title: Comparison between CT and MR in perfusion imaging assessment of high-grade gliomas.
abstract: OBJECTIVE
  The aim of our study was to compare the relative cerebral blood volume (CBV) values obtained by first-pass dynamic susceptibility-weighted contrast-enhanced (DSC) T2-weighted magnetic resonance (MR) and perfusion computed tomography (P-CT) imaging in high-grade gliomas (HGG) in the same patient population.
  
  
  METHODS
  Sixteen patients with histologically proven HGG underwent P-CT and DSC-MR brain imaging. P-CT studies were obtained using a four-row multislice CT scanner and postprocessed with a commercial software package based on a deconvolution-based technique. DSC-MR images were obtained at 1.5 T with a first-pass dynamic susceptibility contrast-enhanced T2-weighted sequence. P-CT and DSC-MR images were obtained within 4 days of each another, always before surgery. Maximum CBV ratios normalised with contralateral white matter (rCBV) were calculated. Statistical analysis was performed with the classical parametric statistic procedure.
  
  
  RESULTS
  A linear correlation between maximum rCBV values obtained with P-CT and DSC-MR imaging was evident. The best linear model is CT=slope×MR+error and provides a highly significant estimate of the slope equal to 1.08. Thus CT results can be predicted from MR values. Therefore, it is also possible to predict MR results from CT values by estimating the linear model MR=slope×CT+error. DSC-MR imaging gave lower rCBV average values (4.92±1.52) compared with P-CT (5.56±1.55).
  
  
  CONCLUSIONS
  In our population of patients, P-CT and DSC-MR imaging showed proportional results in rCBV assessment of HGGs, and thus both modalities may be used interchangeably in HGG of the brain.
authors.affiliation: UOC Neuroradiologia, Dipartimento di Neuroscienze, AORN G. Rummo, Via dell'Angelo 1, 82100, Benevento, Italy. martadesimone@gmail.com
authors.forename: M
authors.initials: M
authors.lastname: De Simone
authors.forename: C F
authors.initials: CF
authors.lastname: Muccio
authors.forename: S M
authors.initials: SM
authors.lastname: Pagnotta
authors.forename: G
authors.initials: G
authors.lastname: Esposito
authors.forename: A
authors.initials: A
authors.lastname: Cianfoni
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001810:Blood Volume; D001932:Brain Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000473:pathology; D003287:Contrast Media; D003937:Diagnosis, Differential; D005260:Female; D005910:Glioma / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000473:pathology; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007479:Iopamidol / Q000031:analogs & derivatives; D016014:Linear Models; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009942:Organometallic Compounds; D012984:Software; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D003287:Contrast Media; D009942:Organometallic Compounds; C057937:iomeprol; C090600:gadobutrol; D007479:Iopamidol