title: Computer-assisted detection as a second reader in symptomatic Asian women with palpable breast cancer.
abstract: OBJECTIVE
  To determine the potential role of a computer-assisted detection (CAD) algorithm as a second reader for experienced and inexperienced radiologists in mammography reading in Asian women.
  
  
  METHODS
  Two-view mammograms performed in 124 consecutive patients who presented with palpable breast cancer masses were retrospectively evaluated by two experienced breast radiologists (7 and 10 years' experience). The original reports of the session radiologists with variable experience of reading mammograms (2 to more than 10 years) were also evaluated. The number of suspicious masses and microcalcification clusters detected in each patient by both groups of radiologists were recorded. The radiologists then re-evaluated the films with the CAD system as a second reader. Any improvement in the detectability of breast pathology by either the experienced radiologists and/or by the session radiologists was then assessed. A total of 127 breasts had biopsy-proven carcinoma; 74 breasts had mastectomy performed. All the imaging results were correlated with tru-cut biopsy or mastectomy histology.
  
  
  RESULTS
  With CAD-aided interpretation, there were altogether 95 visible masses and 77 suspicious microcalcification clusters in 109 mammographically detectable cancers correlated with histology results. There was a 7.4% (7/95) and 10.4% (8/77) increase in the number of masses and microcalcification clusters detected, respectively, by the experienced radiologists after application of CAD, whereas the increase was 13.7% (13/95) and 27.3% (21/77) for detection of masses and microcalcifications by the session radiologists, respectively. In 9 patients, a secondary focus detected by CAD was confirmed by histology. Three patients had contralateral breast tumors, 1 had a satellite invasive tumor while 5 had ductal carcinoma in situ on the same breast. Based on the biopsies and 74 mastectomies, the true-positive and false-positive detection rate of CAD was 92.6% and 31.8% for detection of carcinomas. The true-positive and false-positive detection rates were 100% and 58.8% for microcalcification clusters.
  
  
  CONCLUSIONS
  The current generation CAD algorithm helped to improve the detection rate of carcinomas, calcifications and multifocality in Asian breasts.
authors.affiliation: Department of Diagnostic Radiology and Organ Imaging, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China. winnie@med.cuhk.edu.hk
authors.forename: W C W
authors.initials: WC
authors.lastname: Chu
authors.forename: W W M
authors.initials: WW
authors.lastname: Lam
authors.forename: A L M
authors.initials: AL
authors.lastname: Pang
authors.forename: N M C
authors.initials: NM
authors.lastname: So
authors.forename: A P Y
authors.initials: AP
authors.lastname: Tang
authors.forename: G M K
authors.initials: GM
authors.lastname: Tse
authors.forename: A T
authors.initials: AT
authors.lastname: Ahuja
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D002114:Calcinosis / Q000000981:diagnostic imaging; D005260:Female; D006723:Hong Kong; D006801:Humans; D008327:Mammography; D008875:Middle Aged; D015588:Observer Variation; D010173:Palpation; D011857:Radiographic Image Interpretation, Computer-Assisted; D012189:Retrospective Studies