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Contributions to quantitative dynamic contrast-enhanced MRI
Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
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.
Series
Umeå University medical dissertations, ISSN 0346-6612 ; 1457
Keyword [en]
Dynamic contrast-enhanced MRI, quantitative imaging, parameter estimation, uncertainty estimation, arterial input function
National Category
Medical Image Processing
Research subject
radiofysik
Identifiers
URN: urn:nbn:se:umu:diva-49773ISBN: 978-91-7459-313-6 (print)OAI: oai:DiVA.org:umu-49773DiVA: diva2:457450
Public defence
2011-12-10, Bergasalen, byggnad 27, Norrlands universitetssjukhus, Umeå, 10:00 (English)
Opponent
Supervisors
Available from: 2011-11-18 Created: 2011-11-17 Last updated: 2011-11-22Bibliographically approved
List of papers
1. A novel estimation method for physiological parameters in dynamic contrast-enhanced MRI: application of a distributed parameter model using Fourier-domain calculations
Open this publication in new window or tab >>A novel estimation method for physiological parameters in dynamic contrast-enhanced MRI: application of a distributed parameter model using Fourier-domain calculations
2009 (English)In: IEEE Transactions on Medical Imaging, ISSN 0278-0062, E-ISSN 1558-254X, Vol. 28, no 9, 1375-1383 p.Article in journal (Refereed) Published
Abstract [en]

Dynamic contrast-enhanced magnetic resonance imaging (MRI) is a promising tool in the evaluation of tumor physiology. From rapidly acquired images and a model for contrast agent pharmacokinetics, physiological parameters are derived. One pharmacokinetic model, the tissue homogeneity model, enables estimation of both blood flow and vessel permeability together with parameters that describe blood volume and extracellular extravascular volume fraction. However, studies have shown that parameter estimation with this model is unstable. Therefore, several initial guesses are needed for accurate estimates, which makes the estimation slow. In this study a new estimation algorithm for the tissue homogeneity model, based on Fourier domain calculations, was derived and implemented as a Matlab program. The algorithm was tested with Monte-Carlo simulations and the results were compared to an existing method that uses the adiabatic approximation. The algorithm was also tested on data from a metastasis in the brain. The comparison showed that the new algorithm gave more accurate results on the 2.5th and 97.5th percentile levels, for instance the error in blood volume was reduced by 21%. In addition, the time needed for the computations was reduced with a factor 25. It was concluded that the new algorithm can be used to speed up parameter estimation while accuracy can be gained at the same time.

Keyword
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), parameter estimation, tissue homogeneity models, tracer kinetics
National Category
Medical Image Processing
Identifiers
urn:nbn:se:umu:diva-25803 (URN)10.1109/TMI.2009.2016212 (DOI)19278930 (PubMedID)
Available from: 2009-09-03 Created: 2009-09-03 Last updated: 2011-11-18Bibliographically approved
2. Effects of inflow and radiofrequency spoiling on the arterial input function in dynamic contrast-enhanced MRI: a combined phantom and simulation study
Open this publication in new window or tab >>Effects of inflow and radiofrequency spoiling on the arterial input function in dynamic contrast-enhanced MRI: a combined phantom and simulation study
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
Keyword
dynamic contrast-enhanced MRI, arterial input function, blood flow effects, RF spoiling
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:umu:diva-40860 (URN)10.1002/mrm.22760 (DOI)21305599 (PubMedID)
Available from: 2011-03-11 Created: 2011-03-11 Last updated: 2017-12-11Bibliographically approved
3. Phase-based arterial input functions in humans applied to dynamic contrast-enhanced MRI: potential usefulness and limitations
Open this publication in new window or tab >>Phase-based arterial input functions in humans applied to dynamic contrast-enhanced MRI: potential usefulness and limitations
Show others...
2011 (English)In: Magnetic Resonance Materials in Physics, Biology and Medicine, ISSN 0968-5243, E-ISSN 1352-8661, Vol. 24, no 4, 233-245 p.Article in journal (Refereed) Published
Abstract [en]

Object: Phase-based arterial input functions (AIFs) provide a promising alternative to standard magnitude-based AIFs, for example, because inflow effects are avoided. The usefulness of phase-based AIFs in clinical dynamic contrast-enhanced MRI (DCE-MRI) was investigated, and relevant pitfalls and sources of uncertainty were identified.

Materials and methods: AIFs were registered from eight human subjects on, in total, 21 occasions. AIF quality was evaluated by comparing AIFs from right and left internal carotid arteries and by assessing the reliability of blood plasma volume estimates.

Results: Phase-based AIFs yielded an average bolus peak of 3.9 mM and a residual concentration of 0.37 mM after 3 min, (0.033 mmol/kg contrast agent injection). The average blood plasma volume was 2.7% when using the AIF peak in the estimation, but was significantly different (p < 0.0001) and less physiologically reasonable when based on the AIF tail concentration. Motion-induced phase shifts and accumulation of contrast agent in background tissue regions were identified as main sources of uncertainty.

Conclusions: Phase-based AIFs are a feasible alternative to magnitude AIFs, but sources of errors exist, making quantification difficult, especially of the AIF tail. Improvement of the technique is feasible and also required for the phase-based AIF approach to reach its full potential.

Place, publisher, year, edition, pages
Springer, 2011
Keyword
Dynamic contrast-enhanced MRI, Arterial input function, Phase quantification
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:umu:diva-44372 (URN)10.1007/s10334-011-0257-8 (DOI)000295178100005 ()21626278 (PubMedID)
Available from: 2011-06-01 Created: 2011-06-01 Last updated: 2017-12-11Bibliographically approved
4. Uncertainty estimation in dynamic contrast-enhanced MRI
Open this publication in new window or tab >>Uncertainty estimation in dynamic contrast-enhanced MRI
Show others...
2013 (English)In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 69, no 4, 992-1002 p.Article in journal (Refereed) Published
Abstract [en]

Using dynamic contrast-enhanced MRI (DCE-MRI), it is possible to estimate pharmacokinetic (PK) parameters that convey information about physiological properties, e.g., in tumors. In DCE-MRI, errors propagate in a nontrivial way to the PK parameters. We propose a method based on multivariate linear error propagation to calculate uncertainty maps for the PK parameters. Uncertainties in the PK parameters were investigated for the modified Kety model. The method was evaluated with Monte Carlo simulations and exemplified with in vivo brain tumor data. PK parameter uncertainties due to noise in dynamic data were accurately estimated. Noise with standard deviation up to 15% in the baseline signal and the baseline T1 map gave estimated uncertainties in good agreement with the Monte Carlo simulations. Good agreement was also found for up to 15% errors in the arterial input function amplitude. The method was less accurate for errors in the bolus arrival time with disagreements of 23%, 32%, and 29% for Ktrans, ve, and vp, respectively, when the standard deviation of the bolus arrival time error was 5.3 s. In conclusion, the proposed method provides efficient means for calculation of uncertainty maps, and it was applicable to a wide range of sources of uncertainty.

Place, publisher, year, edition, pages
Wiley-Blackwell, 2013
Keyword
Uncertainty estimation, dynamic contrast-enhanced-MRI, precision analysis, accuracy
National Category
Medical Image Processing Probability Theory and Statistics
Research subject
radiofysik
Identifiers
urn:nbn:se:umu:diva-49758 (URN)10.1002/mrm.24328 (DOI)000316629300013 ()
Available from: 2011-11-17 Created: 2011-11-17 Last updated: 2017-12-08Bibliographically approved

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