基于系统仿真的数字乳腺层析成像性能分析

Objective To assess the imaging performance of digital breast tomography (DBT) based on systematic simulation. Methods The raw measurements of physical phantoms at a variety of radiation dose levels and clinical patients at the normal radiation dose were acquired from a clinical DBT system for low-dose simulation and reconstruction using 3 reconstruction algorithms, namely Feldkamp-Davis-Kress (FDK), simultaneous algebraic reconstruction technique (SART) and adaptive steepest-descent projection onto convex sets with total-variation constraint (ASDPOCS-TV) algorithms. The image quality was compared across different radiation dose levels and reconstruction algorithms in terms of signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), noise-power spectrum (NPS), artifact spread function (ASF) and full width at half maximum (FWHM) of ASF indexes. Results The reliability of low-dose DBT simulation strategy was verified by the experiment. Within a suitable range of dose levels, increasing the doses resulted in reduced high-frequency noise component and significantly increased SNR (P<0.05). But when the value of exposure was below 40 mAs, the images acquired at different dose levels had similar representation. The performance of the 3 reconstruction algorithms varied for different anatomical structures, and the image quality of ASDPOCS-TV algorithm was generally superior to SART and FDK algorithms with less through-plane artifacts and noise. Conclusion The quality of DBT images is significantly affected by both radiation dose and reconstruction algorithms. A tradeoff of the parameters, the overall image quality and the clinical needs for diagnostic purposes should be considered to achieve the optimal imaging performance on a given clinical task.