Energy-Resolved CNR Performance in Dense Breast and Implant X-Ray Mammography Using a CdTe Photon-Counting Detector: A Monte Carlo Study

X-ray imaging of dense breasts and breast implants often suffers from reduced lesion visibility due to strong attenuation, while conventional rhodium (Rh) K-edge filtering typically suppresses high-energy photons. This study presents a Monte Carlo-based simulation and optimization framework for spectroscopic mammography using a voxelated Cadmium Telluride (CdTe) sensor, enabling quantitative evaluation of energy-dependent image quality. The system accurately simulates sensor fluorescence and inter-voxel energy redistribution, enabling direct comparability with real-world performance. Energy-resolved simulations in the 10-50 keV range were used to compute spectroscopic contrast-to-noise ratio (CNR) curves and identify optimal spectral regions and filter configurations. Replacing the standard Rh filter with aluminum (Al) filtration increased CNR by more than 23% with only a ~5% increase in entrance surface dose (ESD), significantly improving the visibility of hydroxyapatite microcalcifications, even behind dense tissue or implants. The shown work demonstrates practical guidelines and analysis for energy-resolved imaging optimizations obtained from simulations. The results imply that spectroscopic photon-counting detectors and methods can enhance dense-breast mammography image quality while maintaining low patient dose.