title: Localized detection and classification of abnormalities on FFDM and tomosynthesis examinations rated under an FROC paradigm.
abstract: OBJECTIVE
  The purpose of our study was to assess diagnostic performance when retrospectively interpreting full-field digital mammography (FFDM) and breast tomosynthesis examinations under a free-response receiver operating characteristic (FROC) paradigm.
  
  
  METHODS
  We performed FROC analysis of a previously reported study in which eight experienced radiologists interpreted 125 examinations, including 35 with verified cancers. The FROC paradigm involves detecting, locating, and rating each suspected abnormality. Radiologists reviewed and rated both FFDM alone and a combined display mode of FFDM and digital breast tomosynthesis (DBT) (combined). Observer performance levels were assessed and compared with respect to the fraction of correctly identified abnormalities, the number of reported location-specific findings (both true and false), and their associated ratings. The analysis accounts for the number and locations of findings and the location-based ratings using a summary performance index (Λ), which is the FROC analog of the area between the receiver operating characteristic curve and the diagonal (chance) line.
  
  
  RESULTS
  Under the FROC paradigm, each reader detected more true abnormalities associated with cancer, or a higher true-positive fraction, under the combined mode. In an analysis focused on both the number of findings and associated location-based ratings, each of the radiologists performed better under the combined mode compared with FFDM alone, with increases in Λ ranging from 5% to 34%. On average, under the combined mode radiologists achieved a 16% improvement in Λ compared with the FFDM alone mode (95% CI, 7-26%; p < 0.01).
  
  
  CONCLUSIONS
  We showed that DBT-based breast imaging in combination with FFDM could result in better performance under the FROC paradigm.
authors.affiliation: Department of Radiology, University of Pittsburgh, Radiology Imaging Research, PA 15213-3180, USA. gurd@upmc.edu
authors.forename: David
authors.initials: D
authors.lastname: Gur
authors.forename: Andriy I
authors.initials: AI
authors.lastname: Bandos
authors.forename: Howard E
authors.initials: HE
authors.lastname: Rockette
authors.forename: Margarita L
authors.initials: ML
authors.lastname: Zuley
authors.forename: Jules H
authors.initials: JH
authors.lastname: Sumkin
authors.forename: Denise M
authors.initials: DM
authors.lastname: Chough
authors.forename: Christiane M
authors.initials: CM
authors.lastname: Hakim
mesh_terms: D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D012372:ROC Curve; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D012189:Retrospective Studies