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Assessment of angiogenesis in rabbit orthotropic liver tumors using three-dimensional dynamic contrast-enhanced ultrasound compared with two-dimensional DCE-US

  • Qiao Zheng
  • Jian-chao Zhang
  • Zhu Wang
  • Si-Min Ruan
  • Wei Li
  • Fu-Shun Pan
  • Li-Da Chen
  • Yu-Chen Zhang
  • Wen-Xin Wu
  • Xiao-Yan Xie
  • Ming-De Lu
  • Quan-Yuan ShanEmail author
  • Wei WangEmail author
Original Article
  • 21 Downloads

Abstract

Objectives

To evaluate quantitative three-dimensional (3D) dynamic contrast-enhanced ultrasound (DCE-US) in the assessment of tumor angiogenesis using an orthotropic liver tumor model.

Methods

Nine New Zealand white rabbits with liver orthotropic VX2 tumors were established and imaged by two-dimensional (2D) and 3D DCE-US after SonoVue® bolus injections. The intraclass correlation coefficients of perfusion parameters, including peak intensity (PI), mean transit time, time to peak, and area under the curve, were calculated based on time-intensity curve. The percentage area of microvascular (PAMV) and the expression of vascular endothelial growth factor (VEGF) were both evaluated by immunohistochemical analysis and weighted by the tumor activity area ratio. Correlations between quantitative and histologic parameters were analyzed.

Results

The reproducibility of 3D DCE-US quantitative parameters was excellent (ICC 0.91–0.99); but only PI showed high reproducibility (ICC 0.97) in 2D. None of the parameters of quantitative 2D DCE-US were significantly correlated with weighted PAMV or VEGF. For 3D DCE-US, there was a positive correlation between PI and weighted PAMV (r = 0.74, P = 0.04) as well as VEGF (r = 0.79, P = 0.02).

Conclusion

Quantitative parameters of 3D DCE-US show feasibility, higher reproducibility and accuracy for the assessment of tumor angiogenesis using an orthotropic liver tumor model compared with 2D DCE-US.

Keywords

Ultrasonography Three-dimensional imaging Pathologic neovascularization Assessment 

Abbreviations

au

Arbitrary units

AUC

Area under the curve

DCE-US

Dynamic contrast-enhanced ultrasound

ICC

Intraclass correlation coefficient

MTT

Mean transit time

PAMV

Percentage area of microvascular

PI

Peak intensity

ROI

Region of interest

3D

Three-dimensional

TIC

Time-intensity curve

TTP

Time to peak

2D

Two-dimensional

VEGF

Vascular endothelial growth factor

VOI

Volume of interest

Notes

Funding

Funding was provided by Natural Science Foundation of China (Grant no. 81601500), Natural Science Foundation of Guangdong Province (Grant nos. 2017A030313661, 2016A030310143), Medical Science and Technology Foundation of Guangdong Province (Grant no. 2017A020215195)

Compliance with ethical standards

Ethical approval

All animal experiments were complied with the ARRIVE guidelines and carried out in accordance with the National Institutes of Health guide for the care and use of Laboratory animals. All applicable institutional and national guidelines for the care and use of animals were followed.

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

11604_2019_861_MOESM1_ESM.doc (82 kb)
Supplementary material (doc 82kb)

References

  1. 1.
    Folkman J. What is the evidence that tumors are angiogenesis dependent? J Natl Cancer Inst. 1990;82(1):4–6.CrossRefGoogle Scholar
  2. 2.
    Duffaud F, Therasse P. New guidelines to evaluate the response to treatment in solid tumors. Bull Cancer. 2000;87(12):881–6.Google Scholar
  3. 3.
    Marcus C, Ladam-Marcus V, Cucu C, Bouché O, Lucas L, Hoeffel C. Imaging techniques to evaluate the response to treatment in oncology: current standards and perspectives. Crit Rev Oncol Hematol. 2009;72(3):217–38.CrossRefGoogle Scholar
  4. 4.
    Greis C. Ultrasound contrast agents as markers of vascularity and microcirculation. Clin Hemorheol Microcirc. 2009;43(1–2):1–9.Google Scholar
  5. 5.
    Greis C. Quantitative evaluation of microvascular blood flow by contrast-enhanced ultrasound (CEUS). Clin Hemorheol Microcirc. 2011;49(1–4):137–49.Google Scholar
  6. 6.
    Bartolotta TV, Midiri M, Galia M, et al. Qualitative and quantitative evaluation of solitary thyroid nodules with contrast-enhanced ultrasound: initial results. Eur Radiol. 2006;16(10):2234–41.CrossRefGoogle Scholar
  7. 7.
    Ripolles T, Martinez MJ, Paredes JM, Blanc E, Flors L, Delgado F. Crohn disease: correlation of findings at contrast-enhanced US with severity at endoscopy. Radiology. 2009;253(1):241–8.CrossRefGoogle Scholar
  8. 8.
    Wang JW, Cao LH, Han F, et al. Contrast-enhanced US quantitatively detects changes of tumor perfusion in a murine breast cancer model during adriamycin chemotherapy. Acta Radiol. 2013;54(8):882–8.CrossRefGoogle Scholar
  9. 9.
    Zhang HP, Shi QS, Li F, et al. Regions of interest and parameters for the quantitative analysis of contrast-enhanced ultrasound to evaluate the anti-angiogenic effects of bevacizumab. Mol Med Rep. 2013;8(1):154–60.CrossRefGoogle Scholar
  10. 10.
    Zhou JH, Cao LH, Zheng W, Liu M, Han F, Li AH. Contrast-enhanced gray-scale ultrasound for quantitative evaluation of tumor response to chemotherapy: preliminary results with a mouse hepatoma model. Am J Roentgenol. 2011;196(1):W13–W1717.CrossRefGoogle Scholar
  11. 11.
    Williams R, Hudson J, Lloyd B, et al. Dynamic microbubble contrast-enhanced US to measure tumor response to targeted therapy: a proposed clinical protocol with results from renal cell carcinoma patients receiving antiangiogenic therapy. Radiology. 2011;260(2):581–90.CrossRefGoogle Scholar
  12. 12.
    Lassau N, Bonastre J, Kind M, et al. Validation of dynamic contrast-enhanced ultrasound in predicting outcomes of antiangiogenic therapy for solid tumors the french multicenter support for innovative and expensive techniques study. Investig Radiol. 2014;49(12):794–800.CrossRefGoogle Scholar
  13. 13.
    Wang HJ, Lutz AM, Hristov D, Tian L, Willmann JK. Intra-animal comparison between three-dimensional molecularly targeted US and three-dimensional dynamic contrast-enhanced US for early antiangiogenic treatment assessment in colon cancer. Radiology. 2017;282(2):443–52.CrossRefGoogle Scholar
  14. 14.
    Zhou J, Zhang H, Wang H, et al. Early prediction of tumor response to bevacizumab treatment in murine colon cancer models using three-dimensional dynamic contrast-enhanced ultrasound imaging. Angiogenesis. 2017;20(4):547–55.CrossRefGoogle Scholar
  15. 15.
    El Kaffas A, Sigrist RMS, Fisher G, et al. Quantitative three-dimensional dynamic contrast-enhanced ultrasound imaging: first-in-human pilot study in patients with liver metastases. Theranostics. 2017;7(15):3745–58.CrossRefGoogle Scholar
  16. 16.
    Wang HJ, Hristov D, Qin JL, Tian L, Willmann JK. Three-dimensional dynamic contrast-enhanced US imaging for early antiangiogenic treatment assessment in a mouse colon cancer model. Radiology. 2015;277(2):424–34.CrossRefGoogle Scholar
  17. 17.
    Yi CA, Lee KS, Kim EA, et al. Solitary pulmonary nodules: dynamic enhanced multi-detector row CT study and comparison with vascular endothelial growth factor and microvessel density. Radiology. 2004;233(1):191–9.CrossRefGoogle Scholar
  18. 18.
    Lassau N, Koscielny S, Albiges L, et al. Metastatic renal cell carcinoma treated with sunitinib: early evaluation of treatment response using dynamic contrast-enhanced ultrasonography. Clin Cancer Res. 2010;16(4):1216–25.CrossRefGoogle Scholar
  19. 19.
    Lassau N, Koscielny S, Chami L, et al. Advanced hepatocellular carcinoma: early evaluation of response to bevacizumab therapy at dynamic contrast-enhanced US with quantification-preliminary results. Radiology. 2011;258(1):291–300.CrossRefGoogle Scholar
  20. 20.
    Feingold S, Gessner R, Guracar IM, Dayton PA. Quantitative volumetric perfusion mapping of the microvasculature using contrast ultrasound. Investig Radiol. 2010;45(10):669–74.CrossRefGoogle Scholar
  21. 21.
    Williams R, Hudson JM, Lloyd BA, et al. Dynamic microbubble contrast-enhanced us to measure tumor response to targeted therapy: a proposed clinical protocol with results from renal cell carcinoma patients receiving antiangiogenic therapy. Radiology. 2011;260(2):581–90.CrossRefGoogle Scholar
  22. 22.
    Wang Z, Wang W, Liu GJ, et al. The role of quantitation of real-time 3-dimensional contrast-enhanced ultrasound in detecting microvascular invasion: an in vivo study. Abdom Radiol (N Y). 2016;41(10):1973–9.CrossRefGoogle Scholar
  23. 23.
    Ferraioli G, Meloni MF. Contrast-enhanced ultrasonography of the liver using SonoVue. Ultrasonography. 2018;37(1):25–35.CrossRefGoogle Scholar
  24. 24.
    Weidner N, Semple JP, Welch WR, Folkman J. Tumor angiogenesis and metastasis-correlation in invasive breast carcinoma. N Engl J Med. 1991;324(1):1–8.CrossRefGoogle Scholar
  25. 25.
    Uzzan B, Nicolas P, Cucherat M, Perret GY. Microvessel density as a prognostic factor in women with breast cancer: a systematic review of the literature and meta-analysis. Cancer Res. 2004;64(9):2941–55.CrossRefGoogle Scholar
  26. 26.
    Weidner N. Tumor angiogenesis: review of current applications in tumor prognostication. Semin Diagn Pathol. 1993;10(4):302–13.Google Scholar
  27. 27.
    Macchiarini P, Fontanini G, Hardin MJ, Squartini F, Angeletti CA. Relation of neovascularisation to metastasis of non-small-cell lung cancer. Lancet (Lond Engl). 1992;340(8812):145–6.CrossRefGoogle Scholar
  28. 28.
    Sharma S, Aggarwal N, Gupta S, Singh M, Gupta R, Dinda A. Angiogenesis in renal cell carcinoma: correlation of microvessel density and microvessel area with other prognostic factors. Int Urol Nephrol. 2011;43(1):125–9.CrossRefGoogle Scholar
  29. 29.
    Shiyan L, Pintong H, Zongmin W, et al. The relationship between enhanced intensity and microvessel density of gastric carcinoma using double contrast-enhanced ultrasonography. Ultrasound Med Biol. 2009;35(7):1086–91.CrossRefGoogle Scholar
  30. 30.
    Mori N, Mugikura S, Takahashi S, et al. Quantitative analysis of contrast-enhanced ultrasound imaging in invasive breast cancer: a novel technique to obtain histopathologic information of microvessel density. Ultrasound Med Biol. 2017;43(3):607–14.CrossRefGoogle Scholar
  31. 31.
    Dvorak HF. Vascular permeability factor/vascular endothelial growth factor: a critical cytokine in tumor angiogenesis and a potential target for diagnosis and therapy. J Clin Oncol. 2002;20(21):4368–80.CrossRefGoogle Scholar
  32. 32.
    Jayson GC, Kerbel R, Ellis LM, Harris AL. Antiangiogenic therapy in oncology: current status and future directions. Lancet. 2016;388(10043):518–29.CrossRefGoogle Scholar
  33. 33.
    Wei X, Li Y, Zhang S, Ming G. Evaluation of thyroid cancer in Chinese females with breast cancer by vascular endothelial growth factor (VEGF), microvessel density, and contrast-enhanced ultrasound (CEUS). Tumour Biol. 2014;35(7):6521–9.CrossRefGoogle Scholar
  34. 34.
    Lucidarme O, Kono Y, Corbeil J, et al. Angiogenesis: noninvasive quantitative assessment with contrast-enhanced functional US in murine model. Radiology. 2006;239(3):730–9.CrossRefGoogle Scholar

Copyright information

© Japan Radiological Society 2019

Authors and Affiliations

  1. 1.Department of Medical Ultrasonics, Institute of Diagnostic and Interventional UltrasoundThe First Affiliated Hospital of Sun Yat-Sen UniversityGuangzhouPeople’s Republic of China
  2. 2.Zhongshan School of MedicineSun Yat-Sen UniversityGuangzhouPeople’s Republic of China
  3. 3.Department of Hepatobiliary SurgeryThe First Affiliated Hospital of Sun Yat-Sen UniversityGuangzhouPeople’s Republic of China

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