirrhosis: hemodynamic evaluation (angiography-assisted CT) with special reference to multi-step hepatocarcinogenesis. Abdom Imaging 36:264–272

    Article  PubMed  PubMed Central  Google Scholar 

  51. Park YN, Yang CP, Fernandez GJ, et al. (1998) Neoangiogenesis and sinusoidal “capillarization” in dysplastic nodules of the liver. Am J Surg Pathol 22:656–662

    Article  CAS  PubMed  Google Scholar 

  52. Kiessling F, Morgenstern B, Zhang C (2007) Contrast agents and applications to assess tumor angiogenesis in vivo by magnetic resonance imaging. Curr Med Chem 14:77–91

    Article  CAS  PubMed  Google Scholar 

  53. Wu L, Lv P, Zhang H, et al. (2015) Dynamic contrast-enhanced (DCE) MRI assessment of microvascular characteristics in the murine orthotopic pancreatic cancer model. Magn Reson Imaging 33:737–760

    Article  PubMed  Google Scholar 

  54. Lin YH, Hwang RM, Chen BB, et al. (2014) Vascular and hepatic enhancements at MR imaging: comparison of Gd-EOB-DTPA and Gd-DTPA in the same subjects. Clin Imaging 38:287–291

    Article  PubMed  Google Scholar 

  55. Narita M, Hatano E, Arizono S, et al. (2009) Expression of OATP1B3 determines uptake of Gd-EOB-DTPA in hepatocellular carcinoma. J Gastroenterol 44:793–798

    Article  CAS  PubMed  Google Scholar 

  56. Kitao A, Matsui O, Yoneda N, et al. (2011) The uptake transporter OATP8 expression decreases during multistep hepatocarcinogenesis: correlation with gadoxetic acid enhanced MR imaging. Eur Radiol 21:2056–2066

    Article  PubMed  Google Scholar 

  57. Sourbron S, Sommer WH, Reiser MF, Zech CJ (2012) Combined quantification of liver perfusion and function with dynamic gadoxetic acid-enhanced MR imaging. Radiology 263:874–883

    Article  PubMed  Google Scholar 

  58. Nilsson H, Nordell A, Vargas R, et al. (2009) Assessment of hepatic extraction fraction and input relative blood flow using dynamic hepatocyte-specific contrast-enhanced MRI. J Magn Reson Imaging 29:1323–1331

    Article  PubMed  Google Scholar 

Download references

Acknowledgement

This study was funded by National Natural Science Foundation of China (Grant Number 81471658).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bin Song.

Ethics declarations

Conflict of interest

Author Jie Chen declares that she has no conflict of interest. Author Chenyang Chen declares that she has no conflict of interest. Author Chunchao Xia declares that he has no conflict of interest. Author Zixing Huang declares that he has no conflict of interest. Author Panli Zuo declares that she has no conflict of interest. Author Alto Stemmer declares that he has no conflict of interest. Author Bin Song declares that he has no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, J., Chen, C., Xia, C. et al. Quantitative free-breathing dynamic contrast-enhanced MRI in hepatocellular carcinoma using gadoxetic acid: correlations with Ki67 proliferation status, histological grades, and microvascular density. Abdom Radiol 43, 1393–1403 (2018). https://doi.org/10.1007/s00261-017-1320-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00261-017-1320-3

Keywords

Navigation