Bayesian modeling of Dynamic Contrast Enhanced MRI data in cerebral glioma patients improves the diagnostic quality of hemodynamic parameter maps

Tietze A, Nielsen A, Klærke Mikkelsen I, et al. PLoS One. 2018;13(9):e0202906



The purpose of this work is to investigate if the curve-fitting algorithm in Dynamic Contrast-Enhanced (DCE) MRI experiments influences the diagnostic quality of calculated parameter maps.


The Bayesian method has the potential to increase the diagnostic reliability of Dynamic Contrast-Enhanced parameter maps in brain tumors. In our data, images based on the 2-compartment-exchange model were superior to those based on the extended Toft’s model.

Read the full article here doi:10.1371/journal.pone.0202906

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