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Correlations of 3T DCE-MRI Quantitative Parameters with Microvessel Density in a Human-Colorectal-Cancer Xenograft Mouse Model

  • Ahn, Sung-Jun (Department of Radiology and Research Institute of Radiological Science, College of Medicine, Yonsei University) ;
  • An, Chan-Sik (Department of Radiology and Research Institute of Radiological Science, College of Medicine, Yonsei University) ;
  • Koom, Woong-Sub (Department of Radiation Oncology, College of Medicine, Yonsei University) ;
  • Song, Ho-Taek (Department of Radiology and Research Institute of Radiological Science, College of Medicine, Yonsei University) ;
  • Suh, Jin-Suck (Department of Radiology and Research Institute of Radiological Science, College of Medicine, Yonsei University)
  • Published : 2011.12.01

Abstract

Objective: To investigate the correlation between quantitative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) parameters and microvascular density (MVD) in a human-colon-cancer xenograft mouse model using 3 Tesla MRI. Materials and Methods: A human-colon-cancer xenograft model was produced by subcutaneously inoculating $1{\times}10^{6}$ DLD-1 human-colon-cancer cells into the right hind limbs of 10 mice. The tumors were allowed to grow for two weeks and then assessed using MRI. DCE-MRI was performed by tail vein injection of 0.3 mmol/kg of gadolinium. A region of interest (ROI) was drawn at the midpoints along the z-axes of the tumors, and a Tofts model analysis was performed. The quantitative parameters ($K^{trans}$, $K_{ep}$ and $V_{e}$) from the whole transverse ROI and the hotspot ROI of the tumor were calculated. Immunohistochemical microvessel staining was performed and analyzed according to Weidner's criteria at the corresponding MRI sections. Additional Hematoxylin and Eosin staining was performed to evaluate tumor necrosis. The Mann-Whitney test and Spearman's rho correlation analysis were performed to prove the existence of a correlation between the quantitative parameters, necrosis, and MVD. Results: Whole transverse ROI of the tumor showed no significant relationship between the MVD values and quantitative DCE-MRI parameters. In the hotspot ROI, there was a difference in MVD between low and high group of $K^{trans}$ and $K_{ep}$ that had marginally statistical significance (ps = 0.06 and 0.07, respectively). Also, $K^{trans}$ and $K_{ep}$ were found to have an inverse relationship with MVD (r = -0.61, p = 0.06 in $K^{trans}$; r = -0.60, p = 0.07 in $K_{ep}$). Conclusion: Quantitative analysis of T1-weighted DCE-MRI using hotspot ROI may provide a better histologic match than whole transverse section ROI. Within the hotspots, $K^{trans}$ and $K_{ep}$ tend to have a reverse correlation with MVD in this colon cancer mouse model.

Keywords

References

  1. Folkman J. New perspectives in clinical oncology from angiogenesis research. Eur J Cancer 1996;32A:2534-2539
  2. Rak JW, St Croix BD, Kerbel RS. Consequences of angiogenesis for tumor progression, metastasis and cancer therapy. Anticancer Drugs 1995;6:3-18
  3. Vermeulen PB, Gasparini G, Fox SB, Toi M, Martin L, McCulloch P, et al. Quantification of angiogenesis in solid human tumours: an international consensus on the methodology and criteria of evaluation. Eur J Cancer 1996;32A:2474-2484 https://doi.org/10.1016/S0959-8049(96)00379-6
  4. Deen S, Ball RY. Basement membrane and extracellular interstitial matrix components in bladder neoplasia--evidence of angiogenesis. Histopathology 1994;25:475-481 https://doi.org/10.1111/j.1365-2559.1994.tb00010.x
  5. Nagy JA, Brown LF, Senger DR, Lanir N, Van de Water L, Dvorak AM, et al. Pathogenesis of tumor stroma generation: a critical role for leaky blood vessels and fibrin deposition. Biochim Biophys Acta 1989;948:305-326
  6. 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
  7. Hawighorst H, Knapstein PG, Weikel W, Knopp MV, Zuna I, Knof A, et al. Angiogenesis of uterine cervical carcinoma: characterization by pharmacokinetic magnetic resonance parameters and histological microvessel density with correlation to lymphatic involvement. Cancer Res 1997;57:4777-4786
  8. Hulka CA, Edmister WB, Smith BL, Tan L, Sgroi DC, Campbell T, et al. Dynamic echo-planar imaging of the breast: experience in diagnosing breast carcinoma and correlation with tumor angiogenesis. Radiology 1997;205:837-842 https://doi.org/10.1148/radiology.205.3.9393545
  9. Collins DJ, Padhani AR. Dynamic magnetic resonance imaging of tumor perfusion. Approaches and biomedical challenges. IEEE Eng Med Biol Mag 2004;23:65-83
  10. de Lussanet QG, Backes WH, Griffioen AW, Padhani AR, Baeten CI, van Baardwijk A, et al. Dynamic contrast-enhanced magnetic resonance imaging of radiation therapy-induced microcirculation changes in rectal cancer. Int J Radiat Oncol Biol Phys 2005;63:1309-1315 https://doi.org/10.1016/j.ijrobp.2005.04.052
  11. Tuncbilek N, Karakas HM, Altaner S. Dynamic MRI in indirect estimation of microvessel density, histologic grade, and prognosis in colorectal adenocarcinomas. Abdom Imaging 2004;29:166-172 https://doi.org/10.1007/s00261-003-0090-2
  12. Zhang XM, Yu D, Zhang HL, Dai Y, Bi D, Liu Z, et al. 3D dynamic contrast-enhanced MRI of rectal carcinoma at 3T: correlation with microvascular density and vascular endothelial growth factor markers of tumor angiogenesis. J Magn Reson Imaging 2008;27:1309-1316 https://doi.org/10.1002/jmri.21378
  13. Ceelen W, Smeets P, Backes W, Van Damme N, Boterberg T, Demetter P, et al. Noninvasive monitoring of radiotherapyinduced microvascular changes using dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) in a colorectal tumor model. Int J Radiat Oncol Biol Phys 2006;64:1188-1196 https://doi.org/10.1016/j.ijrobp.2005.10.026
  14. Weidner N, Semple JP, Welch WR, Folkman J. Tumor angiogenesis and metastasis--correlation in invasive breast carcinoma. N Engl J Med 1991;324:1-8 https://doi.org/10.1056/NEJM199101033240101
  15. Buadu LD, Murakami J, Murayama S, Hashiguchi N, Sakai S, Masuda K, et al. Breast lesions: correlation of contrast medium enhancement patterns on MR images with histopathologic findings and tumor angiogenesis. Radiology 1996;200:639-649 https://doi.org/10.1148/radiology.200.3.8756909
  16. 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
  17. Stomper PC, Winston JS, Herman S, Klippenstein DL, Arredondo MA, Blumenson LE. Angiogenesis and dynamic MR imaging gadolinium enhancement of malignant and benign breast lesions. Breast Cancer Res Treat 1997;45:39-46 https://doi.org/10.1023/A:1005897227030
  18. Schlemmer HP, Merkle J, Grobholz R, Jaeger T, Michel MS, Werner A, et al. Can pre-operative contrast-enhanced dynamic MR imaging for prostate cancer predict microvessel density in prostatectomy specimens? Eur Radiol 2004;14:309-317 https://doi.org/10.1007/s00330-003-2025-2
  19. Galban CJ, Chenevert TL, Meyer CR, Tsien C, Lawrence TS, Hamstra DA, et al. The parametric response map is an imaging biomarker for early cancer treatment outcome. Nat Med 2009;15:572-576 https://doi.org/10.1038/nm.1919
  20. Sahani DV, Holalkere NS, Mueller PR, Zhu AX. Advanced hepatocellular carcinoma: CT perfusion of liver and tumor tissue--initial experience. Radiology 2007;243:736-743 https://doi.org/10.1148/radiol.2433052020
  21. Choi S, Liu H, Shin TB, Lee JH, Yoon SK, Oh JY, et al. Perfusion imaging of the brain using Z-score and dynamic images obtained by subtracting images from before and after contrast injection. Korean J Radiol 2004;5:143-148 https://doi.org/10.3348/kjr.2004.5.3.143

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