• DocumentCode
    836342
  • Title

    Estimation of input function and kinetic parameters using simulated annealing: application in a flow model

  • Author

    Wong, Koon-Pong ; Meikle, Steven R. ; Feng, Dagan ; Fulham, Michael J.

  • Author_Institution
    Dept. of PET & Nucl. Medicine, R. Prince Alfred Hosp., Camperdown, NSW, Australia
  • Volume
    49
  • Issue
    3
  • fYear
    2002
  • fDate
    6/1/2002 12:00:00 AM
  • Firstpage
    707
  • Lastpage
    713
  • Abstract
    Accurate determination of the input function is essential for absolute quantification of physiological parameters in positron emission tomography and single-photon emission computed tomography imaging, but it requires an invasive and tedious procedure of blood sampling that is impractical in clinical studies. We previously proposed a technique that estimates simultaneously kinetic parameters and the input function from the tissue impulse response functions and requires two blood samples. A nonlinear least squares method estimated all the parameters in the impulse response functions and the input function but failed occasionally due to high noise levels in the data, causing an ill-conditioned cost function. This paper investigates the feasibility of applying a Monte Carlo method called simulated annealing to estimate kinetic parameters in the impulse response functions and the input function. Time-activity curves of teboroxime, which is very sensitive to changes in the input function, were simulated based on published data obtained from a canine model. The equations describing the tracer kinetics in different regions were minimized simultaneously by simulated annealing and nonlinear least squares. We found that the physiological parameters obtained with simulated annealing are accurate, and the estimated input function more closely resembled the simulated curve. We conclude that simulated annealing reduces bias in the estimation of physiological parameters and determination of the input function.
  • Keywords
    Monte Carlo methods; biological tissues; blood flow measurement; flow visualisation; least squares approximations; medical computing; nonlinear estimation; physiological models; positron emission tomography; simulated annealing; single photon emission computed tomography; Monte Carlo method; SPECT; blood sampling; canine model; flow model; ill-conditioned cost function; input function; kinetic parameters; nonlinear least squares method; physiological parameters; positron emission tomography; simulated annealing; single-photon emission computed tomography imaging; teboroxime; time-activity curves; tissue impulse response functions; tracer kinetics; Blood; Computational modeling; Computed tomography; Kinetic theory; Least squares methods; Noise level; Parameter estimation; Positron emission tomography; Sampling methods; Simulated annealing;
  • fLanguage
    English
  • Journal_Title
    Nuclear Science, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9499
  • Type

    jour

  • DOI
    10.1109/TNS.2002.1039552
  • Filename
    1039552