title: Enhancing fraction in glioma and its relationship to the tumoral vascular microenvironment: A dynamic contrast-enhanced MR imaging study.
abstract: OBJECTIVE
  EnF is a newly described measure of proportional tumor enhancement derived from DCE-MR imaging. The aim of this study was to assess the relationship between EnF and the more established DCE-MR imaging parameters: K(trans), v(e), and v(p).
  
  
  METHODS
  Forty-two patients with 43 gliomas (16 grade II, 3 grade III, and 24 grade IV) were studied. Imaging included pre- and postcontrast T1-weighted sequences through the lesion and T1-weighted DCE-MR imaging. Parametric maps of EnF, K(trans), v(e), and v(p) were generated. Voxels were classified as enhancing if the IAUC was positive (EnF(IAUC)(60>0)). A threshold of IAUC > 2.5 mmol.s was used to generate EnF(IAUC)(60>2.5). Both measures of EnF were compared with the DCE-MR imaging parameters (K(trans), v(e), and v(p)).
  
  
  RESULTS
  In grade II gliomas, EnF(IAUC60>0) and EnF(IAUC60>2.5) correlated with v(p) (R(2) = 0.6245, P < .0005; and R(2) = 0.4727, P = .003) but not with K(trans) or v(e). In grade IV tumors, both EnF(IAUC60>0) and EnF(IAUC60>2.5) correlated with K(trans) (R(2) = 0.3501, P = .001; and R(2) = 0.4699, P < .0005) and v(p) (R(2) = 0.1564, P = .01; and R(2) = 0.2429, P = .007), but not with v(e). Multiple regression analysis showed K(trans) as the only independent correlate of both EnF(IAUC60>0) and EnF(IAUC60>2.5) for grade IV tumors.
  
  
  CONCLUSIONS
  This study suggests that in grade II tumors, EnF reflects v(p) and varies due to changes in vascular density. In grade IV gliomas, EnF is affected by K(trans) with secondary associated changes in v(p).
authors.affiliation: University of Manchester, United Kingdom. samantha.mills@manchester.ac.uk
authors.forename: S J
authors.initials: SJ
authors.lastname: Mills
authors.forename: C
authors.initials: C
authors.lastname: Soh
authors.forename: J P B
authors.initials: JP
authors.lastname: O'Connor
authors.forename: C J
authors.initials: CJ
authors.lastname: Rose
authors.forename: G
authors.initials: G
authors.lastname: Buonaccorsi
authors.forename: S
authors.initials: S
authors.lastname: Cheung
authors.forename: S
authors.initials: S
authors.lastname: Zhao
authors.forename: G J M
authors.initials: GJ
authors.lastname: Parker
authors.forename: A
authors.initials: A
authors.lastname: Jackson
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D001932:Brain Neoplasms / Q000098:blood supply* / Q000473:pathology / Q000601:surgery; D003198:Computer Simulation; D003287:Contrast Media / Q000008:administration & dosage; D003937:Diagnosis, Differential; D005260:Female; D019786:Gadolinium DTPA; D005910:Glioma / Q000098:blood supply* / Q000473:pathology / Q000601:surgery; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009389:Neovascularization, Pathologic / Q000175:diagnosis* / Q000473:pathology / Q000601:surgery; D012680:Sensitivity and Specificity; D012984:Software; D013223:Statistics as Topic; D055815:Young Adult
chemical_list: D003287:Contrast Media; C064925:gadodiamide; D019786:Gadolinium DTPA