title: Glioma: Application of histogram analysis of pharmacokinetic parameters from T1-weighted dynamic contrast-enhanced MR imaging to tumor grading.
abstract: OBJECTIVE
  The usefulness of pharmacokinetic parameters for glioma grading has been reported based on the perfusion data from parts of entire-tumor volumes. However, the perfusion values may not reflect the entire-tumor characteristics. Our aim was to investigate the feasibility of glioma grading by using histogram analyses of pharmacokinetic parameters including the volume transfer constant, extravascular extracellular space volume per unit volume of tissue, and blood plasma volume per unit volume of tissue from T1-weighted dynamic contrast-enhanced perfusion MR imaging.
  
  
  METHODS
  Twenty-eight patients (14 men, 14 women; mean age, 49.75 years; age range, 25-72 years) with histopathologically confirmed gliomas (World Health Organization grade II, n = 7; grade III, n = 8; grade IV, n = 13) were examined before surgery or biopsy with conventional MR imaging and T1-weighted dynamic contrast-enhanced perfusion MR imaging at 3T. Volume transfer constant, extravascular extracellular space volume per unit volume of tissue, and blood plasma volume per unit volume of tissue were calculated from the entire-tumor volume. Histogram analyses from these parameters were correlated with glioma grades. The parameters with the best percentile from cumulative histograms were identified by analysis of the area under the curve of the receiver operating characteristic analysis and were compared by using multivariable stepwise logistic regression analysis for distinguishing high- from low-grade gliomas.
  
  
  RESULTS
  All parametric values increased with increasing glioma grade. There were significant differences among the 3 grades in all parameters (P < .01). For the differentiation of high- and low-grade gliomas, the highest area under the curve values were found at the 98th percentile of the volume transfer constant (area under the curve, 0.912; cutoff value, 0.277), the 90th percentile of extravascular extracellular space volume per unit volume of tissue (area under the curve, 0.939; cutoff value, 19.70), and the 84th percentile of blood plasma volume per unit volume of tissue (area under the curve, 0.769; cutoff value, 11.71). The 98th percentile volume transfer constant value was the only variable that could be used to independently differentiate high- and low-grade gliomas in multivariable stepwise logistic regression analysis.
  
  
  CONCLUSIONS
  Histogram analysis of pharmacokinetic parameters from whole-tumor volume data can be a useful method for glioma grading. The 98th percentile value of the volume transfer constant was the most significant measure.
authors.affiliation: From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.).
authors.forename: S C
authors.initials: SC
authors.lastname: Jung
authors.affiliation: From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.).
authors.forename: J A
authors.initials: JA
authors.lastname: Yeom
authors.affiliation: From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.).
authors.forename: J-H
authors.initials: JH
authors.lastname: Kim
authors.affiliation: From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.).
authors.forename: I
authors.initials: I
authors.lastname: Ryoo
authors.affiliation: From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.).
authors.forename: S C
authors.initials: SC
authors.lastname: Kim
authors.affiliation: From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.).
authors.forename: H
authors.initials: H
authors.lastname: Shin
authors.affiliation: From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.).
authors.forename: A L
authors.initials: AL
authors.lastname: Lee
authors.affiliation: From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.).
authors.forename: T J
authors.initials: TJ
authors.lastname: Yun
authors.affiliation: Neurosurgery (C.-K.P.).
authors.forename: C-K
authors.initials: CK
authors.lastname: Park
authors.affiliation: From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.).
authors.forename: C-H
authors.initials: CH
authors.lastname: Sohn
authors.affiliation: Pathology (S.-H.P.), Seoul National University College of Medicine, Seoul, Republic of Korea.
authors.forename: S-H
authors.initials: SH
authors.lastname: Park
authors.affiliation: From the Departments of Radiology (S.C., J.a.Y., J.-H.K., I.R., S.C.K., H.S., A.L.L., T.J.Y., C.-H.S., S.H.C.)Center for Nanoparticle Research (S.H.C.), Institute for Basic Science, and School of Chemical and Biological Engineering, Seoul National University, Seoul, Republic of Korea. verocay@snuh.org.
authors.forename: S H
authors.initials: SH
authors.lastname: Choi
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D001932:Brain Neoplasms / Q000145:classification / Q000378:metabolism* / Q000473:pathology*; D003198:Computer Simulation; D003287:Contrast Media / Q000493:pharmacokinetics; D003627:Data Interpretation, Statistical; D005260:Female; D005910:Glioma / Q000145:classification / Q000378:metabolism* / 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; D015233:Models, Statistical; D060787:Neoplasm Grading; D009716:Numerical Analysis, Computer-Assisted; D009942:Organometallic Compounds / Q000493:pharmacokinetics*; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012680:Sensitivity and Specificity
chemical_list: D003287:Contrast Media; D009942:Organometallic Compounds; C090600:gadobutrol