title: A novel method for analyzing DSCE-images with an application to tumor grading.
abstract: OBJECTIVE
  (a) The development of a novel analysis method, named Dynamic pixel intensity Histogram Analysis (DHA) allowing for pixel intensity-histogram-model-parameter fitting of arbitrary-shaped regions defined in dynamic-susceptibility-contrast-enhanced (DSCE) difference MR-image time-series, and (b) its prospective application and evaluation for glioma grading.
  
  
  METHODS
  For each difference-image, pixel intensity histograms of arbitrary-shaped ROIs were computed and fitted using the Levenberg-Marquardt algorithm. Time-dependent histogram center-position- and width-parameters are computed during bolus-passage. The method was applied to 25 patients with low and high grade gliomas.
  
  
  RESULTS
  During bolus outflow-time, histogram-center-position-parameter and histogram-width-parameter reach highest significance levels and discriminate gliomas of different grades. The histogram center-position-parameter discriminated grade-II from grade-III, grade-II from grade-IV but not grade-III from grade-IV. The observed histogram width-parameters discriminated grade-II from grade-III (P < 0.00022), grade-II from grade-IV (P <8.3 10), and grade-III from grade-IV (P < 0.00063).
  
  
  CONCLUSIONS
  DHA is a easy-to-use method for glioma grading; the histogram width parameter is best indicator for histologic grade.
authors.affiliation: Institute of Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, Switzerland. johannes.slotboom@insel.ch
authors.forename: Johannes
authors.initials: J
authors.lastname: Slotboom
authors.forename: Ralph
authors.initials: R
authors.lastname: Schaer
authors.forename: Christoph
authors.initials: C
authors.lastname: Ozdoba
authors.forename: Michael
authors.initials: M
authors.lastname: Reinert
authors.forename: Istvan
authors.initials: I
authors.lastname: Vajtai
authors.forename: Marwan
authors.initials: M
authors.lastname: El-Koussy
authors.forename: Claus
authors.initials: C
authors.lastname: Kiefer
authors.forename: Martin
authors.initials: M
authors.lastname: Zbinden
authors.forename: Gerhard
authors.initials: G
authors.lastname: Schroth
authors.forename: Roland
authors.initials: R
authors.lastname: Wiest
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D001932:Brain Neoplasms / Q000145:classification / Q000175:diagnosis*; D003287:Contrast Media; D005260:Female; D005910:Glioma / Q000145:classification / Q000175:diagnosis*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009942:Organometallic Compounds; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D003287:Contrast Media; D009942:Organometallic Compounds; C090600:gadobutrol