title: Mammographic quantitative image analysis and biologic image composition for breast lesion characterization and classification.
abstract: OBJECTIVE
  To investigate whether biologic image composition of mammographic lesions can improve upon existing mammographic quantitative image analysis (QIA) in estimating the probability of malignancy.
  
  
  METHODS
  The study population consisted of 45 breast lesions imaged with dual-energy mammography prior to breast biopsy with final diagnosis resulting in 10 invasive ductal carcinomas, 5 ductal carcinomain situ, 11 fibroadenomas, and 19 other benign diagnoses. Analysis was threefold: (1) The raw low-energy mammographic images were analyzed with an established in-house QIA method, "QIA alone," (2) the three-compartment breast (3CB) composition measure-derived from the dual-energy mammography-of water, lipid, and protein thickness were assessed, "3CB alone", and (3) information from QIA and 3CB was combined, "QIA + 3CB." Analysis was initiated from radiologist-indicated lesion centers and was otherwise fully automated. Steps of the QIA and 3CB methods were lesion segmentation, characterization, and subsequent classification for malignancy in leave-one-case-out cross-validation. Performance assessment included box plots, Bland-Altman plots, and Receiver Operating Characteristic (ROC) analysis.
  
  
  RESULTS
  The area under the ROC curve (AUC) for distinguishing between benign and malignant lesions (invasive and DCIS) was 0.81 (standard error 0.07) for the "QIA alone" method, 0.72 (0.07) for "3CB alone" method, and 0.86 (0.04) for "QIA+3CB" combined. The difference in AUC was 0.043 between "QIA + 3CB" and "QIA alone" but failed to reach statistical significance (95% confidence interval [-0.17 to + 0.26]).
  
  
  CONCLUSIONS
  In this pilot study analyzing the new 3CB imaging modality, knowledge of the composition of breast lesions and their periphery appeared additive in combination with existing mammographic QIA methods for the distinction between different benign and malignant lesion types.
authors.affiliation: Department of Radiology, University of Chicago, Chicago, Illinois 60637.
authors.forename: Karen
authors.initials: K
authors.lastname: Drukker
authors.affiliation: Radiology Department, University of California, San Francisco, California 94143.
authors.forename: Fred
authors.initials: F
authors.lastname: Duewer
authors.affiliation: Department of Radiology, University of Chicago, Chicago, Illinois 60637.
authors.forename: Maryellen L
authors.initials: ML
authors.lastname: Giger
authors.affiliation: Radiology Department, University of California, San Francisco, California 94143.
authors.forename: Serghei
authors.initials: S
authors.lastname: Malkov
authors.affiliation: Department of Radiology, University of South Florida, Tampa, Florida 33612.
authors.forename: Chris I
authors.initials: CI
authors.lastname: Flowers
authors.affiliation: Radiology Department, University of California, San Francisco, California 94143.
authors.forename: Bonnie
authors.initials: B
authors.lastname: Joe
authors.affiliation: Radiology Department, University of California, San Francisco, California 94143.
authors.forename: Karla
authors.initials: K
authors.lastname: Kerlikowske
authors.affiliation: Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida 33612.
authors.forename: Jennifer S
authors.initials: JS
authors.lastname: Drukteinis
authors.affiliation: Department of Radiology, University of Chicago, Chicago, Illinois 60637.
authors.forename: Hui
authors.initials: H
authors.lastname: Li
authors.affiliation: Radiology Department, University of California, San Francisco, California 94143.
authors.forename: John A
authors.initials: JA
authors.lastname: Shepherd
mesh_terms: D001331:Automation; D001706:Biopsy; D001940:Breast / Q000473:pathology; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D008055:Lipids / Q000737:chemistry; D008327:Mammography / Q000379:methods*; D011336:Probability; D011446:Prospective Studies; D012372:ROC Curve; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D014867:Water / Q000737:chemistry
chemical_list: D008055:Lipids; D014867:Water