Evaluating the sensitivity of the optimization of acquisition geometry to the choice of reconstruction algorithm in digital breast tomosynthesis through a simulation study

Abstract

Due to the limited number of views and limited angular span in digital breast tomosynthesis (DBT), the acquisition geometry design is an important factor that affects the image quality. Therefore, intensive studies have been conducted regarding the optimization of the acquisition geometry. However, different reconstruction algorithms were used in most of the reported studies. Because each type of reconstruction algorithm can provide images with its own image resolution, noise properties and artifact appearance, it is unclear whether the optimal geometries concluded for the DBT system in one study can be generalized to the DBT systems with a reconstruction algorithm different to the one applied in that study. Hence, we investigated the effect of the reconstruction algorithm on the optimization of acquisition geometry parameters through carefully designed simulation studies. Our results show that using various reconstruction algorithms, including the filtered back-projection, the simultaneous algebraic reconstruction technique, the maximum-likelihood method and the total-variation regularized least-square method, gave similar performance trends for the acquisition parameters for detecting lesions. The consistency of system ranking indicates that the choice of the reconstruction algorithm may not be critical for DBT system geometry optimization.

High-resolution, anthropomorphic, computational breast phantom: fusion of rule-based structures with patient-based anatomy

“…For all three phantom variants, simulated images were generated for both mammography and DBT using a previously reported projection and FBP reconstruction algorithm. [39] The resulting images were analyzed for anatomical realism using two techniques, power law slope and Laplacian fractional entropy.…”

Optimization of digital breast tomosynthesis (DBT) acquisition parameters for human observers: effect of reconstruction algorithms

“…As various reconstruction algorithms have been developed for DBT, it is desirable to know whether the use of a different reconstruction algorithm would alter the optimal geometry associated with the current algorithm. We have previously investigated this problem by conducting an in silico imaging trial with digital breast phantoms, simulated DBT system with various reconstruction algorithms, and a computational model observer for image quality evaluation (Zeng et al 2015). System optimization was based on lesion detectability in a location-known task for a Laguerre–Gauss (LG) channelized model observer (CHO).…”

Design of a model observer to evaluate calcification detectability in breast tomosynthesis and application to smoothing prior optimization

“…Possible sources of discrepancies between different model observer implementations were examined by Young et al 10 who showed the need to take interprojection correlations into account when applying the CHO in the projection domain and by Park et al 11 who demonstrated that the choice of different 2D and 3D observer channels resulted in different preferences in system geometry. Focusing on the evaluation of 3D reconstruction techniques, Van de Sompel et al 12 used the CHO to compare variants of filtered backprojection (FBP), the simultaneous algebraic reconstruction technique (SART), and maximum likelihood (ML) reconstruction, while Zeng et al 13 found that the choice of reconstruction method did not influence the ranking of different acquisition geometries.…”