Improving mammographic decision accuracy by incorporating observer ratings with interpretation time.
Mammography is currently the most established technique for the early detection of breast cancer. However, mammography would benefit from further improvements as it does produce some errors, such as not finding all early-stage cancers. The objectives of this study were first, to measure the timing of correct and incorrect reading decisions in mammography and second, to exploit those dependencies to improve accuracy in mammographic interpretation. To address these objectives, an experiment was conducted where experienced breast imaging radiologists reviewed 400 mammographic regions equally divided among images that contained simulated benign masses, malignant masses, malignant microcalcifications and no lesions. The experiment recorded the radiologists' decision as well as the length of time the mammogram was interpreted in. The experiment results showed that incorrect detection as well as incorrect classification decisions were associated with longer interpretation times (p<0.0001). The timing results were used to create a model that would flag cases for review that had a higher probability of error. The flagged cases had a median accuracy drop of 13% for detection decisions and 16% for classification decisions compared with unflagged cases. This suggests that interpretation time can be incorporated into mammographic decision-making in order to identify cases with higher probabilities of perceptual error that require further review.