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.

BACKGROUND: Glioblastoma (GBM) is the deadliest and most common brain tumor in adults, with poor survival and response to aggressive therapy. Limited access of drugs to tumor cells is one reason for such grim clinical outcomes. A driving force for therapeutic delivery is interstitial fluid flow (IFF), both within the tumor and in the surrounding brain parenchyma. However, convective and diffusive transport mechanisms are understudied. In this study, we examined the application of a novel image analysis method to measure fluid flow and diffusion in GBM patients. METHODS: Here, we applied an imaging methodology that had been previously tested and validated in vitro, in silico, and in preclinical models of disease to archival patient data from the Ivy Glioblastoma Atlas Project (GAP) dataset. The analysis required the use of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which is readily available in the database. The analysis results, which consisted of IFF flow velocity and diffusion coefficients, were then compared to patient outcomes such as survival. RESULTS: We characterized IFF and diffusion patterns in patients. We found strong correlations between flow rates measured within tumors and in the surrounding parenchymal space, where we hypothesized that velocities would be higher. Analyzing overall magnitudes indicated a significant correlation with both age and survival in this patient cohort. Additionally, we found that neither tumor size nor resection significantly altered the velocity magnitude. Lastly, we mapped the flow pathways in patient tumors and found a variability in the degree of directionality that we hypothesize may lead to information concerning treatment, invasive spread, and progression in future studies. CONCLUSIONS: An analysis of standard DCE-MRI in patients with GBM offers more information regarding IFF and transport within and around the tumor, shows that IFF is still detected post-resection, and indicates that velocity magnitudes correlate with patient prognosis.

Frequency-specific, valveless flow control in insect-mimetic microfluidic devices.

Inexpensive, portable lab-on-a-chip devices would revolutionize fields like environmental monitoring and global health, but current microfluidic chips are tethered to extensive off-chip hardware. Insects, however, are self-contained and expertly manipulate fluids at the microscale using largely unexplored methods. We fabricated a series of microfluidic devices that mimic key features of insect respiratory kinematics observed by synchrotron-radiation imaging, including the collapse of portions of multiple respiratory tracts in response to a single fluctuating pressure signal. In one single-channel device, the flow rate and direction could be controlled by the actuation frequency alone, without the use of internal valves. Additionally, we fabricated multichannel chips whose individual channels responded selectively (on with a variable, frequency-dependent flow rate, or off) to a single, global actuation frequency. Our results demonstrate that insect-mimetic designs have the potential to drastically reduce the actuation overhead for microfluidic chips, and that insect respiratory systems may share features with impedance-mismatch pumps.

Methods to measure, model and manipulate fluid flow in brain.

The brain consists of a complex network of cells and matrix that is cushioned and nourished by multiple types of fluids: cerebrospinal fluid, blood, and interstitial fluid. The movement of these fluids through the tissues has recently gained more attention due to implications in Alzheimer's Disease and glioblastoma. Therefore, methods to study these fluid flows are necessary and timely for the current study of neuroscience. Imaging modalities such as magnetic resonance imaging have been used clinically and pre-clinically to image flows in healthy and diseased brains. These measurements have been used to both parameterize and validate models of fluid flow both computational and in vitro. Both of these models can elucidate the changes to fluid flow that occur during disease and can assist in linking the compartments of fluid flow with one another, a difficult challenge experimentally. In vitro models, though in limited use with fluid flow, allow the examination of cellular responses to physiological flow. To determine causation, in vivo methods have been developed to manipulate flow, including both physical and pharmacological manipulations, at each point of fluid movement of origination resulting in exciting findings in the preclinical setting. With new targets, such as the brain-draining lymphatics and glymphatic system, fluid flow and tissue drainage within the brain is an exciting and growing research area. In this review, we discuss the methods that currently exist to examine and test hypotheses related to fluid flow in the brain as we attempt to determine its impact on neural function.