New intravascular contrast agent applied to dynamic contrast enhanced MR imaging of human breast cancer

Statistical comparison of dynamic contrast-enhanced MRI pharmacokinetic models in human breast cancer

By fitting dynamic contrast-enhanced MRI data to an appropriate pharmacokinetic model, quantitative physiological parameters can be estimated. In this study, we compare four different models by applying four statistical measures to assess their ability to describe dynamic contrast-enhanced MRI data obtained in 28 human breast cancer patient sets: the chi-square test (χ(2)), Durbin-Watson statistic, Akaike information criterion, and Bayesian information criterion. The pharmacokinetic models include the fast exchange limit model with (FXL_v(p)) and without (FXL) a plasma component, and the fast and slow exchange regime models (FXR and SXR, respectively). The results show that the FXL_v(p) and FXR models yielded the smallest χ(2) in 45.64 and 47.53% of the voxels, respectively; they also had the smallest number of voxels showing serial correlation with 0.71 and 2.33%, respectively. The Akaike information criterion indicated that the FXL_v(p) and FXR models were preferred in 42.84 and 46.59% of the voxels, respectively. The Bayesian information criterion also indicated the FXL_v(p) and FXR models were preferred in 39.39 and 45.25% of the voxels, respectively. Thus, these four metrics indicate that the FXL_v(p) and the FXR models provide the most complete statistical description of dynamic contrast-enhanced MRI time courses for the patients selected in this study.

Dynamic contrast-enhanced MRI in the diagnosis and management of breast cancer

Dynamic contrast-enhanced MRI (DCE-MRI) is an evolving tool for determining breast disease, which benefits from the move to imaging at 3 T. It has major capabilities for the diagnosis, detection and monitoring of malignancy. It benefits from being non-invasive and three-dimensional, allowing visualisation of the extent of disease and its angiogenic properties, visualisation of lesion heterogeneity, detection of changes in angiogenic properties before morphological alterations, and the potential to predict the overall response either before the start of therapy or early during treatment. In addition, DCE-MRI is emerging as a powerful tool for screening high-risk patients and for detecting high-grade ductal carcinoma in situ. However, there are also a number of limitations, including the overlap in enhancement patterns between malignant and benign disease, the failure to resolve microscopic disease particularly in the neoadjuvant setting, and the inconsistent predictive value of the enhancement pattern for clinical outcome. Careful consideration should be given to the technical requirements of individual examinations and the need for automation of post-processing techniques to appropriately handle the growing volume of data acquired. Research continues, focusing on the use of higher field strengths with improved spatial and temporal resolution data, improving understanding of the mechanism of contrast enhancement at the cellular level, and developing macromolecular and targeted contrast agents.

Tumor microvasculature: endothelial leakiness and endothelial pore size distribution in a breast cancer model

Tumor endothelial leakiness is quantified in a rat mammary adenocarcinoma model using dynamic contrast enhancement MRI and contrast agents of widely varying sizes. The contrast agents were constructed to be of globular configuration and have their uptake rate into tumor interstitium be driven by the same diffusion process and limited only by the availability of endothelial pores of passable size. It was observed that the endothelial pore distribution has a steep power law dependence on size, r(-) (β), with an exponent of -4.1. The model of large pore dominance in tumor leakiness as reported in some earlier investigation with fluorescent probes and optical chamber methods is rejected for this tumor model and a number of other tumor types including chemically induced tumors. This steep power law dependence on size is also consistent with observations on human breast cancer.

Predicting grade of cerebral glioma using vascular-space occupancy MR imaging

BACKGROUND AND PURPOSE

MR imaging can measure tissue perfusion and the integrity of the blood-brain barrier. We hypothesize that a combined measure of cerebral blood volume and vascular permeability using vascular-space occupancy (VASO) MR imaging, a recently developed imaging technique, is of diagnostic value for predicting tumor grade.

MATERIALS AND METHODS

Thirty-nine patients (9 World Health Organization [WHO] grade II, 20 grade III, and 10 grade IV as determined by histopathologic assessment) were examined using VASO MR imaging, and regions-of-interest analysis was performed in tumoral regions, as well as in regions contralateral to the tumor. A Mann-Whitney test was conducted on the resulting VASO indices for a pairwise comparison across tumor grades. Nominal logistic regression was used to evaluate the use of VASO parameters for predicting group membership (by the percentage of correct classifications).

RESULTS

The ratio between tumor side and contralateral side, VASO(Ratio), showed significant differences in all 3 of the pairwise comparisons (P < .01). VASO values in the tumoral regions, VASO(Tumor), showed significant difference between grade II and III and between II and IV but not between III and IV. Both VASO(Tumor) and VASO(Ratio) were found to be significant predictors of tumor grade, giving diagnostic accuracies of 66.7% and 71.8%, respectively. When testing to discriminate grade II tumors from higher grade tumors, the areas under the receiver operating characteristic curve were found to be 0.974 and 0.985 for VASO(Tumor) and VASO(Ratio), respectively.

CONCLUSION

VASO MR imaging can be used for noninvasive tumor grade prediction based on cerebral blood volume and vascular permeability. VASO is more effective in separating WHO grade II from higher grades than in separating grade III from grade IV.

A prospective study on the added value of pulsed arterial spin-labeling and apparent diffusion coefficients in the grading of gliomas

BACKGROUND AND PURPOSE

The purpose of this study was to determine whether qualitative and quantitative measures obtained with pulsed arterial spin-labeling (PASL) and apparent diffusion coefficients (ADC) improve glioma grading compared with conventional MR images.

MATERIALS AND METHODS

We prospectively performed 2 qualitative consensus reviews in 33 suspected gliomas: 1) conventional MR images alone and 2) conventional MR images with PASL and ADC. To calculate the diagnostic performance parameters of PASL and ADC, we used a qualitative scoring system on the basis of the tumor perfusion signal intensity (sTP) and visual ADC scoring (sADC). We then analyzed quantitative regions of interest and calculated the ratio of the maximum tumor perfusion signal intensity (rTPmax) and the minimum ADC value (mADC).

RESULTS

Two observers diagnosed accurate tumor grades in 23 of 33 (70%) lesions in the first review and in 29 of 33 (88%) lesions in the second review. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for determining a glioma grading by using combined sTP and sADC scoring were 90.9, 90.9, 95.2, and 83.3%, respectively. Statistical analysis gave a threshold value of 1.24 for rTPmax and 0.98 x 10(-3) mm/s(2) for mADC to provide a sensitivity, specificity, PPV, and NPV of 95.5, 81.8, 91.3, and 90.1% and 90.9, 81.8, 90.9, and 81.8%, respectively. The receiver operator characteristic curve analyses showed no significant difference between the quantitative and combined qualitative parameters.

CONCLUSION

PASL and ADC significantly improve the diagnostic accuracy of glioma grading compared with conventional imaging.

Targeted delivery of multifunctional magnetic nanoparticles

Magnetic nanoparticles and their magnetofluorescent analogues have become important tools for in vivo imaging using magnetic resonance imaging and fluorescent optical methods. A number of monodisperse magnetic nanoparticle preparations have been developed over the last decade for angiogenesis imaging, cancer staging, tracking of immune cells (monocyte/macrophage, T cells) and for molecular and cellular targeting. Phage display and data mining have enabled the procurement of novel tissue- or receptor-specific peptides, while high-throughput screening of diversity-oriented synthesis libraries has identified small molecules that permit or prevent uptake by specific cell types. Next-generation magnetic nanoparticles are expected to be truly multifunctional, incorporating therapeutic functionalities and further enhancing an already diverse repertoire of capabilities.

Clearance of Iron Oxide Particles in Rat Liver

OBJECTIVES

We sought to evaluate the effect of the particle size and coating material of various iron oxide preparations on the rate of rat liver clearance.

MATERIALS AND METHODS

The following iron oxide formulations were used in this study: dextran-coated ferumoxide (size = 97 nm) and ferumoxtran-10 (size = 21 nm), carboxydextran-coated SHU555A (size = 69 nm) and fractionated SHU555A (size = 12 nm), and oxidized-starch coated materials either unformulated NC100150 (size = 15 nm) or formulated NC100150 injection (size = 12 nm). All formulations were administered to 165 rats at 2 dose levels. Quantitative liver R2* values were obtained during a 63-day time period. The concentration of iron oxide particles in the liver was determined by relaxometry, and these values were used to calculate the particle half-lives in the liver.

RESULTS

After the administration of a high dose of iron oxide, the half-life of iron oxide particles in rat liver was 8 days for dextran-coated materials, 10 days for carboxydextran materials, 14 days for unformulated oxidized-starch, and 29 days for formulated oxidized-starch.

CONCLUSIONS

The results of the study indicate that materials with similar coating but different sizes exhibited similar rates of liver clearance. It was, therefore, concluded that the coating material significantly influences the rate of iron oxide clearance in rat liver.

Magnetic Resonance Macromolecular Agents for Monitoring Tumor Microvessels and Angiogenesis Inhibition

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using macromolecular contrast media enables assessments of the tumor vasculature based on the differential distribution of the contrast agent within normal and pathologic tissues. Quantitative assays of both morphologic and functional properties can provide useful diagnostic insight into tissue angiogenesis. The use of MRI enhanced with macromolecular agents for the characterization of tumor microvessels has been experimentally demonstrated in a range of malignant tumor types. Kinetic analysis of DCE-MRI data can be used to estimate microvascular permeability and tumor blood volume. By measuring these functional tumor properties, an accurate, noninvasive, and quantitative description of the microcirculation of individual tumors can be acquired, improving the specificity of imaging examinations for cancer diagnosis and for treatment and follow up. The noninvasive MRI assessment of tumor angiogenesis can be applied in the diagnostic differentiation between benign and malignant tumors and can also provide means for in vivo monitoring of antitumor therapy. In this review, the potential clinical applications and limitations of various macromolecular contrast agents applied for evaluations of tumor angiogenesis, with and without drug interventions, are discussed.

Imaging angiogenesis: applications and potential for drug development

Recognition of the importance of angiogenesis to tumor growth and metastasis has led to efforts to develop new drugs that are targeted to angiogenic vasculature. Clinical trials of these agents are challenging, both because there is no agreed upon method of establishing the correct dosage for drugs whose mechanism of action is not primarily cytotoxic and because of the long time it takes to determine whether such drugs have a clinical effect. Therefore, there is a need for rapid and effective biomarkers to establish drug dosage and monitor clinical response. This review addresses the potential of imaging as a way to accurately and reliably assess changes in angiogenic vasculature in response to therapy. We describe the advantages and disadvantages of several imaging modalities, including positron emission tomography, x-ray computed tomography, magnetic resonance imaging, ultrasound, and optical imaging, for imaging angiogenic vasculature. We also discuss the analytic methods used to derive blood flow, blood volume, empirical semiquantitative hemodynamic parameters, and quantitative hemodynamic parameters from pharmacokinetic modeling. We examine the validity of these methods, citing studies that test correlations between data derived from imaging and data derived from other established methods, their reproducibility, and correlations between imaging-derived hemodynamic parameters and other pathologic indicators, such as microvessel density, pathology score, and disease outcome. Finally, we discuss which imaging methods are most likely to have the sensitivity and reliability required for monitoring responses to cancer therapy and describe ways in which imaging has been used in clinical trials to date.

Molecular imaging: The latest generation of contrast agents and tissue characterization techniques

Molecular Imaging technologies will have a profound impact on both basic research and clinical imaging in the near future. As the field covers many different specialties and scientific disciplines it is not possible to review all in a single article. In the current article we will turn our attention to those modalities that are either currently in use or in development for the medical imaging clinic.