X-ray scatter correction in breast tomosynthesis with a precomputed scatter map library

To develop and evaluate the impact on lesion conspicuity of a software-based x-ray scatter correction algorithm for digital breast tomosynthesis (DBT) imaging into which a precomputed library of x-ray scatter maps is incorporated.

A previously developed model of compressed breast shapes undergoing mammography based on principal component analysis (PCA) was used to assemble 540 simulated breast volumes, of different shapes and sizes, undergoing DBT. A Monte Carlo (MC) simulation was used to generate the cranio-caudal (CC) view DBT x-ray scatter maps of these volumes, which were then assembled into a library. This library was incorporated into a previously developed software-based x-ray scatter correction, and the performance of this improved algorithm was evaluated with an observer study of 40 patient cases previously classified as BI-RADS® 4 or 5, evenly divided between mass and microcalcification cases. Observers were presented with both the original images and the scatter corrected (SC) images side by side and asked to indicate their preference, on a scale from -5 to +5, in terms of lesion conspicuity and quality of diagnostic features. Scores were normalized such that a negative score indicates a preference for the original images, and a positive score indicates a preference for the SC images.

The scatter map library removes the time-intensive MC simulation from the application of the scatter correction algorithm. While only one in four observers preferred the SC DBT images as a whole (combined mean score = 0.169 ± 0.37, p > 0.39), all observers exhibited a preference for the SC images when the lesion examined was a mass (1.06 ± 0.45, p < 0.0001). When the lesion examined consisted of microcalcification clusters, the observers exhibited a preference for the uncorrected images (-0.725 ± 0.51, p < 0.009).

The incorporation of the x-ray scatter map library into the scatter correction algorithm improves the efficiency of the algorithm. The observer study presented here is also the first test of the scatter correction algorithm with patient images and human observers, and demonstrates its potential to improve the clinical performance of DBT.