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Title page for ETD etd-11282012-152629


Type of Document Master's Thesis
Author Hormuth, David Andrew II
Author's Email Address david.a.hormuth@vanderbilt.edu
URN etd-11282012-152629
Title A comparison of individual and population-derived vascular input functions for quantitative DCE-MRI in rats
Degree Master of Science
Department Biomedical Engineering
Advisory Committee
Advisor Name Title
Thomas E. Yankeelov Committee Chair
Mark D. Does Committee Member
Keywords
  • Cancer
  • Imaging
  • DCE-MRI
  • MRI
Date of Defense 2012-11-28
Availability unrestricted
Abstract
Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is a method that can be used to quantitatively and qualitatively assess physiological characteristics of tissue. Quantitative DCE-MRI requires an estimate of the time rate of change of the concentration of the contrast agent in the blood plasma; the so-called vascular input function, or VIF. Measuring the VIF is notoriously difficult as it requires high temporal resolution images limiting the achievable number of slices, field-of-view, spatial resolution, and signal-to-noise. Alternatively, a population-averaged VIF could be used to mitigate the acquisition demands in studies aimed to investigate, for example, tumor vascular characteristics. Eight rats inoculated with C6 glioma cells underwent DCE-MRI at 9.4T. A set of dynamic spoiled gradient-echo images was acquired before, during, and after a bolus injection of Gd-DTPA (Magnevist, Wayne, NJ). Pharmacokinetic parameters (Ktrans, ve, and vp) were extracted from signal-time curves of tumor tissue using both individual and population-averaged VIFs. Standard model voxel values of Ktrans and ve estimated using a population-averaged VIF have a high correlation (concordance correlation coefficient > 0.7852) and a strong linear relationship (Pearson correlation coefficient > 0.9802) with Ktrans and ve values estimated using an individual VIF. Additionally, the extended model voxel values of Ktrans, ve, and vp also showed a high correlation (concordance correlation coefficient > 0.6931) and a strong linear relationship (Pearson correlation coefficient > 0.9159) supporting the use of a population based VIF in DCE-MRI.
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