Analysis of a simulation algorithm for direct brain drug delivery

A Spatial Interpolation Approach to Assign Magnetic Resonance Imaging-Derived Material Properties for Finite Element Models of Adeno-Associated Virus Infusion Into a Recurrent Brain Tumor

Adeno-associated virus (AAV) is a clinically useful gene delivery vehicle for treating neurological diseases. To deliver AAV to focal targets, direct infusion into brain tissue by convection-enhanced delivery (CED) is often needed due to AAV's limited penetration across the blood-brain-barrier and its low diffusivity in tissue. In this study, computational models that predict the spatial distribution of AAV in brain tissue during CED were developed to guide future placement of infusion catheters in recurrent brain tumors following primary tumor resection. The brain was modeled as a porous medium, and material property fields that account for magnetic resonance imaging (MRI)-derived anatomical regions were interpolated and directly assigned to an unstructured finite element mesh. By eliminating the need to mesh complex surfaces between fluid regions and tissue, mesh preparation was expedited, increasing the model's clinical feasibility. The infusion model predicted preferential fluid diversion into open fluid regions such as the ventricles and subarachnoid space (SAS). Additionally, a sensitivity analysis of AAV delivery demonstrated that improved AAV distribution in the tumor was achieved at higher tumor hydraulic conductivity or lower tumor porosity. Depending on the tumor infusion site, the AAV distribution covered 3.67-70.25% of the tumor volume (using a 10% AAV concentration threshold), demonstrating the model's potential to inform the selection of infusion sites for maximal tumor coverage.

A comprehensive review on modeling aspects of infusion-based drug delivery in the brain

Brain disorders represent an ever-increasing health challenge worldwide. While conventional drug therapies are less effective due to the presence of the blood-brain barrier, infusion-based methods of drug delivery to the brain represent a promising option. Since these methods are mechanically controlled and involve multiple physical phases ranging from the neural and molecular scales to the brain scale, highly efficient and precise delivery procedures can significantly benefit from a comprehensive understanding of drug-brain and device-brain interactions. Behind these interactions are principles of biophysics and biomechanics that can be described and captured using mathematical models. Although biomechanics and biophysics have received considerable attention, a comprehensive mechanistic model for modeling infusion-based drug delivery in the brain has yet to be developed. Therefore, this article reviews the state-of-the-art mechanistic studies that can support the development of next-generation models for infusion-based brain drug delivery from the perspective of fluid mechanics, solid mechanics, and mathematical modeling. The supporting techniques and database are also summarized to provide further insights. Finally, the challenges are highlighted and perspectives on future research directions are provided. STATEMENT OF SIGNIFICANCE: Despite the immense potential of infusion-based drug delivery methods for bypassing the blood-brain barrier and efficiently delivering drugs to the brain, achieving optimal drug distribution remains a significant challenge. This is primarily due to our limited understanding of the complex interactions between drugs and the brain that are governed by principles of biophysics and biomechanics, and can be described using mathematical models. This article provides a comprehensive review of state-of-the-art mechanistic studies that can help to unravel the mechanism of drug transport in the brain across the scales, which underpins the development of next-generation models for infusion-based brain drug delivery. More broadly, this review will serve as a starting point for developing more effective treatments for brain diseases and mechanistic models that can be used to study other soft tissue and biomaterials.

Image-guided patient-specific optimization of catheter placement for convection-enhanced nanoparticle delivery in recurrent glioblastoma

BACKGROUND

Proper catheter placement for convection-enhanced delivery (CED) is required to maximize tumor coverage and minimize exposure to healthy tissue. We developed an image-based model to patient-specifically optimize the catheter placement for rhenium-186 (186Re)-nanoliposomes (RNL) delivery to treat recurrent glioblastoma (rGBM).

METHODS

The model consists of the 1) fluid fields generated via catheter infusion, 2) dynamic transport of RNL, and 3) transforming RNL concentration to the SPECT signal. Patient-specific tissue geometries were assigned from pre-delivery MRIs. Model parameters were personalized with either 1) individual-based calibration with longitudinal SPECT images, or 2) population-based assignment via leave-one-out cross-validation. The concordance correlation coefficient (CCC) was used to quantify the agreement between the predicted and measured SPECT signals. The model was then used to simulate RNL distributions from a range of catheter placements, resulting in a ratio of the cumulative RNL dose outside versus inside the tumor, the "off-target ratio" (OTR). Optimal catheter placement) was identified by minimizing OTR.

RESULTS

Fifteen patients with rGBM from a Phase I/II clinical trial (NCT01906385) were recruited to the study. Our model, with either individual-calibrated or population-assigned parameters, achieved high accuracy (CCC > 0.80) for predicting RNL distributions up to 24 h after delivery. The optimal catheter placements identified using this model achieved a median (range) of 34.56 % (14.70 %-61.12 %) reduction on OTR at the 24 h post-delivery in comparison to the original placements.

CONCLUSIONS

Our image-guided model achieved high accuracy for predicting patient-specific RNL distributions and indicates value for optimizing catheter placement for CED of radiolabeled liposomes.

Recombinant polio-rhinovirus immunotherapy for recurrent paediatric high-grade glioma: a phase 1b trial

BACKGROUND

Outcomes of recurrent paediatric high-grade glioma are poor, with a median overall survival of less than 6 months. Viral immunotherapy, such as the polio-rhinovirus chimera lerapolturev, is a novel approach for treatment of recurrent paediatric high-grade glioma and has shown promise in adults with recurrent glioblastoma. The poliovirus receptor CD155 is ubiquitously expressed in malignant paediatric brain tumours and is a treatment target in paediatric high-grade glioma. We aimed to assess the safety of lerapolturev when administered as a single dose intracerebrally by convection enhanced delivery in children and young people with recurrent WHO grade 3 or grade 4 glioma, and to assess overall survival in these patients.

METHODS

This phase 1b trial was done at the Duke University Medical Center (Durham, NC, USA). Patients aged 4-21 years with recurrent high-grade malignant glioma (anaplastic astrocytoma, glioblastoma, anaplastic oligoastrocytoma, anaplastic oligodendroglioma, or anaplastic pleomorphic xanthoastrocytoma) or anaplastic ependymoma, atypical teratoid rhabdoid tumour, or medulloblastoma with infusible disease were eligible for this study. A catheter was tunnelled beneath the scalp for a distance of at least 5 cm to aid in prevention of infection. The next day, lerapolturev at a dose of 5 × 107 median tissue culture infectious dose in 3 mL infusate loaded in a syringe was administered via a pump at a rate of 0·5 mL per h as a one-time dose. The infusion time was approximately 6·5 h to compensate for volume of the tubing. The primary endpoint was the proportion of patients with unacceptable toxic effects during the 14-day period after lerapolturev treatment. The study is registered with ClinicalTrials.gov, NCT03043391.

FINDINGS

Between Dec 5, 2017, and May 12, 2021, 12 patients (11 unique patients) were enrolled in the trial. Eight patients were treated with lerapolturev. The median patient age was 16·5 years (IQR 11·0-18·0), five (63%) of eight patients were male and three (38%) were female, and six (75%) of eight patients were White and two (25%) were Black or African American. The median number of previous chemotherapeutic regimens was 3·50 (IQR 1·25-5·00). Six of eight patients had 26 treatment-related adverse events attributable to lerapolturev. There were no irreversible (ie, persisted longer than 2 weeks) treatment-related grade 4 adverse events or deaths. Treatment-related grade 3 adverse events included headaches in two patients and seizure in one patient. Four patients received low-dose bevacizumab on-study for treatment-related peritumoural inflammation or oedema, diagnosed by both clinical symptoms plus fluid-attenuated inversion recovery MRI. The median overall survival was 4·1 months (95% CI 1·2-10·1). One patient remains alive after 22 months.

INTERPRETATION

Convection enhanced delivery of lerapolturev is safe enough in the treatment of recurrent paediatric high-grade glioma to proceed to the next phase of trial.

FUNDING

Solving Kids Cancer, B+ Foundation, Musella Foundation, and National Institutes of Health.

Convection-Enhanced Delivery of Antiangiogenic Drugs and Liposomal Cytotoxic Drugs to Heterogeneous Brain Tumor for Combination Therapy

Simple Summary

Although developed anticancer drugs have shown desirable effects in preclinical trials, the clinical efficacy of chemotherapy against brain cancer remains disappointing. One of the important obstacles is the highly heterogeneous environment in tumors. This study aims to evaluate the performance of an emerging treatment using antiangiogenic and cytotoxic drugs. Our mathematical modelling confirms the advantage of this combination therapy in homogenizing the intratumoral environment for better drug delivery outcomes. In addition, the effects of local microvasculature and cell density on this therapy are also discussed. The results would contribute to the development of more effective treatments for brain cancer.

Abstract

Although convection-enhanced delivery can successfully bypass the blood-brain barrier, its clinical performance remains disappointing. This is primarily attributed to the heterogeneous intratumoral environment, particularly the tumor microvasculature. This study investigates the combined convection-enhanced delivery of antiangiogenic drugs and liposomal cytotoxic drugs in a heterogeneous brain tumor environment using a transport-based mathematical model. The patient-specific 3D brain tumor geometry and the tumor’s heterogeneous tissue properties, including microvascular density, porosity and cell density, are extracted from dynamic contrast-enhanced magnetic resonance imaging data. Results show that antiangiogenic drugs can effectively reduce the tumor microvascular density. This change in tissue structure would inhibit the fluid loss from the blood to prevent drug concentration from dilution, and also reduce the drug loss by blood drainage. The comparisons between different dosing regimens demonstrate that the co-infusion of liposomal cytotoxic drugs and antiangiogenic drugs has the advantages of homogenizing drug distribution, increasing drug accumulation, and enlarging the volume where tumor cells can be effectively killed. The delivery outcomes are susceptible to the location of the infusion site. This combination treatment can be improved by infusing drugs at higher microvascular density sites. In contrast, infusion at a site with high cell density would lower the treatment effectiveness of the whole brain tumor. Results obtained from this study can deepen the understanding of this combination therapy and provide a reference for treatment design and optimization that can further improve survival and patient quality of life.

Integrating mechanism-based modeling with biomedical imaging to build practical digital twins for clinical oncology

Digital twins employ mathematical and computational models to virtually represent a physical object (e.g., planes and human organs), predict the behavior of the object, and enable decision-making to optimize the future behavior of the object. While digital twins have been widely used in engineering for decades, their applications to oncology are only just emerging. Due to advances in experimental techniques quantitatively characterizing cancer, as well as advances in the mathematical and computational sciences, the notion of building and applying digital twins to understand tumor dynamics and personalize the care of cancer patients has been increasingly appreciated. In this review, we present the opportunities and challenges of applying digital twins in clinical oncology, with a particular focus on integrating medical imaging with mechanism-based, tissue-scale mathematical modeling. Specifically, we first introduce the general digital twin framework and then illustrate existing applications of image-guided digital twins in healthcare. Next, we detail both the imaging and modeling techniques that provide practical opportunities to build patient-specific digital twins for oncology. We then describe the current challenges and limitations in developing image-guided, mechanism-based digital twins for oncology along with potential solutions. We conclude by outlining five fundamental questions that can serve as a roadmap when designing and building a practical digital twin for oncology and attempt to provide answers for a specific application to brain cancer. We hope that this contribution provides motivation for the imaging science, oncology, and computational communities to develop practical digital twin technologies to improve the care of patients battling cancer.

Convection-Enhanced Delivery in Children: Techniques and Applications

Since its first description in 1994, convection-enhanced delivery (CED) has become a reliable method of administering drugs directly into the brain parenchyma. More predictable and effective than simple diffusion, CED bypasses the challenging boundary of the blood brain barrier, which has frustrated many attempts at delivering large molecules or polymers into the brain parenchyma. Although most of the clinical work with CED has been carried out on adults with incurable neoplasms, principally glioblastoma multiforme, an increasing number of studies have recognized its potential for paediatric applications, which now include treatment of currently incurable brain tumours such as diffuse intrinsic pontine glioma (DIPG), as well as metabolic and neurotransmitter diseases. The roadmap for the development of hardware and use of pharmacological agents in CED has been well-established, and some neurosurgical centres throughout the world have successfully undertaken clinical trials, admittedly mostly early phase, on the basis of in vitro, small animal and large animal pre-clinical foundations. However, the clinical efficacy of CED, although theoretically logical, has yet to be unequivocally demonstrated in a clinical trial; this applies particularly to neuro-oncology.This review aims to provide a broad description of the current knowledge of CED as applied to children. It reviews published studies of paediatric CED in the context of its wider history and developments and underlines the challenges related to the development of hardware, the selection of pharmacological agents, and gene therapy. It also reviews the difficulties related to the development of clinical trials involving CED and looks towards its potential disease-modifying opportunities in the future.

Evaluation of a patient-specific algorithm for predicting distribution for convection-enhanced drug delivery into the brainstem of patients with diffuse intrinsic pontine glioma

OBJECTIVE

With increasing use of convection-enhanced delivery (CED) of drugs, the need for software that can predict infusion distribution has grown. In the context of a phase I clinical trial for pediatric diffuse intrinsic pontine glioma (DIPG), CED was used to administer an anti-B7H3 radiolabeled monoclonal antibody, iodine-124-labeled omburtamab. In this study, the authors retrospectively evaluated a software algorithm (iPlan Flow) for the estimation of infusate distribution based on the planned catheter trajectory, infusion parameters, and patient-specific MRI. The actual infusate distribution, as determined on MRI and PET imaging, was compared to the distribution estimated by the software algorithm. Similarity metrics were used to quantify the agreement between predicted and actual distributions.

METHODS

Ten pediatric patients treated at the same dose level in the NCT01502917 trial conducted at Memorial Sloan Kettering Cancer Center were considered for this retrospective analysis. T2-weighted MRI in combination with PET imaging was used to determine the distribution of infusate in this study. The software algorithm was applied for the generation of estimated fluid distribution maps. Similarity measures included object volumes, intersection volume, union volume, Dice coefficient, volume difference, and the center and average surface distances. Acceptable similarity was defined as a simulated distribution volume (Vd Sim) object that had a Dice coefficient higher than or equal to 0.7, a false-negative rate (FNR) lower than 50%, and a positive predictive value (PPV) higher than 50% compared to the actual Vd (Vd PET).

RESULTS

Data for 10 patients with a mean infusion volume of 4.29 ml (range 3.84-4.48 ml) were available for software evaluation. The mean Vd Sim found to be covered by the actual PET distribution (PPV) was 77% ± 8%. The mean percentage of PET volume found to be outside the simulated volume (FNR) was 34% ± 10%. The mean Dice coefficient was 0.7 ± 0.05. In 8 out of 10 patients, the simulation algorithm fulfilled the combined acceptance criteria for similarity.

CONCLUSIONS

iPlan Flow software can be useful to support planning of trajectories that produce intraparenchymal convection. The simulation algorithm is able to model the likely infusate distribution for a CED treatment in DIPG patients. The combination of trajectory planning guidelines and infusion simulation in the software can be used prospectively to optimize personalized CED treatment.

Patient specific, imaging-informed modeling of rhenium-186 nanoliposome delivery via convection-enhanced delivery in glioblastoma multiforme

Convection-enhanced delivery of rhenium-186 (¹⁸⁶Re)-nanoliposomes is a promising approach to provide precise delivery of large localized doses of radiation for patients with recurrent glioblastoma multiforme. Current approaches for treatment planning utilizing convection-enhanced delivery are designed for small molecule drugs and not for larger particles such as¹⁸⁶Re-nanoliposomes. To enable the treatment planning for¹⁸⁶Re-nanoliposomes delivery, we have developed a computational fluid dynamics approach to predict the distribution of nanoliposomes for individual patients. In this work, we construct, calibrate, and validate a family of computational fluid dynamics models to predict the spatio-temporal distribution of¹⁸⁶Re-nanoliposomes within the brain, utilizing patient-specific pre-operative magnetic resonance imaging (MRI) to assign material properties for an advection-diffusion transport model. The model family is calibrated to single photon emission computed tomography (SPECT) images acquired during and after the infusion of¹⁸⁶Re-nanoliposomes for five patients enrolled in a Phase I/II trial (NCT Number NCT01906385), and is validated using a leave-one-out bootstrapping methodology for predicting the final distribution of the particles. After calibration, our models are capable of predicting the mid-delivery and final spatial distribution of¹⁸⁶Re-nanoliposomes with a Dice value of 0.69 ± 0.18 and a concordance correlation coefficient of 0.88 ± 0.12 (mean ± 95% confidence interval), using only the patient-specific, pre-operative MRI data, and calibrated model parameters from prior patients. These results demonstrate a proof-of-concept for a patient-specific modeling framework, which predicts the spatial distribution of nanoparticles. Further development of this approach could enable optimizing catheter placement for future studies employing convection-enhanced delivery.

Convection-Enhanced Delivery and Principles of Extracellular Transport in the Brain

Stereotactic neurosurgery involves a targeted intervention based on congruence of image guidance to a reference fiducial system. This discipline has widespread applications in radiosurgery, tumor therapy, drug delivery, functional lesioning, and neuromodulation. In this article, we focused on convection-enhanced delivery to deliver therapeutic agents to the brain addressing areas of research and clinical development. We performed a robust literature review of all relevant articles highlighting current efforts and challenges of making this delivery technique more widely understood. We further described key biophysical properties of molecular transport in the extracellular space that may impact the efficacy and control of drug delivery using stereotactic methods. Understanding these principles is critical for further refinement of predictive models that can inform advances in stereotactic techniques for convection-enhanced delivery of therapeutic agents to the brain.

Convection Enhanced Delivery for Diffuse Intrinsic Pontine Glioma: Review of a Single Institution Experience

Diffuse intrinsic pontine gliomas (DIPGs) are a pontine subtype of diffuse midline gliomas (DMGs), primary central nervous system (CNS) tumors of childhood that carry a terrible prognosis. Because of the highly infiltrative growth pattern and the anatomical position, cytoreductive surgery is not an option. An initial response to radiation therapy is invariably followed by recurrence; mortality occurs approximately 11 months after diagnosis. The development of novel therapeutics with great preclinical promise has been hindered by the tightly regulated blood-brain barrier (BBB), which segregates the tumor comportment from the systemic circulation. One possible solution to this obstacle is the use of convection enhanced delivery (CED), a local delivery strategy that bypasses the BBB by direct infusion into the tumor through a small caliber cannula. We have recently shown CED to be safe in children with DIPG (NCT01502917). In this review, we discuss our experience with CED, its advantages, and technical advancements that are occurring in the field. We also highlight hurdles that will likely need to be overcome in demonstrating clinical benefit with this therapeutic strategy.

Three-dimensional nonlinear finite element model to estimate backflow during flow-controlled infusions into the brain

Convection-enhanced delivery is a technique to bypass the blood–brain barrier and deliver therapeutic drugs into the brain tissue. However, animal investigations and preliminary clinical trials have reported reduced efficacy to transport the infused drug in specific zones, attributed mainly to backflow, in which an annular gap is formed outside the catheter and the fluid preferentially flows toward the surface of the brain rather than through the tissue in front of the cannula tip. In this study, a three-dimensional human brain finite element model of backflow was developed to study the influence of anatomical structures during flow-controlled infusions. Predictions of backflow length were compared under the influence of ventricular pressure and the distance between the cannula and the ventricles. Simulations with zero relative ventricle pressure displayed similar backflow length predictions for larger cannula-ventricle distances. In addition, infusions near the ventricles revealed smaller backflow length and the liquid was observed to escape to the longitudinal fissure and ventricular cavities. Simulations with larger cannula-ventricle distances and nonzero relative ventricular pressure showed an increase of fluid flow through the tissue and away from the ventricles. These results reveal the importance of considering both the subject-specific anatomical details and the nonlinear effects in models focused on analyzing current and potential treatment options associated with convection-enhanced delivery optimization for future clinical trials.

Convection-Enhanced Delivery: Connection to and Impact of Interstitial Fluid Flow

Convection-enhanced delivery (CED) is a method used to increase transport of therapeutics in and around brain tumors. CED works through locally applying a pressure differential to drive fluid flow throughout the tumor, such that convective forces dominate over diffusive transport. This allows therapies to bypass the blood brain barrier that would otherwise be too large or solely rely on passive diffusion. However, this also drives fluid flow out through the tumor bulk into surrounding brain parenchyma, which results in increased interstitial fluid (IF) flow, or fluid flow within extracellular spaces in the tissue. IF flow has been associated with altered transport of molecules, extracellular matrix rearrangement, and triggering of cellular motility through a number of mechanisms. Thus, the results of a simple method to increase drug delivery may have unintended consequences on tissue morphology. Clinically, prediction of dispersal of agents via CED is important to catheter design, placement, and implementation to optimize contact of tumor cells with therapeutic agent. Prediction software can aid in this problem, yet we wonder if there is a better way to predict therapeutic distribution based simply on IF flow pathways as determined from pre-intervention imaging. Overall, CED based therapy has seen limited success and we posit that integration and appreciation of altered IF flow may enhance outcomes. Thus, in this manuscript we both review the current state of the art in CED and IF flow mechanistic understanding and relate these two elements to each other in a clinical context.

AAVrh.10-Mediated APOE2 Central Nervous System Gene Therapy for APOE4-Associated Alzheimer's Disease

Alzheimer's disease (AD) is a progressive degenerative neurological disorder affecting nearly one in nine elderly people in the United States. Population studies have shown that an inheritance of the apolipoprotein E (APOE) variant APOE4 allele increases the risk of developing AD, whereas APOE2 homozygotes are protected from late-onset AD. It was hypothesized that expression of the "protective" APOE2 variant by genetic modification of the central nervous system (CNS) of APOE4 homozygotes could reverse or prevent progressive neurologic damage. To assess the CNS distribution and safety of APOE2 gene therapy for AD in a large-animal model, intraparenchymal, intracisternal, and intraventricular routes of delivery to the CNS of nonhuman primates of AAVrh.10hAPOE2-HA, an AAVrh.10 serotype coding for an HA-tagged human APOE2 cDNA sequence, were evaluated. To evaluate the route of delivery that achieves the widest extent of APOE2 expression in the CNS, the expression of APOE2 in the CNS was evaluated 2 months following vector administration for APOE2 DNA, mRNA, and protein. Finally, using conventional toxicology assays, the safety of the best route of delivery was assessed. The data demonstrated that while all three routes are capable of mediating ApoE2 expression in AD relevant regions, intracisternal delivery of AAVrh.10hAPOE2-HA safely mediated wide distribution of ApoE2 with the least invasive surgical intervention, thus providing the optimal strategy to deliver vector-mediated human APOE2 to the CNS.

Influence of an intratumoral cyst on drug distribution by convection-enhanced delivery: case report

Convection-enhanced delivery (CED) uses positive pressure to induce convective flow of molecules and maximize drug distribution. Concerns have been raised about the effect of cystic structures on uniform drug distribution with CED. The authors describe the case of a patient with a diffuse intrinsic pontine glioma (DIPG) with a large cyst and examine its effect on drug distribution after CED with a radiolabeled antibody. The patient was treated according to protocol with CED of ¹²⁴I-8H9 to the pons for nonprogressive DIPG after radiation therapy as part of a Phase I trial (clinical trial registration no. NCT01502917, clinicaltrials.gov). Care was taken to avoid the cystic cavity in the planned catheter track and target point. Co-infusion with Gd-DTPA was performed to assess drug distribution. Infusate distribution was examined by MRI immediately following infusion and analyzed using iPlan Flow software. Analysis of postinfusion MR images demonstrated convective distribution around the catheter tip and an elongated configuration of drug distribution, consistent with the superoinferior corticospinal fiber orientation in the brainstem. This indicates that the catheter was functioning and a pressure gradient was established. No infusate entry into the cystic region could be identified on T2-weighted FLAIR or T1-weighted images. The effects of ependymal and pial surfaces on drug delivery using CED in brainstem tumors remain controversial. Drug distribution is a critical component of effective application of CED to neurosurgical lesions. This case suggests that cyst cavities may not always behave as fluid "sinks" for drug distribution. The authors observed that infusate was not lost into the cyst cavity, suggesting that lesions with cystic components can be treated by CED without significant alterations to target and infusion planning.

Advances in optogenetic and chemogenetic methods to study brain circuits in non-human primates

Over the last 10 years, the use of opto- and chemogenetics to modulate neuronal activity in research applications has increased exponentially. Both techniques involve the genetic delivery of artificial proteins (opsins or engineered receptors) that are expressed on a selective population of neurons. The firing of these neurons can then be manipulated using light sources (for opsins) or by systemic administration of exogenous compounds (for chemogenetic receptors). Opto- and chemogenetic tools have enabled many important advances in basal ganglia research in rodent models, yet these techniques have faced a slow progress in non-human primate (NHP) research. In this review, we present a summary of the current state of these techniques in NHP research and outline some of the main challenges associated with the use of these genetic-based approaches in monkeys. We also explore cutting-edge developments that will facilitate the use of opto- and chemogenetics in NHPs, and help advance our understanding of basal ganglia circuits in normal and pathological conditions.

Voxelized Model of Brain Infusion That Accounts for Small Feature Fissures: Comparison With Magnetic Resonance Tracer Studies

Convection enhanced delivery (CED) is a promising novel technology to treat neural diseases, as it can transport macromolecular therapeutic agents greater distances through tissue by direct infusion. To minimize off-target delivery, our group has developed 3D computational transport models to predict infusion flow fields and tracer distributions based on magnetic resonance (MR) diffusion tensor imaging data sets. To improve the accuracy of our voxelized models, generalized anisotropy (GA), a scalar measure of a higher order diffusion tensor obtained from high angular resolution diffusion imaging (HARDI) was used to improve tissue segmentation within complex tissue regions of the hippocampus by capturing small feature fissures. Simulations were conducted to reveal the effect of these fissures and cerebrospinal fluid (CSF) boundaries on CED tracer diversion and mistargeting. Sensitivity analysis was also conducted to determine the effect of dorsal and ventral hippocampal infusion sites and tissue transport properties on drug delivery. Predicted CED tissue concentrations from this model are then compared with experimentally measured MR concentration profiles. This allowed for more quantitative comparison between model predictions and MR measurement. Simulations were able to capture infusate diversion into fissures and other CSF spaces which is a major source of CED mistargeting. Such knowledge is important for proper surgical planning.

AAV viral vector delivery to the brain by shape-conforming MR-guided infusions

Gene transfer technology offers great promise as a potential therapeutic approach to the brain but has to be viewed as a very complex technology. Success of ongoing clinical gene therapy trials depends on many factors such as selection of the correct genetic and anatomical target in the brain. In addition, selection of the viral vector capable of transfer of therapeutic gene into target cells, along with long-term expression that avoids immunotoxicity has to be established. As with any drug development strategy, delivery of gene therapy has to be consistent and predictable in each study subject. Failed drug and vector delivery will lead to failed clinical trials. In this article, we describe our experience with AAV viral vector delivery system, that allows us to optimize and monitor in real time viral vector administration into affected regions of the brain. In addition to discussing MRI-guided technology for administration of AAV vectors we have developed and now employ in current clinical trials, we also describe ways in which infusion cannula design and stereotactic trajectory may be used to maximize the anatomical coverage by using fluid backflow. This innovative approach enables more precise coverage by fitting the shape of the infusion to the shape of the anatomical target.

Convection-enhanced delivery to the central nervous system

Convection-enhanced delivery (CED) is a bulk flow–driven process. Its properties permit direct, homogeneous, targeted perfusion of CNS regions with putative therapeutics while bypassing the blood-brain barrier. Development of surrogate imaging tracers that are co-infused during drug delivery now permit accurate, noninvasive real-time tracking of convective infusate flow in nervous system tissues. The potential advantages of CED in the CNS over other currently available drug delivery techniques, including systemic delivery, intrathecal and/or intraventricular distribution, and polymer implantation, have led to its application in research studies and clinical trials. The authors review the biophysical principles of convective flow and the technology, properties, and clinical applications of convective delivery in the CNS.

Phase 1 clinical trial of intratumoral reovirus infusion for the treatment of recurrent malignant gliomas in adults

Reovirus, an oncolytic RNA virus exhibiting antiglioma activity, was shown in a previous single institution phase 1 study found that the inoculation of the virus to be well tolerated in patients with recurrent malignant glioma (MG). The goals of multicenter study reported herein were to determine the dose-limiting toxicity, maximum tolerated dose, and target lesion response rate when reovirus was administered in a novel fashion via intratumoral infusion for 72 hours in patients with recurrent malignant glioma. Fifteen adult patients were treated in a dose escalation study ranging from 1 × 10(8) to 1 × 10(10) tissue culture infectious dose 50, tentimes the dose achieved in the previous trial. Neurological, functional examinations, and imaging studies were completed pre- and postinfusion. There was one grade 3 adverse event (convulsions) felt to be possibly related to treatment, but no grade 4 adverse events considered probably or definitely related to treatment. Dose-limiting toxicity were not identified and a maximum tolerated dose was not reached. Evidence of antiglioma activity was seen in some patients. This first report of intratumoral infusion of reovirus in patients with recurrent malignant glioma demonstrated the approach to be safe and well tolerated, warranting further studies.

Automated segmentation tool for brain infusions

This study presents a computational tool for auto-segmenting the distribution of brain infusions observed by magnetic resonance imaging. Clinical usage of direct infusion is increasing as physicians recognize the need to attain high drug concentrations in the target structure with minimal off-target exposure. By co-infusing a Gadolinium-based contrast agent and visualizing the distribution using real-time using magnetic resonance imaging, physicians can make informed decisions about when to stop or adjust the infusion. However, manual segmentation of the images is tedious and affected by subjective preferences for window levels, image interpolation and personal biases about where to delineate the edge of the sloped shoulder of the infusion. This study presents a computational technique that uses a Gaussian Mixture Model to efficiently classify pixels as belonging to either the high-intensity infusate or low-intensity background. The algorithm was implemented as a distributable plug-in for the widely used imaging platform OsiriX®. Four independent operators segmented fourteen anonymized datasets to validate the tool’s performance. The datasets were intra-operative magnetic resonance images of infusions into the thalamus or putamen of non-human primates. The tool effectively reproduced the manual segmentation volumes, while significantly reducing intra-operator variability by 67±18%. The tool will be used to increase efficiency and reduce variability in upcoming clinical trials in neuro-oncology and gene therapy.

Rapid inverse planning for pressure-driven drug infusions in the brain

Infusing drugs directly into the brain is advantageous to oral or intravenous delivery for large molecules or drugs requiring high local concentrations with low off-target exposure. However, surgeons manually planning the cannula position for drug delivery in the brain face a challenging three-dimensional visualization task. This study presents an intuitive inverse-planning technique to identify the optimal placement that maximizes coverage of the target structure while minimizing the potential for leakage outside the target. The technique was retrospectively validated using intraoperative magnetic resonance imaging of infusions into the striatum of non-human primates and into a tumor in a canine model and applied prospectively to upcoming human clinical trials.