A quantitative model based on clinically relevant MRI features differentiates lower grade gliomas and glioblastoma.

Journal: European radiology
Published Date: Feb 5, 2020

Abstract

OBJECTIVES: To establish a quantitative MR model that uses clinically relevant features of tumor location and tumor volume to differentiate lower grade glioma (LRGG, grades II and III) and glioblastoma (GBM, grade IV).

Authors

  • Hang Cao
    Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, 410008, China.
  • E Zeynep Erson-Omay
    Department of Neurosurgery, Yale School of Medicine, New Haven, CT, 06520, USA.
  • Xuejun Li
  • Murat Günel
    Department of Neurosurgery, Yale School of Medicine, New Haven, CT, 06520, USA.
  • Jennifer Moliterno
    Department of Neurosurgery, Yale School of Medicine, New Haven, CT, 06520, USA.
  • Robert K Fulbright
    Department of Radiology and Biomedical Imaging, MRRC, Yale School of Medicine, The Anlyan Center N137, PO Box 208043, New Haven, CT, 06520-8043, USA. robert.fulbright@yale.edu.

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