Estimation of tissue perfusion by dynamic contrast-enhanced imaging: simulation-based evaluation of the steepest slope method.

Objective: Tissue perfusion is frequently determined from dynamic contrast-enhanced CT or MRI image series by means of the steepest slope method. It was thus the aim of this study to systematically evaluate the reliability of this analysis method on the basis of simulated tissue curves.Methods: 9600...

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Publicado en:European Radiology Vol. 20; no. 9; pp. 2166 - 2176
Autores principales: Brix G, Zwick S, Griebel J, Fink C, Kiessling F, Brix, Gunnar, Zwick, Stefan, Griebel, Jürgen, Fink, Christian, Kiessling, Fabian
Formato: research Journal Article
Publicado: Springer Nature Sep2010
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Springer Nature
      place: New York, New York
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        atl: Estimation of tissue perfusion by dynamic contrast-enhanced imaging: simulation-based evaluation of the steepest slope method.
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        au:
          Brix G
          Zwick S
          Griebel J
          Fink C
          Kiessling F
          Brix, Gunnar
          Zwick, Stefan
          Griebel, Jürgen
          Fink, Christian
          Kiessling, Fabian
        affil: Department of Medical and Occupational Radiation Protection, Federal Office for Radiation Protection, Oberschleissheim, Germany
      sug:
        subj:
          Algorithms
          Contrast Media Pharmacokinetics
          Magnetic Resonance Imaging Methods
          Image Interpretation, Computer Assisted Methods
          Magnetic Resonance Angiography Methods
          Models, Biological
          Computer Simulation
          Human
          Reproducibility of Results
          Sensitivity and Specificity
      ab: Objective: Tissue perfusion is frequently determined from dynamic contrast-enhanced CT or MRI image series by means of the steepest slope method. It was thus the aim of this study to systematically evaluate the reliability of this analysis method on the basis of simulated tissue curves.Methods: 9600 tissue curves were simulated for four noise levels, three sampling intervals and a wide range of physiological parameters using an axially distributed reference model and subsequently analysed by the steepest slope method.Results: Perfusion is systematically underestimated with errors becoming larger with increasing perfusion and decreasing intravascular volume. For curves sampled after rapid contrast injection with a temporal resolution of 0.72 s, the bias was less than 23% when the mean residence time of tracer molecules in the intravascular distribution space was greater than 6 s. Increasing the sampling interval and the noise level substantially reduces the accuracy and precision of estimates, respectively.Conclusions: The steepest slope method allows absolute quantification of tissue perfusion in a computationally simple and numerically robust manner. The achievable degree of accuracy and precision is considered to be adequate for most clinical applications.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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