SBIR-STTR Award

Feasibility research is proposed for the development of a computer-based expert radiology assistant (XRA) to aid in the diagnosis of breast cancer. The proposed expert system has the potential to assist radiologists in the interpretation of diagnostic images and clinical data using artificial intelligence. The system was formed by encoding in the computer software the knowledge of human experts. The system will assist in the diagnosis of difficult cases and provide ready access to the knowledge of experts, leading to increased distribution and application of mammographic expertise.Specific aims of Phase I are designed to provide experimental evidence to test the capability of an expert system to make diagnoses based upon clinical and image descriptors provided by radiologists. A prototype system will be implemented and tested using verified clinical cases to aid in the discovery of reasoning methods and data descriptors that constitute sufficient knowledge to make diagnoses at expert levels of performance.Having defined a sufficient set of image descriptors, a Phase II effort will concentrate on full implementation of the interactive image-understanding portion of the system, integration of the diagnostic and image analysis subsystems, expansion of the knowledge base, and definitive clinical testing.National Cancer Institute (NCI)

Our research will lead to the development of a computer-based expert radiology assistant to aid in the diagnosis of breast cancer using clinical findings, x-ray manunograms, and ultrasound images as input data. Based upon encouraging feasibility results which demonstrated that the Phase I prototype system produced interpretations comparable to expert radiologists, we will extend the system to more complex diagnostic situations, will incorporate a data base for statistical analysis of mammographic data, will optimize the diagnostic rules, will refine the methods of combining evidence, and will improve the user interface, and to investigate the role of objective image analysis. Specific aims of Phase II are designed to provide experimental evidence to determine the role of expert system technology in breast cancer diagnosis, training of residents, management and reporting of examination data, and assistance in detecting and quantifying of abnormalities. The resulting expert system will be extensively tested, both retrospectively and prospectively, using clinical data to evaluate the practically attainable diagnostic accuracy, overall clinical utility, and potential for commercialization.Awardee's statement of the potential commercial applications of the research:The expert system is an adjunct to diagnostic imaging systems aimed toward improving the accuracy of interpreting medical images for specific commercial application to the diagnosis of breast cancer.National Cancer Institute (NCI)