title: Computer-aided detection with screening mammography in a university hospital setting.
abstract: OBJECTIVE
  To prospectively assess the effect of computer-aided detection (CAD) on screening mammogram interpretation in an academic medical center to determine if the outcome is different than that previously reported for community practices.
  
  
  METHODS
  Institutional review board approval was granted, and informed consent was waived. During a 19-month period, 8682 women (median age, 54 years; range, 33-95 years) underwent screening mammography. Each mammogram was interpreted by one of seven radiologists, followed by immediate re-evaluation of the mammogram with CAD information. Each recalled case was classified as follows: radiologist perceived the finding and CAD marked it, radiologist perceived the finding and CAD did not mark it, or CAD prompted the radiologist to perceive the finding and recall the patient. Lesion type was also recorded. Recalled patients were tracked to determine the effect of CAD on recall and biopsy recommendation rates, positive predictive value (PPV) of biopsy, and cancer detection rate. A 95% confidence interval was calculated for cancer detection rate. Pathologic examination was performed for all cancers.
  
  
  RESULTS
  Of 8682 patients, 863 (9.9%) with 960 findings were recalled for further work-up (Breast Imaging Reporting and Data System category 0). After further diagnostic imaging, it was recommended that biopsy or aspiration be performed for 181 of 960 findings (19%); 165 interventions were confirmed to have been performed. Twenty-nine cancers were found in this group, with a PPV for biopsy of 18% (29 of 165 findings) and a cancer detection rate of 3.3 per 1000 screening mammograms (29 of 8682 patients). CAD-prompted recalls contributed 8% (73 of 960 findings) of total recalled findings and 7% (two of 29 lesions) of cancers detected. Of 29 cancers (59%), 17 manifested as masses and 12 (41%) were microcalcifications. Ten (34%) cancers were ductal carcinoma in situ, and the remaining cancers had an invasive component. Both cancers found with CAD manifested as masses, and both were invasive ductal carcinoma.
  
  
  CONCLUSIONS
  Prospective clinical use of CAD in a university hospital setting resulted in a 7.4% increase (from 27 to 29) in cancers detected. Both cancers were nonpalpable masses.
authors.affiliation: Department of Radiology, S092, Stanford University Medical Center, 300 Pasteur Dr, Stanford, CA 94305-5105, USA. rbirdwell@partners.org
authors.forename: Robyn L
authors.initials: RL
authors.lastname: Birdwell
authors.forename: Parul
authors.initials: P
authors.lastname: Bandodkar
authors.forename: Debra M
authors.initials: DM
authors.lastname: Ikeda
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D005260:Female; D006785:Hospitals, University; D006801:Humans; D008327:Mammography / Q000379:methods; D008875:Middle Aged; D011446:Prospective Studies; D011857:Radiographic Image Interpretation, Computer-Assisted