Academic Radiology
Volume 17, Issue 4 , Pages 468-478 , April 2010

Sensitivity of Quantitative Metrics Derived from DCE MRI and a Pharmacokinetic Model to Image Quality and Acquisition Parameters

  • Yue Cao, PhD

      Affiliations

    • Department of Radiation Oncology, University of Michigan, 519 W William Street, Argus Building 1, Ann Arbor, MI 48103
    • Department of Radiology, University of Michigan, 519 W William Street, Argus Building 1, Ann Arbor, MI 48103
    • Corresponding Author InformationAddress correspondence to: Y.C.
    • ,
  • Diana Li, MS

      Affiliations

    • Department of Nuclear Engineering and Radiological Sciences, University of Michigan, 519 W William Street, Argus Building 1, Ann Arbor, MI 48103
    • ,
  • Zhou Shen, MA

      Affiliations

    • Department of Radiation Oncology, University of Michigan, 519 W William Street, Argus Building 1, Ann Arbor, MI 48103
    • ,
  • Daniel Normolle, PhD

      Affiliations

    • Department of Radiation Oncology, University of Michigan, 519 W William Street, Argus Building 1, Ann Arbor, MI 48103

Received 27 August 2009 ,Accepted 25 October 2009.

References 

  1. Galbraith SM, Rustin GJ, Lodge MA, et al. Effects of 5,6-dimethylxanthenone-4-acetic acid on human tumor microcirculation assessed by dynamic contrast-enhanced magnetic resonance imaging. J Clin Oncol. 2002;20:3826–3840
  2. Morgan B, Thomas AL, Drevs J, et al. Dynamic contrast-enhanced magnetic resonance imaging as a biomarker for the pharmacological response of PTK787/ZK 222584, an inhibitor of the vascular endothelial growth factor receptor tyrosine kinases, in patients with advanced colorectal cancer and liver metastases: results from two phase I studies. J Clin Oncol. 2003;21:3955–3964
  3. Rugo HS, Herbst RS, Liu G, et al. Phase I trial of the oral antiangiogenesis agent AG-013736 in patients with advanced solid tumors: pharmacokinetic and clinical results. J Clin Oncol. 2005;23:5474–5483
  4. Sorensen AG, Batchelor TT, Zhang WT, et al. A “vascular normalization index” as potential mechanistic biomarker to predict survival after a single dose of cediranib in recurrent glioblastoma patients. Cancer Res. 2009;69:5296–5300
  5. Cao Y, Popovtzer A, Li D, et al. Early prediction of outcome in advanced head-and-neck cancer based on tumor blood volume alterations during therapy: a prospective study. Int J Radiat Oncol Biol Phys. 2008;72:1287–1290
  6. Cao Y, Tsien CI, Sundgren P, et al. DCE MRI as a biomarker for prediction of radiation-induced neurocognitive dysfunction. Clin Cancer Res. 2009;15:1747–1754
  7. Henderson E, Rutt BK, Lee TY. Temporal sampling requirements for the tracer kinetics modeling of breast disease. Magn Reson Imaging. 1998;16:1057–1073
  8. Calamante F, Gadian DG, Connelly A. Delay and dispersion effects in dynamic susceptibility contrast MRI: simulations using singular value decomposition. Magn Reson Med. 2000;44:466–473
  9. Cheng HL. Investigation and optimization of parameter accuracy in dynamic contrast-enhanced MRI. J Magn Reson Imaging. 2008;28:736–743
  10. Peeters F, Annet L, Hermoye L, Van Beers BE. Inflow correction of hepatic perfusion measurements using T1-weighted, fast gradient-echo, contrast-enhanced MRI. Magn Reson Med. 2004;51:710–717
  11. Singh A, Rathore RK, Haris M, et al. Improved bolus arrival time and arterial input function estimation for tracer kinetic analysis in DCE-MRI. J Magn Reson Imaging. 2009;29:166–176
  12. Jackson A, Jayson GC, Li KL, et al. Reproducibility of quantitative dynamic contrast-enhanced MRI in newly presenting glioma. Br J Radiol. 2003;76:153–162
  13. Galbraith SM, Lodge MA, Taylor NJ, et al. Reproducibility of dynamic contrast-enhanced MRI in human muscle and tumours: comparison of quantitative and semi-quantitative analysis. NMR Biomed. 2002;15:132–142
  14. Padhani AR, Hayes C, Landau S, et al. Reproducibility of quantitative dynamic MRI of normal human tissues. NMR Biomed. 2002;15:143–153
  15. Yang C, Karczmar GS, Medved M, et al. Reproducibility assessment of a multiple reference tissue method for quantitative dynamic contrast enhanced-MRI analysis. Magn Reson Med. 2009;61:851–859
  16. Lopata RG, Backes WH, van den Bosch PP, et al. On the identifiability of pharmacokinetic parameters in dynamic contrast-enhanced imaging. Magn Reson Med. 2007;58:425–429
  17. Tofts PS, Brix G, Buckley DL, 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
  18. Ewing JR, Knight RA, Nagaraja TN, et al. Patlak plots of Gd-DTPA MRI data yield blood-brain transfer constants concordant with those of 14C-sucrose in areas of blood-brain opening. Magn Reson in Med. 2003;50:283–292
  19. Cao Y. Development of Image Software Tools for Radiation Therapy Assessment. Medical Physics. 2005;32:2136

 Supported in part by 3 PO1 CA59827, RO1 NS064973, R21 CA113699, and R21 CA126137.

PII: S1076-6332(09)00593-5

doi: 10.1016/j.acra.2009.10.021

Academic Radiology
Volume 17, Issue 4 , Pages 468-478 , April 2010

Article Tools

* Image Usage & Resolution