Purpose: The impact of system parameters on signal detectability can be studied with simulation platforms. We describe the steps taken to verify and confirm the accuracy of a local platform developed for the use in virtual clinical trials. Approach: The platform simulates specific targets into existing two-dimensional full-field digital mammography and digital breast tomosynthesis images acquired on a Siemens Inspiration system. There are three steps: (1) creation of voxel models or analytical objects; (2) generation of a realistic object template with accurate resolution, scatter, and noise properties; and (3) insertion and reconstruction. Four objects were simulated: a 0.5-mm aluminium (Al) sphere and a 0.2-mm-thick Al sheet in a PMMA stack, a 0.8-mm steel edge and a three-dimensional mass model in a structured background phantom. Simulated results were compared to acquired data. Results: Peak contrast and signal difference-to-noise ratio (SDNR) were in close agreement ( < 5 % error) for both sphere and sheet. The similarity of pixel value profiles for sphere and sheet in the x y direction and the artifact spread function for real and simulated spheres confirmed accurate geometric modeling. Absolute and relative average deviation between modulation transfer function measured from a real and simulated edges showed accurate sharpness modelling for spatial frequencies up to the Nyquist frequency. Real and simulated objects could not be differentiated visually. Conclusions: The results indicate that this simulation framework is a strong candidate for use in virtual clinical studies.
Purpose: The impact of system parameters on signal detectability can be studied with simulation platforms. We describe the steps taken to verify and confirm the accuracy of a local platform developed for the use in virtual clinical trials. Approach: The platform simulates specific targets into existing two-dimensional full-field digital mammography and digital breast tomosynthesis images acquired on a Siemens Inspiration system. There are three steps: (1) creation of voxel models or analytical objects; (2) generation of a realistic object template with accurate resolution, scatter, and noise properties; and (3) insertion and reconstruction. Four objects were simulated: a 0.5-mm aluminium (Al) sphere and a 0.2-mm-thick Al sheet in a PMMA stack, a 0.8-mm steel edge and a three-dimensional mass model in a structured background phantom. Simulated results were compared to acquired data. Results: Peak contrast and signal difference-to-noise ratio (SDNR) were in close agreement ( < 5 % error) for both sphere and sheet. The similarity of pixel value profiles for sphere and sheet in the x y direction and the artifact spread function for real and simulated spheres confirmed accurate geometric modeling. Absolute and relative average deviation between modulation transfer function measured from a real and simulated edges showed accurate sharpness modelling for spatial frequencies up to the Nyquist frequency. Real and simulated objects could not be differentiated visually. Conclusions: The results indicate that this simulation framework is a strong candidate for use in virtual clinical studies.
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