The three CT components with the greatest impact on image quality are the X-ray source, detection system and reconstruction algorithms. In this paper, we focus on the first two. We describe the state-of-the-art of CT detection systems, their calibrations, software corrections and common performance metrics. The components of CT detection systems, such as scintillator materials, photodiodes, data acquisition electronics and anti-scatter grids, are discussed. Their impact on CT image quality, their most important characteristics, as well as emerging future technology trends for each, are reviewed. The use of detection for multi-energy CT imaging is described. An overview of current CT X-ray sources, their evolution to support major trends in CT imaging and future trends is provided.
BackgroundTo evaluate the feasibility of multicolour quantitative imaging with spectral photon-counting computed tomography (SPCCT) of different mixed contrast agents.MethodsPhantoms containing eleven tubes with mixtures of varying proportions of two contrast agents (i.e. two selected from gadolinium, iodine or gold nanoparticles) were prepared so that the attenuation of each tube was about 280 HU. Scans were acquired at 120 kVp and 100 mAs using a five-bin preclinical SPCCT prototype, generating conventional, water, iodine, gadolinium and gold images. The correlation between prepared and measured concentrations was assessed using linear regression. The cross-contamination was measured for each material as the root mean square error (RMSE) of its concentration in the other material images, where no signal was expected. The contrast-to-noise ratio (CNR) relative to a phosphate buffered saline tube was calculated for each contrast agent.ResultsThe solutions had similar attenuations (279 ± 10 HU, mean ± standard deviation) and could not be differentiated on conventional images. However, a distinction was observed in the material images within the same samples, and the measured and prepared concentrations were strongly correlated (R2 ≥ 0.97, 0.81 ≤ slope ≤ 0.95, -0.68 ≤ offset ≤ 0.89 mg/mL). Cross-contamination in the iodine images for the mixture of gold and gadolinium contrast agents (RMSE = 0.34 mg/mL) was observed. CNR for 1 mg/mL of contrast agent was better for the mixture of iodine and gadolinium (CNRiodine = 3.20, CNRgadolinium = 2.80) than gold and gadolinium (CNRgadolinium = 1.67, CNRgold = 1.37).ConclusionsSPCCT enables multicolour quantitative imaging. As a result, it should be possible to perform imaging of multiple uptake phases of a given tissue/organ within a single scan by injecting different contrast agents sequentially.
The emerging of fast‐rotating MDCT scanners, and the recent approach of the, so called, “Slice War” to its saturation, opened new opportunities for CT evolution. New routes to extend CT applications beyond anatomical imaging have been pursued. Quantitative functional imaging seems to become one of the main trends in this process, with perfusion applications and multi‐energy CT methods as the leading techniques.To enable a simultaneous dual energy CT scanning, using a single X‐ray tube, without FOV, or sampling limitations, a special double‐layer detector CT has been developed in PHILIPS Healthcare. The conventional CT detection pixel has been reconfigured, to consist of 2 Scintillator layers, read simultaneously, by a double‐layer, side‐looking photodiode. The top‐layer scintillator has been chosen to contain, relatively, low atomic‐number elements, while having a very high light output, and very low afterglow. Its thickness has been optimized to achieve a maximum spectral separation between Iodine and Calcium. A 2‐mm layer of GOS has been used for the bottom Scintillator layer, to enable stopping of 99.8% of the X‐rays, transmitted through the top layer, without limiting the GOS light collection which is done sideways. The raw data of each of the detector layers is reconstructed separately, resulting in a Low‐Energy and a High‐Energy HU images. Thus, each slice‐pixel has two HU values assigned to it, the low and the high energy, respectively. In addition, a weighted sum of the two raw data is reconstructed to give the conventional CT image, while the weighting factor can be modified to present the combined image at any desired mean energy, within the system energy range. The pixels of each slice are mapped on a 2D spectral scatter plot, HU_Low_E VS. HU_High_E. The physics nature of the radiation interaction in this energy range, determines that varied concentrations of the same material (same effective atomic number) are represented along a straight line on this map. Also, as will be shown, this method enables the separation and quantification of specific materials, like Iodine, from mixtures with other compounds.The system capability of material identification and quantification enables plaque characterization, non cathartic virtual colonoscopy, virtual non‐contrast imaging, and an accurate quantitative mapping of perfused Iodine for advanced functional CT applications. More than 2000 human patients have been scanned in a fully operated system, as well as plenty of research animals, at the Hadassah University Hospital in Jerusalem. The animal experiments (rabbits) aimed, mainly, at testing the system capability with new, targeted contrast agents, indicating a great opportunity for the use of multi‐energy CT, and full spectral CT in the future.Learning Objectives:1. Understanding the clinical opportunities associated with a dual‐energy CT.2. Understanding the unique advantages, the tradeoffs, and the limitations of the double‐layer detector CT approach.3. Understanding the principles of the material identification and analysis method in the image domain, chosen for this system.
Fast 16-slice spiral CT delivers superior cardiac visualization in comparison to older generation 2-to 8-slice scanners due to the combination of high temporal resolution along with isotropic spatial resolution and large coverage. The large beam opening of such scanners necessitates the use of adequate algorithms to avoid cone beam artifacts. We have developed a multi-cycle phase selective 3D back projection reconstruction algorithm that provides excellent temporal and spatial resolution for 16-slice CT cardiac images free of cone beam artifacts.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.