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Abdominal Radiology

, Volume 43, Issue 7, pp 1661–1669 | Cite as

CT perfusion in normal liver and liver metastases from neuroendocrine tumors treated with targeted antivascular agents

  • Chaan S. Ng
  • Wei Wei
  • Cihan Duran
  • Payel Ghosh
  • Ella F. Anderson
  • Adam G. Chandler
  • James C. Yao
Article

Abstract

Objective

To assess the effects of bevacizumab and everolimus, individually and combined, on CT perfusion (CTp) parameters in liver metastases from neuroendocrine tumors (mNET) and normal liver.

Methods

This retrospective study comprised 27 evaluable patients with mNETs who had participated in a two-arm randomized clinical trial of mono-therapy with bevacizumab (Arm B) or everolimus (Arm E) for 3 weeks, followed by combination of both targeted agents. CTp was undertaken at baseline, 3 and 9 weeks, to evaluate blood flow (BF), blood volume (BV), mean transit time (MTT), permeability surface area product (PS), and hepatic arterial fraction (HAF) of mNET and normal liver, using a dual-input distributed parameter physiological model. Linear mixed models were used to estimate and compare CTp parameter values between time-points.

Results

In tumor, mono-therapy with bevacizumab significantly reduced BV (p = 0.05); everolimus had no effects on CTp parameters. Following dual-therapy, BV and BF were significantly lower than baseline in both arms (p ≤ 0.04), and PS was significantly lower in Arm E (p < 0.0001). In normal liver, mono-therapy with either agent had no significant effects on CTp parameters: dual-therapy significantly reduced BV, MTT, and PS, and increased HAF, relative to baseline in Arm E (p ≤ 0.04); in Arm B, only PS reduced (p = 0.04).

Conclusions

Bevacizumab and everolimus, individually and when combined, have significant and differential effects on CTp parameters in mNETs and normal liver, which is evident soon after starting therapy. CTp may offer an early non-invasive means to investigate the effects of drugs in tumor and normal tissue.

Keywords

Neuroendocrine tumors Computerized tomography, perfusion Liver metastases Bevacizumab Everolimus 

Notes

Compliance with ethical standards

Funding

NIH CCSG Grant (P30 CA016672), Novartis, Genentech and the John S. Dunn, Sr. Distinguished Chair in Diagnostic Imaging provided partial funding support for conduct of the study.

Conflicts of interest

Chaan S. Ng has received research funding from and is a Consultant for GE Healthcare. Adam G. Chandler is employed by GE Healthcare. The other authors (Wei Wei, Cihan Duran, Payel Ghosh, Ella F. Anderson, and James C. Yao) declare that they have no conflicts of interest.

Ethical approval

This retrospective analysis was approved by our institutional review board (IRB), with waiver of informed consent. Patients for this analysis were drawn from an earlier prospective clinical trial which was undertaken in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration. Informed consent was obtained from all individual participants included in the prospective study.

References

  1. 1.
    Dixon AK, Gilbert FJ (2012) Standardising measurement of tumour vascularity by imaging: recommendations for ultrasound, computed tomography, magnetic resonance imaging and positron emission tomography. Eur Radiol 22(7):1427–1429CrossRefPubMedGoogle Scholar
  2. 2.
    Miles KA, Charnsangavej C, Lee FT, et al. (2000) Application of CT in the investigation of angiogenesis in oncology. Acad Radiol 7(10):840–850CrossRefPubMedGoogle Scholar
  3. 3.
    Miles KA, Griffiths MR (2003) Perfusion CT: a worthwhile enhancement? Br J Radiol 76(904):220–231CrossRefPubMedGoogle Scholar
  4. 4.
    Kambadakone AR, Sahani DV (2009) Body perfusion CT: technique, clinical applications, and advances. Radiol Clin North Am 47(1):161–178CrossRefPubMedGoogle Scholar
  5. 5.
    Garcia-Figueiras R, Goh VJ, Padhani AR, et al. (2013) CT perfusion in oncologic imaging: a useful tool? Am J Roentgenol 200(1):8–19CrossRefGoogle Scholar
  6. 6.
    Tamm EP, Kim EE, Ng CS (2007) Imaging of neuroendocrine tumors. Hematol Oncol Clin North Am 21(3):409–432CrossRefPubMedGoogle Scholar
  7. 7.
    Cen P, Amato RJ (2012) Treatment of advanced pancreatic neuroendocrine tumors: potential role of everolimus. Onco Targets Ther 5:217–224PubMedPubMedCentralGoogle Scholar
  8. 8.
    Hicklin DJ, Ellis LM (2005) Role of the vascular endothelial growth factor pathway in tumor growth and angiogenesis. J Clin Oncol 23(5):1011–1027CrossRefPubMedGoogle Scholar
  9. 9.
    Konno H, Arai T, Tanaka T, et al. (1998) Antitumor effect of a neutralizing antibody to vascular endothelial growth factor on liver metastasis of endocrine neoplasm. Jpn J Cancer Res 89(9):933–939CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Terris B, Scoazec JY, Rubbia L, et al. (1998) Expression of vascular endothelial growth factor in digestive neuroendocrine tumours. Histopathology 32(2):133–138CrossRefPubMedGoogle Scholar
  11. 11.
    Zhang J, Jia Z, Li Q, et al. (2007) Elevated expression of vascular endothelial growth factor correlates with increased angiogenesis and decreased progression-free survival among patients with low-grade neuroendocrine tumors. Cancer 109(8):1478–1486CrossRefPubMedGoogle Scholar
  12. 12.
    Jiang T, Kambadakone A, Kulkarni NM, Zhu AX, Sahani DV (2012) Monitoring response to antiangiogenic treatment and predicting outcomes in advanced hepatocellular carcinoma using image biomarkers, CT perfusion, tumor density, and tumor size (RECIST). Invest Radiol 47(1):11–17CrossRefPubMedGoogle Scholar
  13. 13.
    Zhu AX, Holalkere NS, Muzikansky A, Horgan K, Sahani DV (2008) Early antiangiogenic activity of bevacizumab evaluated by computed tomography perfusion scan in patients with advanced hepatocellular carcinoma. Oncologist 13(2):120–125CrossRefPubMedGoogle Scholar
  14. 14.
    Ng CS, Charnsangavej C, Wei W, Yao JC (2011) Perfusion CT findings in patients with metastatic carcinoid tumors undergoing bevacizumab and interferon therapy. Am J Roentgenol 196(3):569–576CrossRefGoogle Scholar
  15. 15.
    D’Onofrio M, Cingarlini S, Ortolani S, et al. (2017) Perfusion CT changes in liver metastases from pancreatic neuroendocrine tumors during everolimus treatment. Anticancer Res 37(3):1305–1311CrossRefPubMedGoogle Scholar
  16. 16.
    Yao JC, Phan AT, Hess K, et al. (2015) Perfusion computed tomography as functional biomarker in randomized run-in study of bevacizumab and everolimus in well-differentiated neuroendocrine tumors. Pancreas 44(2):190–197CrossRefPubMedGoogle Scholar
  17. 17.
    Ng CS, Hobbs BP, Chandler AG, et al. (2013) Metastases to the liver from neuroendocrine tumors: effect of duration of scan acquisition on CT perfusion values. Radiology 269(3):758–767CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Chandler A, Wei W, Anderson EF, et al. (1016) Validation of motion correction techniques for liver CT perfusion studies. Br J Radiol 2012(85):e514–e522Google Scholar
  19. 19.
    Willett CG, Boucher Y, di Tomaso E, et al. (2004) Direct evidence that the VEGF-specific antibody bevacizumab has antivascular effects in human rectal cancer. Nat Med 10(2):145–147CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Jain RK (2001) Normalizing tumor vasculature with anti-angiogenic therapy: a new paradigm for combination therapy. Nat Med 7(9):987–989CrossRefPubMedGoogle Scholar
  21. 21.
    Guyennon A, Mihaila M, Palma J, et al. (2010) Perfusion characterization of liver metastases from endocrine tumors: computed tomography perfusion. World J Radiol 2(11):449–454CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Lefort T, Pilleul F, Mule S, et al. (2012) Correlation and agreement between contrast-enhanced ultrasonography and perfusion computed tomography for assessment of liver metastases from endocrine tumors: normalization enhances correlation. Ultrasound Med Biol 38(6):953–961CrossRefPubMedGoogle Scholar
  23. 23.
    Catalano OA, Choy G, Zhu A, Hahn PF, Sahani DV (2010) Differentiation of malignant thrombus from bland thrombus of the portal vein in patients with hepatocellular carcinoma: application of diffusion-weighted MR imaging. Radiology 254(1):154–162CrossRefPubMedGoogle Scholar
  24. 24.
    Ng CS, Chandler AG, Wei W, et al. (2012) Effect of dual vascular input functions on CT perfusion parameter values and reproducibility in liver tumors and normal liver. J Comput Assist Tomogr 36(4):388–393CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Ng CS, Chandler AG, Wei W, et al. (2013) Effect of duration of scan acquisition on CT perfusion parameter values in primary and metastatic tumors in the lung. Eur J Radiol 82(10):1811–1818CrossRefPubMedGoogle Scholar
  26. 26.
    Morais C (2014) Sunitinib resistance in renal cell carcinoma. J Kidney Cancer VHL 1(1):1–11CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Chaan S. Ng
    • 1
  • Wei Wei
    • 2
  • Cihan Duran
    • 1
  • Payel Ghosh
    • 1
  • Ella F. Anderson
    • 1
  • Adam G. Chandler
    • 3
  • James C. Yao
    • 4
  1. 1.Department of Radiology, Unit 1473University of TexasHoustonUSA
  2. 2.Department of Biostatistics, Unit 1411University of TexasHoustonUSA
  3. 3.GE HealthcareWaukeshaUSA
  4. 4.Department of Gastrointestinal Medical Oncology, Unit 0426University of TexasHoustonUSA

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