Role of Tissue Hydraulic Permeability in Convection-Enhanced Delivery of Nanoparticle-Encapsulated Chemotherapy Drugs to Brain Tumour

Exploring tissue permeability of brain tumours in different grades: Insights from pore-scale fluid dynamics analysis

Interstitial fluid (ISF) flow is identified as an essential physiological process that plays an important role in the development and progression of brain tumours. However, the relationship between the permeability of the tumour tissue, a complex porous medium, and the interstitial fluid flow around the tumour cells at the microscale is not well understood. To shed light on this issue, and in the absence of experimental techniques that can provide direct measurements, we develop a computational model to predict the tissue permeability of brain tumours in different grades by analysing the ISF flow at the pore scale. The 3-D geometrical models of tissue extracellular spaces are digitally reconstructed for each grade tumour based on their morphological properties measured from microscopic images. The predictive accuracy of the framework is validated by experimental results reported in the literature. Our results indicate that high-grade brain tumours are less permeable despite their higher porosity, whereas necrotic areas of glioblastoma are more permeable than the viable tumour areas. This implies that tissue permeability is primarily governed by both tissue porosity and the deposition of hyaluronic acid (HA), a key component of the extracellular matrix, while the HA deposition can have a greater effect than macro-level porosity. Parametric studies show that tissue permeability falls exponentially with increasing HA concentration in all grades of brain tumours, and this can be captured using an empirically derived relationship in a quantitative manner. These findings provide an improved understanding of the hydraulic properties of brain tumours and their intrinsic links to tumour microstructure. This work can be used to reveal the intratumoural physiochemical processes that rely on fluid flow and offer a powerful tool to tune textured and porous biomaterials for desired transport properties. STATEMENT OF SIGNIFICANCE: Interstitial fluid flow in the extracellular space of brain tumours plays a crucial role in their progression, development, and response to drug treatments. However, the mechanisms of interstitial fluid transport around tumour cells and the characterization of these microscale transports at the tissue scale to meet clinical requirements are largely unknown. In the absence of advanced experimental techniques to capture these pore-scale transport phenomena, we have developed and validated a computational framework to successfully reveal these phenomena across all grades of brain tumours. For the first time, we have quantitatively determined the tissue permeability of all grades of brain tumours as a function of the concentration of hyaluronic acid, a key component of the extracellular matrix. This framework will enhance our ability to capture the intratumoural physicochemical processes in brain tumours and correlate them with tumour tissue-scale behaviours.

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.

The Influence of Size on the Intracranial Distribution of Biomedical Nanoparticles Administered by Convection-enhanced Delivery in Minipigs

Because of the blood-brain barrier (BBB), successful drug delivery to the brain has long been a key objective for the medical community, calling for pioneering technologies to overcome this challenge. Convection-enhanced delivery (CED), a form of direct intraparenchymal microinfusion, shows promise but requires optimal infusate design and real-time distribution monitoring. The size of the infused substances appears to be especially critical, with current knowledge being limited. Herein, we examined the intracranial administration of polyethylene glycol (PEG)-coated nanoparticles (NPs) of various sizes using CED in groups of healthy minipigs (n = 3). We employed stealth liposomes (LIPs, 130 nm) and two gold nanoparticle designs (AuNPs) of different diameters (8 and 40 nm). All were labeled with copper-64 for quantitative and real-time monitoring of the infusion via positron emission tomography (PET). NPs were infused via two catheters inserted bilaterally in the putaminal regions of the animals. Our results suggest CED with NPs holds promise for precise brain drug delivery, with larger LIPs exhibiting superior distribution volumes and intracranial retention over smaller AuNPs. PET imaging alongside CED enabled dynamic visualization of the process, target coverage, timely detection of suboptimal infusion, and quantification of distribution volumes and concentration gradients. These findings may augment the therapeutic efficacy of the delivery procedure while mitigating unwarranted side effects associated with nonvisually monitored delivery approaches. This is of vital importance, especially for chronic intermittent infusions through implanted catheters, as this information enables informed decisions for modulating targeted infusion volumes on a catheter-by-catheter, patient-by-patient basis.

Physico-chemical characterization of the tumour microenvironment of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive lethal malignancy that accounts for more than 90% of pancreatic cancer diagnoses. Our research is focused on the physico-chemical properties of the tumour microenvironment (TME), including its tumoural extracellular matrix (tECM), as they may have an important impact on the success of cancer therapies. PDAC xenografts and their decellularized tECM offer a great material source for research in terms of biomimicry with the original human tumour. Our aim was to evaluate and quantify the physico-chemical properties of the PDAC TME. Both cellularized (native TME) and decellularized (tECM) patient-derived PDAC xenografts were analyzed. A factorial design of experiments identified an optimal combination of factors for effective xenograft decellularization. Our results provide a complete advance in our understanding of the PDAC TME and its corresponding stroma, showing that it presents an interconnected porous architecture with very low permeability and small pores due to the contractility of the cellular components. This fact provides a potential therapeutic strategy based on the therapeutic agent size.

Linking fluid-axons interactions to the macroscopic fluid transport properties of the brain

Many brain disorders, including Alzheimer's Disease and Parkinson's Disease, and drug delivery procedures are linked to fluid transport in the brain; yet, while neurons are extremely soft and can be easily deformed, how the microscale channel flow interacts with the neuronal structures (especially axons) deformation and how these interactions affect the macroscale tissue function and transport properties is poorly understood. Misrepresenting these relationships may lead to the erroneous prediction of e.g. disease spread, drug delivery, and nerve injury in the brain. However, understanding fluid-neuron interactions is an outstanding challenge because the behaviours of both phases are not only dynamic but also occur at an extremely small length scale (the width of the flow channel is ∼100 nm), which cannot be captured by state-of-the-art experimental techniques. Here, by explicitly simulating the dynamics of the flow and axons at the microstructural level, we, for the first time, establish the link between micromechanical tissue response to the physical laws governing the macroscopic transport property of the brain white matter. We found that interactions between axons and the interstitial flow are very strong, thus playing an essential role in the brain fluid/mass transport. Furthermore, we proposed the first anisotropic pressure-dependent permeability tensor informed by microstructural dynamics for more accurate brain modelling at the macroscale, and analysed the effect of the variation of the microstructural parameters that influence such tensor. These findings will shed light on some unsolved issues linked to brain functions and medical treatments relying on intracerebral transport, and the mathematical model provides a framework to more realistically model the brain and design brain-tissue-like biomaterials. STATEMENT OF SIGNIFICANCE: This study reveals how neurons interact with the fluid flowing around them and how these microscale interactions affect macroscale transport behaviour of the brain tissue. The findings provide unprecedented insights into some unsolved issues linked to brain functions and medical treatments relying on intracerebral fluid transport. Furthermore, we, for the first time, established a microstructure-informed permeability tensor as a function of local hydraulic pressure and pressure gradient for the brain tissue, which inherently captures the dynamic transport property of the brain. This study is a cornerstone to advance the predicting accuracy of brain tissue transport property and neural tissue engineering.

Mathematical Optimisation of Magnetic Nanoparticle Diffusion in the Brain White Matter

Magnetic nanoparticles (MNPs) are a promising drug delivery system to treat brain diseases, as the particle transport trajectory can be manipulated by an external magnetic field. However, due to the complex microstructure of brain tissues, particularly the arrangement of nerve fibres in the white matter (WM), how to achieve desired drug distribution patterns, e.g., uniform distribution, is largely unknown. In this study, by adopting a mathematical model capable of capturing the diffusion trajectories of MNPs, we conducted a pilot study to investigate the effects of key parameters in the MNP delivery on the particle diffusion behaviours in the brain WM microstructures. The results show that (i) a uniform distribution of MNPs can be achieved in anisotropic tissues by adjusting the particle size and magnetic field; (ii) particle size plays a key role in determining MNPs' diffusion behaviours. The magnitude of MNP equivalent diffusivity is reversely correlated to the particle size. The MNPs with a dimension greater than 90 nm cannot reach a uniform distribution in the brain WM even in an external magnitude field; (iii) axon tortuosity may lead to transversely anisotropic MNP transport in the brain WM; however, this effect can be mitigated by applying an external magnetic field perpendicular to the local axon track. This study not only advances understanding to answer the question of how to optimise MNP delivery, but also demonstrates the potential of mathematical modelling to help achieve desired drug distributions in biological tissues with a complex microstructure.