BME MS Defense: Divya Raman

In Vitro And In Vivo Quantification of Glioma Cell MPIO Uptake, Long-Term Viability and Motility And Implications for Modeling the Spread of Brain Cancer

Supervised by Prof. Walter O'Dell

Abstract

Brain tumor recurrence in humans has been shown to occur more frequently along white matter tracts. We have developed a computational model for migration of cancer cells that is influenced by the underlying brain fiber architecture measured from Magnetic Resonance Diffusion Tensor Imaging (MR-DTI). The long-term objective is to refine this theoretical computational model of cell migration into a robust and evidence-based computational model to predict the spread of brain tumor that can then be applied clinically for radiation treatment planning. This study aims at developing an animal model to study glioma cell spread pattern in rats and also establish the use of MPIO (micrometer sized paramagnetic iron oxide particles- an MR contrast agent) labeling and cell tracking to monitor the migration patterns of native glioma cells.

Results obtained have demonstrated that our computational model, when applied to a rat brain DTI data set, can demonstrate elongated migration along major fibers when compared to gray matter. Through histological analysis, it has been shown that real tumor cells migrate farther in vivo from the site of engraftment along major fiber tracts compared to gray matter. It has also been verified that MPIO labeling does not affect motility and viability of CNS-1 glioma cells, thereby facilitating the possibility of utilizing these particles for tracking cells over long periods of time. Thus, the study suggests that MPIO labeling can be used in future studies to track in vivo CNS-1 rat glioma cell migration with MRI, the goal being to quantify critical physiologic cell migration parameters such as in vivo migration velocity, persistence in direction and strength of affinity for fiber bundles, which can then be used to extend the existing model with details from real physiological parameters.