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 non-uniform perfusion of an MR-visible tracer, 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 Ktrans 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.

Convection-enhanced delivery (CED) is a promising local delivery technique for overcoming the blood–brain barrier (BBB) and treating diseases of the central nervous system (CNS). For CED, therapeutics are infused directly into brain tissue and the drug agent is spread through the extracellular space, considered to be highly tortuous porous media. In this study, 3D computational models developed using magnetic resonance (MR) diffusion tensor imaging data sets were used to predict CED transport in the rat ventral hippocampus using a voxelized modeling previously developed by our group. Predicted albumin tracer distributions were compared with MR-measured distributions from in vivo CED in the ventral hippocampus up to 10 μL of Gd-DTPA albumin tracer infusion. Predicted and measured tissue distribution volumes and distribution patterns after 5 and 10 μL infusions were found to be comparable. Tracers were found to occupy the underlying landmark structures with preferential transport found in regions with less fluid resistance such as the molecular layer of the dentate gyrus. Also, tracer spread was bounded by high fluid resistance layers such as the granular cell layer and pyramidal cell layer of dentate gyrus. Leakage of tracers into adjacent CSF spaces was observed towards the end of infusions.

Convection-enhanced delivery (CED) has emerged as a promising method of targeted drug-delivery for treating central nervous system (CNS) disorders, but the influence of brain structure on infusate distribution is unclear. We have utilized this approach to study extracellular transport and distribution of a contrast agent in the hippocampus, a complex structure susceptible to CNS disorders. The magnetic resonance (MR) contrast agent diethylene triamene penta-acetic acid chelated gadoliniumlabeled albumin (Gd-albumin), tagged with Evans blue dye, was directly infused into the dorsal and ventral hippocampus of seven male Sprague-Dawley rats. The final distribution profile of the contrast agent, a product of CED and limited diffusion, was observed in vivo using high-resolution T1-weighted MR imaging at 11.1 Tesla. Dense cell layers, such as the granule cell layer of the dentate gyrus and the pyramidal cell layer of CA1, appeared to be barriers to transport of the tracer. Threedimensional distribution shape and volume (V d ) differences, between the dorsal and ventral hippocampus infusions, were determined from the MR images using a semi-automatic segmentation routine (Dorsal V d = 23.4 ± 1.8 μl, Ventral V d = 36.4 ± 5.1 μl). Finer structural detail of the hippocampus was obtained using a combination of histological analysis and fluorescence imaging. This study demonstrates that CED has the potential to target all regions of the hippocampus and that tracer distribution is influenced by infusion site, underlying structure and circuitry, and extent of backflow. Therefore, CED, combined with high-resolution MR imaging, may be a useful strategy for delivering therapeutics for the treatment of CNS disorders affecting the hippocampus.

Convection-enhanced delivery (CED), i.e., direct tissue infusion, has emerged as a promising local drug delivery method for treating diseases of the nervous system. Determination of the spatial distribution of therapeutic agents after infusion is important in evaluating the efficacy of treatment, optimizing infusion protocols, and improving the understanding of drug pharmacokinetics. In this study, we provide a methodology to determine the concentration distribution of Gd-labeled tracers during infusion using contrast-enhanced MR imaging. To the best of our knowledge, MR studies that quantify concentration profiles for CED have not been previously reported. The methodology utilizes intrinsic material properties (T 1 and R 1 ) and reduces the effect of instrumental factors (e.g., inhomogeneity of MR detection field). As a methodology investigation, this study used an agarose hydrogel phantom as a tissue substitute for infusion. An 11.1 T magnet system was used to image infusion of Gd-DTPA labeled albumin (Gd-albumin) into the hydrogel. By using data from preliminary scans, Gd-albumin distribution was determined from the signal intensity of the MR images. As a validation test, MR-derived concentration profiles were found comparable to both results measured directly using quantitative optical imaging and results from a computational transport model in porous media. In future studies, the developed methodology will be used to quantitatively monitor the distribution of Gd-tracer following infusion directly into tissues.

Direct tissue infusion, e.g., convection-enhanced delivery (CED), is a promising local delivery technique for treating diseases of the central nervous system. Predictive models of spatial drug distribution during and following direct tissue infusion are necessary for treatment optimization and planning of surgery. In this study, a 3D interstitial transport modeling approach in which tissue properties and anatomical boundaries are assigned on a voxel-by-voxel basis using tissue alignment data from diffusion tensor imaging (DTI) is presented. The modeling approach is semi-automatic and utilizes porous media transport theory to estimate interstitial transport in isotropic and anisotropic tissue regions. Rat spinal cord studies compared predicted distributions of albumin tracer (for varying DTI resolution) following infusion into the dorsal horn with tracer distributions measured by Wood et al. in a previous study. Tissue distribution volumes compared favorably for small infusion volumes (<4 µl). The presented DTI-based methodology provides a rapid means of estimating interstitial flows and tracer distributions following CED into the spinal cord. Quantification of these transport fields provides an important step toward development of drug-specific transport models of infusion.