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recent work

Understanding the micro-environment of brain tumors

Waker, C.A., Keoni, C., Schurko, B., Brown, T.L., Lober, R.M. Hypoxia-inducible factors regulate diffuse intrinsic pontine glioma growth in normoxic culture. International Society for Pediatric Neuro-Oncology. Denver, CO. July 1, 2018.

Waker, C.A., Shahin, M., Kamian, A., Lober, Z.C., Lober, R.M. Differential hypoxic response in human DIPG cell lines. Society for Neuro-Oncology. New York, NY. June 15-16, 2017.

Portions of DIPG tumors have low blood flow and poor oxygenation, which activates proteins known as hypoxia-inducible factors (HIF). This potentially causes them to behave more aggressively. In these studies we found that individual DIPG tumors had distinct responses to low oxygen. In general HIF proteins appeared to be activated regardless of how much oxygen was present, impacting tumor growth and metabolism.

Machine learning to understand the variable microscopic conditions found within brain tumors

Parker, J.G., Diller, E.E., Lober, R.M. Quantifying individual and collective prediction accuracy of MR contrasts for glioma tissue compartment classification. International Society for Magnetic Resonance in Medicine / European Society for Magnetic Resonance in Medicine and Biology. Paris, France. June 19, 2018.

This is pioneering work spearheaded by our collaborator Dr. Jason Parker at Indiana University. It is a mathematical approach to classifying types of brain tumor tissue based on clinical imaging. Machine learning was applied to understand how each piece of information from an MRI scan can contribute to a computer’s ability to classify the tumor tissue into specific categories, which may be used in the future to help with diagnosis, prognosis, and treatment planning.





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