Ceelen, Wim

De Naeyer, Dieter

Segers, Patrick

Verdonck, Pascal

English

Ghent University Academic Bibliography

Belgian Day on Biomedical Engineering November 26, 2010ESTIMATORS FOR KINETIC MODELING OF DYNAMICCONTRAST-ENHANCED MAGNETIC RESONANCE DATAFROM SPOILED GRADIENT ECHO PULSE SEQUENCESD. De Naeyer1, W. Ceelen2, P. Segers1, P. Verdonck11Ghent University, IBiTech, Belgium2Ghent University Hospital, Department of Surgery, BelgiumAbstractIn this work, the influence of the estimator was investigated on the accuracy and reproducibility of kinetic modeling of dynamic contrast enhanced MRI (DCE-MRI) data from spoiled gradient echo pulse sequences (SPGRE). The commonly used least square (LSQ) estimator was compared with a LSQ and a maximum likelihood estimator (MLM) both corrected for concentration bias. It was shown that the MLM estimator can reduce the kinetic parameter bias up to a factor 28, and decrease the width of its confidence interval with 12%. Keyword: modeling of physiological systems 1 IntroductionKinetic modeling of DCE-MRI data is increasingly used in tumor diagnosis, in the evaluation of novel anti-angiogenic therapies or for the monitoring of tumor response to treatment. The Tofts model describes the extravasation of contrast agent (CA)from the plasma to the tumor as a function of the extracellular extravascular space fraction ve and the transendothelial transfer constant Ktrans')'(exp)'()(0 !"#$%&''()tetransptranst dtttKtCKtC*:When the arterial input function (Cp) is known, Ktransand ve are fitted from the MR-measured concentration curve C t. Several studies have shown  a strong positive correlation between Ktransandphysiological properties as permeability and perfusion, or a significant reduction of Ktrans2 Methodsafter successful therapy. However, the technique suffers from low accuracy and weak reproducibility of these transfer constants estimates. This work investigates the influence of the estimator on the accuracy and the reproducibility of the kinetic parameters, fitted from DCE-MRI data from SGPRE pulse sequences.Due to the non-linearity between the CA concentration and the SPGRE signal intensity,SPGRE-measured concentration data are biased and heteroskedastic. Therefore we have compared 3 estimators: the commonly used LSQ estimator (LSQ1), a LSQ estimator with a correction for the bias (LSQ2), and a MLM estimator with a correction for the bias (MLM1). The concentration bias correction was calculated from a taylor expansion of the SPGRE equation. Simulations were performed in Matlab, to compare these estimators for theirkinetic parameter bias and their uncertainty (linearly related to the width of the confidence interval).3 ResultsKtrans[min-1/ v]eBias in KtransBias in v[%] eLSQ1[%]LSQ2 MLM LSQ1 LSQ2 MLM0.03/0.3 3.5 0.5 0.7 4.8 1.7 1.60.03/0.5 2.8 0.2 0.1 5.5 3.6 4.21.2/0.3 2.1 0.6 0.6 1.7 0.2 0.21.2/0.5 2.4 0.7 0.7 1.5 0.2 0.2Ktrans[min-1]/ veKtransv-uncertainty[%]eLSQ1-uncertainty[%]LSQ2 MLM LSQ1 LSQ2 MLM0.03/0.3 10.4 10.3 10.3 11.1 11.1 11.10.03/0.5 8.7 8.6 8.6 16.4 16.4 16.41.2/0.3 16.6 16.3 14.8 3.2 3.2 3.01.2/0.5 13.9 13.6 12.4 2.3 2.3 2.2The bias correction reduces Ktrans-bias with a factor 3 up to 28 and the ve-bias with a factor 1.5 to 8.5. Regarding uncertainty, the MLM performs better than the LSQ estimators and reduces the width of the confidence intervals of high Ktrans4 Conclusionup to 12%.  The accuracy and the reproducibility of kinetic parameter estimates, fitted from DCE-MRI data from SPGRE pulse sequences, can be significantly increased by using maximum likelihood estimators, with a correction for concentration bias. 

Estimators for kinetic modeling of dynamic contrast-enhanced magnetic rensonance data from spoiled gradient echo pulse sequences

https://biblio.ugent.be/publication/1851055/file/1851057

Estimators for kinetic modeling of dynamic contrast-enhanced magnetic rensonance data from spoiled gradient echo pulse sequences

Abstract

Similar works

Full text

Available Versions

Ghent University Academic Bibliography