title: A novel AIF tracking method and comparison of DCE-MRI parameters using individual and population-based AIFs in human breast cancer.
abstract: Quantitative analysis of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data requires the accurate determination of the arterial input function (AIF). A novel method for obtaining the AIF is presented here and pharmacokinetic parameters derived from individual and population-based AIFs are then compared. A Philips 3.0 T Achieva MR scanner was used to obtain 20 DCE-MRI data sets from ten breast cancer patients prior to and after one cycle of chemotherapy. Using a semi-automated method to estimate the AIF from the axillary artery, we obtain the AIF for each patient, AIF(ind), and compute a population-averaged AIF, AIF(pop). The extended standard model is used to estimate the physiological parameters using the two types of AIFs. The mean concordance correlation coefficient (CCC) for the AIFs segmented manually and by the proposed AIF tracking approach is 0.96, indicating accurate and automatic tracking of an AIF in DCE-MRI data of the breast is possible. Regarding the kinetic parameters, the CCC values for K(trans), v(p) and v(e) as estimated by AIF(ind) and AIF(pop) are 0.65, 0.74 and 0.31, respectively, based on the region of interest analysis. The average CCC values for the voxel-by-voxel analysis are 0.76, 0.84 and 0.68 for K(trans), v(p) and v(e), respectively. This work indicates that K(trans) and v(p) show good agreement between AIF(pop) and AIF(ind) while there is a weak agreement on v(e).
authors.affiliation: Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, USA.
authors.forename: Xia
authors.initials: X
authors.lastname: Li
authors.forename: E Brian
authors.initials: EB
authors.lastname: Welch
authors.forename: Lori R
authors.initials: LR
authors.lastname: Arlinghaus
authors.forename: A Bapsi
authors.initials: AB
authors.lastname: Chakravarthy
authors.forename: Lei
authors.initials: L
authors.lastname: Xu
authors.forename: Jaime
authors.initials: J
authors.lastname: Farley
authors.forename: Mary E
authors.initials: ME
authors.lastname: Loveless
authors.forename: Ingrid A
authors.initials: IA
authors.lastname: Mayer
authors.forename: Mark C
authors.initials: MC
authors.lastname: Kelley
authors.forename: Ingrid M
authors.initials: IM
authors.lastname: Meszoely
authors.forename: Julie A
authors.initials: JA
authors.lastname: Means-Powell
authors.forename: Vandana G
authors.initials: VG
authors.lastname: Abramson
authors.forename: Ana M
authors.initials: AM
authors.lastname: Grau
authors.forename: John C
authors.initials: JC
authors.lastname: Gore
authors.forename: Thomas E
authors.initials: TE
authors.lastname: Yankeelov
mesh_terms: D000465:Algorithms; D001366:Axillary Artery / Q000503:physiopathology*; D001943:Breast Neoplasms / Q000098:blood supply* / Q000175:diagnosis / Q000188:drug therapy; D003198:Computer Simulation; D003287:Contrast Media / Q000493:pharmacokinetics*; D005260:Female; 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*; D008954:Models, Biological; D055420:Perfusion Imaging / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D003287:Contrast Media; D019786:Gadolinium DTPA