Spectral Computed Tomography System Research Articles

Spectral computed tomography for quantitative decomposition of vulnerable plaques using a dual-energy technique: a Monte Carlo simulation study

A spectral computed tomography (CT) system based on an energy-resolved photon-counting Cadmium Zinc Telluride (CZT) detector with a dual energy technique can provide spectral information and can possibly distinguish between two or more materials with a single X-ray exposure using energy thresholds. This work provides the potential for three-material decomposition of vulnerable plaques using two inverse fitting functions. Additionally, there exists the possibility of using gold nanoparticles as a contrast agent for the spectral CT system in conjunction with a CZT photon-counting detector. In this simulation study, we used fan beam CT geometry that consisted of a 90 kVp X-ray spectrum and performed calculations by using the SpekCal program (REAL Software, Inc.) with Monte Carlo simulations. A basic test phantom was imaged with the spectral CT system for the calibration and decomposition process. This phantom contained three different materials, including lipid, iodine and gold nanoparticles, with six holes 3 mm in diameter. In addition to reducing pile-up and charge sharing effect, the photon counting detector was considered an ideal detector. Then, the accuracy of material decomposition techniques with two inverse fitting functions were evaluated between decomposed images and reference images in terms of root mean square error (RMSE). The results showed that decomposed images had a good volumetric fraction for each material, and the RMSE between the measured and true volumes of lipid, iodine and gold nanoparticle fractions varied from 12.51% to 1.29% for inverse fitting functions. The study indicated that spectral CT in conjunction with a CZT photon-counting detector in conjunction with a dual energy technique can be used to identifying materials and may be a promising modality for quantifying material properties of vulnerable plaques.

Comparison of spectral CT imaging methods based a photon-counting detector: Experimental study

Photon-counting detectors allow spectral computed tomography (CT) imaging using energy-resolved information from a polychromatic X-ray spectrum. The spectral CT images based on the photon-counting detectors are dependent on the energy ranges defined by energy bins for image acquisition. In this study, K-edge and energy weighting imaging methods were experimentally implemented by using a spectral CT system with a cadmium zinc telluride (CZT)-based photon-counting detector. The spectral CT images were obtained by various energy bins and compared in terms of CNR improvement for investigating the effect of energy bins and the efficiency of the spectral CT imaging methods. The results showed that the spectral CT image quality was improved by using the particular energy bins, which were optimized for each spectral CT imaging method and target material. The CNR improvement was different for the spectral CT imaging methods and target materials. It can be concluded that an appropriate selection of imaging method for each target material and the optimization of energy bin can maximize the quality of spectral CT images.

The effects of extending the spectral information acquired by a photon-counting detector for spectral CT

Photon-counting x-ray detectors with pulse-height analysis provide spectral information that may improve material decomposition and contrast-to-noise ratio (CNR) in CT images. The number of energy measurements that can be acquired simultaneously on a detector pixel is equal to the number of comparator channels. Some spectral CT designs have a limited number of comparator channels, due to the complexity of readout electronics. The spectral information could be extended by changing the comparator threshold levels over time, sub pixels, or view angle. However, acquiring more energy measurements than comparator channels increases the noise and/or dose, due to differences in noise correlations across energy measurements and decreased dose utilisation. This study experimentally quantified the effects of acquiring more energy measurements than comparator channels using a bench-top spectral CT system. An analytical and simulation study modeling an ideal detector investigated whether there was a net benefit for material decomposition or optimal energy weighting when acquiring more energy measurements than comparator channels. Experimental results demonstrated that in a two-threshold acquisition, acquiring the high-energy measurement independently from the low-energy measurement increased noise standard deviation in material-decomposition basis images by factors of 1.5–1.7 due to changes in covariance between energy measurements. CNR in energy-weighted images decreased by factors of 0.92–0.71. Noise standard deviation increased by an additional factor of due to reduced dose utilisation. The results demonstrated no benefit for two-material decomposition noise or energy-weighted CNR when acquiring more energy measurements than comparator channels. Understanding the noise penalty of acquiring more energy measurements than comparator channels is important for designing spectral detectors and for designing experiments and interpreting data from prototype systems with a limited number of comparator channels.

Allowable forward model misspecification for accurate basis decomposition in a silicon detector based spectral CT.

Material basis decomposition in the sinogram domain requires accurate knowledge of the forward model in spectral computed tomography (CT). Misspecifications over a certain limit will result in biased estimates and make quantum limited (where statistical noise dominates) quantitative CT difficult. We present a method whereby users can determine the degree of allowed misspecification error in a spectral CT forward model and still have quantification errors that are limited by the inherent statistical uncertainty. For a particular silicon detector based spectral CT system, we conclude that threshold determination is the most critical factor and that the bin edges need to be known to within 0.15 keV in order to be able to perform quantum limited material basis decomposition. The method as such is general to all multibin systems.

Breast tissue decomposition with spectral distortion correction: a postmortem study.

To investigate the feasibility of an accurate measurement of water, lipid, and protein composition of breast tissue using a photon-counting spectral computed tomography (CT) with spectral distortion corrections. Thirty-eight postmortem breasts were imaged with a cadmium-zinc-telluride-based photon-counting spectral CT system at 100 kV. The energy-resolving capability of the photon-counting detector was used to separate photons into low and high energy bins with a splitting energy of 42 keV. The estimated mean glandular dose for each breast ranged from 1.8 to 2.2 mGy. Two spectral distortion correction techniques were implemented, respectively, on the raw images to correct the nonlinear detector response due to pulse pileup and charge-sharing artifacts. Dual energy decomposition was then used to characterize each breast in terms of water, lipid, and protein content. In the meantime, the breasts were chemically decomposed into their respective water, lipid, and protein components to provide a gold standard for comparison with dual energy decomposition results. The accuracy of the tissue compositional measurement with spectral CT was determined by comparing to the reference standard from chemical analysis. The averaged root-mean-square error in percentage composition was reduced from 15.5% to 2.8% after spectral distortion corrections. The results indicate that spectral CT can be used to quantify the water, lipid, and protein content in breast tissue. The accuracy of the compositional analysis depends on the applied spectral distortion correction technique.

Quantitative material decomposition using spectral computed tomography with an energy-resolved photon-counting detector

Dual-energy computed tomography (CT) techniques have been used to decompose materials and characterize tissues according to their physical and chemical compositions. However, these techniques are hampered by the limitations of conventional x-ray detectors operated in charge integrating mode. Energy-resolved photon-counting detectors provide spectral information from polychromatic x-rays using multiple energy thresholds. These detectors allow simultaneous acquisition of data in different energy ranges without spectral overlap, resulting in more efficient material decomposition and quantification for dual-energy CT. In this study, a pre-reconstruction dual-energy CT technique based on volume conservation was proposed for three-material decomposition. The technique was combined with iterative reconstruction algorithms by using a ray-driven projector in order to improve the quality of decomposition images and reduce radiation dose. A spectral CT system equipped with a CZT-based photon-counting detector was used to implement the proposed dual-energy CT technique. We obtained dual-energy images of calibration and three-material phantoms consisting of low atomic number materials from the optimal energy bins determined by Monte Carlo simulations. The material decomposition process was accomplished by both the proposed and post-reconstruction dual-energy CT techniques. Linear regression and normalized root-mean-square error (NRMSE) analyses were performed to evaluate the quantitative accuracy of decomposition images. The calibration accuracy of the proposed dual-energy CT technique was higher than that of the post-reconstruction dual-energy CT technique, with fitted slopes of 0.97–1.01 and NRMSEs of 0.20–4.50% for all basis materials. In the three-material phantom study, the proposed dual-energy CT technique decreased the NRMSEs of measured volume fractions by factors of 0.17–0.28 compared to the post-reconstruction dual-energy CT technique. It was concluded that the proposed dual-energy CT technique can potentially be used to decompose mixtures into basis materials and characterize tissues according to their composition.

TU-F-18C-08: Micro-Calcification Detectability Using Spectral Breast CT Based On a Si Strip Detector

Purpose: To investigate the feasibility of micro-calcification (μCa) detectability by using an energy-resolved photon-counting Si strip detector for spectral breast computed tomography (CT). Methods: A bench-top CT system was constructed using a tungsten anode x-ray source with a focal spot size of 0.8 mm and a single line 256-pixel Si strip photon counting detector with a pixel pitch of 100 μm. The slice thickness was 0.5 mm. Five different size groups of calcium carbonate grains, from 105 to 215 μm in diameter, were embedded in a cylindrical resin phantom with a diameter of 16 mm to simulate μCas. The phantoms were imaged at 65 kVp with an Entrance Skin Air Kerma (ESAK) of 1.2, 3, 6, and 8 mGy. The images were reconstructed using a standard filtered back projection (FBP) with a ramp filter. A total of 200 μCa images (5 different sizes of μCas × 4 different doses × 10 images for each setting) were combined with another 200 control images without μCas, to ultimately form 400 images for the reader study. The images were displayed in random order to three blinded observers, who were asked to give a binary score on each image regarding the presence of μCas.more » The μCa detectability for each image was evaluated in terms of binary decision theory metrics. The sensitivity, specificity, and accuracy were calculated to study the size and dose-dependence for μCa detectability. Additionally, the influence of the partial volume effect on the μCa detectability was investigated by simulation. Results: For a μCa larger than 140 μm in diameter, detection accuracy of above 90 % was achieved with the investigated prototype spectral CT system at ESAK of 1.2 mGy. Conclusion: The proposed Si strip detector is expected to offer superior image quality with the capability to detect μCas for low dose breast imaging.« less

TU-F-18C-01: Breast Tissue Decomposition Using Spectral CT After Distortion Correction

Purpose: To investigate the feasibility of accurate breast tissue compositional characterization by using spectral-distortion-corrected dual energy images from a photon-counting spectral CT. Methods: Thirty eight postmortem breasts were imaged with a Cadmium-Zinc-Telluride (CZT)-based photon-counting spectral CT system at beam energy of 100 kVp. The energy-resolved detector sorted photons into low and high energy bins with a splitting energy of 42 keV. The estimated mean glandular dose (MGD) for each breast was approximately 2.0 mGy. Dual energy technique was used to decompose breast tissue into water, lipid, and protein contents. Two image-based methods were investigated to improve the accuracy of tissue compositional characterization. The first method simply limited the recorded spectra up to 90 keV. This reduced the pulse pile-up artifacts but it has some dose penalty. The second method corrected the spectral information of all measured photons by using a spectral distortion correction technique. Breasts were then chemically decomposed into their respective water, lipid, and protein contents, which was used as the reference standard. The accuracy of the tissue compositional measurement with spectral CT was evaluated by the root-mean-square (RMS) errors in percentage composition. Results: The errors in quantitative material decomposition were significantly reduced after the appropriate image processing methods. As compared to the chemical analysis as the reference standard, the averages of the RMS errors were estimated to be 15.5%, 3.3%, and 2.8% for the raw, energy-limited, and spectral-corrected images, respectively. Conclusion: Spectral CT can be used to accurately quantify the water, lipid, and protein contents in breast tissues by implementing a spectral distortion correction algorithm. The tissue compositional information can potentially improve the sensitivity and specificity for breast cancer diagnosis.

Spectral CT: a technology primer for contrast agent development

Recent developments in spectral CT systems featuring binned photon-counting detector technology have enabled an imaging concept on a pre-clinical level that has been coined K-edge imaging. This exciting concept allows the selective and quantitative imaging of contrast media by exploiting the K-edge discontinuity in the photo-electric component of X-ray absorption. An ideal application for K-edge imaging is CT imaging of target-specific and conventional contrast agents that have been designed to be spectral-CT-visible. Current limitations in detector hardware, however, result in typically high noise levels that hamper the application of K-edge imaging. In order to battle noise and assure sufficient sensitivity, the development of dedicated K-edge contrast media in combination with advanced image processing techniques is imperative. This work attempts a comprehensive overview on how the concert of dedicated contrast media, optimized data acquisition and innovative data processing techniques improve sensitivity of K-edge imaging which will foster clinical translation of the technology.

基于MARS系统的X射线能谱K-edge特性CT成像技术

The typical conventional CT system employs the digital integrating sensor, for which it is difficult to identify attenuation characteristics of different energy X-ray. This paper focuses on X-ray spectral imaging technology based on MARS X-ray spectral CT system. We scanned some singular element materials and a multi-material phantom with different energy X-ray bins, obtained some material K-edge characteristic curves, and reconstructed CT images of multi-material phantom. By means of CT images based on material K-edge characteristics, we can discriminate different materials or recognize more attenuation information of different materials. Compared to conventional X-ray CT technology, X-ray spectral CT can provide much richer attenuation information.

SU-D-116-03: Radiation Dose Reduction for High Resolution Spectral Breast CT Using Tensor-Framelet Based Iterative Reconstruction

Purpose: To investigate the feasibility of dose reduction using tensor‐framelet based iterative reconstruction (TFIR) method for a dedicated high resolution spectral breast computed tomography (CT). Methods: A simulation study was conducted with a phantom of 14 cm in diameter for a high resolution breast CT system based on an energy‐resolved photon‐counting Si strip detector with 0.1 mm pixel size. The modulation transfer function (MTF) calculated from images reconstructed by TFIR and FBP with simulation data was compared to the measured detector MTF. In the experimental study, a water phantom of 16 mm in diameter with Al wires of various diameters and a polyethylene (PE) plastic phantom of 13 mm in diameter with three water filled holes of 1, 2 and 3 mm were imaged with 1229 projections over 360° during a CT scan. The images were reconstructed by filtered back projection (FBP) and by TFIR with various projection undersampling ratio and the image quality between these two methods was compared. The spatial resolution was evaluated using Al wires of various diameters and the contrast to noise ratio (CNR) was evaluated using the PE phantom. Results: The MTFs calculated from the simulated large phantom images reconstructed by TFIR and FBP are comparable to the measured detector MTF. The spatial resolution was comparable for the images reconstructed by TFIR with 204 projections and by FBP with 614 projections. There was a slight in CNR using TFIR with 204 projections. Conclusion: The radiation dose of a high resolution spectral breast CT system is reduced by 67% by the TFIR technique without any reduction in the image quality. Therefore, TFIR can potentially be used for a high resolution spectral breast CT system to reduce the radiation dose for breast screening.

TH-A-103-08: System Optimization of Spectral Breast CT Based On An Energy-Resolved Photon-Counting Si Strip Detector: A Simulation Study

Purpose: To determine the optimal design parameters for a high resolution spectral breast CT system based on an energy-resolved photon counting Si strip detector for breast imaging. Methods: A simulation package was developed for a spectral breast CT system. The focal spot size (100 to 300 μm), magnification (1.1 to 1.4), motion blurring and detector pixel size (intrinsic pixel pitch and 4×4 pixel binning) were considered to optimize the system design. Simulations were conducted using single slice fan beam geometry at 60 kVp with 2 mm Al filter. The system modulation transfer functions (MTFs) were calculated from reconstructed image of a 10 μm diameter tungsten wire. The performance of the system with optimal design parameters was evaluated with a simulated breast phantom. A 14 cm diameter cylindrical phantom made of breast tissue with 20% glandularity was used to simulate an average-sized breast. The soft tissue lesions and microcalcifications were simulated with spheres of glandular tissues (1,2, and 4 mm in diameter) and hydroxyapatite (100 to 250 μm in diameter), respectively. Results: The spatial frequencies at 10 % of the maximum MTF was calculated to be 1.6 lp/mm and 6.4 lp/mm with and without a 4 x 4 pixel binning, respectively. The optimal system magnification was estimated to be 1.2. There was minimal improvement in system MTF when the x-ray tube focal spot size was changed from 300 to 100 μm. In the simulated breast phantom image, 100 μm microcalcifications can be clearly identified and the soft tissue contrast-to-noise ratio was improved with separate image processing, where 4×4 pixel binning was used at a dose level of 6 mGy. Conclusion: The simulation results show that the proposed system can potentially detect micro-calcifications and soft tissue lesions with a dose level equivalent to that of a standard two-view mammography.

TH‐A‐103‐06: Radiation Dose Reduction with Optimal Energy Weighting for a Prototype Energy‐Resolved Photon‐Counting Si Strip Detector

Purpose: To develop simulation and experimental methods for optimal energy weighting to reduce dose and enhance contrast for the detection of microcalcification, soft‐tissue lesions and iodine‐contrast objects using a prototype energy‐resolved photon‐counting Si strip CT detector. Methods: A prototype energy‐resolved photon‐counting Si strip CT detector was investigated for optimal energy weighting. The Si strip detector has 256 pixels with 100 μm pitch. It was placed in an edge‐on geometry which results in an effective attenuation length of 0.6 mm. A tungsten anode X‐ray spectrum of 65 kVp with 2 mm Al filter was used. Glandular and Adipose equivalent phantoms were constructed using PMMA and polyethylene. Water, calcium hydroxyapatite and iodine with different concentrations were used to simulate soft tissue lesion, microcalcification and contrast material in breast tissue. A simulation package was generated to reconstruct images from charge‐integrated and energy‐resolving photon‐counting detectors. Energy weighting factors based on projection and image based methods were used in the four energy bins to enhance contrast. Different energy thresholds were investigated based on iodine K‐edge, equal counts per bin, and equally spaced bins. CNR was computed to compare image quality between methods. Results: Simulation results indicate that using an optimized energy weighting image reconstruction improves CNR for water (30%–40%), for hydroxyapatite (30% –50%), and for iodine (35%–40%) in comparison of those images from charge‐integrated reconstruction. Conclusion: The implementation of energy weighting methods in image reconstruction for the prototype energy‐resolved photon‐counting Si strip CT detector can improve CNR or reduce radiation dose. This technique can potentially be used for detection of microcalcification, soft‐tissue lesions and iodine‐contrast object in a spectral breast CT system.

TH‐A‐103‐04: Microcalcification and Mass Detection with a Photon‐Counting Si Detector for Low Dose Breast Computed Tomography

Purpose: To investigate the feasibility of microcalcification and soft tissue lesion detection using an energy‐resolved photon‐counting detector based on Si strips for breast spectral computed tomography (CT). Methods: Simulations and experiments were performed with a prototype spectral CT system equipped with a Si‐based photon‐counting detector with energy discrimination capability and 0.1 mm pixel pitch. Simulations were performed according to the realistic experimental setup. The attenuation coefficient was computed from the linear combination of the individual linear attenuation coefficient of compositional elements. The detector was simulated with intrinsic pixel pitch along with 4×4 pixel binning for microcalcification and soft tissue lesion detection, respectively. In the experiment, two cylindrical phantoms of 13 mm in diameter were constructed from polymethyl methacrylate (PMMA) and polyethylene (PE) plastic for microcalcification and soft tissue lesion detection, respectively. Five cylindrical holes were bored onto the PMMA phantom and filled with resin inserts, which contained five groups of calcium hydroxyapatite (HA) granules, ranging in sizes from 0.090 to 0.210 mm. Three holes of diameters of 1, 2, and 3 mm were bored into the PE phantom and filled with water, which represents the contrast between soft tissue lesion and adipose tissue background. The phantoms were imaged at 65 kVp with an Entrance Skin Air Kerma (ESAK) of 3 mGy. Images were also reconstructed at reduced dose levels by under sampling the full sinogram. Results: The simulated phantom images agree well with those from the experiment. microcalcifications of approximately 0.1 mm can be observed with the investigated prototype spectral CT system at ESAK of 1 mGy. The contrast‐to‐noise ratio of water in PE background was improved with 4×4 binning. Conclusion: The proposed Si strip detector is expected to offer superior image quality with the capability to detect microcalcifications and masses for low dose breast imaging.

Real-Time Two-Dimensional Spatiotemporal Terahertz Imaging Based on Noncollinear Free-Space Electrooptic Sampling and Application to Functional Terahertz Imaging of Moving Object

We review 2-D spatiotemporal (2D-ST) terahertz (THz) imaging based on noncollinear free-space electrooptic sampling and its application to THz reflection tomography, THz spectral imaging, and THz spectral computed tomography (CT). 2D-ST THz imaging enables high-speed image acquisition at much higher rates than previously. Two-dimensional THz reflection tomography was effective for visualizing the internal structure of a moving paint film. A THz color scanner demonstrated the potential of rapid nondestructive inspection of moving pharmaceutical tablets. A THz spectral CT system using real-time line projection of a THz beam was effectively applied to a continuously rotating object. 2D-ST THz imaging enables functional THz imaging of moving objects in various practical applications.

Breast composition measurement with a cadmium-zinc-telluride based spectral computed tomography system

To investigate the feasibility of breast tissue composition in terms of water, lipid, and protein with a cadmium-zinc-telluride (CZT) based computed tomography (CT) system to help better characterize suspicious lesions. Simulations and experimental studies were performed using a spectral CT system equipped with a CZT-based photon-counting detector with energy resolution. Simulations of the figure-of-merit (FOM), the signal-to-noise ratio (SNR) of the dual energy image with respect to the square root of mean glandular dose (MGD), were performed to find the optimal configuration of the experimental acquisition parameters. A calibration phantom 3.175 cm in diameter was constructed from polyoxymethylene plastic with cylindrical holes that were filled with water and oil. Similarly, sized samples of pure adipose and pure lean bovine tissues were used for the three-material decomposition. Tissue composition results computed from the images were compared to the chemical analysis data of the tissue samples. The beam energy was selected to be 100 kVp with a splitting energy of 40 keV. The tissue samples were successfully decomposed into water, lipid, and protein contents. The RMS error of the volumetric percentage for the three-material decomposition, as compared to data from the chemical analysis, was estimated to be approximately 5.7%. The results of this study suggest that the CZT-based photon-counting detector may be employed in the CT system to quantify the water, lipid, and protein mass densities in tissue with a relatively good agreement.

TU‐G‐110‐07: Quantitative Measurement of an Iodinated Contrast Agent with Dual Energy and Spectral Breast Computed Tomography

Purpose: To investigate the feasibility of quantifying an iodinated contrast agent with dual energy and spectral breast computed tomography (CT).Methods: A cylindrical Polymethyl methacrylate (PMMA) phantom with a diameter of 4.5 cm was constructed using various iodine concentrations that ranged from 0.4 to 4 mg/ml. Calibrations and measurements were carried out with (1) a flat panel detector using dual kVp technique and (2) a Cadmium‐Zinc‐Telluride (CZT) photon counting detector using a single kVp approach in a spectral CT system. Based on the simulation results, energies of 50 and 120 kVp were chosen for the dual kVp imaging. Energy splitting at 34 keV, which is just above the k‐edge of iodine, was used to bin photons into two images within a single energy acquisition at 50 kVp. Results: Iodinated solutions with different concentrations can be clearly identified in the dedicated iodine image obtained from both dual kVp flat panel imaging and CZT‐based spectral CT. The linear fitting of the experimental data as a function of the known values yielded slopes of 0.998 and 1.021 for the dual kVp and spectral CT techniques, respectively. This suggested that the measured iodine concentrations agreed very well with the known values. Conclusion: The experimental results suggest that both dual kVp and spectral CT can be used for quantitative decomposition of contrast‐enhanced breast imaging. Meanwhile, the CZT‐based spectral CT system may offer a better image quality than the comparable flat panel based dual energy CT system.

TU-A-301-04: Breast Composition Measurement with a Cadmium-Zinc-Telluride (CZT) Based Spectral Computed Tomography System

Purpose: To investigate the feasibility of breast tissue composition in terms of water, lipid and protein with a Cadmium‐Zinc‐Telluride (CZT) based computed tomographysystem, as that information may help to better characterize suspicious lesions. Methods: Simulations and experimental studies were performed with a spectral CTsystem equipped with a CZT‐ based photon countingdetector with energy resolution. Simulations of the figure‐of‐merit (FOM), which represents the signal‐to‐noise ratio (SNR) of the dual energy image with respect to mean glandular dose, were performed to find the optimal configuration of experimental acquisition parameters. A calibration phantom of 3.175 cm in diameter was constructed from a polyoxymethylene plastic with cylindrical holes and filled with water and oil. Similar size samples of pure adipose and lean bovine tissue were used for the three‐material decomposition. Tissue composition results computed from the images were compared to data from chemical analysis of prior tissue samples. Results: The beam energy was selected to be 100 kVp with a threshold energy of 40 keV. The tissue samples were successfully decomposed into water, lipid and protein contents. The RMS percentage errors of the mass density for the three‐material decomposition, as compared to data from chemical analysis, were estimated to be approximately 6.92%. Conclusion: The results of this study suggest that the CZT‐based photon countingdetector may be employed in the CTsystem to quantify the water, lipid, and protein mass densities in tissue with relatively good agreement.

Photon counting spectral CT versus conventional CT: comparative evaluation for breast imaging application

Spectral CT systems with photon counting detectors have more advantages compared to conventional CT systems. However, clinical applications have been hampered for a long time due to the high demands of clinical systems and limitations of spectroscopic x-ray detectors. Photon counting detector technology has gained considerable improvements in the past decade, and spectral CT has become a hot topic. Several experimental spectral CT systems are under investigation. The purpose of this work was to perform the first direct, side-by-side comparison of existing spectral CT technology with a mature clinical CT system based on a conventional energy integrating detector. We have built an experimental spectral CT system whose main parameters are similar to the parameters of a clinical CT system. The system uses a spectroscopic cadmium zinc telluride (CZT) detector. The detector includes two rows of CZT pixels with 256 pixels in each row. The pixel size is 1 × 1 mm2, and the maximum count rate is 2 Mcounts/pixel/s. The spectral CT system has a magnification factor of 1.62 and the source to detector and source to image distances of 85 and 53 cm, respectively. The above parameters are similar to those of the clinical CT system, Siemens Sensation 16, used for comparison. The two systems were compared by imaging spatial resolution and contrast resolution phantoms made from acrylic cylinders with 14 cm diameters. The resolution phantom included Al wires with 0.3, 0.6, and 1 mm diameters, and 0.25 g cc−1 CaCO3 contrast. The contrast phantom included contrast elements with 1.7, 5, and 15 mg cc−1 iodine, and 1.1, 3.3, and 10 mg cc−1 gadolinium. The phantoms were imaged with the two systems using 120 kVp tube voltage and 470 mR total skin exposure. The spectral CT showed CT numbers, image noise, and spatial and contrast resolutions to be similar within 10% compared to the Siemens 16 system, and provided an average of 10% higher CNR. However, the spectral CT system had a major advantage in that the iodine, gadolinium, and CaCO3 contrasts were decomposed by dual-energy and K-edge subtraction methods using energy selective CT data acquired in a single CT scan and fixed tube voltage. It is concluded that photon counting spectral CT technology is close to feasibility for routine clinical applications. Furthermore, it is ready for some clinical applications such as dedicated breast CT which has relatively lower demands on photon counting detectors.

Atherosclerotic Plaque Composition: Analysis with Multicolor CT and Targeted Gold Nanoparticles

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. 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. 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. Spectral CT used with carefully chosen contrast agents may yield valuable information about atherosclerotic plaque composition.