Computerized detection of breast cancer on automated breast ultrasound imaging of women with dense breasts

Purpose: 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.