title: Clinical MR-mammography: are computer-assisted methods superior to visual or manual measurements for curve type analysis? A systematic approach.
abstract: OBJECTIVE
  Enhancement characteristics after administration of a contrast agent are regarded as a major criterion for differential diagnosis in magnetic resonance mammography (MRM). However, no consensus exists about the best measurement method to assess contrast enhancement kinetics. This systematic investigation was performed to compare visual estimation with manual region of interest (ROI) and computer-aided diagnosis (CAD) analysis for time curve measurements in MRM.
  
  
  METHODS
  A total of 329 patients undergoing surgery after MRM (1.5 T) were analyzed prospectively. Dynamic data were measured using visual estimation, including ROI as well as CAD methods, and classified depending on initial signal increase and delayed enhancement.
  
  
  RESULTS
  Pathology revealed 469 lesions (279 malignant, 190 benign). Kappa agreement between the methods ranged from 0.78 to 0.81. Diagnostic accuracies of 74.4% (visual), 75.7% (ROI), and 76.6% (CAD) were found without statistical significant differences.
  
  
  CONCLUSIONS
  According to our results, curve type measurements are useful as a diagnostic criterion in breast lesions irrespective of the method used.
authors.affiliation: Institutes of Diagnostic and Interventional Radiology, Friedrich-Schiller-University Jena, Erlanger Allee 101, D-07740 Jena, Germany. pascal.baltzer@med.uni-jena.de
authors.forename: Pascal Andreas Thomas
authors.initials: PA
authors.lastname: Baltzer
authors.forename: Christian
authors.initials: C
authors.lastname: Freiberg
authors.forename: Sebastian
authors.initials: S
authors.lastname: Beger
authors.forename: Tibor
authors.initials: T
authors.lastname: Vag
authors.forename: Matthias
authors.initials: M
authors.lastname: Dietzel
authors.forename: Aimee B
authors.initials: AB
authors.lastname: Herzog
authors.forename: Mieczyslaw
authors.initials: M
authors.lastname: Gajda
authors.forename: Oumar
authors.initials: O
authors.lastname: Camara
authors.forename: Werner A
authors.initials: WA
authors.lastname: Kaiser
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001185:Artificial Intelligence; D001943:Breast Neoplasms / Q000175:diagnosis*; D003287:Contrast Media / Q000008:administration & dosage; D005260:Female; D019786:Gadolinium DTPA / Q000008:administration & dosage; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008327:Mammography / Q000379:methods; D008875:Middle Aged; D015588:Observer Variation; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D055815:Young Adult
chemical_list: D003287:Contrast Media; D019786:Gadolinium DTPA