Imaging-Based Algorithm for the Local Grading of Glioma

^aFrom the Departments of Imaging Physics (E.D.H.G., J.S.L., J.D.H., D.T.F.), Neurosurgery (J.S.W., S.S.P.), Pathology (G.N.F.), Neuroradiology (D.S.), and Cancer Systems Imaging (D.S.), University of Texas MD Anderson Cancer Center, Houston, Texas
^bUniversity of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences (E.D.H.G.), Houston, Texas
^cBaylor College of Medicine (J.S.L.), Houston, Texas
^dDepartment of Bioengineering (J.S.L.), Rice University, Houston, Texas
^eRadiology Partners (J.H.), Houston, Texas
^fDepartment of Computational Medicine and Bioinformatics (V.B.), University of Michigan School of Public Health, Ann Arbor, Michigan.

Please address correspondence to Dawid Schellingerhout, MD, Neuroradiology and Cancer Systems Imaging, University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1482, Houston, TX 77030; e-mail: Dawid.Schellingerhout{at}mdanderson.org

Funding

Partial support for this study are provided by the Dunn Chair funds (to Dr Bill Murphy), the M D Anderson Cancer Center Internal Research Grant and Clinical Research Support mechanisms for physician-sponsored clinical trials, and the Greenspun neurosurgical research fund.
National Cancer Institute
P30 CA016672; R01-CA160736; R01-CA194391