title: Magnetic resonance dispersion imaging for localization of angiogenesis and cancer growth.
abstract: OBJECTIVE
  Cancer angiogenesis can be imaged by using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Pharmacokinetic modeling can be used to assess vascular perfusion and permeability, but the assessment of angiogenic changes in the microvascular architecture remains challenging. This article presents 2 models enabling the characterization of the microvascular architecture by DCE-MRI.
  
  
  BACKGROUND
  The microvascular architecture is reflected in the dispersion coefficient according to the convective dispersion equation. A solution of this equation, combined with the Tofts model, permits defining a dispersion model for magnetic resonance imaging. A reduced dispersion model is also presented.
  
  
  METHODS
  The proposed models were evaluated for prostate cancer diagnosis. Dynamic contrast-enhanced magnetic resonance imaging was performed, and concentration-time curves were calculated in each voxel. The simultaneous generation of parametric maps related to permeability and dispersion was obtained through model fitting. A preliminary validation was carried out through comparison with the histology in 15 patients referred for radical prostatectomy.
  
  
  RESULTS
  Cancer localization was accurate with both dispersion models, with an area under the receiver operating characteristic curve greater than 0.8. None of the compared parameters, aimed at assessing vascular permeability and perfusion, showed better results.
  
  
  CONCLUSIONS
  A new DCE-MRI method is proposed to characterize the microvascular architecture through the assessment of intravascular dispersion, without the need for separate arterial-input-function estimation. The results are promising and encourage further research.
authors.affiliation: From the *Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven; Departments of †Radiology, ‡Urology, Academic Medical Center, University of Amsterdam, Amsterdam; §Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven; and ∥Department of MR Clinical Science, Philips Healthcare, Best, the Netherlands.
authors.forename: Massimo
authors.initials: M
authors.lastname: Mischi
authors.forename: Simona
authors.initials: S
authors.lastname: Turco
authors.forename: Cristina
authors.initials: C
authors.lastname: Lavini
authors.forename: Kyveli
authors.initials: K
authors.lastname: Kompatsiari
authors.forename: Jean J M C H
authors.initials: JJ
authors.lastname: de la Rosette
authors.forename: Marcel
authors.initials: M
authors.lastname: Breeuwer
authors.forename: Hessel
authors.initials: H
authors.lastname: Wijkstra
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003287:Contrast Media / Q000493:pharmacokinetics; D005240:Feasibility Studies; D019786:Gadolinium DTPA / Q000493:pharmacokinetics; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D055806:Microvessels / Q000378:metabolism / Q000473:pathology*; D008954:Models, Biological; D009389:Neovascularization, Pathologic / Q000209:etiology / Q000378:metabolism / Q000473:pathology*; D011471:Prostatic Neoplasms / Q000150:complications / Q000378:metabolism / Q000473:pathology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D047368:Tumor Burden
chemical_list: D003287:Contrast Media; D019786:Gadolinium DTPA