Probability modeling applied to CAD systems for mammography

A practical model based on basic probability theory is developed to evaluate the operational and financial performance of mammography systems. The model is intended to be used by decision makers to evaluate overall sensitivity, overall specificity, positive and negative predictive values, and expected cost. As an illustration, computer aided detection (CAD) systems that support a radiologist's diagnosis are compared with standard mammography to determine conditions that would support their use. The model's input parameters include the operational performance of mammography (with and without CAD), the age of the patient, the cost of administering the mammogram and the expected costs associated with false positive and false negative outcomes. Sensitivity analyses are presented that show the CAD system projecting financial benefit over ranges of uncertainty associated with each model parameter.