Precision analysis of kinetic modelling estimates in dynamic contrast enhanced MRI

Naeyer, Dieter De; Deene, Yves De; Ceelen, Wim; Segers, Patrick; Verdonck, Pascal

doi:10.1007/s10334-010-0235-6

Cited by 18 publications

(24 citation statements)

References 42 publications

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“…This is in line with what was reported by [29]: the standard deviation of the contrast agent concentration distribution vary with the concentration.…”

Section: Discussionsupporting

confidence: 81%

Accuracy of Contrast Agent Quantification in MRI: A Comparison Between Two k-space Sampling Schemes

2015

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Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) plays an important role in many applications, such as perfusion imaging in oncology. Several aspects of data acquisition should be taken into account when developing protocols for DCE MRI both to facilitate integration of results from multiple institutions and to ensure that the data reflect the underlying physiology as accurately as possible.In this study we focused on the trade-off between accurate contrast agent (CA) quantification ad temporal resolution. The commonly used spoiled gradient-echo k-space scheme known as Fast Low Angle SHot (FLASH) can suffer from low temporal resolution if a large field of view must be scanned. Recently, a k-space under-sampling and data-sharing method known as Time-resolved angiography With Stochastic Trajectories (TWIST) has been proposed to obtain high temporal resolution without sacrificing the spatial resolution. However, the losses in CA quantification have not been analyzed yet.The aim of this study was to evaluate the accuracy of TWIST CA quantification with respect to FLASH.Seven vials containing different Gd-DTPA solutions were prepared. Images were acquired using breast coils and several combinations of the different parameters of the two schemes analyzed. Quantification accuracy has been evaluated in terms of relative error and standard deviation. Also the repeatability for both sequence was evaluated on ten measures.The accuracy of CA quantification with both sequences depends on the specific amount of Gd-DTPA present in the prepared solutions.However, our results show that FLASH and TWIST give comparable accurac

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“…This is in line with what was reported by [29]: the standard deviation of the contrast agent concentration distribution vary with the concentration.…”

Section: Discussionsupporting

confidence: 81%

Accuracy of Contrast Agent Quantification in MRI: A Comparison Between Two k-space Sampling Schemes

2015

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“…The reproducibility of Tofts' model parameters was studied, among others, by Galbraith et al [41]. The uncertainty in the measurement of the AIF as a function of the temporal sampling was addressed by Henderson et al [26]; the effect of uncertainty due to noise was investigated by de Naeyer et al [23]. Port et al and Walker-Samuel et al investigated the effect of AIF variability [9,42].…”

Section: Comparison With the Literaturementioning

confidence: 98%

“…Previous work has already been published in which the propagation of errors in PKM was addressed [9,[23][24][25][26][27][28][29][30]. These studies either concentrate on the error generated on the PMPs by measurement limitations such as noise [24] or insufficient temporal sampling [26,27], or focus on only one of the two PKM inputs (either AIF [9] or tissue concentration [24,25,28]).…”

Section: Introductionmentioning

confidence: 99%

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Simulating the effect of input errors on the accuracy of Tofts’ pharmacokinetic model parameters

Lavini

2015

Magnetic Resonance Imaging

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“…The a priori identifiability is influenced by the nonlinear model structure itself and by the experimental design – sampling and duration of the experiment . The a posteriori identifiability includes the errors in the measurement – the signal‐to‐noise ratio, arterial input function errors, and the inaccuracy of conversion from the T1‐weighted image sequence to the concentration‐time curves . Additionally, the local minima may also be caused by an improper discretization of the model …”

Section: Introductionmentioning

confidence: 99%

Spatially regularized estimation of the tissue homogeneity model parameters in DCE‐MRI using proximal minimization

Bartoš

Rajmic

Šorel

et al. 2019

Magnetic Resonance in Med

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Purpose The Tofts and the extended Tofts models are the pharmacokinetic models commonly used in dynamic contrast‐enhanced MRI (DCE‐MRI) perfusion analysis, although they do not provide two important biological markers, namely, the plasma flow and the permeability‐surface area product. Estimates of such markers are possible using advanced pharmacokinetic models describing the vascular distribution phase, such as the tissue homogeneity model. However, the disadvantage of the advanced models lies in biased and uncertain estimates, especially when the estimates are computed voxelwise. The goal of this work is to improve the reliability of the estimates by including information from neighboring voxels. Theory and Methods Information from the neighboring voxels is incorporated in the estimation process through spatial regularization in the form of total variation. The spatial regularization is applied on five maps of perfusion parameters estimated using the tissue homogeneity model. Since the total variation is not differentiable, two proximal techniques of convex optimization are used to solve the problem numerically. Results The proposed algorithm helps to reduce noise in the estimated perfusion‐parameter maps together with improving accuracy of the estimates. These conclusions are proved using a numerical phantom. In addition, experiments on real data show improved spatial consistency and readability of perfusion maps without considerable lowering of the quality of fit. Conclusion The reliability of the DCE‐MRI perfusion analysis using the tissue homogeneity model can be improved by employing spatial regularization. The proposed utilization of modern optimization techniques implies only slightly higher computational costs compared to the standard approach without spatial regularization.

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Precision analysis of kinetic modelling estimates in dynamic contrast enhanced MRI

Abstract: CRLB provide a golden standard to construct 95% confidence intervals, which can be used to perform protocol optimization and to test the statistical significance of K (trans)-changes in treatment evaluation.

Cited by 18 publications

References 42 publications

Accuracy of Contrast Agent Quantification in MRI: A Comparison Between Two k-space Sampling Schemes

Accuracy of Contrast Agent Quantification in MRI: A Comparison Between Two k-space Sampling Schemes

Simulating the effect of input errors on the accuracy of Tofts’ pharmacokinetic model parameters

Spatially regularized estimation of the tissue homogeneity model parameters in DCE‐MRI using proximal minimization

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