Roland Proksa

Experimental feasibility of multi-energy photon-counting K-edge imaging in pre-clinical computed tomography

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.

K-edge imaging in x-ray computed tomography using multi-bin photon counting detectors

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.

Atherosclerotic plaque composition: analysis with multicolor CT and targeted gold nanoparticles.

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, calcification, 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, iodine-based 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.

Resampling of data between arbitrary grids using convolution interpolation

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 the authors 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, the authors like to introduce a new technique to derive the sampling density function needed for the first step of their 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.

3D cone-beam CT reconstruction for circular trajectories

3D reconstruction from 2D projections obtained along a single circular source trajectory is most commonly done using an algorithm due to Feldkamp, Davis and Kress. In this paper we propose an alternative approach based on a cone-beam to parallel-beam rebinning step, a corresponding rebinning step into a rectangular virtual detector plane and a filtered backprojection. This approach yields an improved image quality reflected by a decreased low-intensity drop which is well known for 3D reconstruction from projection data obtained along circular trajectories. At the same time the computational complexity is lower than in Feldkamps original approach. Based on this idea, a hybrid 3D cone-beam reconstruction method is formulated that enlarges the reconstruction volume in its dimension along the rotation axis of the cone-beam CT system. This enlargement is achieved by applying different reconstruction conditions for each voxel. An optimal ratio between the reconstructible and irradiated volume of the scanned object is achieved.

Multienergy Photon-counting K-edge Imaging: Potential for Improved Luminal Depiction in Vascular Imaging

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.

Computed tomography in color: NanoK-enhanced spectral CT molecular imaging.

New multidetector cardiac computed tomography (MDCT) can image the heart within the span of a few beats, and as such, it is the favored noninvasive approach to assess coronary anatomy rapidly. However, MDCT has proven to be more useful for excluding coronary disease than for making positive diagnoses. The inability to detect unstable cardiac disease arises from the confounding attenuating effects of calcium deposits within atherosclerotic plaques, which obscure lumen anatomy, and from the insensitivity of CT X-rays to image low attenuating intraluminal thrombus adhered to a disrupted plaque cap, the absolute condition of ruptured plaque and unstable disease.[1–6] It is now well understood that the sensitive detection and quantification of small intravascular thrombus in coronary arteries with molecular imaging techniques could provide a direct metric to diagnose and risk stratify patients presenting with chest pain.[7,8]

Helical cardiac cone beam reconstruction using retrospective ECG gating.

In modern computer tomography (CT) systems, the fast rotating gantry and the increased detector width enable 3D imaging of the heart. Cardiac volume CT has a high potential for non-invasive coronary angiography with high spatial resolution and short scan time. Due to the increased detector width, true cone beam reconstruction methods are needed instead of adapted 2D reconstruction schemes. In this paper, the extended cardiac reconstruction method is introduced. It integrates the idea of retrospectively gated cardiac reconstruction for helical data acquisition into a cone beam reconstruction framework. It leads to an efficient and flexible algorithmic scheme for the reconstruction of single- and multi-phase cardiac volume datasets. The method automatically adapts the number of cardiac cycles used for the reconstruction. The cone beam geometry is fully taken into account during the reconstruction process. Within this paper, results are presented on patient datasets which have been acquired using a 16-slice cone beam CT system.

The n-PI-method for helical cone-beam CT

A new class of acquisition schemes for helical cone-beam computed tomography (CB-CT) scanning is introduced, and their effect on the reconstruction methods is analyzed. These acquisition schemes are based on a new detector shape that is bounded by the helix. It will be shown that the data acquired with these schemes are compatible with exact reconstruction methods, and the adaptation of exact reconstruction algorithms to the new acquisition geometry is described. At the same time, the so-called PI-sufficiency condition is fulfilled. Moreover, a good fit to the acquisition requirements of the various medical applications of cone-beam CT is achieved. In contrast to other helical cone-beam acquisition and reconstruction methods, the n-PI-method introduced in this publication allows for variable pitches of the acquisition helix. This additional feature will introduce a higher flexibility into the acquisition protocols of future medical cone-beam scanners. An approximative n-PI-filtered backprojection (n-PI-FBP) reconstruction method is presented and verified. It yields convincing image quality.

Noise and resolution in images reconstructed with FBP and OSC algorithms for CT

This paper presents a comparison between an analytical and a statistical iterative reconstruction algorithm for computed transmission tomography concerning their noise and resolution performance. The reconstruction of two-dimensional images from simulated fan-beam transmission data is performed with a filtered back-projection (FBP) type reconstruction and an iterative ordered subsets convex (OSC) maximum-likelihood method. A special software phantom, which allows measuring the resolution and noise in a nonambiguous way, is used to simulate transmission tomography scans with different signal-to-noise ratios (SNR). The noise and modulation transfer function is calculated for FBP and OSC reconstruction at several positions, distributed over the field-of-view (FOV). The reconstruction with OSC using different numbers of subsets shows an inverse linear relation to the number of iterations that are necessary to reach a certain resolution and SNR, i.e., increasing the number of subsets by a factor x reduces the number of required iterations by the same factor. The OSC algorithm is able to achieve a nearly homogeneous high resolution over the whole FOV, which is not achieved with FBP. The OSC method achieves a lower level of noise compared with FBP at the same resolution. The reconstruction with OSC can save a factor of up to nine of x-ray dose compared with FBP in the investigated range of noise levels.