title: Automatic individual arterial input functions calculated from PCA outperform manual and population-averaged approaches for the pharmacokinetic modeling of DCE-MR images.
abstract: BACKGROUND
  To introduce a segmentation method to calculate an automatic arterial input function (AIF) based on principal component analysis (PCA) of dynamic contrast enhanced MR (DCE-MR) imaging and compare it with individual manually selected and population-averaged AIFs using calculated pharmacokinetic parameters.
  
  
  METHODS
  The study included 65 individuals with prostate examinations (27 tumors and 38 controls). Manual AIFs were individually extracted and also averaged to obtain a population AIF. Automatic AIFs were individually obtained by applying PCA to volumetric DCE-MR imaging data and finding the highest correlation of the PCs with a reference AIF. Variability was assessed using coefficients of variation and repeated measures tests. The different AIFs were used as inputs to the pharmacokinetic model and correlation coefficients, Bland-Altman plots and analysis of variance tests were obtained to compare the results.
  
  
  RESULTS
  Automatic PCA-based AIFs were successfully extracted in all cases. The manual and PCA-based AIFs showed good correlation (r between pharmacokinetic parameters ranging from 0.74 to 0.95), with differences below the manual individual variability (RMSCV up to 27.3%). The population-averaged AIF showed larger differences (r from 0.30 to 0.61).
  
  
  CONCLUSIONS
  The automatic PCA-based approach minimizes the variability associated to obtaining individual volume-based AIFs in DCE-MR studies of the prostate.
authors.affiliation: Biomedical Engineering, Hospital Quirón Valencia, Valencia, Spain.|GIBI230, Hospital Universitari i Politècnic La Fe, Valencia, Spain.
authors.forename: Roberto
authors.initials: R
authors.lastname: Sanz-Requena
authors.affiliation: GIEM, Universitat Politècnica de València, Valencia, Spain.
authors.forename: José Manuel
authors.initials: JM
authors.lastname: Prats-Montalbán
authors.affiliation: GIBI230, Hospital Universitari i Politècnic La Fe, Valencia, Spain.|Radiology Department, Hospital Quirón Valencia, Valencia, Spain.
authors.forename: Luis
authors.initials: L
authors.lastname: Martí-Bonmatí
authors.affiliation: GIBI230, Hospital Universitari i Politècnic La Fe, Valencia, Spain.
authors.forename: Ángel
authors.initials: Á
authors.lastname: Alberich-Bayarri
authors.affiliation: Biomedical Engineering, Hospital Quirón Valencia, Valencia, Spain.|GIBI230, Hospital Universitari i Politècnic La Fe, Valencia, Spain.|CIBER-SAM, Instituto de Salud Carlos III, Madrid, Spain.
authors.forename: Gracián
authors.initials: G
authors.lastname: García-Martí
authors.affiliation: Radiology Department, Hospital Quirón Valencia, Valencia, Spain.
authors.forename: Rosario
authors.initials: R
authors.lastname: Pérez
authors.affiliation: GIEM, Universitat Politècnica de València, Valencia, Spain.
authors.forename: Alberto
authors.initials: A
authors.lastname: Ferrer
mesh_terms: D001783:Blood Flow Velocity; D003198:Computer Simulation; D003287:Contrast Media / Q000493:pharmacokinetics; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D018810:Magnetic Resonance Angiography / Q000379:methods*; D008297:Male; D008536:Meglumine / Q000493:pharmacokinetics*; D008875:Middle Aged; D008954:Models, Biological; D015233:Models, Statistical; D009389:Neovascularization, Pathologic / Q000175:diagnosis / Q000503:physiopathology*; D009942:Organometallic Compounds / Q000493:pharmacokinetics*; D025341:Principal Component Analysis; D011471:Prostatic Neoplasms / Q000175:diagnosis / Q000503:physiopathology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D003287:Contrast Media; D009942:Organometallic Compounds; D008536:Meglumine; C072417:gadoterate meglumine
keywords: MRI; automatic; modeling; perfusion; pharmacokinetics; variability