title: Low-grade (WHO II) and anaplastic (WHO III) gliomas: differences in morphology and MRI signal intensities.
abstract: OBJECTIVE
  To evaluate the diagnostic potential of a multi-factor analysis of morphometric parameters and signal characteristics of brain tumours and peritumoural areas for distinguishing WHO-grade II and III gliomas at magnetic resonance imaging (MRI).
  
  
  METHODS
  MR examinations of 108 patients with histologically proven World Health Organization (WHO) grade II and III gliomas were included. Morphological criteria and MR signal characteristics were evaluated. The data were subjected to a multifactorial logistic regression analysis to differentiate between grade II and grade III gliomas. The discriminatory power was assessed by receiver operating characteristic (ROC).
  
  
  RESULTS
  Logistic regression analysis showed that WHO grade II and III can be distinguished based on contrast enhancement, cortical involvement, margin of the enhancing lesion and maximum diameter (width and length) of the peritumoural area (the so-called tumour infiltration zone). With the final model of logistic regression analysis and with the cut-off value  ≥  0.377, WHO grade III glioma is predicted with a sensitivity of 71.0 % and a specificity of 80.4 %.
  
  
  CONCLUSIONS
  Measurement of maximum diameter of peritumoural area, contrast enhancement as well as cortical involvement and the margin of the contrast-enhancing lesion can be used easily in clinical routine to adequately distinguish WHO grade II from grade III gliomas.
  
  
  CONCLUSIONS
  • MRI offers new information concerning WHO-grade II and III gliomas. • The differentiation between such tumour grades is important for therapeutic decisions. • We assessed differences in enhancement, cortical involvement, margins and peritumoural appearances. • WHO grade III gliomas can be predicted with reasonable sensitivity and specificity.
authors.affiliation: Department of Radiology, Charité-Universitätsmedizin Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353, Berlin, Germany, max-ludwig.schaefer@charite.de.
authors.forename: Max-Ludwig
authors.initials: ML
authors.lastname: Schäfer
authors.forename: Martin H
authors.initials: MH
authors.lastname: Maurer
authors.forename: Michael
authors.initials: M
authors.lastname: Synowitz
authors.forename: Joost
authors.initials: J
authors.lastname: Wüstefeld
authors.forename: Tim
authors.initials: T
authors.lastname: Marnitz
authors.forename: Florian
authors.initials: F
authors.lastname: Streitparth
authors.forename: Edzard
authors.initials: E
authors.lastname: Wiener
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001932:Brain Neoplasms / Q000145:classification* / Q000473:pathology*; D005163:Factor Analysis, Statistical; D005260:Female; D005910:Glioma / Q000145:classification* / Q000473:pathology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D060787:Neoplasm Grading; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D055815:Young Adult