The Effect of Photon Energy Weighting on X-ray Imaging Based on a Photon Counting Detector

Development of photon counting detectors with the ability of energy discrimination would provide additional information. These detectors could improve the contrast-to-noise ratio (CNR) by using photon energy weighting with energy-dependent weighting factors. The purpose of this study was to evaluate the effect of photon energy weighting using GEANT4 Application for Tomographic Emission (GATE) version 6.0. The photon energy weighting depends on the X-ray attenuation coefficient of contrast elements and background materials. In this study, we simulated a photon counting X-ray imaging system. We designed a cadmium telluride (CdTe) photon counting detector (model PID-350, AJAT, Finland), the micro focus X-ray source (model L8601-01, Hamamatsu, Japan) and two phantoms with GATE. In the first case, we were concerned with calcifications in breast tissue or soft tissue. We defined a cubic phantom made of poly (methyl methacrylate) (PMMA) material with a thickness of 40 mm including four CaCO3 contrast elements with different thickness of 1.0, 3.0, 5.0, and 7.0 mm. In the second case, we designed a second phantom for contrast-enhanced digital mammography (CEDM). We defined two cylindrical phantoms made of PMMA with thicknesses of 30 and 40 mm, including four iodine contrast elements with different thicknesses of 0.3, 0.5, 1.0, and 1.5 mm. The effect of photon energy weighting was investigated in terms of the CNR. In all cases, photon energy weighting improve the CNR. The CNR improvements for CaCO3 with thicknesses of 1.0, 3.0, 5.0, and 7.0 mm were 1.41, 1.32, 1.43, and 1.56, respectively. For the second phantom with a thickness of 30 mm, the CNR improvements of iodine contrast elements with thicknesses of 1.0, 3.0, 5.0, and 7.0 mm were 1.01, 1.03, 1.09, and 1.13, respectively, and for the second phantom with a thicknesses of 40 mm, the CNR improvements of iodine contrast elements with thickness of 1.0, 3.0, 5.0, and 7.0 mm were 1.05, 1.07, 1.16, and 1.10, respectively. This study demonstrates that the photon energy weighting using additional information improves the CNR, which allows better detection of calcium, a contrast agent or other contrast elements.