Fundamentals of tracer kinetics for dynamic contrast‐enhanced MRI

Abstract

Tracer kinetic methods employed for quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) share common roots with earlier tracer studies involving arterial-venous sampling and other dynamic imaging modalities. This article reviews the essential foundation concepts and principles in tracer kinetics that are relevant to DCE MRI, including the notions of impulse response and convolution, which are central to the analysis of DCE MRI data. We further examine the formulation and solutions of various compartmental models frequently used in the literature. Topics of recent interest in the processing of DCE MRI data, such as the account of water exchange and the use of reference tissue methods to obviate the measurement of an arterial input, are also discussed. Although the primary focus of this review is on the tracer models and methods for T 1 -weighted DCE MRI, some of these concepts and methods are also applicable for analysis of dynamic susceptibility contrastenhanced MRI data.

Bolus arrival time and its effect on tissue characterization with dynamic contrast-enhanced magnetic resonance imaging

“…14,15 With the exception of the methods that are not sensitive to the bolus arrival delay, 16,17 correction for such a delay is otherwise necessary. 18 This correction can be done by adding the delay as a free parameter to the PK analysis optimization procedure at the expense of making the fitting process more complex. 19,20 There is evidence that PK models that have fewer parameters result in improved robustness and stability of the fit 21 and that exclusion of BAT from the fitting problem reduces the model's degrees of freedom and improves the accuracy of the estimates and the stability of the model.…”

Validation of Microcirculatory Parameters Derived from the Standard Two-Compartment Model with Murine Xenografts Model

“…With such ambiguities in interpretation, it might be difficult to identify appropriate markers for validation of trans . The standard two-compartment model [7][8][9][10] describes tissue microcirculation with distinct parameters, namely, blood flow ( ), vessel permeability surface area product (PS), fractional vascular volume (V 1 ), and fractional interstitial volume (V 2 ). These physiological parameters can be readily validated by comparison with appropriate histological markers or other established tracer techniques.…”

“…These physiological parameters can be readily validated by comparison with appropriate histological markers or other established tracer techniques. More complex tracer kinetic models such as the distributed parameter models [10] are also capable of separately estimating blood flow and permeability. However, the distributed parameter …”

An Efficient Method for Detection of Outliers in Tracer Curves Derived from Dynamic Contrast-Enhanced Imaging

“…Dynamic contrast-enhanced imaging using computed tomography (DCE-CT) or magnetic resonance imaging (DCE-MRI) is a functional imaging method that can be used for in vivo assessment of tumor perfusion and allows for quantitative estimation of physiological parameters pertaining to tumor microcirculation [1,2]. Analysis of DCE imaging data can be performed by fitting a tracer kinetic model to the tissue tracer concentration-time curves estimated from the DCE images.…”