Potential for lower absorbed dose in digital mammography: A JAFROC experiment using clinical hybrid images with simulated dose reduction
To determine how image quality linked to tumor detection is affected by reducing the absorbed dose to 50% and 30% of the clinical levels represented by an average glandular dose (AGO) level of 1.3 mGy for a standard breast according to European guidelines. Materials and methods: 90 normal, unprocessed images were acquired from the screening department using a full-field digital mammography (FFDM) unit Mammomat Novation (Siemens). Into 40 of these, one to three simulated tumors were inserted per image at various positions. These tumors represented irregular-shaped malignant masses. Dose reduction was simulated in all 90 images by adding simulated quantum noise to represent images acquired at 50% and 30% of the original dose, resulting in 270 images, which were subsequently processed for final display. Four radiologists participated in a free-response receiver operating characteristics (FROG) study in which they searched for and marked suspicious positions of the masses as well as rated their degree of suspicion of occurrence on a one to four scale. Using the jackknife FROG (JAFROC) method, a score between 0 and 1 (where 1 represents best performance), referred to as a figure-of-merit (FOM), was calculated for each dose level. Results: The FOM was 0.73, 0.70, and 0.68 for the 100%, 50% and 30% dose levels, respectively. Using Analysis of the Variance (ANOVA) to test for statistically significant differences between any two of the three FOMs revealed that they were not statistically distinguishable (p-value of 0.26). Conclusion: For the masses used in this experiment, there was no significant change in detection by increasing quantum noise, thus indicating a potential for dose reduction.
Timberg, P; Ruschin, M; Båth, M; Hemdal, B; Andersson, I; Mattsson, S; Chakraborty, D; Saunders, R; Samei, E; Tingberg, A
Volume / Issue
International Standard Serial Number (ISSN)
Digital Object Identifier (DOI)