title: Dynamic contrast-enhanced MRI: Study of inter-software accuracy and reproducibility using simulated and clinical data.
abstract: To test the reproducibility and accuracy of pharmacokinetic parameter measurements on five analysis software packages (SPs) for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), using simulated and clinical data.
  
  
  
  This retrospective study was Institutional Review Board-approved. Simulated tissues consisted of pixel clusters of calculated dynamic signal changes for combinations of Tofts model pharmacokinetic parameters (volume transfer constant [K(trans) ], extravascular extracellular volume fraction [ve ]), longitudinal relaxation time (T1 ). The clinical group comprised 27 patients treated for rectal cancer, with 36 3T DCE-MR scans performed between November 2012 and February 2014, including dual-flip-angle T1 mapping and a dynamic postcontrast T1 -weighted, 3D spoiled gradient-echo sequence. The clinical and simulated images were postprocessed with five SPs to measure K(trans) , ve , and the initial area under the gadolinium curve (iAUGC). Modified Bland-Altman analysis was conducted, intraclass correlation coefficients (ICCs) and within-subject coefficients of variation were calculated.
  
  
  
  Thirty-one examinations from 23 patients were of sufficient technical quality and postprocessed. Measurement errors were observed on the simulated data for all the pharmacokinetic parameters and SPs, with a bias ranging from -0.19 min(-1) to 0.09 min(-1) for K(trans) , -0.15 to 0.01 for ve , and -0.65 to 1.66 mmol.L(-1) .min for iAUGC. The ICC between SPs revealed moderate agreement for the simulated data (K(trans) : 0.50; ve : 0.67; iAUGC: 0.77) and very poor agreement for the clinical data (K(trans) : 0.10; ve : 0.16; iAUGC: 0.21).
  
  
  
  Significant errors were found in the calculated DCE-MRI pharmacokinetic parameters for the perfusion analysis SPs, resulting in poor inter-software reproducibility. J. Magn. Reson. Imaging 2016;43:1288-1300.
authors.affiliation: Department of Radiology, CHU Rennes, France.
authors.forename: Luc
authors.initials: L
authors.lastname: Beuzit
authors.affiliation: PRISM-Biosit CNRS UMS 3480, INSERM UMS 018, University of Rennes 1, France.
authors.forename: Pierre-Antoine
authors.initials: PA
authors.lastname: Eliat
authors.affiliation: Department of Radiology, CHU Rennes, France.
authors.forename: Vanessa
authors.initials: V
authors.lastname: Brun
authors.affiliation: Department of Radiology, CHU Rennes, France.|Neurinfo MR Imaging Platform, University of Rennes 1, France.
authors.forename: Jean-Christophe
authors.initials: JC
authors.lastname: Ferré
authors.affiliation: Department of Radiology, CHU Rennes, France.
authors.forename: Yves
authors.initials: Y
authors.lastname: Gandon
authors.affiliation: Department of Radiology, CHU Rennes, France.|Neurinfo MR Imaging Platform, University of Rennes 1, France.
authors.forename: Elise
authors.initials: E
authors.lastname: Bannier
authors.affiliation: LTSI, UMR 1099, INSERM, University of Rennes 1, France.|Eugène Marquis Cancer Institute, Rennes, France.
authors.forename: Hervé
authors.initials: H
authors.lastname: Saint-Jalmes
mesh_terms: D000328:Adult; D000368:Aged; D003198:Computer Simulation; D003287:Contrast Media / Q000493:pharmacokinetics; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007680:Kidney Neoplasms / Q000000981:diagnostic imaging* / Q000378:metabolism* / Q000473:pathology; D008279:Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods*; D008297:Male; D008536:Meglumine / Q000493:pharmacokinetics*; D008875:Middle Aged; D008954:Models, Biological; D009942:Organometallic Compounds / Q000493:pharmacokinetics*; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D012986:Software Validation
chemical_list: D003287:Contrast Media; D009942:Organometallic Compounds; D008536:Meglumine; C072417:gadoterate meglumine
keywords: DCE-MRI; Tofts model; inter-software variability; quantitative parameters; rectal cancer; simulated images