Application of a model observer for detection of lesions in synthetic mammograms

Purpose: To investigate the possibility of evaluating synthetic mammograms (SM) with a 3D structured phantom combined with model observer scoring. Methods: SM images were acquired on the Siemens Mammomat Revelation in order to set up a human observer study with 6 readers. Regions of interest with lesions (microcalcifications and masses) present and absent were selected for use in a four-alternative forced choice study. Image acquisitions and reading was performed at AEC,½ AEC and 2×AEC dose levels. The percentage correct (PC) results were calculated for all readers together with the standard error of the mean (SEM). A two-layer non-biased Channelized Hotelling Observer (CHO) for lesion detection was used: a two Laguerre-Gauss channel CHO applied first for localization and then an eight Gabor channel CHO for classification. Observer PC results were estimated using a bootstrap method, and the standard deviation (SD) was used as a figure of merit for reproducibility. Results: Following tuning steps, good correlation was found between the MO and human observer results for both microcalcifications and masses, at the three dose levels. The CHO predicted the PC values of the human readers, but with better reproducibility than the human readers. The detection threshold trends of the CHO matched those of the human observers. Conclusion: A two-layer CHO, with appropriate tuning and testing steps, could approximate the human observer detection results for microcalcifications and masses in SM images acquired on a Siemens Revelation DBT systems over three dose levels . The model observer developed is a promising candidate to track imaging performance in SM.