Abstract #1716

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

David Lu¹, Jay J. Pillai^1,2, 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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