Accelerating Monte Carlo image reconstruction of a PMMA phantom through variance reduction techniques for quality control in digital mammography

Mammography is a non-invasive technique used for the detection of breast lesions. The use of this technique in a breast screening program requires a continuous quality control testing in mammography units for ensuring a minimum absorbed glandular dose without modifying image quality. Digital mammography has been progressively introduced in screening centers, since recent evolution of photostimulable phosphor detectors. The aim of this work is the validation of a methodology for reconstructing digital images of a polymethyl-methacrylate (PMMA) phantom (P01 model) under pure Monte Carlo techniques. A reference image has been acquired for this phantom under automatic exposure control (AEC) mode (28 kV and 14 mAs). Some variance reduction techniques (VRT) have been applied to improve the efficiency of the simulations, defined as the number of particles reaching the imaging system per starting particle. All images have been used and stored in DICOM format. The results prove that the signal-to-noise ratio (SNR) of the reconstructed images have been increased with the use of the VRT, showing similar values between different employed tallies. As a conclusion, these images could be used during quality control testing for showing any deviation of the exposition parameters from the desired reference level.