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“Traditionally, glioblastoma patients are given this diagnosis based on the histology of their tumor, and then assigned a grade and a stage,” said Daniel Rubin, MD, associate professor of biomedical data science, of radiology and of medicine. “But this information is not always specific enough to clearly inform treatment. We’ve developed a new method of classifying glioblastomas by quantitatively analyzing the magnetic resonance imaging that is routinely performed during diagnosis.” Rubin is the senior author of the study, which will be published online Dec. 22 in Neuro-Oncology. Postdoctoral scholar Tiffany Ting Liu, PhD, is the lead author of the paper. A deadly brain tumor Glioblastoma is one of the most common, and most deadly, brain tumors. About 12,000 people in the United States are diagnosed each year. The median survival is about 15 months after diagnosis. Until recently, clinicians and patients pinned their hopes on a class of chemotherapy drugs called anti-angiogenic compounds that are meant to block the growth of new blood vessels into the tumor. Blocking this growth, they believed, should starve the tumors of oxygen and nutrients.
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