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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Published on: August 30, 2013
[Clinical value of computer aided detection system in direct full-field digital mammography: a preliminary
1Department of Oncologic Surgery, First Affiliated Hospital, China Medical University, Shenyang 110001, China.
Objective:
To study the clinical value of computer aided detection (CAD) in direct full-field digital mammography.
Methods:
480 digital mammograms of 120 patients with pathologically proved breast cancer were randomly selected and interpreted by an expert radiologist without knowing the pathologic diagnosis, then analyzed by CAD system, and finally read by the radiologist again to make the final diagnosis. The sensitivity for breast cancer detection of the radiologist in diagnosis of breast cancer was calculated before and after using CAD. Data of the breast density, diameters of mass and calcification, being spiculate or not, and pathology of each case were reviewed to determine how they impacted on the improvement of sensitivity with the assistance of CAD.
Results:
The sensitivity for breast cancer detection by the radiologist before using CAD was 74.2%, significantly lower than that after using CAD (89.2%, chi(2) = 37.628, P = 0.000). Breast density (chi(2) = 7.352, P = 0.007), diameter of calcification (chi(2) = 10.549, P = 0.014) and pathologic pattern (chi(2) = 13.751, P = 0.003) were highly correlated with the improvement of sensitivity. Use of CAD might overcome type 1 missed diagnosis, and not type 2 missed diagnosis.
Conclusion:
Computer-aided detection helps radiologist improve their diagnostic accuracy of breast cancer, however, is not capable of differentiating benign from malignant lesions.

