title: Computerized detection of breast cancer on automated breast ultrasound imaging of women with dense breasts.
abstract: OBJECTIVE
  Develop a computer-aided detection method and investigate its feasibility for detection of breast cancer in automated 3D ultrasound images of women with dense breasts.
  
  
  METHODS
  The HIPAA compliant study involved a dataset of volumetric ultrasound image data, "views," acquired with an automated U-Systems Somo●V(®) ABUS system for 185 asymptomatic women with dense breasts (BI-RADS Composition/Density 3 or 4). For each patient, three whole-breast views (3D image volumes) per breast were acquired. A total of 52 patients had breast cancer (61 cancers), diagnosed through any follow-up at most 365 days after the original screening mammogram. Thirty-one of these patients (32 cancers) had a screening-mammogram with a clinically assigned BI-RADS Assessment Category 1 or 2, i.e., were mammographically negative. All software used for analysis was developed in-house and involved 3 steps: (1) detection of initial tumor candidates, (2) characterization of candidates, and (3) elimination of false-positive candidates. Performance was assessed by calculating the cancer detection sensitivity as a function of the number of "marks" (detections) per view.
  
  
  RESULTS
  At a single mark per view, i.e., six marks per patient, the median detection sensitivity by cancer was 50.0% (16/32) ± 6% for patients with a screening mammogram-assigned BI-RADS category 1 or 2--similar to radiologists' performance sensitivity (49.9%) for this dataset from a prior reader study--and 45.9% (28/61) ± 4% for all patients.
  
  
  CONCLUSIONS
  Promising detection sensitivity was obtained for the computer on a 3D ultrasound dataset of women with dense breasts at a rate of false-positive detections that may be acceptable for clinical implementation.
authors.affiliation: Department of Radiology, MC2026, The University of Chicago, 5841 South Maryland Avenue, Chicago, Illinois 60637.
authors.forename: Karen
authors.initials: K
authors.lastname: Drukker
authors.affiliation: Department of Radiology, MC2026, The University of Chicago, 5841 South Maryland Avenue, Chicago, Illinois 60637.
authors.forename: Charlene A
authors.initials: CA
authors.lastname: Sennett
authors.affiliation: Department of Radiology, MC2026, The University of Chicago, 5841 South Maryland Avenue, Chicago, Illinois 60637.
authors.forename: Maryellen L
authors.initials: ML
authors.lastname: Giger
mesh_terms: D000368:Aged; D001940:Breast / Q000473:pathology*; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005189:False Positive Reactions; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D021621:Imaging, Three-Dimensional; D008875:Middle Aged; D016217:Ultrasonography, Mammary / Q000379:methods*