Correlating MRE Features with MRI-Based Metrics of Glioma Growth Dynamics

Glioma is a devastating, invasive form of brain cancer with a 36-month median overall survival. The highest grade tumors, glioblastomas, have an even shorter prognosis of about 15 months. A glioma often requires an intense combination of treatments including surgery, chemotherapy, and radiotherapy, often resulting in very damaging side effects. Due to their sensitive location in the brain, which is often difficult to access because of the skull, gliomas are most often visualized using magnetic resonance imaging (MRI), a non-invasive imaging method. Because high grade gliomas (HGGs) are highly aggressive and recurrence is common, patients diagnosed with these tumors stand to significantly benefit from novel, advanced MRI techniques that can lead to better patient-specific tumor characterization and improved response assessment. Magnetic resonance elastography (MRE) is a MRI-based method that measures the mechanical properties of tissue, and has the potential to significantly enhance the ability to distinguish malignant vs. healthy brain tissue by determining spatial differences in physical stiffness. We investigated whether the addition of MRE to standard clinical glioma MRI protocols would provide a more accurate understanding of the extent of tumor invasion. Using routinely available T2-weighted and contrast enhancing T1-weighted clinical MRI images, the Swanson lab has developed the Proliferation-Invasion (PI) model of brain tumor growth. Using this model, we quantify the relative diffusion (D) and proliferation (�) of tumor cells as D/�. Clinical MRIs were segmented in order to parameterize the model and determine these tumor growth metrics for each patient in our retrospective study. Next, we compare these tumor growth metrics with MRE features of physical stiffness of malignant tissue to determine whether there are correlations with the PI model's kinetic parameters. We hypothesized that MRE stiffness measurements would be associated with the PI model of glioma growth and may provide additional patient-specific tumor characterization information useful for optimally choosing treatment and understanding treatment response. MRE has the potential to be a useful addition to the clinical management of glioma and be integral to further understanding tumor growth and invasiveness.