Imaging-Based Algorithm for the Local Grading of Glioma.

Journal: AJNR. American journal of neuroradiology
Published Date: Feb 6, 2020

Abstract

BACKGROUND AND PURPOSE: Gliomas are highly heterogeneous tumors, and optimal treatment depends on identifying and locating the highest grade disease present. Imaging techniques for doing so are generally not validated against the histopathologic criterion standard. The purpose of this work was to estimate the local glioma grade using a machine learning model trained on preoperative image data and spatially specific tumor samples. The value of imaging in patients with brain tumor can be enhanced if pathologic data can be estimated from imaging input using predictive models.

Authors

  • E D H Gates
    From 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.
  • J S Lin
    From 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.
  • J S Weinberg
    From 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.
  • S S Prabhu
    From 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.
  • J Hamilton
    Radiology Partners (J.H.), Houston, Texas.
  • J D Hazle
    Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • G N Fuller
    From 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.
  • V Baladandayuthapani
    Department of Computational Medicine and Bioinformatics (V.B.), University of Michigan School of Public Health, Ann Arbor, Michigan.
  • D T Fuentes
    From 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.
  • D Schellingerhout
    From 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 Dawid.Schellingerhout@mdanderson.org.

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