Vascular endothelial growth factor blockade alters magnetic resonance imaging biomarkers of vascular function and decreases barrier permeability in a rat model of lung cancer brain metastasis.

BACKGROUND: Blockade of vascular endothelial growth factor (VEGF) to promote vascular normalization and inhibit angiogenesis has been proposed for the treatment of brain metastases; however, vascular normalization has not been well-characterized in this disease. We investigated the effect of treatment with bevacizumab anti-VEGF antibody on magnetic resonance imaging (MRI) biomarkers of brain tumor vascular characteristics in comparison to small molecule delivery in a rat model of human lung cancer brain metastasis. METHODS: Athymic rats with A549 human lung adenocarcinoma intracerebral xenografts underwent MRI at 11.75 T before and one day after treatment with bevacizumab (n = 8) or saline control (n = 8) to evaluate tumor volume, free water content (edema), blood volume and vascular permeability (Ktrans). One day later, permeability to 14C-aminoisobutyric acid (AIB) was measured in tumor and brain to assess the penetration of a small drug-like molecule. RESULTS: In saline control animals, tumor volume, edema and permeability increased over the two day assessment period. Compared to controls, bevacizumab treatment slowed the rate of tumor growth (P = 0.003) and blocked the increase in edema (P = 0.033), but did not alter tumor blood volume. Bevacizumab also significantly reduced Ktrans (P = 0.033) and AIB passive permeability in tumor (P = 0.04), but not to peritumoral tissue or normal brain. Post-treatment Ktrans correlated with AIB levels in the bevacizumab-treated rats but not in the saline controls. CONCLUSIONS: The correlation of an MRI biomarker for decreased vascular permeability with decreased AIB concentration in tumor after antiangiogenic treatment suggests that bevacizumab partially restored the normal low permeability characteristics of the blood-brain barrier in a model of human lung cancer brain metastasis.

MRI-based computational model of heterogeneous tracer transport following local infusion into a mouse hind limb tumor.

Systemic drug delivery to solid tumors involving macromolecular therapeutic agents is challenging for many reasons. Amongst them is their chaotic microvasculature which often leads to inadequate and uneven uptake of the drug. Localized drug delivery can circumvent such obstacles and convection-enhanced delivery (CED)--controlled infusion of the drug directly into the tissue--has emerged as a promising delivery method for distributing macromolecules over larger tissue volumes. In this study, a three-dimensional MR image-based computational porous media transport model accounting for realistic anatomical geometry and tumor leakiness was developed for predicting the interstitial flow field and distribution of albumin tracer following CED into the hind-limb tumor (KHT sarcoma) in a mouse. Sensitivity of the model to changes in infusion flow rate, catheter placement and tissue hydraulic conductivity were investigated. The model predictions suggest that 1) tracer distribution is asymmetric due to heterogeneous porosity; 2) tracer distribution volume varies linearly with infusion volume within the whole leg, and exponentially within the tumor reaching a maximum steady-state value; 3) infusion at the center of the tumor with high flow rates leads to maximum tracer coverage in the tumor with minimal leakage outside; and 4) increasing the tissue hydraulic conductivity lowers the tumor interstitial fluid pressure and decreases the tracer distribution volume within the whole leg and tumor. The model thus predicts that the interstitial fluid flow and drug transport is sensitive to porosity and changes in extracellular space. This image-based model thus serves as a potential tool for exploring the effects of transport heterogeneity in tumors.

Inhibition of SUR1 decreases the vascular permeability of cerebral metastases.

Inhibition of sulfonylurea receptor 1 (SUR1) by glyburide has been shown to decrease edema after subarachnoid hemorrhage. We investigated if inhibiting SUR1 reduces cerebral edema due to metastases, the most common brain tumor, and explored the putative association of SUR1 and the endothelial tight junction protein, zona occludens-1 (ZO-1). Nude rats were intracerebrally implanted with small cell lung carcinoma (SCLC) LX1 or A2058 melanoma cells (n = 36). Rats were administered vehicle, glyburide (4.8 µg twice, orally), or dexamethasone (0.35 mg, intravenous). Blood-tumor barrier (BTB) permeability (K (trans)) was evaluated before and after treatment using dynamic contrast-enhanced magnetic resonance imaging. SUR1 and ZO-1 expression was evaluated using immunofluorescence and Western blots. In both models, SUR1 expression was significantly increased (P < .05) in tumors. In animals with SCLC, control mean K (trans) (percent change ± standard error) was 101.8 ± 36.6%, and both glyburide (-21.4 ± 14.2%, P < .01) and dexamethasone (-14.2 ± 13.1%, P < .01) decreased BTB permeability. In animals with melanoma, compared to controls (117.1 ± 43.4%), glyburide lowered BTB permeability increase (3.2 ± 15.4%, P < .05), while dexamethasone modestly lowered BTB permeability increase (63.1 ± 22.1%, P > .05). Both glyburide (P < .001) and dexamethasone (P < .01) decreased ZO-1 gap formation. By decreasing ZO-1 gaps, glyburide was at least as effective as dexamethasone at halting increased BTB permeability caused by SCLC and melanoma. Glyburide is a safe, inexpensive, and efficacious alternative to dexamethasone for the treatment of cerebral metastasis-related vasogenic edema.

Evaluation of a voxelized model based on DCE-MRI for tracer transport in tumor.

Recent advances in the treatment of cancer involving therapeutic agents have shown promising results. However, treatment efficacy can be limited due to inadequate and uneven uptake in solid tumors, thereby making the prediction of drug transport important for developing effective therapeutic strategies. In this study, a patient-specific computational porous media model (voxelized model) was developed for predicting the interstitial flow field and distribution of a systemically delivered magnetic resonance (MR) visible tracer in a tumor. The benefits of a voxel approach include less labor and less computational time (approximately an order of magnitude reduction compared to the traditional computational fluid dynamics (CFD) approach developed earlier by our group). The model results were compared with that obtained from a previous approach based on unstructured meshes along with MR-measured tracer concentration data within tumors, using statistical analysis and qualitative representations. The statistical analysis indicated the similarity between the structured and unstructured models' results with a low root mean square error (RMS) and a high correlation coefficient. The voxelized model captured features of the flow field and tracer distribution such as high interstitial fluid pressure inside the tumor and the heterogeneous distribution of the tracer. Predictions of tracer distribution by the voxelized approach also resulted in low RMS error when compared with MR-measured data over a 1 h time course. The similarity in the voxelized model results with experiment and the nonvoxelized model predictions were maintained across three different tumors. Overall, the voxelized model serves as a reliable and swift alternative to approaches using unstructured meshes in predicting extracellular transport within tumors.

Role of convection and diffusion on DCE-MRI parameters in low leakiness KHT sarcomas.

The solid tumor is an abnormal environment that is resistant to systemically delivered drugs. Increased plasma leakiness and extracellular matrix density along with poor lymphatic function can result in interstitial flow that attenuates the effectiveness of therapeutics. This study expands upon a previously presented magnetic resonance (MR) imaging-based porous media model by investigating low permeability tumors, where interstitial flow may have increased effect on systemically delivered solutes. The solute transport of the porous media model is compared to that of experiment and the two-compartment model. Small non-necrotic tumors (n=3) were MR-imaged, serially, for 90 min after a bolus injection of Gd-based contrast agent (CA). These data provided for the calculation of experimental CA concentration over 90 min, while only early time points (15 min) were used to create vascular permeability, K(trans), maps for the porous media model. A K(trans) scale factor (range=1.3-2.5) in the porous media model was found to account for the reduction of permeability (measured by two-compartment model) due to interstitial flow. The optimized porous media simulations showed: 1) better dynamic CA behavior agreement with the experimental data than the two-compartment model (>33% reduction of RMS error); 2) similar spatial CA distribution trends across tumor with increased uptake at the tumor boundary.

Sensitivity analysis of an image-based solid tumor computational model with heterogeneous vasculature and porosity.

An MR image-based computational model of a murine KHT sarcoma is presented that allows the calculation of plasma fluid and solute transport within tissue. Such image-based models of solid tumors may be used to optimize patient-specific therapies. This model incorporates heterogeneous vasculature and tissue porosity to account for nonuniform perfusion of an MR-visible tracer, gadolinium-diethylenetriamine pentaacetic acid (Gd-DTPA). Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was conducted following intravenous infusion of Gd-DTPA to provide 1 h of tracer-concentration distribution data within tissue. Early time points (19 min) were used to construct 3D K(trans) and porosity maps using a two-compartment model; tracer transport was predicted at later time points using a 3D porous media model. Model development involved selecting an arterial input function (AIF) and conducting a sensitivity analysis of model parameters (tissue, vascular, and initial estimation of solute concentration in plasma) to investigate the effects on transport for a specific tumor. The developed model was then used to predict transport in two additional tumors. The sensitivity analysis suggests that plasma fluid transport is more sensitive to parameter changes than solute transport due to the dominance of transvascular exchange. Gd-DTPA distribution was similar to experimental patterns, but differences in Gd-DTPA magnitude at later time points may result from inaccurate selection of AIF. Thus, accurate AIF estimation is important for later time point prediction of low molecular weight tracer or drug transport in smaller tumors.

Characterization of an Anisotropic Hydrogel Tissue Substrate for Infusion Testing.

Artificial tissue models that capture specific transport properties are useful for investigating physical phenomena important to drug delivery. In this study, an in vitro tissue model was developed and characterized with the goal of mimicking aligned tissue. An anisotropic porous medium was developed by the construction of a 1% agarose hydrogel implanted with different volume fractions (~ 5, 10, and 20%) of 10-µm-diameter glass fibers. The developed substrate was able to capture anisotropic transport after the direct infusion of a macromolecular tracer, Evans blue albumin (EBA). To further characterize the test substrate, the diffusion tensor of water was measured by diffusion tensor imaging, and the ratios of the diffusivities in the directions parallel and perpendicular to the glass fibers were 1.16, 1.20, and 1.26 for 5, 10, and 20% fiber volume fractions, respectively. The hydraulic conductivity was estimated by the measurement of pressure gradients across samples under controlled microflow conditions in the direction parallel to implanted fibers. The hydraulic conductivities at various hydrogel concentrations without fibers and in a 1% hydrogel with various fiber volume fractions were measured; for example, K(||) = 1.20 × 10(-12) m(4) N(-1) s(-1) (where K(||) is the conductivity component in the direction parallel to the glass fibers) for 20% fiber volume fractions. Also, EBA distributions were fit to porous medium transport models to estimate hydraulic conductivity in the direction perpendicular to glass fibers. The estimated ratio of directional hydraulic conductivity, K(||)/K(⊥) (where K(⊥) is the conductivity component in the direction perpendicular to the glass fibers), ranged from approximately 3 to 5, from 6 to 10, and from 40 to 90 for 5, 10, and 20% fiber volume fractions, respectively. These agarose hydrogel models provided convenient media for quantifying infusion protocols at low flow rates.