title: The positive predictive value of BI-RADS microcalcification descriptors and final assessment categories.
abstract: OBJECTIVE
  The purpose of this article is to retrospectively assess the likelihood of malignancy of microcalcifications according to the BI-RADS descriptors in a digital mammography environment.
  
  
  METHODS
  The study included 146 women with calcifications who underwent imaging-guided biopsy between April 2005 and July 2006. Digital mammograms procured before biopsy were analyzed independently by two breast imaging subspecialists blinded to biopsy results. Lesions described discordantly were settled by consensus. One of the radiologists provided a BI-RADS final assessment score.
  
  
  RESULTS
  The overall positive predictive value of biopsies was 28.8%. The individual morphologic descriptors predicted the risk of malignancy as follows: fine linear/branching, 16 (70%) of 23 cases; fine pleomorphic, 14 (28%) of 50 cases; coarse heterogeneous, two (20%) of 10 cases; amorphous, 10 (20%) of 51 cases; and typically benign, zero (0%) of 12 cases. Fisher-Freeman-Halton exact testing showed statistical significance among morphology descriptors (p < 0.001) and distribution descriptors (p < 0.001). The positive predictive value for malignancy according to BI-RADS assessment categories were as follows: category 2, 0%; category 3, 0%; category 4A, 13%; category 4B, 36%; category 4C, 79%; and category 5, 100%.
  
  
  CONCLUSIONS
  BI-RADS morphology and distribution descriptors can aid in assessing the risk of malignancy of microcalcifications detected on full-field digital mammography. The positive predictive value increased in successive BI-RADS categories (4A, 4B, and 4C), verifying that subdivision provides an improved assessment of suspicious microcalcifications in terms of likelihood of malignancy.
authors.affiliation: Department of Radiological Sciences, David Geffen School of Medicine at the University of California, Los Angeles, 200 UCLA Medical Plaza, Rm 165-47, Box 956952, Los Angeles, CA 90095, USA. cbent@ucla.edu
authors.forename: Chris K
authors.initials: CK
authors.lastname: Bent
authors.forename: Lawrence W
authors.initials: LW
authors.lastname: Bassett
authors.forename: Carl J
authors.initials: CJ
authors.lastname: D'Orsi
authors.forename: James W
authors.initials: JW
authors.lastname: Sayre
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; D006801:Humans; D008297:Male; D008327:Mammography / Q000379:methods*; D008875:Middle Aged; D011230:Precancerous Conditions / Q000000981:diagnostic imaging*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity