Fully digitalized triple-energy x-ray computed tomography with high spatial resolutions using beam hardening

To regulate the effective photon energy with a constant tube voltage and to perform enhanced K-edge x-ray imaging, we built a prototype fully digitalized triple-energy x-ray computed tomography (TECT) scanner utilizing beam hardening. An object on the turntable is irradiated by a 0.1-mm-focus x-ray tube at 1.4-time-magnification. 720 raw radiograms are obtained using a flat panel detector, and 512 tomograms are reconstructed. With an increasing digital amplification factor, the gray raw-density projections obtained using low-energy-photon absorption disappeared at a constant maximum raw density, and the effective energy was increased by x-ray beam hardening. TECT was performed at digital amplifier factors below 3.0, and the effective energy increased with increasing amplification factors. In particular, fine blood vessels were visible using gadolinium-K-edge CT.

Spectral Photon-Counting Computed Tomography: Technical Principles and Applications in the Assessment of Cardiovascular Diseases

Spectral Photon-Counting Computed Tomography (SPCCT) represents a groundbreaking advancement in X-ray imaging technology. The core innovation of SPCCT lies in its photon-counting detectors, which can count the exact number of incoming x-ray photons and individually measure their energy. The first part of this review summarizes the key elements of SPCCT technology, such as energy binning, energy weighting, and material decomposition. Its energy-discriminating ability represents the key to the increase in the contrast between different tissues, the elimination of the electronic noise, and the correction of beam-hardening artifacts. Material decomposition provides valuable insights into specific elements' composition, concentration, and distribution. The capability of SPCCT to operate in three or more energy regimes allows for the differentiation of several contrast agents, facilitating quantitative assessments of elements with specific energy thresholds within the diagnostic energy range. The second part of this review provides a brief overview of the applications of SPCCT in the assessment of various cardiovascular disease processes. SPCCT can support the study of myocardial blood perfusion and enable enhanced tissue characterization and the identification of contrast agents, in a manner that was previously unattainable.

Photon-Counting Versus Energy-Integrating Detector CT Angiography of the Lower Extremity in a Human Cadaveric Model With Continuous Extracorporeal Perfusion

OBJECTIVES

Detailed visualization of the arterial runoff is mandatory for the assessment of peripheral arterial occlusive disease. This study aims to compare the performance of a first-generation photon-counting detector computed tomography (PCD-CT) to a third-generation energy-integrating detector CT (EID-CT).

MATERIALS AND METHODS

Computed tomography angiographies of 8 upper leg arterial runoffs were performed on human cadaveric models with continuous extracorporeal perfusion. For both PCD-CT and EID-CT, radiation dose-equivalent 120 kVp acquisition protocols (low-/medium-/high-dose: CTDI Vol = 3/5/10 mGy) were used. All scans were performed with standard collimation (PCD-CT: 144 × 0.4 mm; EID-CT: 96 × 0.6 mm), a pitch factor of 0.4, and a gantry rotation time of 1.0 second. Reformatting of data included the use of comparable vascular kernels (Bv 48/49), a slice thickness and increment of 1.0 mm, and a field of view of 150 × 150 mm. Eight radiologists evaluated image quality independently using a browser-based pairwise forced-choice comparison setup. Kendall concordance coefficient ( W ) was calculated to estimate interrater agreement. Signal-to-noise ratio and contrast-to-noise ratio (CNR) were compared based on 1-way analyses of variance and linear regression analysis.

RESULTS

Low-dose PCD-CT achieved superior signal-to-noise ratio/CNR values compared with high-dose EID-CT ( P < 0.001). Linear regression analysis suggested that an EID-CT scan with a CTDI Vol of at least 15.5 mGy was required to match the CNR value of low-dose PCD-CT. Intraluminal contrast attenuation was higher in PCD-CT than EID-CT, irrespective of dose level (415.0 ± 31.9 HU vs 329.2 ± 29.4 HU; P < 0.001). Subjective image quality of low-dose PCD-CT was considered superior to high-dose EID-CT ( P < 0.001). Interrater agreement was high ( W = 0.989).

CONCLUSIONS

Using cadaveric models with continuous extracorporeal perfusion allows for intraindividual image quality comparisons between PCD-CT and EID-CT on variable dose levels. With superior luminal contrast attenuation and denoising in angiographies of the peripheral arterial runoff, PCD-CT displayed potential for radiation saving of up to 83% compared with EID-CT.

Cardiovascular Applications of Photon-Counting CT Technology: A Revolutionary New Diagnostic Step

Photon-counting computed tomography (PCCT) is an emerging technology that can potentially transform clinical CT imaging. After a brief description of the PCCT technology, this review summarizes its main advantages over conventional CT: improved spatial resolution, improved signal and contrast behavior, reduced electronic noise and artifacts, decreased radiation dose, and multi-energy capability with improved material discrimination. Moreover, by providing an overview of the existing literature, this review highlights how the PCCT benefits have been harnessed to enhance and broaden the diagnostic capabilities of CT for cardiovascular applications, including the detection of coronary artery calcifications, evaluation of coronary plaque extent and composition, evaluation of coronary stents, and assessment of myocardial tissue characteristics and perfusion.

Standardization and Quantitative Imaging With Photon-Counting Detector CT

ABSTRACT

Computed tomography (CT) images display anatomic structures across 3 dimensions and are highly quantitative; they are the reference standard for 3-dimensional geometric measurements and are used for 3-dimensional printing of anatomic models and custom implants, as well as for radiation therapy treatment planning. The pixel intensity in CT images represents the linear x-ray attenuation coefficient of the imaged materials after linearly scaling the coefficients into a quantity known as CT numbers that is conveyed in Hounsfield units. When measured with the same scanner model, acquisition, and reconstruction parameters, the mean CT number of a material is highly reproducible, and quantitative applications of CT scanning that rely on the measured CT number, such as for assessing bone mineral density or coronary artery calcification, are well established. However, the strong dependence of CT numbers on x-ray beam spectra limits quantitative applications and standardization from achieving robust widespread success. This article reviews several quantitative applications of CT and the challenges they face, and describes the benefits brought by photon-counting detector (PCD) CT technology. The discussed benefits of PCD-CT include that it is inherently multienergy, expands material decomposition capabilities, and improves spatial resolution and geometric quantification. Further, the utility of virtual monoenergetic images to standardize CT numbers is discussed, as virtual monoenergetic images can be the default image type in PCD-CT due to the full-time spectral nature of the technology.

Dual-Source Photon-Counting Computed Tomography-Part I: Clinical Overview of Cardiac CT and Coronary CT Angiography Applications

The photon-counting detector (PCD) is a new computed tomography detector technology (photon-counting computed tomography, PCCT) that provides substantial benefits for cardiac and coronary artery imaging. Compared with conventional CT, PCCT has multi-energy capability, increased spatial resolution and soft tissue contrast with near-null electronic noise, reduced radiation exposure, and optimization of the use of contrast agents. This new technology promises to overcome several limitations of traditional cardiac and coronary CT angiography (CCT/CCTA) including reduction in blooming artifacts in heavy calcified coronary plaques or beam-hardening artifacts in patients with coronary stents, and a more precise assessment of the degree of stenosis and plaque characteristic thanks to its better spatial resolution. Another potential application of PCCT is the use of a double-contrast agent to characterize myocardial tissue. In this current overview of the existing PCCT literature, we describe the strengths, limitations, recent applications, and promising developments of employing PCCT technology in CCT.

An experimental framework for assessing the detective quantum efficiency of spectroscopic x-ray detectors

BACKGROUND

Assessing the performance of spectroscopic x-ray detectors (SXDs) requires measurement of the frequency-dependent detective quantum efficiency (DQE). Analytical expressions of the task-based DQE and task-independent DQE of SXDs have been presented in the literature, but standardizable experimental methods for measuring them have not. The task-based DQE quantifies the efficiency with which an SXD uses the x-ray quanta incident upon it to either quantify or detect a basis material (e.g., soft tissue or bone) of interest. The task-independent DQE is akin to the conventional DQE in that it is independent of the basis material to be detected or quantified.

PURPOSE

The purpose of this paper is to develop an experimental framework to present a method for experimental analysis of the DQE of SXDs, including the task-based DQE and task-independent DQE.

METHODS

We develop methods to measure the frequency-dependent DQE for task of quantifying or detecting a perturbation in a known basis material. We also develop methods for measuring a task-independent DQE. We show that the task-based DQEs and the task-independent DQE can be measured using a modest extension of the methods prescribed by International Electrotechnical Commission (IEC). Specifically, measuring the task-independent DQE requires measuring the modulation transfer function (MTF) and noise power spectrum (NPS) of each energy-bin image, in addition to the cross NPS between energy-bin images. Measuring the task-based DQEs requires an additional measurement of the transmission fraction through a thin basis-material absorber. We implemented the developed methods using standardized IEC x-ray spectra, aluminum (Al) and polymethyl methacrylyte (PMMA) basis materials, and a cadmium telluride (CdTe) SXD equipped with two energy bins and analog charge summing (ACS) for charge-sharing suppression. We also performed a regression analysis to determine whether or not the task-independent DQE is predictive of the task-based DQEs.

RESULTS

Experimental results of the task-based DQEs were consistent with simulation results presented in the literature. In general, and as expected, ACS increased the task-based DQEs and task-independent DQE. This effect was most pronounced for quantification tasks, in some instances yielding a five-fold increase in the DQE. For both spectra, with and without ACS for charge sharing correction, the task-based DQEs were linearly related to the task-independent DQE, as demonstrated by R² -values ranging from 0.89 to 1.00.

CONCLUSIONS

We have extended experimental DQE analysis to SXDs that count photons in multiple energy bins in a single x-ray exposure. The developed framework is an extension of existing IEC methods, and provides a standardized approach to assessing the performance of SXDs.

Photon-Counting Computed Tomography (PCCT): Technical Background and Cardio-Vascular Applications

Photon-counting computed tomography (PCCT) is a new advanced imaging technique that is going to transform the standard clinical use of computed tomography (CT) imaging. Photon-counting detectors resolve the number of photons and the incident X-ray energy spectrum into multiple energy bins. Compared with conventional CT technology, PCCT offers the advantages of improved spatial and contrast resolution, reduction of image noise and artifacts, reduced radiation exposure, and multi-energy/multi-parametric imaging based on the atomic properties of tissues, with the consequent possibility to use different contrast agents and improve quantitative imaging. This narrative review first briefly describes the technical principles and the benefits of photon-counting CT and then provides a synthetic outline of the current literature on its use for vascular imaging.

Model-based pulse pileup and charge sharing compensation for photon counting detectors: A simulation study

Purpose

We aim at developing a model‐based algorithm that compensates for the effect of both pulse pileup (PP) and charge sharing (CS) and evaluates the performance using computer simulations.

Methods

The proposed PCP algorithm for PP and CS compensation uses cascaded models for CS and PP we previously developed, maximizes Poisson log‐likelihood, and uses an efficient three‐step exhaustive search. For comparison, we also developed an LCP algorithm that combines models for a loss of counts (LCs) and CS. Two types of computer simulations, slab‐ and computed tomography (CT)‐based, were performed to assess the performance of both PCP and LCP with 200 and 800 mA, (300 µm)² × 1.6‐mm cadmium telluride detector, and a dead‐time of 23 ns. A slab‐based assessment used a pair of adipose and iodine with different thicknesses, attenuated X‐rays, and assessed the bias and noise of the outputs from one detector pixel; a CT‐based assessment simulated a chest/cardiac scan and a head‐and‐neck scan using 3D phantom and noisy cone‐beam projections.

Results

With the slab simulation, the PCP had little or no biases when the expected counts were sufficiently large, even though a probability of count loss (PCL) due to dead‐time loss or PP was as high as 0.8. In contrast, the LCP had significant biases (>±2 cm of adipose) when the PCL was higher than 0.15. Biases were present with both PCP and LCP when the expected counts were less than 10–120 per datum, which was attributed to the fact that the maximum likelihood did not approach the asymptote. The noise of PCP was within 8% from the Cramér–Rao lower bounds for most cases when no significant bias was present. The two CT studies essentially agreed with the slab simulation study. PCP had little or no biases in the estimated basis line integrals, reconstructed basis density maps, and synthesized monoenergetic CT images. But the LCP had significant biases in basis line integrals when X‐ray beams passed through lungs and near the body and neck contours, where the PCLs were above 0.15. As a consequence, basis density maps and monoenergetic CT images obtained by LCP had biases throughout the imaged space.

Conclusion

We have developed the PCP algorithm that uses the PP–CS model. When the expected counts are more than 10–120 per datum, the PCP algorithm is statistically efficient and successfully compensates for the effect of the spectral distortion due to both PP and CS providing little or no biases in basis line integrals, basis density maps, and monoenergetic CT images regardless of count‐rates. In contrast, the LCP algorithm, which models an LC due to pileup, produces severe biases when incident count‐rates are high and the PCL is 0.15 or higher.

Coronary CT Angiography with Photon-counting CT: First-In-Human Results

Background Spatial resolution, soft-tissue contrast, and dose-efficient capabilities of photon-counting CT (PCCT) potentially allow a better quality and diagnostic confidence of coronary CT angiography (CCTA) in comparison to conventional CT. Purpose To compare the quality of CCTA scans obtained with a clinical prototype PCCT system and an energy-integrating detector (EID) dual-layer CT (DLCT) system. Materials and Methods In this prospective board-approved study with informed consent, participants with coronary artery disease underwent retrospective electrocardiographically gated CCTA with both systems after injection of 65-75 mL of 400 mg/mL iodinated contrast agent at 5 mL/sec. A prior phantom task-based quality assessment of the detectability index of coronary lesions was performed. Ultra-high-resolution parameters were used for PCCT (1024 matrix, 0.25-mm section thickness) and EID DLCT (512 matrix, 0.67-mm section thickness). Three cardiac radiologists independently performed a blinded analysis using a five-point quality score (1 = insufficient, 5 = excellent) for overall image quality, diagnostic confidence, and diagnostic quality of calcifications, stents, and noncalcified plaques. A logistic regression model, adjusted for radiologists, was used to evaluate the proportion of improvement in scores with the best method. Results Fourteen consecutive participants (12 men; mean age, 61 years ± 17) were enrolled. Scores of overall quality and diagnostic confidence were higher with PCCT images with a median of 5 (interquartile range [IQR], 2) and 5 (IQR, 1) versus 4 (IQR, 1) and 4 (IQR, 3) with EID DLCT images, using a mean tube current of 255 mAs ± 0 versus 349 mAs ± 111 for EID DLCT images (P < .01). Proportions of improvement with PCCT images for quality of calcification, stent, and noncalcified plaque were 100%, 92% (95% CI: 71, 98), and 45% (95% CI: 28, 63), respectively. In the phantom study, detectability indexes were 2.3-fold higher for lumen and 2.9-fold higher for noncalcified plaques with PCCT images. Conclusion Coronary CT angiography with a photon-counting CT system demonstrated in humans an improved image quality and diagnostic confidence compared with an energy-integrating dual-layer CT. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Sandfort and Bluemke in this issue.

A detective quantum efficiency for spectroscopic X-ray imaging detectors

PURPOSE

Spectroscopic X-ray detectors (SXDs) are under development for X-ray imaging applications. Recent efforts to extend the detective quantum efficiency (DQE) to SXDs impose a barrier to experimentation and/or do not provide a task-independent measure of detector performance. The purpose of this article is to define a task-independent DQE for SXDs that can be measured using a modest extension of established DQE-metrology methods.

METHODS

We defined a task-independent spectroscopic DQE and performed a simulation study to determine the relationship between the zero-frequency DQE and the ideal-observer signal-to-noise ratio (SNR) of low-frequency soft-tissue, bone, iodine, and gadolinium signals. In our simulations, we used calibrated models of the spatioenergetic response of cadmium telluride (CdTe) and cadmium-zinc-telluride (CdZnTe) SXDs. We also measured the zero-frequency DQE of a CdTe detector with two energy bins and of a CdZnTe detector with up to six energy bins for an RQA9 spectrum and compared with model predictions.

RESULTS

The spectroscopic DQE accounts for spectral distortions, energy-bin-dependent spatial resolution, interbin spatial noise correlations, and intrabin spatial noise correlations; it is mathematically equivalent to the squared SNR per unit fluence of the generalized least-squares estimate of the height of an X-ray impulse in a uniform noisy background. The zero-frequency DQE has a strong linear relationship with the ideal-observer SNR of low-frequency soft-tissue, bone, iodine, and gadolinium signals, and can be expressed in terms of the product of the quantum efficiency and a Swank noise factor that accounts for DQE degradation due to, for example, charge sharing (CS) and electronic noise. The spectroscopic Swank noise factor of the CdTe detector was measured to be 0.81 ± 0.04 and 0.83 ± 0.04 with and without anticoincidence logic for CS suppression, respectively. The spectroscopic Swank noise factor of the CdZnTe detector operated with four energy bins was measured to be 0.82 ± 0.02 which is within 5% of the theoretical value.

CONCLUSIONS

The spectroscopic DQE defined here is (1) task-independent, (2) can be measured using a modest extension of existing DQE-metrology methods, and (3) is predictive of the ideal-observer SNR of soft-tissue, bone, iodine, and gadolinium signals. For CT applications, the combination of CS and electronic noise in CdZnTe spectroscopic detectors will degrade the zero-frequency DQE by 10 %-20 % depending on the electronic noise level and pixel size.

Calculation of Stopping-Power Ratio from Multiple CT Numbers Using Photon-Counting CT System: Two- and Three-Parameter-Fitting Method

The two-parameter-fitting method (PFM) is commonly used to calculate the stopping-power ratio (SPR). This study proposes a new formalism: a three-PFM, which can be used in multiple spectral computed tomography (CT). Using a photon-counting CT system, seven rod-shaped samples of aluminium, graphite, and poly(methyl methacrylate) (PMMA), and four types of biological phantom materials were placed in a water-filled sample holder. The X-ray tube voltage and current were set at 150 kV and 40 μA respectively, and four CT images were obtained at four threshold settings. A semi-empirical correction method that corrects the difference between the CT values from the photon-counting CT images and theoretical values in each spectral region was also introduced. Both the two- and three-PFMs were used to calculate the effective atomic number and electron density from multiple CT numbers. The mean excitation energy was calculated via parameterisation with the effective atomic number, and the SPR was then calculated from the calculated electron density and mean excitation energy. Then, the SPRs from both methods were compared with the theoretical values. To estimate the noise level of the CT numbers obtained from the photon-counting CT, CT numbers, including noise, were simulated to evaluate the robustness of the aforementioned PFMs. For the aluminium and graphite, the maximum relative errors for the SPRs calculated using the two-PFM and three-PFM were 17.1% and 7.1%, respectively. For the PMMA and biological phantom materials, the maximum relative errors for the SPRs calculated using the two-PFM and three-PFM were 5.5% and 2.0%, respectively. It was concluded that the three-PFM, compared with the two-PFM, can yield SPRs that are closer to the theoretical values and is less affected by noise.

Photon-counting computed tomography of lanthanide contrast agents with a high-flux 330-μm-pitch cadmium zinc telluride detector in a table-top system

Purpose: We present photon-counting computed tomography (PCCT) imaging of contrast agent triplets similar in atomic number ( Z ) achieved with a high-flux cadmium zinc telluride (CZT) detector. Approach: The table-top PCCT imaging system included a 330 - μ m -pitch CZT detector of size 8    mm × 24    mm 2 capable of using six energy bins. Four 3D-printed 3-cm-diameter phantoms each contained seven 6-mm-diameter vials with water and low and high concentration solutions of various contrast agents. Lanthanum ( Z = 57 ), gadolinium (Gd) ( Z = 64 ), and lutetium ( Z = 71 ) were imaged together and so were iodine ( Z = 53 ), Gd, and holmium ( Z = 67 ). Each phantom was imaged with 1-mm aluminum-filtered 120-kVp cone beam x rays to produce six energy-binned computed tomography (CT) images. Results: K -edge images were reconstructed using a weighted sum of six CT images, which distinguished each contrast agent with a root-mean-square error (RMSE) of < 0.29 % and 0.51% for the 0.5% and 5% concentrations, respectively. Minimal cross-contamination in each K -edge image was seen, with RMSE values < 0.27 % in vials with no contrast. Conclusion: This is the first preliminary demonstration of simultaneously imaging three similar Z contrast agents with a difference in Z as low as 3.

Assessment of Multienergy Interpixel Coincidence Counters (MEICC) for Charge Sharing Correction or Compensation for Photon Counting Detectors With Boxcar Signals

Recently, multi-energy inter-pixel coincidence counter (MEICC) has been proposed for charge sharing correction and compensation for photon counting detectors (PCDs), which uses energy-dependent coincidence counters to record coincident events between multiple energy windows of a pixel-of-interest and those of neighboring pixels. A Monte Carlo (MC) simulation study was performed to assess the performance of MEICC; however, the performance might have been overestimated in a previous study. The charge sharing increases the number of photons recorded at a PCD pixel at the expense of the spatial resolution, and therefore, when spatially uniform flat-field x-ray signals are used, it gives PCDs with charge sharing more signals than a PCD without charge sharing. In this paper, we propose to use spatially modulated boxcar signals for evaluating the performances for high spatial frequency tasks because they provide consistent signals regardless of the presence of absence of charge sharing. The flat-field signals must be used for low spatial frequency tasks. We assessed the performances of MEICC and other PCDs with both flat-field signals and boxcar signals, with optimal threshold energies, and with two different pixel sizes. As it is expected, normalized Cramér-Rao lower bounds (nCRLBs) measured with the boxcar signals were worse than those with flat-field signals in general. The nCRLBs of MEICC with 225-μm pixel were close to the current 450-μm PCD. We studied a combination of flat-field signals and N×N super-pixels, where the output of N×N pixels were added, using an MC simulation and a simple charge sharing counting model. The study showed that charge sharing had two opposing impacts on the conventional CT imaging-a negative impact with double-counting among N×N pixels and a positive impact with single-counting spill-in and spill-out across the super-pixel boundary-and the positive impact diminished with increasing N. A use of large N×N super-pixels such as N≥25 was suggested to approximate the zero-frequency detection quantum efficiency of PCD with charge sharing.

Multi-energy inter-pixel coincidence counters for charge sharing correction and compensation in photon counting detectors

PURPOSE

Smaller pixel sizes of x-ray photon counting detectors (PCDs) are advantageous for count rate capabilities but disadvantageous for charge sharing. With charge sharing, the energy of an x-ray photon may be split and one photon may produce two or more counts at adjacent pixels, both at lower energies than the incident energy. This "double-counting" increases noise variance and degrades the spectral response. Overall, it has a significantly negative impact on the performance of PCD-based computed tomography (CT). Charge sharing is induced by the detection physics and occurs regardless of count rates; thus, it is impossible to avoid. We propose in this paper a method that has a potential to address both noise and bias added by charge sharing.

METHODS

We propose applying a multi-energy inter-pixel coincidence counter (MEICC) technique, which uses energy-dependent coincidence counters, keeps the book of charge sharing events during data acquisition, and provides the exact number of charge sharing occurrences, which can be used to either correct or compensate for them after the acquisition is completed. MEICC does not interfere with the primary counting process; therefore, PCDs with MEICC will remain as fast as those without MEICC. MEICC can be implemented using current electronics technology because its inter-pixel coincidence counters used to handle digital data are rather simple. We evaluated Cramér-Rao lower bound (CRLB) of PCDs with and without MEICC using a Monte Carlo simulation.

RESULTS

When the number of energy windows was four or larger and eight neighboring pixels were used, the CRLBs of 225-µm PCD with MEICC normalized by those of the current PCD with the same number of windows were 0.361-0.383 for water density images of two basis functions, which was only 5.7-16.4% worse than those of a PCD without charge sharing (which were at 0.329-0.358). In contrast, the normalized CRLBs of the PCD with one coincidence counter were 0.466-0.499, which were 37.3-45.6% worse than the PCD without charge sharing. The use of eight neighboring pixels provided ~10% better CRLB values than four neighboring pixels for MEICC. With four energy windows, decreasing the number of coincidence counters from 16 to 9 only slightly increased the CRLB from 0.255 to 0.269 (which corresponded to as little as a 5.5% change). The normalized CRLBs of MEICC for K-edge imaging (gold) were 0.295-0.426, while those of the one coincidence counter were 0.926-0.959 and the ideal PCDs were 0.126-0.146.

CONCLUSIONS

The proposed MEICC provides spectral information that can be used to address charge sharing problems in PCDs and is expected to satisfy the requirements for clinical x-ray CT. MEICC is very effective, especially for K-edge imaging, which requires accurate spectral information.

Feasibility of multi-contrast imaging on dual-source photon counting detector (PCD) CT: An initial phantom study

PURPOSE

Photon-counting-detector-computed tomography (PCD-CT) allows separation of multiple, simultaneously imaged contrast agents, such as iodine (I), gadolinium (Gd), and bismuth (Bi). However, PCDs suffer from several technical limitations such as charge sharing, K-edge escape, and pulse pile-up, which compromise spectral separation of multi-energy data and degrade multi-contrast imaging performance. The purpose of this work was to determine the performance of a dual-source (DS) PCD-CT relative to a single-source (SS) PCD-CT for the separation of simultaneously imaged I, Gd, and Bi contrast agents.

METHODS

Phantom experiments were performed using a research whole-body PCD-CT and head/abdomen-sized phantoms containing vials of different I, Gd, Bi concentrations. To emulate a DS-PCD-CT, the phantoms were scanned twice on the SS-PCD-CT using different tube potentials for each scan. A tube potential of 80 kV (energy thresholds = 25/50 keV) was used for low-energy tube, while the high-energy tube used Sn140 kV (Sn indicates tin filter) and thresholds of 25/90 keV. The same phantoms were scanned also on the SS-PCD-CT using the chess acquisition mode. In chess mode, the 4 × 4 subpixels within a macro detector pixel are split into two sets based on a chess-board pattern. With each subpixel set having two energy thresholds, chess mode allows four energy-bin data sets, which permits simultaneous multi-contrast imaging. Because of this design, only 50% area of each detector pixel is configured to receive photons of a pre-defined threshold, leading to 50% dose utilization efficiency. To compensate for this dose inefficiency, the radiation dose for this scan was doubled compared to DS-PCD-CT. A 140 kV tube potential and thresholds = 25/50/75/90 keV were used. These settings were determined based on the K-edges of Gd, and Bi, and were found to yield good differentiation of I/Gd/Bi based on phantom experiments and other literature. The energy-bin images obtained from each scan (scan pair) were used to generate I-, Gd-, Bi-specific image via material decomposition. Root-mean-square-error (RMSE) between the known and measured concentrations was calculated for each scenario. A 20-cm water cylinder phantom was scanned on both systems, which was used for evaluating the magnitude of noise, and noise power spectra (NPS) of I/Gd/Bi-specific images.

RESULTS

Phantom results showed that DS-PCD-CT reduced noise in material-specific images for both head and body phantoms compared to SS-PCD-CT. The noise level of SS-PCD was reduced from 2.55 to 0.90 mg/mL (I), 1.97 to 0.78 mg/mL (Gd), and 0.85 to 0.74 mg/mL (Bi) using DS-PCD. NPS analysis showed that the noise texture of images acquired on both systems is similar. For the body phantom, the RMSE for SS-PCD-CT was reduced relative to DS-PCD-CT from 10.52 to 2.76 mg/mL (I), 7.90 to 2.01 mg/mL (Gd), and 1.91 to 1.16 mg/mL (Bi). A similar trend was observed for the head phantom: RMSE reduced from 2.59 (SS-PCD) to 0.72 (DS-PCD) mg/mL (I), 2.02 to 0.58 mg/mL (Gd), and 0.85 to 0.57 mg/mL (Bi).

CONCLUSION

We demonstrate the feasibility of performing simultaneous imaging of I, Gd, and Bi materials on DS-PCD-CT. Under the condition without cross scattering, DS-PCD reduced the RMSE for quantification of material concentration in relative to a SS-PCD-CT system using chess mode.

Current and Emerging Preclinical Approaches for Imaging-Based Characterization of Atherosclerosis

Atherosclerotic plaques can remain quiescent for years, but become life threatening upon rupture or disruption, initiating clot formation in the vessel lumen and causing acute myocardial infarction and ischemic stroke. Whether and how a plaque ruptures is determined by its macroscopic structure and microscopic composition. Rupture-prone plaques usually consist of a thin fibrous cap with few smooth muscle cells, a large lipid core, a dense infiltrate of inflammatory cells, and neovessels. Such lesions, termed high-risk plaques, can remain asymptomatic until the thrombotic event. Various imaging technologies currently allow visualization of morphological and biological characteristics of high-risk atherosclerotic plaques. Conventional protocols are often complex and lack specificity for high-risk plaque. Conversely, new imaging approaches are emerging which may overcome these limitations. Validation of these novel imaging techniques in preclinical models of atherosclerosis is essential for effective translational to clinical practice. Imaging the vessel wall, as well as its biological milieu in small animal models, is challenging because the vessel wall is a small structure that undergoes continuous movements imposed by the cardiac cycle as it is adjacent to circulating blood. The focus of this paper is to provide a state-of-the-art review on techniques currently available for preclinical imaging of atherosclerosis in small animal models and to discuss the advantages and limitations of each approach.

Dual-source multienergy CT with triple or quadruple x-ray beams

Energy-resolved photon-counting-detector CT (PCD-CT) is promising for material decomposition with multiple contrast agents using two or more energy bins. However, corrections for nonidealities of PCDs are required, which are still active research topics. In addition, PCD-CT is also likely to have a very high cost due to the current lack of mass production capabilities. We proposed an alternative approach to perform multienergy CT (MECT), which is achieved by acquiring triple or quadruple x-ray beam measurements on a dual-source CT scanner. This strategy was based on a "twin-beam" design on a single-source scanner for dual-energy CT. Examples of beam filters and spectra for triple and quadruple x-ray beam were provided. Computer simulation studies were performed to evaluate the noise and accuracy of material decomposition for multiple contrast mixtures using both triple- and quadruple-beam configurations, compared with the performance on a PCD-CT platform. The results demonstrated that the image quality and dose efficiency of the triple-beam configuration in the proposed MECT technique were comparable to that in PCD-CT. The proposed technique can be readily implemented on a dual-source scanner, which may allow material decomposition of multiple contrast agents to be performed on clinical CT scanners with energy-integrating detectors.

Impact of anti-charge sharing on the zero-frequency detective quantum efficiency of CdTe-based photon counting detector system: cascaded systems analysis and experimental validation

Inter-pixel communication and anti-charge sharing (ACS) technologies have been introduced to photon counting detector (PCD) systems to address the undesirable charge sharing problem. In addition to improving the energy resolution of PCD, ACS may also influence other aspects of PCD performance such as detector multiplicity (i.e. the number of pixels triggered by each interacted photon) and detective quantum efficiency (DQE). In this work, a theoretical model was developed to address how ACS impacts the multiplicity and zero-frequency DQE [DQE(0)] of PCD systems. The work focused on cadmium telluride (CdTe)-based PCD that often involves the generation and transport of K-fluorescence photons. Under the parallel cascaded systems analysis framework, the theory takes both photoelectric and scattering effects into account, and it also considers both the reabsorption and escape of photons. In a new theoretical treatment of ACS, it was considered as a modified version of the conventional single pixel (i.e. non-ACS) mode, but with reduced charge spreading distance and K-fluorescence travel distance. The proposed theoretical model does not require prior knowledge of the detailed ACS implementation method for each specific PCD, and its parameters can be experimentally determined using a radioisotope without invoking any Monte-Carlo simulation. After determining the model parameters, independent validation experiments were performed using a diagnostic x-ray tube and four different polychromatic beams (from 50 to 120 kVp). Both the theoretical and experimental results demonstrate that ACS increased the first and second moments of multiplicity for a majority of the x-ray energy and threshold levels tested, except when the threshold level was much lower than the x-ray energy level. However, ACS always improved DQE(0) at all energy and threshold levels tested.

K-edge energy-based calibration method for photon counting detectors

In recent years, potential applications of energy-resolved photon counting detectors (PCDs) in the x-ray medical imaging field have been actively investigated. Unlike conventional x-ray energy integration detectors, PCDs count the number of incident x-ray photons within certain energy windows. For PCDs, the interactions between x-ray photons and photoconductor generate electronic voltage pulse signals. The pulse height of each signal is proportional to the energy of the incident photons. By comparing the pulse height with the preset energy threshold values, x-ray photons with specific energies are recorded and sorted into different energy bins. To quantitatively understand the meaning of the energy threshold values, and thus to assign an absolute energy value to each energy bin, energy calibration is needed to establish the quantitative relationship between the threshold values and the corresponding effective photon energies. In practice, the energy calibration is not always easy, due to the lack of well-calibrated energy references for the working energy range of the PCDs. In this paper, a new method was developed to use the precise knowledge of the characteristic K-edge energy of materials to perform energy calibration. The proposed method was demonstrated using experimental data acquired from three K-edge materials (viz., iodine, gadolinium, and gold) on two different PCDs (Hydra and Flite, XCounter, Sweden). Finally, the proposed energy calibration method was further validated using a radioactive isotope (Am-241) with a known decay energy spectrum.

Human Imaging With Photon Counting-Based Computed Tomography at Clinical Dose Levels: Contrast-to-Noise Ratio and Cadaver Studies

OBJECTIVES

The purpose of this work was to measure and compare the iodine contrast-to-noise ratio (CNR) between a commercial energy-integrating detector (EID) computed tomography (CT) system and a photon-counting detector (PCD) CT scanner capable of human imaging at clinical dose rates, as well as to determine clinical feasibility using human cadavers.

MATERIALS AND METHODS

A research dual-source PCD-CT scanner was used, where the "A" tube/detector subsystem used an EID and the "B" tube/detector subsystem used a PCD. Iodine CNR was measured in 4 anthropomorphic phantoms, simulating 4 patient sizes, at 4 tube potential settings. After biospecimen committee approval, PCD scans were performed on a fresh-frozen human head and a whole-body cadaver using clinical dose rates. Scans were repeated using the EID and identical parameters, and qualitative side-by-side comparisons were performed.

RESULTS

For the same photon fluence, phantom measurements demonstrated a mean increase in CNR of 11%, 23%, 31%, 38% for the PCD system, relative to the EID system, at 80, 100, 120, and 140 kV, respectively. Photon-counting detector CT additionally provided energy-selective imaging, where low- and high-energy images reflected the energy dependence of the iodine signal. Photon-counting detector images of cadaveric anatomy demonstrated decreased beam hardening and calcium blooming in the high-energy bin images and increased contrast in the low-energy bins images relative to the EID images. Threshold-based PCD images were qualitatively deemed equivalent in other aspects.

CONCLUSIONS

The evaluated research PCD-CT system was capable of clinical levels of image quality at clinical dose rates. It further provided improved CNR relative to state-of-the-art EID-CT. The energy-selective bin images provide further opportunity for dual-energy and multienergy analyses.

Estimation of signal and noise for a whole-body research photon-counting CT system

Photon-counting detector CT has a large number of acquisition parameters that require optimization, particularly the energy threshold configurations. Fast and accurate estimation of both signal and noise in photon-counting CT (PCCT) images can facilitate such optimization. Using the detector response function of a research PCCT system, we derived mathematical models for both signal and noise estimation, taking into account beam spectrum and filtration, object attenuation, water beam hardening, detector response, radiation dose, energy thresholds, and the propagation of noise. To determine the absolute noise value, a noise lookup table (LUT) for all available energy thresholds was acquired using a number of calibration scans. The noise estimation algorithm then used the noise LUT to estimate noise for scans with a variety of combination of energy thresholds, dose levels, and object attenuations. Validation of the estimation algorithms was performed on a whole-body research PCCT system using semianthropomorphic water phantoms and solutions of calcium and iodine. Clinical feasibility of noise estimation was assessed with scans of a cadaver head and a living swine. The algorithms achieved accurate estimation of both signal and noise for a variety of scanning parameter combinations. Maximum discrepancies were below 15%, while most errors were below 5%.

Spatio-energetic cross talk in photon counting detectors: Detector model and correlated Poisson data generator

PURPOSE

An x-ray photon interacts with photon counting detectors (PCDs) and generates an electron charge cloud or multiple clouds. The clouds (thus, the photon energy) may be split between two adjacent PCD pixels when the interaction occurs near pixel boundaries, producing a count at both of the pixels. This is called double-counting with charge sharing. (A photoelectric effect with K-shell fluorescence x-ray emission would result in double-counting as well). As a result, PCD data are spatially and energetically correlated, although the output of individual PCD pixels is Poisson distributed. Major problems include the lack of a detector noise model for the spatio-energetic cross talk and lack of a computationally efficient simulation tool for generating correlated Poisson data. A Monte Carlo (MC) simulation can accurately simulate these phenomena and produce noisy data; however, it is not computationally efficient.

METHODS

In this study, the authors developed a new detector model and implemented it in an efficient software simulator that uses a Poisson random number generator to produce correlated noisy integer counts. The detector model takes the following effects into account: (1) detection efficiency; (2) incomplete charge collection and ballistic effect; (3) interaction with PCDs via photoelectric effect (with or without K-shell fluorescence x-ray emission, which may escape from the PCDs or be reabsorbed); and (4) electronic noise. The correlation was modeled by using these two simplifying assumptions: energy conservation and mutual exclusiveness. The mutual exclusiveness is that no more than two pixels measure energy from one photon. The effect of model parameters has been studied and results were compared with MC simulations. The agreement, with respect to the spectrum, was evaluated using the reduced χ² statistics or a weighted sum of squared errors, χ_red²(≥1), where χ_red²=1 indicates a perfect fit.

RESULTS

The model produced spectra with flat field irradiation that qualitatively agree with previous studies. The spectra generated with different model and geometry parameters allowed for understanding the effect of the parameters on the spectrum and the correlation of data. The agreement between the model and MC data was very strong. The mean spectra with 90 keV and 140 kVp agreed exceptionally well: χ_red² values were 1.049 with 90 keV data and 1.007 with 140 kVp data. The degrees of cross talk (in terms of the relative increase from single pixel irradiation to flat field irradiation) were 22% with 90 keV and 19% with 140 kVp for MC simulations, while they were 21% and 17%, respectively, for the model. The covariance was in strong agreement qualitatively, although it was overestimated. The noisy data generation was very efficient, taking less than a CPU minute as opposed to CPU hours for MC simulators.

CONCLUSIONS

The authors have developed a novel, computationally efficient PCD model that takes into account double-counting and resulting spatio-energetic correlation between PCD pixels. The MC simulation validated the accuracy.

Interventional dual-energy imaging-Feasibility of rapid kV-switching on a C-arm CT system

PURPOSE

In the last years, dual-energy CT imaging has shown clinical value, thanks to its ability to differentiate materials based on their atomic number and to exploit different properties of images acquired at two different energies. C-arm CT systems are used to guide procedures in the interventional suite. Until now, there are no commercially available systems that employ dual-energy material decomposition. This paper explores the feasibility of implementing a fast kV-switching technique on a clinically available angiographic system for acquiring dual-energy C-arm CT images.

METHODS

As an initial proof of concept, a fast kV-switching approach was implemented on an angiographic C-arm system and the peak tube voltage during 3D rotational scans was measured. The tube voltage measurements during fast kV-switching scans were compared to corresponding measurements on kV-constant scans. Additionally, to prove stability of the requested exposure parameters, the accuracy of the delivered tube current and pulse width were also recorded and compared. In a first phantom experiment, the voxel intensity values of the individual tube voltage components of the fast kV-switching scans were compared to their corresponding kV-constant scans. The same phantom was used for a simple material decomposition between different iodine concentrations and pure water using a fast kV-switching protocol of 81 and 125 kV. In the last experiment, the same kV-switching protocol as in the phantom scan was used in an in vivo pig study to demonstrate the clinical feasibility.

RESULTS

During rapid kV-switching acquisitions, the measured tube voltage of the x-ray tube during fast switching scans has an absolute deviation of 0.23 ± 0.13 kV compared to the measured tube voltage produced during kV-constant acquisitions. The stability of the peak tube voltage over different scan requests was about 0.10 kV for the low and 0.46 for the high energy kV-switching scans and less than 0.1 kV for kV-constant scans, indicating slightly lower stability for kV-switching scans. The tube current resulted in a relative deviation of -1.6% for the low and 6.6% overestimation for the high tube voltage of the kV-switching scans compared to the kV-constant scans. The pulse width showed no deviation for the longer pulse width and only minor deviations (0.02 ± 0.02 ms) for the shorter pulse widths compared to the kV-constant scans. The phantom experiment using different iodine concentrations showed an accurate correlation (R² > 0.99) between the extracted intensity values in the kV-switching and kV-constant reconstructed volumes, and allows for an automatic differentiation between contrast concentration down to 10% (350 mg/ml iodine) and pure water under low-noise conditions. Preliminary results of iodine and soft tissue separation showed also promising results in the first in vivo pig study.

CONCLUSIONS

The feasibility of dual-energy imaging using a fast kV-switching method on an angiographic C-arm CT system was investigated. Direct measurements of beam quality in the x-ray field demonstrate the stability of the kV-switching method. Phantom and in vivo experiments showed that images did not deviate from those of corresponding kV-constant scans. All performed experiments confirmed the capability of performing fast kV-switching scans on a clinically available C-arm CT system. More complex material decomposition tasks and postprocessing steps will be part of future investigations.

Superiorization-based multi-energy CT image reconstruction

The recently-developed superiorization approach is efficient and robust for solving various constrained optimization problems. This methodology can be applied to multi-energy CT image reconstruction with the regularization in terms of the prior rank, intensity and sparsity model (PRISM). In this paper, we propose a superiorized version of the simultaneous algebraic reconstruction technique (SART) based on the PRISM model. Then, we compare the proposed superiorized algorithm with the Split-Bregman algorithm in numerical experiments. The results show that both the Superiorized-SART and the Split-Bregman algorithms generate good results with weak noise and reduced artefacts.

Cardiac CT Imaging of Plaque Vulnerability: Hype or Hope?

Advances in cardiovascular computed tomography (CT) have resulted in an excellent ability to exclude coronary heart disease (CHD). Anatomical information, functional information, and spectral information can already be obtained with current CT technologies. Moreover, novel developments such as targeted nanoparticle contrast agents, photon-counting CT, and phase contrast CT will further enhance the diagnostic value of cardiovascular CT. This review provides an overview of current state of the art and future cardiovascular CT imaging.

Spectral X-Ray CT Image Reconstruction with a Combination of Energy-Integrating and Photon-Counting Detectors

The purpose of this paper is to develop an algorithm for hybrid spectral computed tomography (CT) which combines energy-integrating and photon-counting detectors. While the energy-integrating scan is global, the photon-counting scan can have a local field of view (FOV). The algorithm synthesizes both spectral data and energy-integrating data. Low rank and sparsity prior is used for spectral CT reconstruction. An initial estimation is obtained from the projection data based on physical principles of x-ray interaction with the matter, which provides a more accurate Taylor expansion than previous work and can guarantee the convergence of the algorithm. Numerical simulation with clinical CT images are performed. The proposed algorithm produces very good spectral features outside the FOV when no K-edge material exists. Exterior reconstruction of K-edge material can be partially achieved.

Abdominal Imaging with Contrast-enhanced Photon-counting CT: First Human Experience

PURPOSE

To evaluate the performance of a prototype photon-counting detector (PCD) computed tomography (CT) system for abdominal CT in humans and to compare the results with a conventional energy-integrating detector (EID).

MATERIALS AND METHODS

The study was HIPAA-compliant and institutional review board-approved with informed consent. Fifteen asymptomatic volunteers (seven men; mean age, 58.2 years ± 9.8 [standard deviation]) were prospectively enrolled between September 2 and November 13, 2015. Radiation dose-matched delayed contrast agent-enhanced spiral and axial abdominal EID and PCD scans were acquired. Spiral images were scored for image quality (Wilcoxon signed-rank test) in five regions of interest by three radiologists blinded to the detector system, and the axial scans were used to assess Hounsfield unit accuracy in seven regions of interest (paired t test). Intraclass correlation coefficient (ICC) was used to assess reproducibility. PCD images were also used to calculate iodine concentration maps. Spatial resolution, noise-power spectrum, and Hounsfield unit accuracy of the systems were estimated by using a CT phantom.

RESULTS

In both systems, scores were similar for image quality (median score, 4; P = .19), noise (median score, 3; P = .30), and artifact (median score, 1; P = .17), with good interrater agreement (image quality, noise, and artifact ICC: 0.84, 0.88, and 0.74, respectively). Hounsfield unit values, spatial resolution, and noise-power spectrum were also similar with the exception of mean Hounsfield unit value in the spinal canal, which was lower in the PCD than the EID images because of beam hardening (20 HU vs 36.5 HU; P < .001). Contrast-to-noise ratio of enhanced kidney tissue was improved with PCD iodine mapping compared with EID (5.2 ± 1.3 vs 4.0 ± 1.3; P < .001).

CONCLUSION

The performance of PCD showed no statistically significant difference compared with EID when the abdomen was evaluated in a conventional scan mode. PCD provides spectral information, which may be used for material decomposition.

New Applications of Cardiac Computed Tomography: Dual-Energy, Spectral, and Molecular CT Imaging

Computed tomography (CT) has evolved into a powerful diagnostic tool, and it is impossible to imagine current clinical practice without CT imaging. Because of its widespread availability, ease of clinical application, superb sensitivity for the detection of coronary artery disease, and noninvasive nature, CT has become a valuable tool within the armamentarium of cardiologists. In the past few years, numerous technological advances in CT have occurred, including dual-energy CT, spectral CT, and CT-based molecular imaging. By harnessing the advances in technology, cardiac CT has advanced beyond the mere evaluation of coronary stenosis to an imaging tool that permits accurate plaque characterization, assessment of myocardial perfusion, and even probing of molecular processes that are involved in coronary atherosclerosis. Novel innovations in CT contrast agents and pre-clinical spectral CT devices have paved the way for CT-based molecular imaging.

New horizons in cardiac CT

Until recently, cardiovascular computed tomography angiography (CCTA) was associated with considerable radiation doses. The introduction of tube current modulation and automatic tube potential selection as well as high-pitch prospective ECG-triggering and iterative reconstruction offer the ability to decrease dose with approximately one order of magnitude, often to sub-millisievert dose levels. In parallel, advancements in computational technology have enabled the measurement of fractional flow reserve (FFR) from CCTA data (FFRCT). This technique shows potential to replace invasively measured FFR to select patients in need of coronary intervention. Furthermore, developments in scanner hardware have led to the introduction of dual-energy and photon-counting CT, which offer the possibility of material decomposition imaging. Dual-energy CT reduces beam hardening, which enables CCTA in patients with a high calcium burden and more robust myocardial CT perfusion imaging. Future-generation CT systems will be capable of counting individual X-ray photons. Photon-counting CT is promising and may result in a substantial further radiation dose reduction, vastly increased spatial resolution, and the introduction of a whole new class of contrast agents.

Dual- and Multi-Energy CT: Principles, Technical Approaches, and Clinical Applications

In x-ray computed tomography (CT), materials having different elemental compositions can be represented by identical pixel values on a CT image (ie, CT numbers), depending on the mass density of the material. Thus, the differentiation and classification of different tissue types and contrast agents can be extremely challenging. In dual-energy CT, an additional attenuation measurement is obtained with a second x-ray spectrum (ie, a second "energy"), allowing the differentiation of multiple materials. Alternatively, this allows quantification of the mass density of two or three materials in a mixture with known elemental composition. Recent advances in the use of energy-resolving, photon-counting detectors for CT imaging suggest the ability to acquire data in multiple energy bins, which is expected to further improve the signal-to-noise ratio for material-specific imaging. In this review, the underlying motivation and physical principles of dual- or multi-energy CT are reviewed and each of the current technical approaches is described. In addition, current and evolving clinical applications are introduced.