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Abstract #1716

Histogram-based CBF quantification allows prediction of histopathologic grade and molecular markers in de novo brain gliomas

David Lu1, Jay J. Pillai1,2, Hanzhang Lu1, and Yang Li1
1Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 2Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, United States

We developed a histogram-based CBF analysis method for the prediction of tumor histopathologic grade and molecular marker (including IDH1 mutation, ATRX loss, p53 mutation, MGMT methylation, and 1p/19q co-deletion) in a group of de novo brain glioma patients. ASL MRI may be a non-invasive and cost-effective approach to assist in brain tumor diagnosis and prognosis.

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