The conspicuity of the detection of small calcifications may be improved, under certain imaging conditions, by delivering higher dose toward the central views of a tomosynthesis scan, while also reducing the dose at peripheral angles to keep total administered radiation dose equivalent. The degree of improvement depends on the choice of reconstruction filters as well as the imaging task. The improvement is more substantial for high-frequency imaging tasks and when an aggressive slice-thickness (ST) filter is applied to reduced the high-frequency noise at peripheral angles.

Purpose A novel Megavoltage (MV) multi-layer imager (MLI) design featuring higher detective quantum efficiency and lower noise than current conventional MV imagers in clinical use has been recently reported. Optimization of the MLI design for multiple applications including tumor tracking, MV-CBCT and portal dosimetry requires a computational model that will provide insight into the physics processes that affect the overall and individual components’ performance. The purpose of the current work was to develop and validate a comprehensive computational model that can be used for MLI optimization. Methods The MLI model was built using the Geant4 Application for Tomographic Emission (GATE) application. The model includes x-ray and charged particle interactions as well as the optical transfer within the phosphor. A first prototype MLI device featuring a stack of four detection layers was used for model validation. Each layer of the prototype contains a copper buildup sheet, a phosphor screen and photodiode array. The model was validated against measured data of Modulation Transfer Function (MTF), Noise Power Spectrum (NPS) and Detective Quantum Efficiency (DQE). MTF was computed using a slanted slit with 2.3° angle and 0.1 mm width. NPS was obtained using the autocorrelation function technique. DQE was calculated from MTF and NPS data. The comparison metrics between simulated and measured data were the Pearson’s correlation coefficient (r) and the normalized root-mean-square error (NRMSE). Results Good agreement between measured and simulated MTF and NPS values was observed. Pearson’s correlation coefficient for the combined signal from all layers of the MLI was equal to 0.9991 for MTF and 0.9992 for NPS; NRMSE was 0.0121 for MTF and 0.0194 for NPS. Similarly, the DQE correlation coefficient for the combined signal was 0.9888 and the NRMSE was 0.0686. Conclusions A comprehensive model of the novel MLI design was developed using the GATE toolkit and validated against measured MTF, NPS and DQE data acquired with a prototype device featuring four layers. This model will be used for further optimization of the imager components and configuration for clinical radiotherapy applications.

We have shown the effect of increasing x-ray energy as well as projection domain subtraction on breast structural noise. Further, we have exhibited the utility of the CLSM for DE and TE subtraction CE imaging in the optimization of imaging parameters such as x-ray energy, f , and w as well as guiding the understanding of their effects on image contrast and noise.