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Effects of inflow and radiofrequency spoiling on the arterial input function in dynamic contrast-enhanced MRI: a combined phantom and simulation study
Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
2011 (English)In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 65, no 6, 1670-1679 p.Article in journal (Refereed) Published
Abstract [en]

The arterial input function is crucial in pharmacokinetic analysis of dynamic contrast-enhanced MRI data. Among other artifacts in arterial input function quantification, the blood inflow effect and nonideal radiofrequency spoiling can induce large measurement errors with subsequent reduction of accuracy in the pharmacokinetic parameters. These errors were investigated for a 3D spoiled gradient-echo sequence using a pulsatile flow phantom and a total of 144 typical imaging settings. In the presence of large inflow effects, results showed poor average accuracy and large spread between imaging settings, when the standard spoiled gradient-echo signal equation was used in the analysis. For example, one of the investigated inflow conditions resulted in a mean error of about 40% and a spread, given by the coefficient of variation, of 20% for K(trans) . Minimizing inflow effects by appropriate slice placement, combined with compensation for nonideal radiofrequency spoiling, significantly improved the results, but they remained poorer than without flow (e.g., 3-4 times larger coefficient of variation for K(trans) ). It was concluded that the 3D spoiled gradient-echo sequence is not optimal for accurate arterial input function quantification and that correction for nonideal radiofrequency spoiling in combination with inflow minimizing slice placement should be used to reduce the errors. Magn Reson Med, 2011. © 2011 Wiley-Liss, Inc.

Place, publisher, year, edition, pages
Wiley , 2011. Vol. 65, no 6, 1670-1679 p.
Keyword [en]
dynamic contrast-enhanced MRI, arterial input function, blood flow effects, RF spoiling
National Category
Radiology, Nuclear Medicine and Medical Imaging
URN: urn:nbn:se:umu:diva-40860DOI: 10.1002/mrm.22760PubMedID: 21305599OAI: diva2:403241
Available from: 2011-03-11 Created: 2011-03-11 Last updated: 2012-05-28Bibliographically approved
In thesis
1. Contributions to quantitative dynamic contrast-enhanced MRI
Open this publication in new window or tab >>Contributions to quantitative dynamic contrast-enhanced MRI
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Background: Dynamic contrast-enhanced MRI (DCE-MRI) has the potential to produce images of physiological quantities such as blood flow, blood vessel volume fraction, and blood vessel permeability. Such information is highly valuable, e.g., in oncology. The focus of this work was to improve the quantitative aspects of DCE-MRI in terms of better understanding of error sources and their effect on estimated physiological quantities.

Methods: Firstly, a novel parameter estimation algorithm was developed to overcome a problem with sensitivity to the initial guess in parameter estimation with a specific pharmacokinetic model. Secondly, the accuracy of the arterial input function (AIF), i.e., the estimated arterial blood contrast agent concentration, was evaluated in a phantom environment for a standard magnitude-based AIF method commonly used in vivo. The accuracy was also evaluated in vivo for a phase-based method that has previously shown very promising results in phantoms and in animal studies. Finally, a method was developed for estimation of uncertainties in the estimated physiological quantities.

Results: The new parameter estimation algorithm enabled significantly faster parameter estimation, thus making it more feasible to obtain blood flow and permeability maps from a DCE-MRI study. The evaluation of the AIF measurements revealed that inflow effects and non-ideal radiofrequency spoiling seriously degrade magnitude-based AIFs and that proper slice placement and improved signal models can reduce this effect. It was also shown that phase-based AIFs can be a feasible alternative provided that the observed difficulties in quantifying low concentrations can be resolved. The uncertainty estimation method was able to accurately quantify how a variety of different errors propagate to uncertainty in the estimated physiological quantities.

Conclusion: This work contributes to a better understanding of parameter estimation and AIF quantification in DCE-MRI. The proposed uncertainty estimation method can be used to efficiently calculate uncertainties in the parametric maps obtained in DCE-MRI.

Place, publisher, year, edition, pages
Umeå: Umeå Universitet, 2011. 108 p.
Umeå University medical dissertations, ISSN 0346-6612 ; 1457
Dynamic contrast-enhanced MRI, quantitative imaging, parameter estimation, uncertainty estimation, arterial input function
National Category
Medical Image Processing
Research subject
urn:nbn:se:umu:diva-49773 (URN)978-91-7459-313-6 (ISBN)
Public defence
2011-12-10, Bergasalen, byggnad 27, Norrlands universitetssjukhus, Umeå, 10:00 (English)
Available from: 2011-11-18 Created: 2011-11-17 Last updated: 2011-11-22Bibliographically approved

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