The limited visibility of breast lesions underlying silicone implants hampers the early detection of breast cancer-like features, highlighting the need for imaging methods that improve contrast behind implants. The present study investigates, both computationally and experimentally, the feasibility of combining spectrum optimization and material decomposition to enhance the contrast-to-noise ratio (CNR) of micro-calcifications in mammographic phantoms with breast implants. The goal is to reconstruct an image with improved CNR by using recovered energy-independent maps of two reference materials and applying the Beer–Lambert equation to the energy bin with the highest identified CNR. The computational study evaluates the approach using aluminum oxide and hydroxyapatite micro-calcifications embedded in standard-density breast tissue and partially obscured by silicone breast implants of four different thicknesses. Energy-bin images are generated from a simulated monochromatic x-ray source and weighted using four Tungsten polychromatic spectra with an additional filter: aluminum (1 mm) at three voltages and rhodium (0.05 mm) at 28 kVp. The experimental study independently assesses the same approach using aluminum oxide micro-calcifications within the Mammo-156 phantom, partially covered by a 250 cc compressed silicone implant. Polymethyl methacrylate slabs are added to simulate a 5 cm-thick breast. The experimental setup consists of a Tungsten micro-focus x-ray source and a hybrid photon counting detector Timepix3, which enables the acquisition of energy bin images and the estimation of entrance radiation dose. Exposure time is adjusted to achieve an entrance radiation dose of approximately 4 mGy for each spectrum, which is a typical value used in mammography. Simulation results demonstrate an enhancement in CNR in the reconstructed images compared with both the input energy-bin images with the highest CNR and the energy-weighted images, for both types of micro-calcifications and in both regions-inside and outside the implant-across all implant thicknesses. Experimental results also show the enhancement in CNR in the reconstructed images under realistic imaging conditions, for micro-calcifications in both inside and outside the implant region.

X-ray phase contrast imaging (XPCI) shows promising potential for analyzing blood vessels affected by a cardiovascular disease and may become a valuable diagnostic tool in angiography. Identifying the most suitable XPCI method for providing optimal visibility at clinically acceptable doses is critical. This study presents a two-dimensional computational simulation in Geant4 to quantitatively compare two XPCI techniques—Inline XPCI and Edge Illumination Single Mask (EISM)—in visualizing atherosclerotic plaques within the projected thickness image of the lumen. The angiographic specimen analyzed was modeled as three concentric cylinders, with half of the inner cylinder simulating the lumen of the blood vessel and the other half simulating an atherosclerotic plaque, the intermediate cylinder simulating the vessel tissue, and the outer cylinder simulating the tissue around the blood vessel. The computational setup consisted of a W-anode polychromatic x-ray source and a photon counting detector, with six spectra and three sample-to-detector distances (magnifications) considered. To enable a direct comparison with Inline XPCI, a multi-material phase retrieval procedure was adapted to work within the EISM framework. Estimates of absorbed dose were also performed for each XPCI method. The results demonstrate that Inline XPCI achieves a superior contrast-to-noise ratio (CNR) as compared to EISM in both analyzed regions of the recovered image, across all spectra and magnifications, while also exhibiting lower absorbed doses. The difference in CNR between the two XPCI methods decreases as the voltage and magnification increases. While Inline XPCI shows superior contrast in the plaque region for all voltages and magnifications studied, EISM excels in recovering the projected thickness in the free-plaque region, achieving better contrast at low voltages for any magnification.

This study presents a two-dimensional computational simulation in Geant4 to quantitatively implement an X-ray spectral multi-material decomposition approach with the edge illumination single mask method. The aim is to simultaneously retrieve the projected thickness maps of different materials in two multi-material samples and directly estimate their phase shift information. Images in multiple energy bins (i.e., energy-bin images) are generated from a simulated monochromatic X-ray source and a weighted polychromatic spectrum. By analyzing the contrast-to-noise ratio (CNR) in each energy-bin image, the optimal energy ranges for inclusion in the spectral approach are identified. The results demonstrate that the approach successfully retrieves the projected thickness maps, showing trends consistent with the theoretical thickness maps. Furthermore, the projected thickness maps for each material are retrieved independently, effectively isolating each material’s contribution even in cases of overlap. By using the obtained projected thickness maps, the phase shift map can be derived. Compared to the phase shift map estimated with the Wiener approach, the proposed approach provides a more accurate phase distribution and remains artifact-free across the entire image.

Edge Illumination Single Mask (EISM) is an X-ray phase-contrast imaging method that simultaneously retrieves absorption and differential phase-shift information from a single image. Recent applications have focused on exploiting this method to obtain additional information, such as projected thickness maps of the materials composing the sample. This study presents a two-dimensional computational comparison of two EISM multi-material phase retrieval approaches—the Beltran approach and the spectral multi-material decomposition approach—to evaluate their suitability for retrieving the projected thickness of different materials in two complex samples. To enable a comparison under equivalent absorbed dose conditions, the Beltran approach is combined with energy-weighting. The results demonstrate that the spectral multi-material decomposition approach provides higher contrast-to-noise ratio (CNR) than the energy-weighted Beltran approach when retrieving the projected thickness of a single material. However, its CNR decreases as the number of materials to be retrieved increases. While the energy-weighted Beltran approach shows higher CNR in the projected thickness maps retrieved, the spectral multi-material decomposition approach excels at isolating each material’s contribution and providing projected thickness maps that are free of residual cross-material visibility in regions containing overlapping materials.

X-ray imaging of dense breasts and breast implants often suffers from reduced lesion visibility because strong attenuation lowers contrast, while conventional rhodium (Rh) K-edge filtering suppresses part of the high-energy spectral tail. This study presents a Monte Carlo framework for spectroscopic mammography using a voxelated 1 mm thick cadmium telluride (CdTe) sensor and a first-order detector interaction model to evaluate energy-dependent image quality. The model reproduces fluorescence and inter-voxel energy redistribution in CdTe, but not the full detector chain, and remains idealized with respect to charge transport, carrier collection, threshold dispersion, and pile-up. Energy-resolved simulations in the 10–50 keV range were used to compute spectroscopic contrast-to-noise ratio (CNR) curves and to form integrated-spectrum (IS) images for four tested spectra. For the dense-breast calcium hydroxyapatite (HA) speck detection task considered here, and under the present simulation assumptions, replacing the standard 28 kVp + 50 μm Rh spectrum with 28 kVp + 1 mm Al increased the simulated IS image CNR by 23.11%, with an approximately 5% increase in estimated primary-incident air kerma at the phantom entrance plane. Preliminary experimental implant-phantom images were included as a qualitative feasibility check, showing a trend consistent with simulations. Within the limits of this task-specific simulation, the results suggest that preserving the transmitted high-energy tail can improve HA speck visibility for the present 1 mm CdTe photon-counting detector, with the 28 kVp + 1 mm Al spectrum outperforming the other tested cases.