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.

Two-dimensional ordered arrays of gold (Au) nanoparticles were fabricated using two different variants of the nanosphere lithography technique. First, ordered arrays of polystyrene nanospheres on Si substrate were used as deposition masks through which gold films were deposited by electron beam evaporation. After the removal of the nanospheres, an array of triangular Au nanodisks was left on the Si substrate. After thermal annealing at increasing temperature, systematic shape transition of the nanostructures from original triangular Au nanodisks to rounded nanoparticles was observed. This approach allows us to systematically vary the size and morphology of the particles. In the second and novel technique, we made use of reactive ion etching to simultaneously reduce the dimension of the masking nanospheres and create arrays of nanopores on the substrate prior to the deposition of the Au films. These samples were subsequently annealed, which resulted in size-tunable and ordered Au nanoparticle arrays with the nanoparticles nested in the nanopores of the templated substrate. With the nanoparticles anchored in the nanopores, the substrate could be useful as a template for growth of other nanomaterials.

The IVIM-fitted post-processing of DWI-signal decay in human gliomas could show significantly different values of fractional perfusion-related volume and fast diffusion coefficient between low- and high-grade tumors, which might enable a noninvasive WHO grading in vivo.

This study was institutional review board approved, with waived patient consent for retrospective analysis of the data. The hepatic perfusion at dynamic contrast material-enhanced magnetic resonance (MR) imaging was commonly described and assessed by using a dual-input one-compartment tracer kinetics model. Although the tracer kinetics in normal liver parenchyma can be described by using a single compartment, functional changes in the tumor microenvironment can result in distinctly different tracer behavior that entails a second tissue compartment. A dual-input two-compartment model is proposed to describe the tracer behavior in hepatic metastases. The authors applied this model to the dynamic MR imaging data obtained in three patients. Perfusion parameter maps and region-of-interest analysis revealed that tracer behavior in hepatic metastases-in contrast to that in surrounding normal liver tissue, which effectively involves one compartment-can be described by using two compartments.

Perfusion magnetic resonance imaging (MRI) studies quantify the microcirculatory status of liver parenchyma and liver lesions, and can be used for the detection of liver metastases, assessing the effectiveness of anti-angiogenic therapy, evaluating tumor viability after anti-cancer therapy or ablation, and diagnosis of liver cirrhosis and its severity. In this review, we discuss the basic concepts of perfusion MRI using tracer kinetic modeling, the common kinetic models applied for analyses, the MR scanning techniques, methods of data processing, and evidence that supports its use from published clinical and research studies. Technical standardization and further studies will help to establish and validate perfusion MRI as a clinical imaging modality.

We present a multiple compartment, mammillary distributed-parameter model for capillary-tissue exchange, which can be implemented with dynamic contrast-enhanced imaging to study kinetic heterogeneity in tumors. The proposed n-compartment model consists of a vascular distributed-parameter compartment in direct exchange with a number (n - 1) of interstitial compartments. It is applied to a prostate tumor case study to illustrate the possible co-existence of two kinetically distinct compartments in the tumor, and the estimation of useful physiological parameters (such as perfusion, mean transit time, fractional volumes, and transfer and rate constants) associated with tissue microcirculation. The present model exhibits the convenient property of a separable impulse residue response function in time domain, which can be used to provide further insights and understanding on the physiological basis of tissue enhancement parameters commonly used for correlation studies with tumor histological diagnosis.

Perfusion CT of oropharyngeal and oral cavity cancer in clinical routine is feasible and helps outlining the malignant tissue as well as differentiating recurrent disease from nonspecific post-therapeutic changes.

We present two regression models for the automatic estimation of bolus arrival times (BATs) in dynamic contrast MRI datasets. Results of Monte Carlo simulation experiments show that the means and standard deviations of the estimated BATs are within the sampling interval even in the presence of significant noise.