title: Mammographic density measured with quantitative computer-aided method: comparison with radiologists' estimates and BI-RADS categories.
abstract: OBJECTIVE
  To retrospectively compare computer-aided mammographic density estimation (MDEST) with radiologist estimates of percentage density and Breast Imaging Reporting and Data System (BI-RADS) density classification.
  
  
  METHODS
  Institutional Review Board approval was obtained for this HIPAA-compliant study; patient informed consent requirements were waived. A fully automated MDEST computer program was used to measure breast density on digitized mammograms in 65 women (mean age, 53 years; range, 24-89 years). Pixel gray levels in detected breast borders were analyzed, and dense areas were segmented. Percentage density was calculated by dividing the number of dense pixels by the total number of pixels within the borders. Seven breast radiologists (five trained with MDEST, two not trained) prospectively assigned qualitative BI-RADS density categories and visually estimated percentage density on 260 mammograms. Qualitative BI-RADS assessments were compared with new quantitative BI-RADS standards. The reference standard density for this study was established by allowing the five trained radiologists to manipulate the MDEST gray-level thresholds, which segmented mammograms into dense and nondense areas. Statistical tests performed include Pearson correlation coefficients, Bland-Altman agreement method, kappa statistics, and unpaired t tests.
  
  
  RESULTS
  There was a close correlation between the reference standard and radiologist-estimated density (R = 0.90-0.95) and MDEST density (R = 0.89). Untrained radiologists overestimated percentage density by an average of 37%, versus 6% for trained radiologists (P < .001). MDEST showed better agreement with the reference standard (average overestimate, 1%; range, -15% to +18%). MDEST correlated better with percentage density than with qualitative BI-RADS categories. There were large overlaps and ranges of percentage density in qualitative BI-RADS categories 2-4. Qualitative BI-RADS categories correlated poorly with new quantitative BI-RADS categories, and 16 (6%) of 260 views were erroneously classified by MDEST.
  
  
  CONCLUSIONS
  MDEST compared favorably with radiologist estimates of percentage density and is more reproducible than radiologist estimates when qualitative BI-RADS density categories are used. Qualitative and quantitative BI-RADS density assessments differed markedly.
authors.affiliation: Associated Radiologists Limited, Mesa, Ariz, USA. yango@cox.net
authors.forename: Katherine E
authors.initials: KE
authors.lastname: Martin
authors.forename: Mark A
authors.initials: MA
authors.lastname: Helvie
authors.forename: Chuan
authors.initials: C
authors.lastname: Zhou
authors.forename: Marilyn A
authors.initials: MA
authors.lastname: Roubidoux
authors.forename: Janet E
authors.initials: JE
authors.lastname: Bailey
authors.forename: Chintana
authors.initials: C
authors.lastname: Paramagul
authors.forename: Caroline E
authors.initials: CE
authors.lastname: Blane
authors.forename: Katherine A
authors.initials: KA
authors.lastname: Klein
authors.forename: Seema S
authors.initials: SS
authors.lastname: Sonnad
authors.forename: Heang-Ping
authors.initials: HP
authors.lastname: Chan
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000145:classification* / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D008327:Mammography; D008875:Middle Aged; D011857:Radiographic Image Interpretation, Computer-Assisted; D012189:Retrospective Studies