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European Radiology

, Volume 20, Issue 9, pp 2166–2175 | Cite as

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

  • Gunnar Brix
  • Stefan Zwick
  • Jürgen Griebel
  • Christian Fink
  • Fabian Kiessling
Experimental

Abstract

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.

Keywords

Dynamic-contrast-enhanced imaging Steepest slope method Tissue perfusion Microcirculation Tracer kinetic modelling CT MRI 

Notes

Acknowledgement

This work as supported in part by the German ‘Competence Alliance on Radiation Research’ (BMBF 03NUK008F)

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Copyright information

© European Society of Radiology 2010

Authors and Affiliations

  • Gunnar Brix
    • 1
    • 6
  • Stefan Zwick
    • 2
    • 3
  • Jürgen Griebel
    • 1
  • Christian Fink
    • 4
  • Fabian Kiessling
    • 5
  1. 1.Department of Medical and Occupational Radiation ProtectionFederal Office for Radiation ProtectionOberschleissheimGermany
  2. 2.Department of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ)HeidelbergGermany
  3. 3.Department of Radiology, Medical PhysicsUniversity Hospital FreiburgFreiburgGermany
  4. 4.Institute of Clinical Radiology and Nuclear MedicineUniversity Medical Center Mannheim, University of HeidelbergMannheimGermany
  5. 5.Department of Experimental Molecular ImagingRWTH-Aachen UniversityAachenGermany
  6. 6.Abteilung für medizinischen und beruflichen StrahlenschutzBundesamt für StrahlenschutzOberschleissheimGermany

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