Evaluating the impact of reconstruction algorithms on digital breast tomosynthesis system optimization for...

Early detection of microcalcifications in digital breast tomosynthesis (DBT) depends on optimizing both image reconstruction algorithms and system design parameters. Thisin-silicostudy evaluates the combined effects of x-ray tube motion, angular dose distribution, and detector characteristics on reconstruction algorithms for microcalcification detectability. A synthetic breast phantom containing 127 microcalcification clusters was generated and imaged under four acquisition conditions varying in tube motion (continuous vs. step-and-shot), angular dose distribution (uniform vs. non-uniform), and detector performance (noise level and pixel size). Projection data were reconstructed using filtered back-projection (FBP) and the simultaneous algebraic reconstruction technique (SART). Detection performance was assessed using a 2D Filtered Channel Observer in a multi-reader, multi-case study. Evaluation metrics included signal-to-noise ratio and area under the receiver operating characteristic (ROC) curve. Results show that SART performs best under step-and-shot acquisition by minimizing motion blur and enhancing fine detail, while FBP benefits more from non-uniform angular dose distributions. Detector improvements-lower noise and finer resolution-enhance detectability across all configurations, with FBP showing the largest gains. These findings highlight the interdependence of reconstruction algorithm, tube motion, dose strategy, and detector design in DBT system optimization. This study provides a detailed investigation into classical reconstruction strategies and establishes a methodological baseline for future DBT optimization research, offering actionable guidance for acquisition protocol design and hardware development.