title: Quantitative pharmacokinetic analysis of DCE-MRI data without an arterial input function: a reference region model.
abstract: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can assess tumor perfusion, microvascular vessel wall permeability and extravascular-extracellular volume fraction. Analysis of DCE-MRI data is usually based on indicator dilution theory that requires knowledge of the concentration of the contrast agent in the blood plasma, the arterial input function (AIF). A method is presented that compares the tissues of interest (TOI) curve shape to that of a reference region (RR), thereby eliminating the need for direct AIF measurement. By assigning literature values for Ktrans (the blood perfusion-vessel permeability product) and v(e) (extravascular-extracellular volume fraction) in a reference tissue, it is possible to extract the Ktrans and v(e) values for a TOI without knowledge of the AIF. The operational RR equation for DCE-MRI analysis is derived, and its sensitivity to noise and incorrect assignment of the RR parameters is tested via simulations. The method is robust at noise levels of 10%, returning accurate (+/-20% in the worst case) and precise (+/-15% in the worst case) values. Errors in the TOI Ktrans and v(e) values scale approximately linearly with the errors in the assigned RR Ktrans and v(e) values. The methodology is then applied to a Lewis Lung Carcinoma mouse tumor model. A slowly enhancing TOI yielded Ktrans=0.039+/-0.002 min-1 and v(e)=0.46+/-0.01, while a rapidly enhancing region yielded Ktrans=0.35+/-0.05 min-1 and v(e)=0.31+/-0.01. Parametric Ktrans and v(e) mappings manifested a tumor periphery with elevated Ktrans (>0.30 min-1) and v(e) (>0.30) values. The main advantage of the RR approach is that it allows for quantitative assessment of tissue properties without having to obtain high temporal resolution images to characterize an AIF. This allows for acquiring images with higher spatial resolution and/or SNR, and therefore, increased ability to probe tissue heterogeneity.
authors.affiliation: Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232-2675, USA. thomas.yankeelov@vanderbilt.edu
authors.forename: Thomas E
authors.initials: TE
authors.lastname: Yankeelov
authors.forename: Jeffrey J
authors.initials: JJ
authors.lastname: Luci
authors.forename: Martin
authors.initials: M
authors.lastname: Lepage
authors.forename: Rui
authors.initials: R
authors.lastname: Li
authors.forename: Laura
authors.initials: L
authors.lastname: Debusk
authors.forename: P Charles
authors.initials: PC
authors.lastname: Lin
authors.forename: Ronald R
authors.initials: RR
authors.lastname: Price
authors.forename: John C
authors.initials: JC
authors.lastname: Gore
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D003287:Contrast Media / Q000493:pharmacokinetics*; D019786:Gadolinium DTPA / Q000493:pharmacokinetics*; D006614:Hindlimb; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D051379:Mice; D008807:Mice, Inbred BALB C; D009374:Neoplasms, Experimental / Q000098:blood supply*; D012680:Sensitivity and Specificity
chemical_list: D003287:Contrast Media; D019786:Gadolinium DTPA