AG-013736, a novel inhibitor of VEGF receptor tyrosine kinases, inhibits breast cancer growth and decreases vascular permeability as detected by dynamic contrast-enhanced magnetic resonance imaging

Dynamic contrast-enhanced MRI (DCE-MRI) was used to noninvasively evaluate the effects of AG-03736, a novel inhibitor of vascular endothelial growth factor (VEGF) receptor tyrosine kinases, on tumor microvasculature in a breast cancer model. First, a dose response study was undertaken to determine the responsiveness of the BT474 human breast cancer xenograft to AG-013736. Then, DCE-MRI was used to study the effects of a 7-day treatment regimen on tumor growth and microvasculature. Two DCE-MRI protocols were evaluated: (1) a high molecular weight (MW) contrast agent (albumin-(GdDTPA)(30)) with pharmacokinetic analysis of the contrast uptake curve and (2) a low MW contrast agent (GdDTPA) with a clinically utilized empirical parametric analysis of the contrast uptake curve, the signal enhancement ratio (SER). AG-013736 significantly inhibited growth of breast tumors in vivo at all doses studied (10-100 mg/kg) and disrupted tumor microvasculature as assessed by DCE-MRI. Tumor endothelial transfer constant (K(ps)) measured with albumin-(GdDTPA)(30) decreased from 0.034+/-0.005 to 0.003+/-0.001 ml min(-1) 100 ml(-1) tissue (P<.0022) posttreatment. No treatment-related change in tumor fractional plasma volume (fPV) was detected. Similarly, in the group of mice studied with GdDTPA DCE-MRI, AG-013736-induced decreases in tumor SER measures were observed. Additionally, our data suggest that 3D MRI-based volume measurements are more sensitive than caliper measurements for detecting small changes in tumor volume. Histological staining revealed decreases in tumor cellularity and microvessel density with treatment. These data demonstrate that both high and low MW DCE-MRI protocols can detect AG-013736-induced changes in tumor microvasculature. Furthermore, the correlative relationship between microvasculature changes and tumor growth inhibition supports DCE-MRI methods as a biomarker of VEGF receptor target inhibition with potential clinical utility.     

Pharmacokinetic analysis of glioma compartments with dynamic Gd-DTPA-enhanced magnetic resonance imaging

Dynamic contrast-enhanced magnetic resonance imaging (MRI) is widely used for measuring perfusion and blood volume, especially cerebral blood volume (CBV). In case of blood-brain barrier (BBB) disruption, the conventional techniques only partially determine the pharmacokinetic parameters of contrast medium (CM) exchange between different compartments. Here a modified pharmacokinetic model is applied, which is based on the bidirectional CM exchange between blood and two interstitial compartments in terms of the fractional volumes of the compartments and the vessel permeabilities between them. The evaluation technique using this model allows one to quantify the fractional volumes of the different compartments (blood, cells, slowly and fast enhancing interstitium) as well as the vessel permeabilities and cerebral blood flow (CBF) with a single T1-weighted dynamic MRI measurement. The method has been successfully applied in 25 glioma patients for generating maps of all of these parameters. The fractional volume maps allow for the differentiation of glioma vascularization types. The maps show a good correlation with the histological grading of these tumors. Furthermore, regions with enhanced interstitial volumes are found in high-grade gliomas. Differences in permeability maps of Gd-DTPA apart from BBB disruption do not exist between different tissue types. CBF measured in high-grade glioma is less pronounced than it would be expected from their blood volume. Therefore pharmacokinetic imaging provides an additional tool for glioma characterization.     

Magnetic resonance of brain tumors: considerations of imaging contrast on the basis of relaxation measurements

Proton spin-lattice and spin-spin relaxation times have been measured in surgically-removed normal CNS tissues and a variety of tumors of the brain. All measurements were made at 20 MHz and 37 degrees C. Between grey and white matter from autopsy human or canine specimens significant differences in T1 or T2 were observed, with greater differences seen in T1. Such discrimination was reduced in samples obtained from live brain-tumor patients due to lengthening in T1 and T2 of white matter near tumorous lesions. Edematous white matter showed T1 and T2 values higher than those of autopsy disease-free white matter. Compared to normal CNS tissues, most brain tumors examined in this study demonstrated elevated T1 and T2 values. Exceptions, however, did exist. No definitive correlation was indicated on a T1 or T2 basis which allowed a distinction to be made between benign and malignant states. Furthermore, considerable variation in relaxation times occurred from tumor to tumor of the same type, suggesting that within a tumor type there are important differences in physiology, biology, and/or pathologic state. Such variation caused partial overlap in relaxation times among certain tumor types and hence may limit the capability of magnetic resonance imaging (MR) alone for the diagnosis of specific disease. Nonetheless, this study predicts that on the basis of T1 or T2 differences most brain tumors are readily detectable by MR via saturation recovery or inversion recovery with appropriate selections of pulse-spacing parameters. In general, tumors can be discriminated against white matter better than grey matter and contrast between glioma and grey matter is usually superior to that between meningioma and grey matter. This work did not consider tissue-associated proton density which should be addressed together with T1 and T2 for a complete treatment of MR contrast.     

Quantitative correlation between (1)H MRS and dynamic contrast-enhanced MRI of human breast cancer

Proton magnetic resonance spectroscopy (¹H MRS) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) provide functional information, including vascular volume, vascular permeability and choline (Cho) metabolism. In this study, we applied these two imaging modalities to quantitatively characterize 36 malignant breast lesions in 32 patients and analyzed the correlation between them. Cho concentration was quantified by single-voxel ¹H MRS using water as an internal reference. The measured Cho levels ranged from 0.32 to 10.47 mmol/kg, consistent with previously reported values. In 25 mass-type lesions, the Cho concentration was significantly correlated with tumor size (r=.69, P<.0002). In addition, the Cho level was found to be significantly higher in lesions presenting as mass-type lesions compared to non-mass-type diffuse enhancements (P=.035). The enhancement kinetics from tissues covered within each MRS voxel were measured and analyzed with a two-compartmental model to obtain pharmacokinetic parameters K^trans and k_ep. A significant correlation was found between the Cho level and the pharmacokinetic parameter k_ep (r=.62, P<.0001), indicating that tissues with a high Cho level have higher wash-out rates in DCE MRI. The results suggest a correlation between Cho metabolism and angiogenesis activity, which might be explained by the association of Cho with cell replication and angiogenesis required to support tumor growth.     

Reconstruction of dynamic contrast enhanced magnetic resonance imaging of the breast with temporal constraints

A number of methods using temporal and spatial constraints have been proposed for reconstruction of undersampled dynamic magnetic resonance imaging (MRI) data. The complex data can be constrained or regularized in a number of different ways, for example, the time derivative of the magnitude and phase image voxels can be constrained separately or jointly. Intuitively, the performance of different regularizations will depend on both the data and the chosen temporal constraints. Here, a complex temporal total variation (TV) constraint was compared to the use of separate real and imaginary constraints, and to a magnitude constraint alone. Projection onto Convex Sets (POCS) with a gradient descent method was used to implement the diverse temporal constraints in reconstructions of DCE MRI data. For breast DCE data, serial POCS with separate real and imaginary TV constraints was found to give relatively poor results while serial/parallel POCS with a complex temporal TV constraint and serial POCS with a magnitude-only temporal TV constraint performed well with an acceleration factor as large as R=6. In the tumor area, the best method was found to be parallel POCS with complex temporal TV constraint. This method resulted in estimates for the pharmacokinetic parameters that were linearly correlated to those estimated from the fully-sampled data, with K^trans,R=6=0.97 K^trans,R=1+0.00 with correlation coefficient r=0.98, k_ep,R=6=0.95 k_ep,R=1+0.00 (r=0.85). These results suggest that it is possible to acquire highly undersampled breast DCE-MRI data with improved spatial and/or temporal resolution with minimal loss of image quality.     

Limitations of the permeability-limited compartment model in estimating vascular permeability and interstitial volume fraction in DCE-MRI

Dynamic contrast-enhanced magnetic resonance imaging commonly uses compartment models to estimate tissue parameters in general and perfusion parameters in particular. Compartment models assume a homogeneous distribution of the injected tracer throughout the compartment volume. Since tracer distribution within a compartment cannot be assessed, the parameters obtained by means of a compartment model might differ from the actual physical values.This work systematically examines the widely used permeability-surface-limited one-compartment model to determine the reliability of the parameters obtained by comparing them with their actual values. A computer simulation was used to model spatial tracer distribution within the interstitial volume using diffusion of contrast agent in tissue. Vascular parameters were varied as well as tissue parameters. The vascular parameters used were capillary radius (4 and 12 μm), capillary permeability (from 0.03 to 3.3 μm/s) and intercapillary distances from 30 to 300 μm. The tissue parameters used were tortuosity (λ), porosity (α) and interstitial volume fraction (v_e).Our results suggest that the permeability-surface-limited compartment model generally underestimates capillary permeability for capillaries with a radius of 4 μm by factors from ≈0.03 for α=0.04, to ≈ 0.1 for α=0.2, to ≈ 0.5 for α=1.0. An overestimation of actual capillary permeability for capillaries with a radius of 12 μm by a factor of ≥1.3 was found for α=1.0, while α=0.2 yielded an underestimation by a factor of ≈0.3 and α=0.04 by a factor of ≈ 0.03. The interstitial volume fraction, v_e, obtained by the compartment model differed with increasing intercapillary distances and for low vessel permeability, whereas v_e was found to be estimated approximately accurately for P=0.3 μm/s and P=3.3 μm/s for vessel distances <100 μm.     

Perfusion imaging of cerebral arteriovenous malformations: a study comparing quantitative continuous arterial spin labeling and dynamic contrast-enhanced magnetic resonance imaging at 3 T

Assessment of hemodynamics in arteriovenous malformations (AVMs) is important for estimating the risk of bleeding as well as planning and monitoring therapy. In tissues with perfusion values significantly higher than cerebral cortex, continuous arterial spin labeling (CASL) permits both adequate representation and quantification of perfusion. Thirteen patients who had cerebral AVMs were examined with two magnetic resonance imaging (MRI) techniques: perfusion imaging using a CASL technique with two delay times, 800 and 1200 ms, and T₂-weighted dynamic contrast-enhanced MRI (T₂-DCE-MRI). The signal-to-noise ratio obtained in our study with the CASL technique at 3 T was sufficient to estimate perfusion in gray matter. Both nidal and venous perfusion turned out larger by factors of 1.71±2.01 and 2.48±1.51 in comparison to T₂-DCE-MRI when using CASL at delay times of 800 and 1200 ms, respectively. Moreover, the venous and nidal perfusion values of the AVMs measured at T₂-DCE-MRI did not correlate with those observed at CASL. Evaluation of average perfusion values yielded significantly different results when using a shorter versus a longer delay time. Average gray matter perfusion was 15.8% larger when measured at delay times of w=800 ms versus w=1200 ms, while nidal perfusion was 15.7% larger and venous perfusion was 34.6% larger, respectively.In conclusion, the extremely high perfusion within an AVM could be successfully quantified using CASL. A shorter postlabeling delay time of w=800 ms seems to be more appropriate than a longer time of w=1200 ms because of possible inflow of unlabeled spins at the latter.     

Single voxel vascular transport functions of arteries,capillaries and veins; and the associated arterial input function in dynamic susceptibility contrast magnetic resonance brain perfusion imaging

PurposeThe composite vascular transport function of a brain voxel consists of one convolutional component for the arteries, one for the capillaries and one for the veins in the voxel of interest. Here, the goal is to find each of these three convolutional components and the associated arterial input function.Pharmacokinetic modellingThe single voxel vascular transport functions for arteries, capillaries and veins were all modelled as causal exponential functions. Each observed multipass tissue contrast function was as a first approximation modelled as the resulting parametric composite vascular transport function convolved with a nonparametric and voxel specific multipass arterial input function. Subsequently, the residue function was used in the true perfusion equation to optimize the three parameters of the exponential functions.Deconvolution methodsFor each voxel, the parameters of the three exponential functions were estimated by successive iterative blind deconvolutions using versions of the Lucy-Richardson algorithm. The final multipass arterial input function was then computed by nonblind deconvolution using the Lucy-Richardson algorithm and the estimated composite vascular transport function.ResultsSimulations showed that the algorithm worked. The estimated mean transit time of arteries, capillaries and veins of the simulated data agreed with the known input values. For real data, the estimated capillary mean transit times agreed with known values for this parameter. The nonparametric multipass arterial input functions were used to derive the associated map of the arrival time. The arrival time map of a healthy volunteer agreed with known arterial anatomy and physiology.ConclusionClinically important new voxelwise hemodynamic information for arteries, capillaries and veins separately can be estimated using multipass tissue contrast functions and the iterative blind Lucy-Richardson deconvolution algorithm.