Error estimation for perfusion parameters obtained using the two-compartment exchange model in dynamic contrast-enhanced MRI: a simulation study

Abstract

In theory, the application of the two-compartment exchange model (2CXM) to data from a dynamic contrast-enhanced (DCE) MRI exam allows the estimation of the plasma flow, plasma volume, extraction flow and extravascular-extracellular volume. The aim of this paper was to explore whether simulations based on the 2CXM could provide useful information on the trustworthiness of the results. The deviations from the input values of the haemodynamic quantities were estimated for a 'reference tissue' with a clear bi-phasic response and four 'limit tissues' with more challenging 2CXM fitting properties. The impact of the instrumental factors sampling step (T(s)), acquisition window (T(acq)) and contrast-to-noise ratio (CNR) was investigated. Each factor was varied separately, while keeping the other ones at a value above concern. Measurement guidelines to ensure that all deviations fell within a predefined range (±20%) could not be derived, but simulations for fixed T(s) and T(acq) were found to provide a practical tool for studying the error behaviour to be expected from a given experimental set-up and for comparing measurement protocols. At the level of an individual DCE exam, a bootstrap version of the simulation approach was shown to lead to a useful estimate of the errors on the fitted parameters.

The prognostic value of dynamic contrast-enhanced MRI contrast agent transfer constant Ktrans in cervical cancer is explained by plasma flow rather than vessel permeability

“…Plasma volume fraction was not prognostic despite a positive correlation with F p (Pearson r =0.6, data not shown). Simulation data from Luypaert et al (2010) suggests 2CXM estimates of v p are less precise than F p , which would explain reduced prognostic ability if effects of F p and v p on survival are similar.…”

Accelerated Brain DCE-MRI Using Iterative Reconstruction With Total Generalized Variation Penalty for Quantitative Pharmacokinetic Analysis: A Feasibility Study

“…The noise content of the CA concentration curve has been quantified as contrast-to-noise ratio (CNR) that is the ratio of maximum peak to the standard deviation of Gaussian random noise. 79 The reported CNR value of CA concentration curves ranged from 4 to 20. 64,80 In earlier studies, polynomial filters have been used in the model-free DCE-MRI analysis.…”

Simulation study of the effect of golden-angle KWIC with generalized kinetic model analysis on diagnostic accuracy for lesion discrimination

“…There exist many alternative approaches to DCE-MRI pharmacokinetic modeling, including more complicated pharmacokinetic models [26,27,28,29,30,31,32,33,34,35,36,37,38,39] as well as AIF estimation using reference region models [40,41,42,43]. Use of a different pharmacokinetic model and/or AIF estimation method will likely produce results that differ from those presented in the current study.…”