title: Computer-aided detection of breast masses depicted on full-field digital mammograms: a performance assessment.
abstract: OBJECTIVE
  To investigate the feasibility of converting a computer-aided detection (CAD) scheme for digitised screen-film mammograms to full-field digital mammograms (FFDMs) and assessing CAD performance on a large database.
  
  
  METHODS
  The database included 6478 FFDM images acquired on 1120 females, with 525 cancer cases and 595 negative cases. The database was divided into five case groups: (1) cancer detected during screening, (2) interval cancers, (3) "high-risk" recommended for surgical excision, (4) recalled but negative and (5) negative (not recalled). A previously developed CAD scheme for masses depicted on digitised images was converted and re-optimised for FFDM images while keeping the same image-processing structure. CAD performance was analysed on the entire database.
  
  
  RESULTS
  The case-based sensitivity was 75.6% (397/525) for the current mammograms and 40.8% (42/103) for the prior mammograms deemed negative during clinical interpretation but "visible" during retrospective review. The region-based sensitivity was 58.1% (618/1064) for the current mammograms and 28.4% (57/201) for the prior mammograms. The CAD scheme marked 55.7% (221/397) and 35.7% (15/42) of the masses on both views of the current and the prior examinations, respectively. The overall CAD-cued false-positive rate was 0.32 per image, ranging from 0.29 to 0.51 for the five case groups.
  
  
  CONCLUSIONS
  This study indicated that (1) digitised image-based CAD can be converted for FFDMs while performing at a comparable, or better, level; (2) CAD detects a substantial fraction of cancers depicted on prior examinations, albeit most having been marked only on one view; and (3) CAD tends to mark more false-positive results on "difficult" negative cases that are more visually difficult for radiologists to interpret.
authors.affiliation: Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA. zhengb@upmc.edu
authors.forename: B
authors.initials: B
authors.lastname: Zheng
authors.forename: J H
authors.initials: JH
authors.lastname: Sumkin
authors.forename: M L
authors.initials: ML
authors.lastname: Zuley
authors.forename: D
authors.initials: D
authors.lastname: Lederman
authors.forename: X
authors.initials: X
authors.lastname: Wang
authors.forename: D
authors.initials: D
authors.lastname: Gur
mesh_terms: D001941:Breast Diseases / Q000000981:diagnostic imaging*; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D008875:Middle Aged; D011856:Radiographic Image Enhancement; D011857:Radiographic Image Interpretation, Computer-Assisted