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Uncertainty estimation in dynamic contrast-enhanced MRI
Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
Sveriges lantbruksuniversitet, Centre of Biostochastiscs.
Lunds universitet, Medicinsk strålningsfysik.
Visa övriga samt affilieringar
2013 (Engelska)Ingår i: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 69, nr 4, s. 992-1002Artikel i tidskrift (Refereegranskat) 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.

Ort, förlag, år, upplaga, sidor
Wiley-Blackwell, 2013. Vol. 69, nr 4, s. 992-1002
Nyckelord [en]
Uncertainty estimation, dynamic contrast-enhanced-MRI, precision analysis, accuracy
Nationell ämneskategori
Medicinsk bildbehandling Sannolikhetsteori och statistik
Forskningsämne
radiofysik
Identifikatorer
URN: urn:nbn:se:umu:diva-49758DOI: 10.1002/mrm.24328ISI: 000316629300013OAI: oai:DiVA.org:umu-49758DiVA, id: diva2:457242
Tillgänglig från: 2011-11-17 Skapad: 2011-11-17 Senast uppdaterad: 2018-06-08Bibliografiskt granskad
Ingår i avhandling
1. Contributions to quantitative dynamic contrast-enhanced MRI
Öppna denna publikation i ny flik eller fönster >>Contributions to quantitative dynamic contrast-enhanced MRI
2011 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
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.

Ort, förlag, år, upplaga, sidor
Umeå: Umeå Universitet, 2011. s. 108
Serie
Umeå University medical dissertations, ISSN 0346-6612 ; 1457
Nyckelord
Dynamic contrast-enhanced MRI, quantitative imaging, parameter estimation, uncertainty estimation, arterial input function
Nationell ämneskategori
Medicinsk bildbehandling
Forskningsämne
radiofysik
Identifikatorer
urn:nbn:se:umu:diva-49773 (URN)978-91-7459-313-6 (ISBN)
Disputation
2011-12-10, Bergasalen, byggnad 27, Norrlands universitetssjukhus, Umeå, 10:00 (Engelska)
Opponent
Handledare
Tillgänglig från: 2011-11-18 Skapad: 2011-11-17 Senast uppdaterad: 2018-06-08Bibliografiskt granskad

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