title: Computerized analysis of shadowing on breast ultrasound for improved lesion detection.
abstract: Sonography is being considered for the screening of women at high risk for breast cancer. We are developing computerized detection methods to aid in the localization of lesions on breast ultrasound images. The detection scheme presented here is based on the analysis of posterior acoustic shadowing, since posterior acoustic shadowing is observed for many malignant lesions. The method uses a nonlinear filtering technique based on the skewness of the gray level distribution within a kernel of image data. The database used in this study included 400 breast ultrasound cases (757 images) consisting of complicated cysts, solid benign lesions, and malignant lesions. At a false-positive rate of 0.25 false positives per image, a detection sensitivity of 80% by case (66% by image) was achieved for malignant lesions. The performance for the overall database (at 0.25 false positives per image) was less at 42% sensitivity by case (30% by image) due to the more limited presence of posterior acoustic shadowing for benign solid lesions and the presence of posterior acoustic enhancement for cysts. Our computerized method for the detection of lesion shadows alerts radiologists to lesions that exhibit posterior acoustic shadowing. While this is not a characterization method, its performance is best for lesions that exhibit posterior acoustic shadowing such as malignant and, to a lesser extent, benign solid lesions. This method, in combination with other computerized sonographic detection methods, may ultimately help facilitate the use of ultrasound for breast cancer screening.
authors.affiliation: Department of Radiology MC2026, University of Chicago, 5841 South Maryland Avenue, Chicago, Illinois 60637, USA. kdrukker@hotmail.com
authors.forename: Karen
authors.initials: K
authors.lastname: Drukker
authors.forename: Maryellen L
authors.initials: ML
authors.lastname: Giger
authors.forename: Ellen B
authors.initials: EB
authors.lastname: Mendelson
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000145:classification* / Q000000981:diagnostic imaging*; D003720:Densitometry / Q000379:methods*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016217:Ultrasonography, Mammary / Q000379:methods*