Mammographic computer-aided detection systems

While mammography is regarded as the best means available to screen for breast cancer, reading mammograms is a tedious, error-prone task. Given the repetitiveness of the process and the fact that less than 1% of mammograms in the average screening population contain cancer, it's no wonder that a significant number of breast cancers--about 28%--are missed by radiologists. The fact that human error is such a significant obstacle makes mammography screening an ideal application for computer-aided detection (CAD) systems. CAD systems serve as a "second pair of eyes" to ensure that radiologists don't miss a suspect area on an image. They analyze patterns on a digitized mammographic image, identify regions that may contain an abnormality indicating cancer, and mark these regions. The marks are then inspected and classified by a radiologist. But CAD systems provide no diagnosis of any kind--it's up to the radiologist to analyze the marked area and decide if it shows cancer. In this Evaluation, we describe the challenges posed by screening mammography, the operating principles and overall efficacy of CAD systems, and the characteristics to consider when purchasing a system. We also compare the performance of two commercially available systems, iCAD's MammoReader and R2's ImageChecker. Because the two systems offer comparable sensitivity, our judgments are based on other performance characteristics, including their ease of use, the number of false marks they produce, the degree to which they can integrate with hospital information systems, and their processing speed.