• Pattana Wangaryattawanich, Masumeh Hatami, Jixin Wang, Ginu Thomas, Adam Flanders, Justin Kirby, Max Wintermark, Erich S Huang, Ali Shojaee Bakhtiari, Markus M Luedi, Syed S Hashmi, Daniel L Rubin, James Y Chen, Scott N Hwang, John Freymann, Chad A Holder, Pascal O Zinn, and Rivka R Colen.
• Departments of Radiology, University of Texas MD Anderson Cancer Center, Houston, Texas (P.W., M.H., J.W., G.T., A.S.B., M.M.L., R.R.C.); Department of Radiology, Neuroradiology Division, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (P.W.); Department of Radiology, Division of Neuroradiology/ENT, Thomas Jefferson University Hospital, Philadelphia, Pennsylvania (A.F.); Bioinformatics Analyst III, Clinical Monitoring Research Program (CMRP), Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Rockville, Maryland (J.K.); Department of Radiology, Neuroradiology Division, Stanford University, Stanford, California (M.W.); Cancer Research, Sage Bionetworks, Seattle, Washington (E.S.H.); Department of Diagnostic and Interventional Imaging, University of Texas Health Sciences Center, Houston, Texas (S.S.H.); Department of Radiology, Stanford University, Stanford, California (D.L.R.); Department of Radiology, University of California San Diego, San Diego, California (J.Y.C.); Neuroradiology Section, St Jude Children's Research Hospital, Memphis, Tennessee (S.N.H.); Clinical Monitoring Research Program, Leidos Biomedical Research, Inc., Rockville, Maryland (J.F.); Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia (C.A.H.); Department of Neurosurgery, Baylor College of Medicine, Houston, Texas (P.O.Z.); Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, Texas (P.O.Z.); Department of Cancer Systems Imaging, University of Texas MD Anderson Cancer Center, Houston, Texas (R.R.C.).
• Neuro-oncology. 2015 Nov 1; 17 (11): 1525-37.

BackgroundDespite an aggressive therapeutic approach, the prognosis for most patients with glioblastoma (GBM) remains poor. The aim of this study was to determine the significance of preoperative MRI variables, both quantitative and qualitative, with regard to overall and progression-free survival in GBM.MethodsWe retrospectively identified 94 untreated GBM patients from the Cancer Imaging Archive who had pretreatment MRI and corresponding patient outcomes and clinical information in The Cancer Genome Atlas. Qualitative imaging assessments were based on the Visually Accessible Rembrandt Images feature-set criteria. Volumetric parameters were obtained of the specific tumor components: contrast enhancement, necrosis, and edema/invasion. Cox regression was used to assess prognostic and survival significance of each image.ResultsUnivariable Cox regression analysis demonstrated 10 imaging features and 2 clinical variables to be significantly associated with overall survival. Multivariable Cox regression analysis showed that tumor-enhancing volume (P = .03) and eloquent brain involvement (P < .001) were independent prognostic indicators of overall survival. In the multivariable Cox analysis of the volumetric features, the edema/invasion volume of more than 85 000 mm(3) and the proportion of enhancing tumor were significantly correlated with higher mortality (Ps = .004 and .003, respectively).ConclusionsPreoperative MRI parameters have a significant prognostic role in predicting survival in patients with GBM, thus making them useful for patient stratification and endpoint biomarkers in clinical trials.© The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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