Theoretical considerations predicted the feasibility of K-edge x-ray computed tomography (CT) imaging using energy discriminating detectors with more than two energy bins. This technique enables material-specific imaging in CT, which in combination with high-Z element based contrast agents, opens up possibilities for new medical applications. In this paper, we present a CT system with energy detection capabilities, which was used to demonstrate the feasibility of quantitative K-edge CT imaging experimentally. A phantom was imaged containing PMMA, calcium-hydroxyapatite, water and two contrast agents based on iodine and gadolinium, respectively. Separate images of the attenuation by photoelectric absorption and Compton scattering were reconstructed from energy-resolved projection data using maximum-likelihood basis-component decomposition. The data analysis further enabled the display of images of the individual contrast agents and their concentrations, separated from the anatomical background. Measured concentrations of iodine and gadolinium were in good agreement with the actual concentrations. Prior to the tomographic measurements, the detector response functions for monochromatic illumination using synchrotron radiation were determined in the energy range 25 keV-60 keV. These data were used to calibrate the detector and derive a phenomenological model for the detector response and the energy bin sensitivities.

After passage through matter, the energy spectrum of a polychromatic beam of x-rays contains valuable information about the elemental composition of the absorber. Conventional x-ray systems or x-ray computed tomography (CT) systems, equipped with scintillator detectors operated in the integrating mode, are largely insensitive to this type of spectral information, since the detector output is proportional to the energy fluence integrated over the whole spectrum. The main purpose of this paper is to investigate to which extent energy-sensitive photon counting devices, operated in the pulse-mode, are capable of revealing quantitative information about the elemental composition of the absorber. We focus on the detection of element-specific, K-edge discontinuities of the photo-electric cross-section. To be specific, we address the question of measuring and imaging the local density of a gadolinium-based contrast agent, in the framework of a generalized dual-energy pre-processing. Our results are very promising and seem to open up new possibilities for the imaging of the distribution of elements with a high atomic number Z in the human body using x-ray attenuation measurements. To demonstrate the usefulness of the detection and the appropriate processing of the spectral information, we present simulated images of an artherosclerotic coronary vessel filled with gadolinium-based contrast agent. While conventional systems, equipped with integrating detectors, often fail to differentiate between contrast filled lumen and artherosclerotic plaque, the use of an energy-selective detection system based on the counting of individual photons reveals a strong contrast between plaque and contrast agent.

Purpose:To investigate the potential of spectral computed tomography (CT) (popularly referred to as multicolor CT), used in combination with a gold high-density lipoprotein nanoparticle contrast agent (Au-HDL), for characterization of macrophage burden, calcifi cation, and stenosis of atherosclerotic plaques. Materials and Methods:The local animal care committee approved all animal experiments. A preclinical spectral CT system in which incident x-rays are divided into six different energy bins was used for multicolor imaging. Au-HDL, an iodine-based contrast agent, and calcium phosphate were imaged in a variety of phantoms. Apolipoprotein E knockout (apo E-KO) mice were used as the model for atherosclerosis. Gold nanoparticles targeted to atherosclerosis (Au-HDL) were intravenously injected at a dose of 500 mg per kilogram of body weight. Iodine-based contrast material was injected 24 hours later, after which the mice were imaged. Wild-type mice were used as controls. Macrophage targeting by Au-HDL was further evaluated by using transmission electron microscopy and confocal microscopy of aorta sections. Results:Multicolor CT enabled differentiation of Au-HDL, iodinebased contrast material, and calcium phosphate in the phantoms. Accumulations of Au-HDL were detected in the aortas of the apo E-KO mice, while the iodine-based contrast agent and the calcium-rich tissue could also be detected and thus facilitated visualization of the vasculature and bones (skeleton), respectively, during a single scanning examination. Microscopy revealed Au-HDL to be primarily localized in the macrophages on the aorta sections; hence, the multicolor CT images provided information about the macrophage burden. Conclusion:Spectral CT used with carefully chosen contrast agents may yield valuable information about atherosclerotic plaque composition.q RSNA, 2010Supplemental material: http://radiology.rsna.org/lookup /suppl

For certain medical applications resampling of data is required. In magnetic resonance tomography (MRT) or computer tomography (CT), e.g., data may be sampled on nonrectilinear grids in the Fourier domain. For the image reconstruction a convolution-interpolation algorithm, often called gridding, can be applied for resampling of the data onto a rectilinear grid. Resampling of data from a rectilinear onto a nonrectilinear grid are needed, e.g., if projections of a given rectilinear data set are to be obtained. In this paper we introduce the application of the convolution interpolation for resampling of data from one arbitrary grid onto another. The basic algorithm can be split into two steps. First, the data are resampled from the arbitrary input grid onto a rectilinear grid and second, the rectilinear data is resampled onto the arbitrary output grid. Furthermore, we like to introduce a new technique to derive the sampling density function needed for the first step of our algorithm. For fast, sampling-pattern-independent determination of the sampling density function the Voronoi diagram of the sample distribution is calculated. The volume of the Voronoi cell around each sample is used as a measure for the sampling density. It is shown that the introduced resampling technique allows fast resampling of data between arbitrary grids. Furthermore, it is shown that the suggested approach to derive the sampling density function is suitable even for arbitrary sampling patterns. Examples are given in which the proposed technique has been applied for the reconstruction of data acquired along spiral, radial, and arbitrary trajectories and for the fast calculation of projections of a given rectilinearly sampled image.

The purpose of this study was to investigate whether spectral computed tomography (CT) has the potential to improve luminal depiction by differentiating among intravascular gadolinium-based contrast agent, calcified plaque, and stent material by using the characteristic k edge of gadolinium. A preclinical spectral CT scanner with a photon-counting detector and six energy threshold levels was used to scan a phantom vessel. A partially occluded stent was simulated by using a calcified plaque isoattenuated to a surrounding gadolinium chelate solution. The reconstructed images showed an effective isolation of the gadolinium with subsequent clear depiction of the perfused vessel lumen. The calcified plaque and the stent material are suppressed.