Background: Although Spectral CT is still in its early clinical development stages, K-edge contrast agents designed to specifically target thrombus could provide rapid stratification of ED patients with unclear CP etiology. Objective: To develop and demonstrate a systemically administered Spectral CT molecular imaging agent to diagnose intravascular thrombus in rabbits. Materials: A nanocolloid (~200nm) comprised of bismuth oleate in oil (20 vol%) encapsulated with phosphatidylcholine and functionalized with an anti-fibrin peptide -PEG2000-phosphatidylethanolamine conjugate was developed (Anti-fibrin BiOL NC). Results: Rabbits with iliac thrombus received anti-fibrin BiOL NC (1.5 ml/kg) via ear vein, which circulated for 2 hrs. The vessels were excised and imaged with a first generation Spectral CT scanner. K-edge contrast enhancement was appreciated in animals receiving anti-fibrin BiOL NC (n=4), but not in those given irrelevant-targeted BiOL NC, fibrin-targeted control nanocolloid or saline. (Figure) O...
In interventional MR, 3D visualization of catheters is hampered by low spatial and temporal resolution as conventional image reconstruction requires data sampling at or above the Nyquist rate. We propose a model-based reconstruction technique to fit a parameterised model of a catheter to acquired MRI data by minimising the -norm in Fourier space. A modelled image of the catheter shape is transformed to the Fourier space and then registered to the acquired data. Thereby the number of independent degrees of freedom to be solved for in reconstruction is reduced. Using computer simulations and phantom data it is demonstrated that the catheter shape can be reconstructed from highly undersampled data indicating the potential of the method for 3D imaging of catheters.
One major obstacle for MR-guided catheterizations is long acquisition times associated with visualizing interventional devices. Therefore, most techniques presented hitherto rely on single-plane imaging to visualize the catheter. Recently, accelerated three-dimensional (3D) imaging based on compressed sensing has been proposed to reduce acquisition times. However, frame rates with this technique remain low, and the 3D reconstruction problem yields a considerable computational load. In X-ray angiography, it is well understood that the shape of interventional devices can be derived in 3D space from a limited number of projection images. In this work, this fact is exploited to develop a method for 3D visualization of active catheters from multiplanar two-dimensional (2D) projection MR images. This is favorable to 3D MRI as the overall number of acquired profiles, and consequently the acquisition time, is reduced. To further reduce measurement times, compressed sensing is employed. Furthermore, a novel single-channel catheter design is presented that combines a solenoidal tip coil in series with a single-loop antenna, enabling simultaneous tip tracking and shape visualization. The tracked tip and catheter properties provide constraints for compressed sensing reconstruction and subsequent 2D/3D curve fitting. The feasibility of the method is demonstrated in phantoms and in an in vivo pig experiment.
The development of spectral computed tomography (CT) using binned photon-counting detectors has garnered great interest in recent years and has enabled selective imaging of K-edge materials. A practical challenge in CT image reconstruction of K-edge materials is the mitigation of image artifacts that arise from reduced-view and/or noisy decomposed sinogram data. In this note, we describe and investigate sparsity-regularized penalized weighted least squares-based image reconstruction algorithms for reconstructing K-edge images from few-view decomposed K-edge sinogram data. To exploit the inherent sparseness of typical K-edge images, we investigate use of a total variation (TV) penalty and a weighted sum of a TV penalty and an ℓ1-norm with a wavelet sparsifying transform. Computer-simulation and experimental phantom studies are conducted to quantitatively demonstrate the effectiveness of the proposed reconstruction algorithms.
Flat field calibration methods are commonly used in computed tomography (CT) to correct for system imperfections. Unfortunately, they cannot be applied in energy-resolving CT when using bow-tie filters owing to spectral distortions imprinted by the filter. This work presents a novel semi-analytical calibration method for photon-counting spectral CT systems, which is applicable with a bow-tie filter in place and efficiently compensates pile-up effects at fourfold increased photon flux compared to a previously published method without degradation of image quality. The achieved reduction of the scan time enabled the first K-edge imaging in-vivo. The method employs a calibration measurement with a set of flat sheets of only a single absorber material and utilizes an analytical model to predict the expected photon counts, taking into account factors such as x-ray spectrum and detector response. From the ratios of the measured x-ray intensities and the corresponding simulated photon counts, a look-up table is generated. By use of this look-up table, measured photon-counts can be corrected yielding data in line with the analytical model. The corrected data show low pixel-to-pixel variations and pile-up effects are mitigated. Consequently, operations like material decomposition based on the same analytical model yield accurate results. The method was validated on a experimental spectral CT system equipped with a bow-tie filter in a phantom experiment and an in-vivo animal study. The level of artifacts in the resulting images is considerably lower than in images generated with a previously published method. First in-vivo K-edge images of a rabbit selectively depict vessel occlusion by an ytterbium-based thermoresponsive polymer.
Recently, a K-edge imaging technique for energy-resolving photon-counting detectors based on Maximum-Likelihood estimation for material separation in the projection domain with subsequent image formation using filtered back projection (FBP) was presented. Despite its computational load, use of statistical reconstruction techniques for image reconstruction from material-specific sinograms is favourable as they feature superior signal to noise ratio (SNR). This work presents an estimation of the noise in material-decomposed sinograms using Fisher information in order to enable statistical image reconstruction. Simulations demonstrate that a gain of two in SNR compared to FBP reconstruction can be obtained. This improvement may be used for x-ray dose reduction but is in particular desirable to limit count rates and, thus, which is a significant challenge with current photon-counting detectors.
Introduction Fast visualization of catheters in 3D is indispensable for safe and convenient navigation in MR-guided interventions. With standard dynamic 3D imaging methods sufficient spatial resolution is difficult to achieve at the required temporal rates. The advent of MR-safe guidewires [1] holds great promise for operating active devices without hazardous heating effects in-vivo. With respect to accelerated imaging, active devices lend themselves well to undersampling methods given their confined sensitivity volume. Methods such as Compressed Sensing (CS) [2] are ideally suited to exploit the image sparseness inherent to images acquired with active catheter antennae. While CS allows for fast data acquisition times, its iterative reconstruction algorithms are time-expensive. Thus, the number of iterations has to be as low as possible in order to meet the real-time requirements for catheter tracking. In this work, the feasibility of using CS for accelerating 3D imaging of active catheters is investigated. Dedicated constraints are introduced, taking into account the known catheter length and the catheter position, in order to keep the computational burden of the reconstruction step to a minimum.
The very high x-ray flux rates employed in today's human computed tomography (CT) scanners in order to keep scanning times at a conveniently low level constitute the most challenging obstacle to the advent of clinical, photon-counting (spectral) CT. Even with most sophisticated, application-specific, energy-discriminating, photon-counting readout electronics, designed for room-temperature semi-conductor sensors like CdTe or CZT, the effects of spectral degradation due to pulse pile-up, i.e., count rate losses and gains will have to be taken into account in a clinical setting. The energy registered in a first-order pile-up event (superposition of two pulses) depends strongly on the energies of the two primaries involved, the difference in their arrival times and the spectral detector response behavior. We present an analytic model for the number of expected counts in binned photon-counting detectors, which is based on work by Wielopolski and Gardner and takes into account the combined effects of a spectral detector response function and 1 st order pulse pile-up. The analytic model is validated by means of Monte-Carlo simulations and is applied to a simulation of a clinical spectral CT scenario in the context of K-edge imaging of a high-atomic number element as a contrast material. The artifacts in the reconstructed single-bin images and their manifestation in material-decomposed images are discussed and interpreted in terms of gains and losses of counts due to pile-up. Finally, we discuss the shortcomings of the model like the limitation to 1 st order pile-up and the inherent restriction of the Wielopolski-Gardner model to peak pile-up.
'%3e%3cpath fill='%23012169' d='M0 0v30h60V0z'/%3e%3cpath stroke='%23fff' stroke-width='6' d='m0 0 60 30m0-30L0 30'/%3e%3cpath stroke='%23C8102E' stroke-width='4' d='m0 0 60 30m0-30L0 30' clip-path='url(%23b)'/%3e%3cpath stroke='%23fff' stroke-width='10' d='M30 0v30M0 15h60'/%3e%3cpath stroke='%23C8102E' stroke-width='6' d='M30 0v30M0 15h60'/%3e%3c/g%3e%3c/svg%3e)
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)
'%3e%3ccircle r='20' fill='%23008'/%3e%3ccircle r='17.5' fill='%23fff'/%3e%3ccircle r='3.5' fill='%23008'/%3e%3cg id='d'%3e%3cg id='c'%3e%3cg id='b'%3e%3cg id='a' fill='%23008'%3e%3ccircle r='.875' transform='rotate(7.5 -8.75 133.5)'/%3e%3cpath d='M0 17.5.6 7 0 2l-.6 5L0 17.5z'/%3e%3c/g%3e%3cuse xlink:href='%23a' transform='rotate(15)'/%3e%3c/g%3e%3cuse xlink:href='%23b' transform='rotate(30)'/%3e%3c/g%3e%3cuse xlink:href='%23c' transform='rotate(60)'/%3e%3c/g%3e%3cuse xlink:href='%23d' transform='rotate(120)'/%3e%3cuse xlink:href='%23d' transform='rotate(-120)'/%3e%3c/g%3e%3c/svg%3e)