title: Diagnostic performance of whole brain volume perfusion CT in intra-axial brain tumors: preoperative classification accuracy and histopathologic correlation.
abstract: BACKGROUND
  To evaluate the preoperative diagnostic power and classification accuracy of perfusion parameters derived from whole brain volume perfusion CT (VPCT) in patients with cerebral tumors.
  
  
  METHODS
  Sixty-three patients (31 male, 32 female; mean age 55.6 ± 13.9 years), with MRI findings suspected of cerebral lesions, underwent VPCT. Two readers independently evaluated VPCT data. Volumes of interest (VOIs) were marked circumscript around the tumor according to maximum intensity projection volumes, and then mapped automatically onto the cerebral blood volume (CBV), flow (CBF) and permeability Ktrans perfusion datasets. A second VOI was placed in the contra lateral cortex, as control. Correlations among perfusion values, tumor grade, cerebral hemisphere and VOIs were evaluated. Moreover, the diagnostic power of VPCT parameters, by means of positive and negative predictive value, was analyzed.
  
  
  RESULTS
  Our cohort included 32 high-grade gliomas WHO III/IV, 18 low-grade I/II, 6 primary cerebral lymphomas, 4 metastases and 3 tumor-like lesions. Ktrans demonstrated the highest sensitivity, specificity and positive predictive value, with a cut-off point of 2.21 mL/100mL/min, for both the comparisons between high-grade versus low-grade and low-grade versus primary cerebral lymphomas. However, for the differentiation between high-grade and primary cerebral lymphomas, CBF and CBV proved to have 100% specificity and 100% positive predictive value, identifying preoperatively all the histopathologically proven high-grade gliomas.
  
  
  CONCLUSIONS
  Volumetric perfusion data enable the hemodynamic assessment of the entire tumor extent and provide a method of preoperative differentiation among intra-axial cerebral tumors with promising diagnostic accuracy.
authors.affiliation: Department of Neuroradiology, Georg-August University, University Hospital of Goettingen, Robert-Koch Strasse 40, 37075 Goettingen, Germany. argyro.xyda@med.uni-goettingen.de
authors.forename: Argyro
authors.initials: A
authors.lastname: Xyda
authors.forename: Ulrike
authors.initials: U
authors.lastname: Haberland
authors.forename: Ernst
authors.initials: E
authors.lastname: Klotz
authors.forename: Klaus
authors.initials: K
authors.lastname: Jung
authors.forename: Hans Christoph
authors.initials: HC
authors.lastname: Bock
authors.forename: Ramona
authors.initials: R
authors.lastname: Schramm
authors.forename: Michael
authors.initials: M
authors.lastname: Knauth
authors.forename: Peter
authors.initials: P
authors.lastname: Schramm
mesh_terms: D000465:Algorithms; D001932:Brain Neoplasms / Q000150:complications / Q000000981:diagnostic imaging / Q000473:pathology*; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009389:Neovascularization, Pathologic / Q000000981:diagnostic imaging / Q000209:etiology / Q000473:pathology*; D055420:Perfusion Imaging / Q000379:methods*; D011300:Preoperative Care; D011379:Prognosis; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*; D047368:Tumor Burden