title: Multiparametric analysis of magnetic resonance images for glioma grading and patient survival time prediction.
abstract: BACKGROUND
  A systematic comparison of magnetic resonance imaging (MRI) options for glioma diagnosis is lacking.
  
  
  OBJECTIVE
  To investigate multiple MR-derived image features with respect to diagnostic accuracy in tumor grading and survival prediction in glioma patients.
  
  
  METHODS
  T1 pre- and post-contrast, T2 and dynamic susceptibility contrast scans of 74 glioma patients with histologically confirmed grade were acquired. For each patient, a set of statistical features was obtained from the parametric maps derived from the original images, in a region-of-interest encompassing the tumor volume. A forward stepwise selection procedure was used to find the best combinations of features for grade prediction with a cross-validated logistic model and survival time prediction with a cox proportional-hazards regression.
  
  
  RESULTS
  Presence/absence of enhancement paired with kurtosis of the FM (first moment of the first-pass curve) was the feature combination that best predicted tumor grade (grade II vs. grade III-IV; median AUC = 0.96), with the main contribution being due to the first of the features. A lower predictive value (median AUC = 0.82) was obtained when grade IV tumors were excluded. Presence/absence of enhancement alone was the best predictor for survival time, and the regression was significant (P < 0.0001).
  
  
  CONCLUSIONS
  Presence/absence of enhancement, reflecting transendothelial leakage, was the feature with highest predictive value for grade and survival time in glioma patients.
authors.affiliation: Department of Circulation and Medical Imaging, NTNU, Trondheim, Norway. benjamin.garzon@ntnu.no
authors.forename: Benjamín
authors.initials: B
authors.lastname: Garzón
authors.forename: Kyrre E
authors.initials: KE
authors.lastname: Emblem
authors.forename: Kim
authors.initials: K
authors.lastname: Mouridsen
authors.forename: Baard
authors.initials: B
authors.lastname: Nedregaard
authors.forename: Paulina
authors.initials: P
authors.lastname: Due-Tønnessen
authors.forename: Terje
authors.initials: T
authors.lastname: Nome
authors.forename: John K
authors.initials: JK
authors.lastname: Hald
authors.forename: Atle
authors.initials: A
authors.lastname: Bjørnerud
authors.forename: Asta K
authors.initials: AK
authors.lastname: Håberg
authors.forename: Yngve
authors.initials: Y
authors.lastname: Kvinnsland
mesh_terms: D000328:Adult; D000368:Aged; D001932:Brain Neoplasms / Q000401:mortality* / Q000473:pathology*; D005260:Female; D005910:Glioma / Q000401:mortality* / Q000473:pathology*; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D060787:Neoplasm Grading / Q000379:methods*