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Statistical Analysis of Pharmacokinetic Models in Dynamic Contrast-Enhanced Magnetic Resonance Imaging

  • Volker J. Schmid
  • Brandon J. Whitcher
  • Guang-Zhong Yang
  • N. Jane Taylor
  • Anwar R. Padhani
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3750)

Abstract

This paper assesses the estimation of kinetic parameters from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Asymptotic results from likelihood-based nonlinear regression are compared with results derived from the posterior distribution using Bayesian estimation, along with the output from an established software package (MRIW). By using the estimated error from kinetic parameters, it is possible to produce more accurate clinical statistics, such as tumor size, for patients with breast tumors. Further analysis has also shown that Bayesian methods are more accurate and do not suffer from convergence problems, but at a higher computational cost.

Keywords

Posterior Distribution Gadolinium Concentration Extracellular Extravascular Space Proton Density Weighted Image Prior Probability Density Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Volker J. Schmid
    • 1
  • Brandon J. Whitcher
    • 2
  • Guang-Zhong Yang
    • 1
  • N. Jane Taylor
    • 3
  • Anwar R. Padhani
    • 3
  1. 1.Institute for Biomedical EngineeringImperial CollegeSouth Kensington, LondonUnited Kingdom
  2. 2.Translational Medicine & Genetics, GlaxoSmithKlineGreenfordUnited Kingdom
  3. 3.Paul Strickland Scanner CentreMount Vernon HospitalNorthwoodUnited Kingdom

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