The long-term goal is to develop the software, image database and knowledge-base for an intelligent computer workstation that supports interpretation of mammograms for breast cancer detection. The workstation will reinforce perceptive and cognitive elements of mammography interpretation and provide a dynamic, interactive tool for teaching these skills. The system will be based on an existing prototype mammography expert system developed by us. Before undertaking full commercial development, we want to test the clinical appropriateness of the image recall strategies using an expanded image database in Phase I. We will also refine design specifications during this phase. The final system will draw from a large image database (greater than 1000 cases) and knowledge-base in order to assemble highly context-sensitive, patient-specific output that is expected to improve the accuracy of mammographic diagnosis. This project addresses the important public health problem of breast cancer, the most common non-preventable cause of cancer death in women. Its training and decision support capabilities could potentially alleviate projected manpower shortages caused by current rapid increases in mammography volume, and could also improve the quality of mammography interpretation.Awardee's statement of the potential commercial applications of the research:The Mammo/Icon system elicited strong radiologist interest at national medical meetings where it has been demonstrated. Projected increases in mammography volume and shortage of trained personnel will likely contribute to increasing commercial demand for training tools and quality assurance products in mammography. We will distribute the final system on CD-ROM discs.National Cancer Institute (NCI)
