This study demonstrated the following 3 new important concepts. 1) Dynamic imaging can yield meaningful clinical diagnostic information objectively, without need for human expertise. The same methodology can be applicable to any quantitative pathophysiological assessment. 2) Using classical FFT and elementary statistics (Student's t tests and z-value statistics, or alpha and beta statistics), the authors have shown how to reduce thousands of observations to a single quantitative clinical diagnostic parameter. This approach should be applicable to any multiparametric diagnostic technique. 3) After 3 decades of controversial reports on the use of thermal imaging in the diagnosis of breast cancer, the authors have shown that dynamic infrared imaging (in contrast to static thermal imaging), using a plausible pathophysiological model and up-to-date infrared equipment, can distinguish between noncancerous and cancerous breasts with a highly impressive sensitivity and specificity.