Raghu Raghavan

Poor drug distribution as a possible explanation for the results of the PRECISE trial

OBJECT Convection-enhanced delivery (CED) is a novel intracerebral drug delivery technique with considerable promise for delivering therapeutic agents throughout the CNS. Despite this promise, Phase III clinical trials employing CED have failed to meet clinical end points. Although this may be due to inactive agents or a failure to rigorously validate drug targets, the authors have previously demonstrated that catheter positioning plays a major role in drug distribution using this technique. The purpose of the present work was to retrospectively analyze the expected drug distribution based on catheter positioning data available from the CED arm of the PRECISE trial. METHODS Data on catheter positioning from all patients randomized to the CED arm of the PRECISE trial were available for analyses. BrainLAB iPlan Flow software was used to estimate the expected drug distribution. RESULTS Only 49.8% of catheters met all positioning criteria. Still, catheter positioning score (hazard ratio 0.93, p = 0.043) and the number of optimally positioned catheters (hazard ratio 0.72, p = 0.038) had a significant effect on progression-free survival. Estimated coverage of relevant target volumes was low, however, with only 20.1% of the 2-cm penumbra surrounding the resection cavity covered on average. Although tumor location and resection cavity volume had no effect on coverage volume, estimations of drug delivery to relevant target volumes did correlate well with catheter score (p < 0.003), and optimally positioned catheters had larger coverage volumes (p < 0.002). Only overall survival (p = 0.006) was higher for investigators considered experienced after adjusting for patient age and Karnofsky Performance Scale score. CONCLUSIONS The potential efficacy of drugs delivered by CED may be severely constrained by ineffective delivery in many patients. Routine use of software algorithms and alternative catheter designs and infusion parameters may improve the efficacy of drugs delivered by CED.

Clinical utility of a patient-specific algorithm for simulating intracerebral drug infusions

Convection-enhanced delivery (CED) is a novel drug delivery technique that uses positive infusion pressure to deliver therapeutic agents directly into the interstitial spaces of the brain. Despite the promise of CED, clinical trials have demonstrated that target-tissue anatomy and patient-specific physiology play a major role in drug distribution using this technique. In this study, we retrospectively tested the ability of a software algorithm using MR diffusion tensor imaging to predict patient-specific drug distributions by CED. A tumor-targeted cytotoxin, cintredekin besudotox (interleukin 13-PE38QQR), was coinfused with iodine 123-labeled human serum albumin (123I-HSA), in patients with recurrent malignant gliomas. The spatial distribution of 123I-HSA was then compared to a drug distribution simulation provided by the software algorithm. The algorithm had a high sensitivity (71.4%) and specificity (100%) for identifying the high proportion (7 of 14) of catheter trajectories that failed to deliver drug into the desired anatomical region (p = 0.021). This usually occurred when catheter trajectories crossed deep sulci, resulting in leak of the infusate into the subarachnoid cerebrospinal fluid space. The mean concordance of the volume of distribution at the 50% isodose level between the actual 123I-HSA distribution and simulation was 65.75% (95% confidence interval [CI], 52.0%-79.5%), and the mean maximal inplane deviation was less than 8.5 mm (95% CI, 4.0-13.0 mm). The use of this simulation algorithm was considered clinically useful in 84.6% of catheters. Routine use of this algorithm, and its further developments, should improve prospective selection of catheter trajectories, and thereby improve the efficacy of drugs delivered by this promising technique.

Intraparenchymal drug delivery via positive-pressure infusion: experimental and modeling studies of poroelasticity in brain phantom gels

We have used agarose gel to develop a robust model of the intraparenchymal brain tissues for the purpose of simulating positive-pressure infusion of therapeutic agents directly into the brain. In parallel with that effort, we have synthesized a mathematical description of the infusion process on the basis of a poroelastic theory for the swelling of the tissues under the influence of the infusates penetration into the interstitial space. Infusion line pressure measurements and video microscopy determinations of infusate volume of distribution within the gel demonstrate a good match between theory and experiment over a wide range of flow rates (0.5-10.0 microliters/min) and have clinical relevance for the convection-enhanced delivery of drugs into the brain without hindrance by the blood-brain barrier. We have put the brain phantom gel and the infusion measurement system into routine use in determining performance characteristics of novel types of neurosurgical catheters. This approach simplifies the catheter design process and helps to avoid some of the costs of in vivo testing. It also will allow validation of the elementary aspects of treatment planning systems that predict infusion distribution volumes on the basis of theoretical descriptions such as those derived from the poroelastic model.

Induction of hyperintense signal on t2-weighted MR images correlates with infusion distribution from intracerebral convection-enhanced delivery of a tumor-targeted cytotoxin

OBJECTIVE Convection-enhanced delivery is a promising approach to intracerebral drug delivery in which a fluid pressure gradient is used to infuse therapeutic macromolecules through an indwelling catheter into the interstitial spaces of the brain. Our purpose was to test the hypothesis that hyperintense signal changes on T2-weighted images produced by such infusions can be used to track drug distribution. SUBJECTS AND METHODS Seven adults with recurrent malignant glioma underwent concurrent intracerebral infusions of the tumor-targeted cytotoxin cintredekin besudotox and 123I-labeled human serum albumin. The agents were administered through a total of 18 catheters among the seven patients. Adequacy of distribution of drug was determined by evidence of distribution of 123I-labeled human serum albumin on SPECT images coregistered with MR images. Qualitative analysis was performed by three blinded observers. Quantitative analysis also was performed. RESULTS Infusions into 12 catheters produced intraparenchymal distribution as seen on SPECT images, but infusions into six catheters did not. At qualitative assessment of signal changes on MR images, reviewers correctly predicted which catheters would produce extraparenchymal distribution and which catheters would produce parenchymal distribution. Of the 12 infusions that produced intraparenchymal distribution, four catheters had been placed in regions of relatively normal signal intensity and produced regions of newly increased signal intensity, the volume of which highly correlated with the volume and geometry of distribution on SPECT (r2 = 0.9502). Eight infusions that produced intraparenchymal distribution were performed in regions of preexisting hyperintense signal. In these brains, additional signal changes were always produced, but quantitative correlations between areas of newly increased signal intensity and the volume and geometry of distribution on SPECT could not be established. CONCLUSION Convection-enhanced infusions frequently do not provide intraparenchymal drug distribution, and these failures can be identified with MRI soon after infusion. When infusions are performed into regions of normal signal intensity, development of hyperintense signal change strongly correlates with the volume and geometry of distribution of infusate.

Colocalization of Gadolinium-Diethylene Triamine Pentaacetic Acid With High-Molecular-Weight Molecules After Intracerebral Convection-Enhanced Delivery in Humans

BACKGROUND:Convection-enhanced delivery (CED) permits site-specific therapeutic drug delivery within interstitial spaces at increased dosages through circumvention of the blood-brain barrier. CED is currently limited by suboptimal methodologies for monitoring the delivery of therapeutic agents that would permit technical optimization and enhanced therapeutic efficacy. OBJECTIVE:To determine whether a readily available small-molecule MRI contrast agent, gadolinium-diethylene triamine pentaacetic acid (Gd-DTPA), could effectively track the distribution of larger therapeutic agents. METHODS:Gd-DTPA was coinfused with the larger molecular tracer, 124I-labeled human serum albumin (124I-HSA), during CED of an EGFRvIII-specific immunotoxin as part of treatment for a patient with glioblastoma. RESULTS:Infusion of both tracers was safe in this patient. Analysis of both Gd-DTPA and 124I-HSA during and after infusion revealed a high degree of anatomical and volumetric overlap. CONCLUSION:Gd-DTPA may be able to accurately demonstrate the anatomic and volumetric distribution of large molecules used for antitumor therapy with high resolution and in combination with fluid-attenuated inversion recovery (FLAIR) imaging, and provide additional information about leaks into cerebrospinal fluid spaces and resection cavities. Similar studies should be performed in additional patients to validate our findings and help refine the methodologies we used.

Volume morphing methods for landmark-based 3D image deformation

Volume morphing is a technique used for generating smooth 3D image transformations and deformations. In this paper, several algorithms are developed for morphing transformations that create new forms and simulate shape deformation and growth in biomedical applications. Three-dimensional biological point landmarks and their movements are defined to guide the morphing transformation using a scattered data interpolation algorithm. Two types of morphing algorithms, the Shepard-based interpolation and the radial basis function approach, are investigated in detail and applied for volume morphing in growth predictions of children and shape transformations between species.

Deformable volume rendering by 3D texture mapping and octree encoding

Rendering deformable volume data currently needs separate processes for deformation and rendering, and is expensive in terms of both computational and memory costs. Recognizing the importance of unifying these processes, we present a new approach to the direct rendering of deformable volumes without explicitly constructing the intermediate deformed volumes. The volume deformation is done by a radial basis function that is piecewise linearly approximated by an adaptive subdivision of the octree encoded target volume. The octree blocks in the target volume are then projected, reverse morphed and texture mapped, using the SGI 3D texture mapping hardware, in a back-to-front order. A template-based Z-plane/block intersection method is used to expedite the block projection computation.

Fluid infusions from catheters into elastic tissue: I. Azimuthally symmetric backflow in homogeneous media

Directly injecting therapeutics into brain tissue has been investigated both experimentally and theoretically. Paul Morrison and others from the National Institutes of Health pointed out the importance of backflow along and outside a catheter inserted into the tissue, once steady state conditions have been reached. Here we investigate and extend their model. We begin with a reformulation of their results and demonstrate an exact solution that exhibits the scaling behavior of the model where the surrounding tissue medium is homogeneous and isotropic. We report on experimental tests of our predictions in agarose gels. We describe the limitations of the assumptions used and the utility of our reformulation. Extensions of the model, including improvements on some of its crude assumptions and generalizations to inhomogeneous media, will be submitted separately.

Predictive models for pressure-driven fluid infusions into brain parenchyma

Direct infusions into brain parenchyma of biological therapeutics for serious brain diseases have been, and are being, considered. However, individual brains, as well as distinct cytoarchitectural regions within brains, vary in their response to fluid flow and pressure. Further, the tissue responds dynamically to these stimuli, requiring a nonlinear treatment of equations that would describe fluid flow and drug transport in brain. We here report in detail on an individual-specific model and a comparison of its prediction with simulations for living porcine brains. Two critical features we introduced into our model-absent from previous ones, but requirements for any useful simulation-are the infusion-induced interstitial expansion and the backflow. These are significant determinants of the flow. Another feature of our treatment is the use of cross-property relations to obtain individual-specific parameters that are coefficients in the equations. The quantitative results are at least encouraging, showing a high fraction of overlap between the computed and measured volumes of distribution of a tracer molecule and are potentially clinically useful. Several improvements are called for; principally a treatment of the interstitial expansion more fundamentally based on poroelasticity and a better delineation of the diffusion tensor of a particle confined to the interstitial spaces.

Volume morphing and rendering—an integrated approach

In this paper, we first introduce a 3D morphing method for landmark-based volume deformation, using various scattered data interpolation schemes. Qualitative and speed comparisons are also made for different interpolation schemes. To efficiently render the volume morphing process, a new deformable volume rendering algorithm is presented. The algorithm renders the deformed volume directly without going through the expensive volume construction process. Piecewise linear approximation of the deformation function by adaptive space subdivision and template-based block projection are used to speed up the rendering process. While the resultant timings is slower than real time, it is much faster than existing volume morphing/rendering pipelines.