The performance of mammography screening programmes is focussed mainly on breast cancer detection rates. However, when the benefits and risks of mammography are considered, the risk of radiation-induced cancer is calculated for only the examined breast using Mean Glandular Dose (MGD). The risk from radiation during mammography is often described as low or minimal. This study aims to evaluate the effective lifetime risk from full field digital mammography (FFDM) for a number of national screening programmes. Using an ATOM phantom, radiation doses to multiple organs were measured during standard screening mammography. Sixteen FFDM machines were used and the effective lifetime risk was calculated across the female lifespan for each machine. Once the risks were calculated using the phantom, the total effective lifetime risk across 48 national screening programmes was then calculated; this assumed that all these programmes use FFDM for screening. Large differences exist in effective lifetime risk, varying from 42.21 [39.12-45.30] cases/106 (mean [95% CI]) in the Maltese screening programme to 1099.67 [1019.25-1180.09] cases/106 for high breast cancer risk women in the United States of America. These differences are mainly attributed to the commencement age of screening mammography and the time interval between successive screens. Effective risk should be considered as an additional parameter for the assessment of screening mammography programme performance, especially for those programmes which recommend an early onset and more frequent screening mammography.

Objective: Motion blur is a known phenomenon in full-field digital mammography, but the impact on lesion detection is unknown. This is the first study to investigate detection performance with varying magnitudes of simulated motion blur. Methods: 7 observers (15 ± 5 years' reporting experience) evaluated 248 cases (62 containing malignant masses, 62 containing malignant microcalcifications and 124 normal cases) for 3 conditions: no blurring (0 mm) and 2 magnitudes of simulated blurring (0.7 and 1.5 mm). Abnormal cases were biopsy proven. Mathematical simulation was used to provide a pixel shift in order to simulate motion blur. A free-response observer study was conducted to compare lesion detection performance for the three conditions. The equally weighted jackknife alternative free-response receiver operating characteristic was used as the figure of merit. Test alpha was set at 0.05 to control probability of Type I error. Results: The equally weighted jackknife alternative free-response receiver operating characteristic analysis found a statistically significant difference in lesion detection performance for both masses [F(2,22) = 6.01, p = 0.0084] and microcalcifications [F(2,49) = 23.14, p < 0.0001]. The figures of merit reduced as the magnitude of simulated blurring increased. Statistical differences were found between some of the pairs investigated for the detection of masses (0.0 vs 0.7 and 0.0 vs 1.5 mm) and all pairs for microcalcifications (0.0 vs 0.7, 0.0 vs 1.5 and 0.7 vs 1.5 mm). No difference was detected between 0.7 and 1.5 mm for masses. Conclusion: The mathematical simulation of motion blur caused a statistically significant reduction in lesion detection performance. These false-negative decisions could have implications for clinical practice. Advances in knowledge: This research demonstrates for the first time that motion blur has a negative and statistically significant impact on lesion detection performance in digital mammography.