Utilizing Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to Analyze Interstitial Fluid Flow and Transport in Glioblastoma and the Surrounding Parenchyma in Human Patients

Image-based predictive modelling frameworks for personalised drug delivery in cancer therapy

Personalised drug delivery enables a tailored treatment plan for each patient compared to conventional drug delivery, where a generic strategy is commonly employed. It can not only achieve precise treatment to improve effectiveness but also reduce the risk of adverse effects to improve patients' quality of life. Drug delivery involves multiple interconnected physiological and physicochemical processes, which span a wide range of time and length scales. How to consider the impact of individual differences on these processes becomes critical. Multiphysics models are an open system that allows well-controlled studies on the individual and combined effects of influencing factors on drug delivery outcomes while accommodating the patient-specific in vivo environment, which is not economically feasible through experimental means. Extensive modelling frameworks have been developed to reveal the underlying mechanisms of drug delivery and optimise effective delivery plans. This review provides an overview of currently available models, their integration with advanced medical imaging modalities, and code packages for personalised drug delivery. The potential to incorporate new technologies (i.e., machine learning) in this field is also addressed for development.

Hydraulic conductivity of human cancer tissue: A hybrid study

Background

Elevated tumor tissue interstitial fluid pressure (IFP) is an adverse biomechanical biomarker that predicts poor therapy response and an aggressive phenotype. Advances in functional imaging have opened the prospect of measuring IFP non-invasively. Image-based estimation of the IFP requires knowledge of the tissue hydraulic conductivity (K), a measure for the ease of bulk flow through the interstitium. However, data on the magnitude of K in human cancer tissue are not available.

Methods

We measured the hydraulic conductivity of tumor tissue using modified Ussing chambers in surgical resection specimens. The effect of the tumor microenvironment (TME) on K was investigated by quantifying the collagen content, cell density, and fibroblast density of the tested samples using quantitative immune histochemistry. Also, we developed a computational fluid dynamics (CFD) model to evaluate the role of K on interstitial fluid flow and drug transport in solid tumors.

Results

The results show that the hydraulic conductivity of human tumor tissues is very limited, ranging from approximately 10-15 to 10-14 m2/Pa∙s. Moreover, K values varied significantly between tumor types and between different samples from the same tumor. A significant inverse correlation was found between collagen fiber density and hydraulic conductivity values. However, no correlation was detected between K and cancer cell or fibroblast densities. The computational model demonstrated the impact of K on the interstitial fluid flow and the drug concentration profile: higher K values led to a lower IFP and deeper drug penetration.

Conclusions

Human tumor tissue is characterized by a very limited hydraulic conductivity, representing a barrier to effective drug transport. The results of this study can inform the development of realistic computational models, facilitate non-invasive IFP estimation, and contribute to stromal targeting anticancer therapies.

Drug transport modeling in solid tumors: A computational exploration of spatial heterogeneity of biophysical properties

Inadequate uptake of therapeutic agents by tumor cells is still a major barrier in clinical cancer therapy. Mathematical modeling is a powerful tool to describe and investigate the transport phenomena involved. However, current models for interstitial flow and drug delivery in solid tumors have not yet embedded the existing heterogeneity of tumor biomechanical properties. The purpose of this study is to introduce a novel and more realistic methodology for computational models of solid tumor perfusion and drug delivery accounting for these regional heterogeneities as well as lymphatic drainage effects. Several tumor geometries were studied using an advanced computational fluid dynamics (CFD) modeling approach of intratumor interstitial fluid flow and drug transport. Hereby, the following novelties were implemented: (i) the heterogeneity of tumor-specific hydraulic conductivity and capillary permeability; (ii) the effect of lymphatic drainage on interstitial fluid flow and drug penetration. Tumor size and shape both have a crucial role on the interstitial fluid flow regime as well as drug transport illustrating a direct correlation with interstitial fluid pressure (IFP) and an inverse correlation with drug penetration, except for large tumors having a diameter larger than 50 mm. The results also suggest that the interstitial fluid flow and drug penetration in small tumors depend on tumor shape. A parameter study on the necrotic core size illustrated that the core effect (i.e. fluid flow and drug penetration alteration) was only profound in small tumors. Interestingly, the impact of a necrotic core on drug penetration differs depending on the tumor shape from having no effect in ideally spherical tumors to a clear effect in elliptical tumors with a necrotic core. A realistic presence of lymphatic vessels only slightly affected tumor perfusion, having no substantial effect on drug delivery. In conclusion, our findings illustrated that our novel parametric CFD modeling strategy in combination with accurate profiling of heterogeneous tumor biophysical properties can provide a powerful tool for better insights into tumor perfusion and drug transport, enabling effective therapy planning.

Fluids and flows in brain cancer and neurological disorders

Interstitial fluid (IF) and cerebrospinal fluid (CSF) are an integral part of the brain, serving to cushion and protect the brain parenchymal cells against damage and aid in their function. The brain IF contains various ions, nutrients, waste products, peptides, hormones, and neurotransmitters. IF moves primarily by pressure-dependent bulk flow through brain parenchyma, draining into the ventricular CSF. The brain ventricles and subarachnoid spaces are filled with CSF which circulates through the perivascular spaces. It also flows into the IF space regulated, in part, by aquaporin channels, removing waste solutes through a process of IF-CSF mixing. During disease development, the composition, flow, and volume of these fluids changes and can lead to brain cell dysfunction. With the improvement of imaging technology and the help of genomic profiling, more information has been and can be obtained from brain fluids; however, the role of CSF and IF in brain cancer and neurobiological disease is still limited. Here we outline recent advances of our knowledge of brain fluid flow in cancer and neurodegenerative disease based on our understanding of its dynamics and composition. This article is categorized under: Cancer > Biomedical Engineering Neurological Diseases > Biomedical Engineering.

Interstitial fluid pressure as an emerging biomarker in solid tumors

The physical microenvironment of cancer is characterized by elevated stiffness and tissue pressure, the main component of which is the interstitial fluid pressure (IFP). Elevated IFP is an established negative predictive and prognostic parameter, directly affecting malignant behavior and therapy response. As such, measurement of the IFP would allow to develop strategies aimed at engineering the physical microenvironment of cancer. Traditionally, IFP measurement required the use of invasive methods. Recent progress in dynamic and functional imaging methods such as dynamic contrast enhanced (DCE) magnetic resonance imaging and elastography, combined with numerical models and simulation, allows to comprehensively assess the biomechanical landscape of cancer, and may help to overcome physical barriers to drug delivery and immune cell infiltration. Here, we provide a comprehensive overview of the origin of elevated IFP, and its role in the malignant phenotype. Also, we review the methods used to measure IFP using invasive and imaging based methods, and highlight remaining obstacles and potential areas of progress in order to implement IFP measurement in clinical practice.

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.

A patient-designed tissue-engineered model of the infiltrative glioblastoma microenvironment

Glioblastoma is an aggressive brain cancer characterized by diffuse infiltration. Infiltrated glioma cells persist in the brain post-resection where they interact with glial cells and experience interstitial fluid flow. We use patient-derived glioma stem cells and human glial cells (i.e., astrocytes and microglia) to create a four-component 3D model of this environment informed by resected patient tumors. We examine metrics for invasion, proliferation, and putative stemness in the context of glial cells, fluid forces, and chemotherapies. While the responses are heterogeneous across seven patient-derived lines, interstitial flow significantly increases glioma cell proliferation and stemness while glial cells affect invasion and stemness, potentially related to CCL2 expression and differential activation. In a screen of six drugs, we find in vitro expression of putative stemness marker CD71, but not viability at drug IC50, to predict murine xenograft survival. We posit this patient-informed, infiltrative tumor model as a novel advance toward precision medicine in glioblastoma treatment.

Delivery strategies for cell-based therapies in the brain: overcoming multiple barriers

Cell-based therapies to the brain are promising for the treatment of multiple brain disorders including neurodegeneration and cancers. In order to access the brain parenchyma, there are multiple physiological barriers that must be overcome depending on the route of delivery. Specifically, the blood-brain barrier has been a major difficulty in drug delivery for decades, and it still presents a challenge for the delivery of therapeutic cells. Other barriers, including the blood-cerebrospinal fluid barrier and lymphatic-brain barrier, are less explored, but may offer specific challenges or opportunities for therapeutic delivery. Here we discuss the barriers to the brain and the strategies currently in place to deliver cell-based therapies, including engineered T cells, dendritic cells, and stem cells, to treat diseases. With a particular focus on cancers, we also highlight the current ongoing clinical trials that use cell-based therapies to treat disease, many of which show promise at treating some of the deadliest illnesses.

Drug Design: Where We Are and Future Prospects

Medicinal chemistry is facing new challenges in approaching precision medicine. Several powerful new tools or improvements of already used tools are now available to medicinal chemists to help in the process of drug discovery, from a hit molecule to a clinically used drug. Among the new tools, the possibility of considering folding intermediates or the catalytic process of a protein as a target for discovering new hits has emerged. In addition, machine learning is a new valuable approach helping medicinal chemists to discover new hits. Other abilities, ranging from the better understanding of the time evolution of biochemical processes to the comprehension of the biological meaning of the data originated from genetic analyses, are on their way to progress further in the drug discovery field toward improved patient care. In this sense, the new approaches to the delivery of drugs targeted to the central nervous system, together with the advancements in understanding the metabolic pathways for a growing number of drugs and relating them to the genetic characteristics of patients, constitute important progress in the field.

Microphysiological models of the central nervous system with fluid flow

There are over 1,000 described neurological and neurodegenerative disorders affecting nearly 100 million Americans - roughly one third of the U.S. population. Collectively, treatment of neurological conditions is estimated to cost $800 billion every year. Lowering this societal burden will require developing better model systems in which to study these diverse disorders. Microphysiological systems are promising tools for modeling healthy and diseased neural tissues to study mechanisms and treatment of neuropathology. One major benefit of microphysiological systems is the ability to incorporate biophysical forces, namely the forces derived from biological fluid flow. Fluid flow in the central nervous system (CNS) is a complex but important element of physiology, and pathologies as diverse as traumatic or ischemic injury, cancer, neurodegenerative disease, and natural aging have all been found to alter flow pathways. In this review, we summarize recent advances in three-dimensional microphysiological systems for studying the biology and therapy of CNS disorders and highlight the ability and growing need to incorporate biological fluid flow in these miniaturized model systems.

Convection Enhanced Delivery in the Setting of High-Grade Gliomas

Development of effective treatments for high-grade glioma (HGG) is hampered by (1) the blood–brain barrier (BBB), (2) an infiltrative growth pattern, (3) rapid development of therapeutic resistance, and, in many cases, (4) dose-limiting toxicity due to systemic exposure. Convection-enhanced delivery (CED) has the potential to significantly limit systemic toxicity and increase therapeutic index by directly delivering homogenous drug concentrations to the site of disease. In this review, we present clinical experiences and preclinical developments of CED in the setting of high-grade gliomas.