A software-based x-ray scatter correction method for breast tomosynthesis

Abstract

Purpose: To develop a software-based scatter correction method for digital breast tomosynthesis (DBT) imaging and investigate its impact on the image quality of tomosynthesis reconstructions of both phantoms and patients. Methods: A Monte Carlo (MC) simulation of x-ray scatter, with geometry matching that of the cranio-caudal (CC) view of a DBT clinical prototype, was developed using the Geant4 toolkit and used to generate maps of the scatter-to-primary ratio (SPR) of a number of homogeneous standard-shaped breasts of varying sizes. Dimension-matched SPR maps were then deformed and registered to DBT acquisition projections, allowing for the estimation of the primary x-ray signal acquired by the imaging system. Noise filtering of the estimated projections was then performed to reduce the impact of the quantum noise of the x-ray scatter. Three dimensional (3D) reconstruction was then performed using the maximum likelihood-expectation maximization (MLEM) method. This process was tested on acquisitions of a heterogeneous 50/50 adipose/glandular tomosynthesis phantom with embedded masses, fibers, and microcalcifications and on acquisitions of patients. The image quality of the reconstructions of the scatter-corrected and uncorrected projections was analyzed by studying the signal-difference-to-noise ratio (SDNR), the integral of the signal in each mass lesion (integrated mass signal, IMS), and the modulation transfer function (MTF). Results: The reconstructions of the scatter-corrected projections demonstrated superior image quality. The SDNR of masses embedded in a 5 cm thick tomosynthesis phantom improved 60%-66%, while the SDNR of the smallest mass in an 8 cm thick phantom improved by 59% (p < 0.01). The IMS of the masses in the 5 cm thick phantom also improved by 15%-29%, while the IMS of the masses in the 8 cm thick phantom improved by 26%-62% (p < 0.01). Some embedded microcalcifications in the tomosynthesis phantoms were visible only in the scatter-corrected reconstructions. The visibility of the findings in two patient images was also improved by the application of the scatter correction algorithm. The MTF of the images did not change after application of the scatter correction algorithm, indicating that spatial resolution was not adversely affected. Conclusions: Our software-based scatter correction algorithm exhibits great potential in improving the image quality of DBT acquisitions of both phantoms and patients. The proposed algorithm does not require a time-consuming MC simulation for each specific case to be corrected, making it applicable in the clinical realm.