DOI QR코드

DOI QR Code

Dynamic Contrast-Enhanced MRI for Monitoring Antiangiogenic Treatment: Determination of Accurate and Reliable Perfusion Parameters in a Longitudinal Study of a Mouse Xenograft Model

  • Song, Youngkyu (Division of Magnetic Resonance, Korea Basic Science Institute) ;
  • Cho, Gyunggoo (Division of Magnetic Resonance, Korea Basic Science Institute) ;
  • Suh, Ji-Yeon (Division of Magnetic Resonance, Korea Basic Science Institute) ;
  • Lee, Chang Kyung (Division of Magnetic Resonance, Korea Basic Science Institute) ;
  • Kim, Young Ro (Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital) ;
  • Kim, Yoon Jae (Asan Medical Center, University of Ulsan College of Medicine) ;
  • Kim, Jeong Kon (Division of Magnetic Resonance, Korea Basic Science Institute)
  • Received : 2012.11.06
  • Accepted : 2013.03.24
  • Published : 2013.07.01

Abstract

Objective: To determine the reliable perfusion parameters in dynamic contrast-enhanced MRI (DCE-MRI) for the monitoring antiangiogenic treatment in mice. Materials and Methods: Mice, with U-118 MG tumor, were treated with either saline (n = 3) or antiangiogenic agent (sunitinib, n = 8). Before (day 0) and after (days 2, 8, 15, 25) treatment, DCE examinations using correlations of perfusion parameters ($K_{ep}$, $K_{el}$, and $A^H$ from two compartment model; time to peak, initial slope and % enhancement from time-intensity curve analysis) were evaluated. Results: Tumor growth rate was found to be 129% ${\pm}$ 28 in control group, -33% ${\pm}$ 11 in four mice with sunitinib-treatment (tumor regression) and 47% ${\pm}$ 15 in four with sunitinib-treatment (growth retardation). $K_{ep}$ (r = 0.80) and initial slope (r = 0.84) showed strong positive correlation to the initial tumor volume (p < 0.05). In control mice, tumor regression group and growth retardation group animals, $K_{ep}$ (r : 0.75, 0.78, 0.81, 0.69) and initial slope (r : 0.79, 0.65, 0.67, 0.84) showed significant correlation with tumor volume (p < 0.01). In four mice with tumor re-growth, $K_{ep}$ and initial slope increased 20% or greater at earlier (n = 2) than or same periods (n = 2) to when the tumor started to re-grow with 20% or greater growth rate.

Keywords

References

  1. Kerbel RS. Tumor angiogenesis. N Engl J Med 2008;358:2039-2049 https://doi.org/10.1056/NEJMra0706596
  2. Gossmann A, Helbich TH, Kuriyama N, Ostrowitzki S, Roberts TP, Shames DM, et al. Dynamic contrast-enhanced magnetic resonance imaging as a surrogate marker of tumor response to anti-angiogenic therapy in a xenograft model of glioblastoma multiforme. J Magn Reson Imaging 2002;15:233-240 https://doi.org/10.1002/jmri.10072
  3. Maxwell RJ, Wilson J, Prise VE, Vojnovic B, Rustin GJ, Lodge MA, et al. Evaluation of the anti-vascular effects of combretastatin in rodent tumours by dynamic contrast enhanced MRI. NMR Biomed 2002;15:89-98 https://doi.org/10.1002/nbm.754
  4. Rosen MA, Schnall MD. Dynamic contrast-enhanced magnetic resonance imaging for assessing tumor vascularity and vascular effects of targeted therapies in renal cell carcinoma. Clin Cancer Res 2007;13(2 Pt 2):770s-776s https://doi.org/10.1158/1078-0432.CCR-06-1921
  5. Ferl GZ, Port RE. Quantification of antiangiogenic and antivascular drug activity by kinetic analysis of DCE-MRI data. Clin Pharmacol Ther 2012;92:118-124 https://doi.org/10.1038/clpt.2012.63
  6. Potapova O, Laird AD, Nannini MA, Barone A, Li G, Moss KG, et al. Contribution of individual targets to the antitumor efficacy of the multitargeted receptor tyrosine kinase inhibitor SU11248. Mol Cancer Ther 2006;5:1280-1289 https://doi.org/10.1158/1535-7163.MCT-03-0156
  7. Mendel DB, Laird AD, Xin X, Louie SG, Christensen JG, Li G, et al. In vivo antitumor activity of SU11248, a novel tyrosine kinase inhibitor targeting vascular endothelial growth factor and platelet-derived growth factor receptors: determination of a pharmacokinetic/pharmacodynamic relationship. Clin Cancer Res 2003;9:327-337
  8. Hoffmann U, Brix G, Knopp MV, Hess T, Lorenz WJ. Pharmacokinetic mapping of the breast: a new method for dynamic MR mammography. Magn Reson Med 1995;33:506-514 https://doi.org/10.1002/mrm.1910330408
  9. Buckley DL, Kerslake RW, Blackband SJ, Horsman A. Quantitative analysis of multi-slice Gd-DTPA enhanced dynamic MR images using an automated simplex minimization procedure. Magn Reson Med 1994;32:646-651 https://doi.org/10.1002/mrm.1910320514
  10. Tofts PS. Modeling tracer kinetics in dynamic Gd-DTPA MR imaging. J Magn Reson Imaging 1997;7:91-101 https://doi.org/10.1002/jmri.1880070113
  11. Zou KH, Tuncali K, Silverman SG. Correlation and simple linear regression. Radiology 2003;227:617-622 https://doi.org/10.1148/radiol.2273011499
  12. Muruganandham M, Lupu M, Dyke JP, Matei C, Linn M, Packman K, et al. Preclinical evaluation of tumor microvascular response to a novel antiangiogenic/antitumor agent RO0281501 by dynamic contrast-enhanced MRI at 1.5 T. Mol Cancer Ther 2006;5:1950-1957 https://doi.org/10.1158/1535-7163.MCT-06-0010
  13. Pickles MD, Manton DJ, Lowry M, Turnbull LW. Prognostic value of pre-treatment DCE-MRI parameters in predicting disease free and overall survival for breast cancer patients undergoing neoadjuvant chemotherapy. Eur J Radiol 2009;71:498-505 https://doi.org/10.1016/j.ejrad.2008.05.007
  14. Elsayed YA, Sausville EA. Selected novel anticancer treatments targeting cell signaling proteins. Oncologist 2001;6:517-537 https://doi.org/10.1634/theoncologist.6-6-517
  15. Morgan B, Utting JF, Higginson A, Thomas AL, Steward WP, Horsfield MA. A simple, reproducible method for monitoring the treatment of tumours using dynamic contrast-enhanced MR imaging. Br J Cancer 2006;94:1420-1427 https://doi.org/10.1038/sj.bjc.6603140
  16. Brix G, Semmler W, Port R, Schad LR, Layer G, Lorenz WJ. Pharmacokinetic parameters in CNS Gd-DTPA enhanced MR imaging. J Comput Assist Tomogr 1991;15:621-628 https://doi.org/10.1097/00004728-199107000-00018
  17. Tofts PS, Brix G, Buckley DL, Evelhoch JL, Henderson E, Knopp MV, et al. Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusable tracer: standardized quantities and symbols. J Magn Reson Imaging 1999;10:223-232 https://doi.org/10.1002/(SICI)1522-2586(199909)10:3<223::AID-JMRI2>3.0.CO;2-S
  18. Evelhoch J, Garwood M, Vigneron D, Knopp M, Sullivan D, Menkens A, et al. Expanding the use of magnetic resonance in the assessment of tumor response to therapy: workshop report. Cancer Res 2005;65:7041-7044 https://doi.org/10.1158/0008-5472.CAN-05-0674
  19. de Lussanet QG, Langereis S, Beets-Tan RG, van Genderen MH, Griffioen AW, van Engelshoven JM, et al. Dynamic contrastenhanced MR imaging kinetic parameters and molecular weight of dendritic contrast agents in tumor angiogenesis in mice. Radiology 2005;235:65-72 https://doi.org/10.1148/radiol.2351040411
  20. Buckley DL, Drew PJ, Mussurakis S, Monson JR, Horsman A. Microvessel density of invasive breast cancer assessed by dynamic Gd-DTPA enhanced MRI. J Magn Reson Imaging 1997;7:461-464 https://doi.org/10.1002/jmri.1880070302
  21. Cooper RA, Carrington BM, Loncaster JA, Todd SM, Davidson SE, Logue JP, et al. Tumour oxygenation levels correlate with dynamic contrast-enhanced magnetic resonance imaging parameters in carcinoma of the cervix. Radiother Oncol 2000;57:53-59 https://doi.org/10.1016/S0167-8140(00)00259-0
  22. Ahn SJ, An CS, Koom WS, Song HT, Suh JS. Correlations of 3T DCE-MRI quantitative parameters with microvessel density in a human-colorectal-cancer xenograft mouse model. Korean J Radiol 2011;12:722-730 https://doi.org/10.3348/kjr.2011.12.6.722
  23. Kang H, Lee HY, Lee KS, Kim JH. Imaging-based tumor treatment response evaluation: review of conventional, new, and emerging concepts. Korean J Radiol 2012;13:371-390 https://doi.org/10.3348/kjr.2012.13.4.371
  24. Kim JK, Jang YJ, Cho G. Multidisciplinary functional MR imaging for prostate cancer. Korean J Radiol 2009;10:535-551 https://doi.org/10.3348/kjr.2009.10.6.535
  25. Knopp MV, Weiss E, Sinn HP, Mattern J, Junkermann H, Radeleff J, et al. Pathophysiologic basis of contrast enhancement in breast tumors. J Magn Reson Imaging 1999;10:260-266 https://doi.org/10.1002/(SICI)1522-2586(199909)10:3<260::AID-JMRI6>3.0.CO;2-7

Cited by

  1. Early detection of antiangiogenic treatment responses in a mouse xenograft tumor model using quantitative perfusion MRI vol.3, pp.1, 2013, https://doi.org/10.1002/cam4.177
  2. Characteristics of quantitative perfusion parameters on dynamic contrast‐enhanced MRI in mammographically occult breast cancer vol.17, pp.5, 2013, https://doi.org/10.1120/jacmp.v17i5.6091
  3. Preclinical Molecular Imaging for Precision Medicine in Breast Cancer Mouse Models vol.2019, pp.None, 2013, https://doi.org/10.1155/2019/8946729
  4. Bridging the translational gap: Implementation of multimodal small animal imaging strategies for tumor burden assessment in a co-clinical trial vol.14, pp.4, 2019, https://doi.org/10.1371/journal.pone.0207555
  5. Sinoporphyrin sodium is a promising sensitizer for photodynamic and sonodynamic therapy in glioma vol.44, pp.4, 2013, https://doi.org/10.3892/or.2020.7695
  6. Tumor Microenvironment Modifications Recorded With IVIM Perfusion Analysis and DCE-MRI After Neoadjuvant Radiotherapy: A Preclinical Study vol.11, pp.None, 2013, https://doi.org/10.3389/fonc.2021.784437