title: Can the size of microcalcifications predict malignancy of clusters at mammography?
abstract: OBJECTIVE
  The purpose of this study was to determine whether the size of mammographically detected microcalcifications is predictive of malignancy.
  
  
  METHODS
  Two hundred sixty mammograms showing clustered microcalcifications with proven diagnoses (160 malignant, 100 benign) were respectively reviewed by experienced mammographers. Lesions that were obviously benign in appearance were excluded from the study. A computer-aided diagnosis system digitized the lesions at 600 dpi, and the microcalcifications on the digital image were interactively defined by mammographers. Subsequently, three quantitative features that reflected the size of the microcalcifications-length, area, and brightness-were automatically extracted by the system. For each feature, the standard average of values obtained for individual calcifications within the cluster and the average with emphasis on extreme values (E) obtained in a single cluster were analyzed and matched with pathologic results.
  
  
  RESULTS
  In the malignant group of cases, the mean values of the standard average length and area were significantly higher (P < .0001) than the mean values in the benign group. Distribution analysis demonstrated that an average length of more than 0.41 mm was associated with malignant lesions 77% of the time, while an average length of less than 0.41 mm was associated with benign lesions 71% of the time. The mean of the average length (E) and area (E) of microcalcifications within the cluster demonstrated an even higher discriminative power when compared with the standard average length and area. The average brightness, on the other hand, showed only a low discriminative power.
  
  
  CONCLUSIONS
  Digital computerized analysis of mammographically detected calcifications demonstrated that the average length and area of the calcifications in benign clusters were significantly smaller than those in malignant clusters.
authors.affiliation: Department of Radiology, Montefiore Medical Center, The University Hospital for the Albert Einstein College of Medicine, Bronx, NY, USA.
authors.forename: Shalom S
authors.initials: SS
authors.lastname: Buchbinder
authors.forename: Isaac S
authors.initials: IS
authors.lastname: Leichter
authors.forename: Richard B
authors.initials: RB
authors.lastname: Lederman
authors.forename: Boris
authors.initials: B
authors.lastname: Novak
authors.forename: Philippe N
authors.initials: PN
authors.lastname: Bamberger
authors.forename: Helise
authors.initials: H
authors.lastname: Coopersmith
authors.forename: Scott I
authors.initials: SI
authors.lastname: Fields
mesh_terms: D000328:Adult; D000368:Aged; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D002114:Calcinosis / Q000000981:diagnostic imaging* / Q000473:pathology; D005189:False Positive Reactions; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D008875:Middle Aged; D012372:ROC Curve; D011857:Radiographic Image Interpretation, Computer-Assisted; D012189:Retrospective Studies