Objective: The two objectives of this study were to create an ex vivo phantom model that closely mimics human breast cancer for detection tasks and to compare the performance of full-field digital mammography with screen-film mammography in detecting and characterizing small breast masses in a phantom with a spectrum of complex tissue backgrounds.
Materials and methods: Sixteen phantom breast masses of varying sizes (0.3-1.2 cm), shapes (round and irregular), and densities (high and low) were created from shaved tumor specimens and imaged using both full-field digital and screen-film mammography techniques. We created 408 detection tasks that were captured on 68 films. On each radiograph, six detection tasks were partially obscured by areas of varying breast-pattern complexity, including low (predominantly fatty), mixed (scattered fibroglandular densities and heterogeneously dense), and high (extremely dense) density patterns. Each detection task was scored using a five-point confidence scale by three mammographers. Receiver operating characteristic (ROC) curve analysis was performed to analyze differences in detection of masses between the two imaging systems, and sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were computed.
Results: Full-field digital mammography showed higher area under the ROC curve than screen-film mammography for detecting masses in each breast background and performed significantly better than screen-film mammography in mixed (p = 0.010), dense (p = 0.029), and all breast backgrounds combined (p = 0.004). Full-field digital mammography was superior to screen-film mammography for characterizing round and irregular masses and low- and high-density masses.
Conclusion: Full-field digital mammography was significantly superior to screen-film technique for detecting and characterizing small masses in mixed and dense breast backgrounds in a phantom model.