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BACKGROUND: Slow kVp switching technique is an important approach to realize dual-energy CT (DECT) imaging, but its performance has not been thoroughly investigated yet. OBJECTIVE: This study aims at comparing and evaluating the DECT imaging performance of different slow kVp switching protocols, and thus helps determining the optimal system settings. METHODS: To investigate the impact of energy separation, two different beam filtration schemes are compared: the stationary beam filtration and dynamic beam filtration. Moreover, uniform tube voltage modulation and weighted tube voltage modulation are compared along with various modulation frequencies. A model-based direct decomposition algorithm is employed to generate the water and iodine material bases. Both numerical and physical experiments are conducted to verify the slow kVp switching DECT imaging performance. RESULTS: Numerical and experimental results demonstrate that the material decomposition is less sensitive to beam filtration, voltage modulation type and modulation frequency. As a result, robust material-specific quantitative decomposition can be achieved in slow kVp switching DECT imaging. CONCLUSIONS: Quantitative DECT imaging can be implemented with slow kVp switching under a variety of system settings.
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Yodo , Tomografía Computarizada por Rayos X , Fantasmas de Imagen , Tomografía Computarizada por Rayos X/métodos , AlgoritmosRESUMEN
PURPOSE: To compare the quantitative parameters and qualitative image quality of dual-energy CT angiography (CTA) between two rapid kVp-switching dual-energy CT scanners. MATERIALS AND METHODS: Between May 2021 and March 2022, 79 participants underwent whole-body CTA using either Discovery CT750 HD (Group A, n = 38) or Revolution CT Apex (Group B, n = 41). All data were reconstructed at 40-keV and with adaptive statistical iterative reconstruction-Veo of 40%. The two groups were compared in terms of CT numbers of the thoracic and abdominal aorta, and the iliac artery, background noise, signal-to-noise ratio (SNR) of the artery, CT dose-index volume (CTDIvol), and qualitative scores for image noise, sharpness, diagnostic acceptability, and arterial depictions. RESULTS: The median CT number of the abdominal aorta (p = 0.04) and SNR of the thoracic aorta (p = 0.02) were higher in Group B than in Group A, while no difference was observed in the other CT numbers and SNRs of the artery (p = 0.09-0.23). The background noises at the thoracic (p = 0.11), abdominal (p = 0.85), and pelvic (p = 0.85) regions were comparable between the two groups. CTDIvol was lower in Group B than in Group A (p = 0.006). All qualitative scores were higher in Group B than in Group A (p < 0.001-0.04). The arterial depictions were nearly identical in both two groups (p = 0.005-1.0). CONCLUSION: In dual-energy CTA at 40-keV, Revolution CT Apex improved qualitative image quality and reduced radiation dose.
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Angiografía por Tomografía Computarizada , Tomografía Computarizada por Rayos X , Humanos , Angiografía por Tomografía Computarizada/métodos , Tomografía Computarizada por Rayos X/métodos , Aorta Abdominal , Tomógrafos Computarizados por Rayos X , Dosis de Radiación , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Medios de ContrasteRESUMEN
Using two different energy levels, dual-energy computed tomography (DECT) allows for material differentiation, improves image quality and iodine conspicuity, and allows researchers the opportunity to determine iodine contrast and radiation dose reduction. Several commercialized platforms with different acquisition techniques are constantly being improved. Furthermore, DECT clinical applications and advantages are continually being reported in a wide range of diseases. We aimed to review the current applications of and challenges in using DECT in the treatment of liver diseases. The greater contrast provided by low-energy reconstructed images and the capability of iodine quantification have been mostly valuable for lesion detection and characterization, accurate staging, treatment response assessment, and thrombi characterization. Material decomposition techniques allow for the non-invasive quantification of fat/iron deposition and fibrosis. Reduced image quality with larger body sizes, cross-vendor and scanner variability, and long reconstruction time are among the limitations of DECT. Promising techniques for improving image quality with lower radiation dose include the deep learning imaging reconstruction method and novel spectral photon-counting computed tomography.
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Dual-energy computed tomography (DECT) uses different energy spectrum x-ray beams for differentiating materials with similar attenuation at a certain energy. Compared with single-energy CT, it provides images with better diagnostic performance and a potential reduction of contrast agent and radiation doses. There are different commercially available DECT technologies, with machines that may display two x-ray sources and two detectors, a single source capable of fast switching between two energy levels, a specialized detector capable of acquiring high- and low-energy data sets, and a filter splitting the beam into high- and low-energy beams at the output. Sequential acquisition at different tube voltages is an alternative approach. This narrative review describes the DECT technique using a Q&A format and visual representations. Physical concepts, parameters influencing image quality, postprocessing methods, applicability in daily routine workflow, and radiation considerations are discussed. Differences between scanners are described, regarding design, image quality variabilities, and their advantages and limitations. Additionally, current clinical applications are listed, and future perspectives for spectral CT imaging are addressed. Acknowledging the strengths and weaknesses of different DECT scanners is important, as these could be adapted to each patient, clinical scenario, and financial capability. This technology is undoubtedly valuable and will certainly keep improving.
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Tomografía Computarizada por Rayos X , Humanos , Tomografía Computarizada por Rayos X/métodos , Fantasmas de Imagen , Fenómenos FísicosRESUMEN
Purpose: Dual-contrast protocols are a promising clinical multienergy computed tomography (CT) application for focal liver lesion detection and characterization. One avenue to enable multienergy CT is the introduction of photon-counting detectors (PCD). Although clinical translation is highly desired because of the diagnostic benefits of PCDs, it will still be a decade or more before they are broadly available. In our work, we investigated an alternative solution that can be implemented on widely used conventional CT systems (single source and integrating detector) to perform multimaterial spectral decomposition for dual-contrast imaging. Approach: We propose to slowly alternate the x-ray tube voltage between 3 kVp levels so each kVp level covers a few degrees of gantry rotation. This leads to the challenge of sparsely sampled projection data in each energy level. Performing the material decomposition (MD) in the sinogram domain is not directly possible as the projection images of the three energy levels are not angularly aligned. In order to overcome this challenge, we developed a convolutional neural network (CNN) framework for sparse sinogram completion (SC) and MD. To evaluate the feasibility of the slow kVp switching scheme, simulation studies of an abdominal phantom, which included liver lesions, were conducted. Results: The line-integral SC network yielded sinograms with a pixel-wise RMSE < 0.05 of the line-integrals compared to the ground truth. This provided acceptable image quality up to a switching angle of 9 deg per kVp. The MD network we developed allowed us to differentiate iodine and gadolinium in the sinogram domain. The average relative quantification errors for iodine and gadolinium were below 10%. Conclusions: We developed a slow triple kVp switching data acquisition scheme and a CNN-based data processing pipeline. Results from a digital phantom validation illustrate the potential for future applications of dual-contrast agent protocols on practically available single-energy CT systems.
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Cone-beam CT (CBCT) is widely used in diagnostic imaging and image-guided procedures, leading to an increasing need for advanced CBCT techniques, such as dual energy (DE) imaging. Previous studies have shown that DE-CBCT can perform quantitative material decomposition, including quantification of contrast agents, electron density, and virtual monoenergetic images. Currently, most CBCT systems perform DE imaging using a kVp switching technique. However, the disadvantages of this method are spatial and temporal misregistration as well as total scan time increase, leading to errors in the material decomposition. DE-CBCT with a dual layer flat panel detector potentially overcomes these limitations by acquiring the dual energy images simultaneously. In this work, we investigate the DE imaging performance of a prototype dual layer detector by evaluating its material decomposition capability and comparing its performance to that of the kVp switching method. Two sets of x-ray spectra were used for kVp switching: 80/120 kVp and 80/120 kVp + 1 mm Cu filtration. Our results show the dual layer detector outperforms kVp switching at 80/120 kVp with matched dose. The performance of kVp switching was better by adding 1 mm copper filtration to the high energy images (80/120 kVp + 1 mm Cu), though the dual layer detector still provided comparable performance for material decomposition tasks. Overall, both the dual layer detector and kVp switching methods provided quantitative material decomposition images in DE-CBCT, with the dual layer detector having additional potential advantages.
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PURPOSE: To investigate the accuracy of rapid kV-switching single-source dual-energy computed tomography (rsDECT) for prediction of classes of non-uric-acid stones. MATERIALS AND METHODS: Non-uric-acid renal stones retrieved via percutaneous nephrolithotomy were prospectively collected between January 2017 and February 2018 in a single institution. Only stones ≥ 5 mm and with pure composition (i.e., ≥ 80% composed of one component) were included. Stone composition was determined using Fourier Transform Infrared Spectroscopy. The stones were scanned in 32-cm-wide anthropomorphic whole-body phantom using rsDECT. The effective atomic number (Zeff), the attenuation at 40 keV (HU40), 70 keV (HU70), and 140 keV (HU140) virtual monochromatic sets of images as well as the ratios between the attenuations were calculated. Values of stone classes were compared using ANOVA and Mann-Whitney U test. Receiver operating curves and area under curve (AUC) were calculated. A p value < 0.05 was considered statistically significant. RESULTS: The final study sample included 31 stones from 31 patients consisting of 25 (81%) calcium-based, 4 (13%) cystine, and 2 (6%) struvite pure stones. The mean size of the stones was 9.9 ± 2.4 mm. The mean Zeff of the stones was 12.01 ± 0.54 for calcium-based, 11.10 ± 0.68 for struvite, and 10.23 ± 0.75 for cystine stones (p < 0.001). Zeff had the best efficacy to separate different classes of stones. The calculated AUC was 0.947 for Zeff; 0.833 for HU40; 0.880 for HU70; and 0.893 for HU140. CONCLUSION: Zeff derived from rsDECT has superior performance to HU and attenuation ratios for separation of different classes of non-uric-acid stones.
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Imagen Radiográfica por Emisión de Doble Fotón/métodos , Tomografía Computarizada por Rayos X/métodos , Cálculos Urinarios/química , Cálculos Urinarios/diagnóstico por imagen , Adulto , Anciano , Femenino , Humanos , Masculino , Persona de Mediana Edad , Nefrolitotomía Percutánea , Fantasmas de Imagen , Estudios Prospectivos , Interpretación de Imagen Radiográfica Asistida por Computador , Espectroscopía Infrarroja por Transformada de Fourier , Cálculos Urinarios/cirugíaRESUMEN
PURPOSE: The purpose of this study was to investigate the image quality (IQ) considerations of rapid kVp switching dual-energy CT (rsDECT) in the assessment of urolithiasis in patients with large body habitus and to evaluate whether it allows stone characterization. MATERIALS AND METHODS: In this IRB-approved, HIPAA compliant retrospective study, 93 consecutive patients (M/F = 72/21, mean age 56.9 years, range 23-83 years) with large body habitus (> 90 kg/198 lbs) who underwent dual-energy (DE) stone protocol CT on a rapid kVp switching DECT scanner between January 2013 and December 2016 were included. Scan acquisition protocol included an initial unenhanced single-energy CT (SECT) scan of KUB followed by targeted DECT in the region of stones. Two readers evaluated both CT data sets (axial 5 mm 120 kVp/140 kVp QC/70 keV monoenergetic, material density water/iodine images and coronal/sagittal 3 mm images) for the assessment of image quality (Scores: 1-4) and characterization of stone composition (reference standard: crystallography). RESULTS: One hundred and five CT examinations were performed in 93 patients (mean body weight 105.12 ± 13.53 kg, range 91-154 kg), and a total of 321 urinary tract calculi (mean size-4.8 ± 3.2 mm, range 1.2-22 mm) were detected. Both SECT and targeted monoenergetic images were of acceptable image quality (mean IQ: 3.77 and 3.83, kappa 0.79 and 0.87 respectively). Material density water and iodine images had lower IQ scores (mean IQ: 2.97 and 3.09 respectively) with image quality deterioration due to severe photon starvation/streak artifacts in 20% (21/105) and 17% (18/105) scans, respectively. Characterization of stone composition into uric acid/non-uric acid stones was achieved in 93.14% (299/321) of calculi (mean size: 4.99 ± 3.3 mm, range 1.2-22 mm), while 7% (22/321) stones could not be characterized (mean size 3.03 ± 1.16 mm, range 1.6-6.4 mm) (p < 0.001). Most common reason for non-characterization was image quality deterioration of the material density iodine images due to severe photon starvation artifacts. On multivariate regression, stone size and patient weight were predictors of stone composition determination on DECT (p < 0.05). The transverse diameter had a weak negative correlation with stone composition determination, but it was not statistically significant. Stone characterization into uric acid vs. non-uric acid stones was accurate in 95% (n = 38/40) of stones in comparison with crystallography. CONCLUSION: In patients with large body habitus, rsDECT allowed characterization of most calculi (93%) despite image quality deterioration due to photon starvation/streak artifacts in up to 20% of material density images. Stone size and patient weight were predictors of stone composition determination on DECT, and small calculi in very large patients may not be characterized.
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Tamaño Corporal , Imagen Radiográfica por Emisión de Doble Fotón/métodos , Tomografía Computarizada por Rayos X/métodos , Urolitiasis/diagnóstico por imagen , Adulto , Anciano , Anciano de 80 o más Años , Medios de Contraste , Femenino , Humanos , Masculino , Persona de Mediana Edad , Interpretación de Imagen Radiográfica Asistida por Computador , Estudios RetrospectivosRESUMEN
PURPOSE: Cone beam CT (CBCT) has been widely used in radiation therapy. However, its main application is still to acquire anatomical information for patient positioning. This study proposes a multienergy element-resolved (MEER) CBCT framework that employs energy-resolved data acquisition on a conventional CBCT platform and then simultaneously reconstructs images of x-ray attenuation coefficients, electron density relative to water (rED), and elemental composition (EC) to support advanced applications. METHODS: The MEER-CBCT framework is realized on a Varian TrueBeam CBCT platform using a kVp-switching scanning scheme. A simultaneous image reconstruction and elemental decomposition model is formulated as an optimization problem. The objective function uses a least square term to enforce fidelity between x-ray attenuation coefficients and projection measurements. Spatial regularization is introduced via sparsity under a tight wavelet-frame transform. Consistency is imposed among rED, EC, and attenuation coefficients and inherently serves as a regularization term along the energy direction. The EC is further constrained by a sparse combination of ECs in a dictionary containing tissues commonly existing in humans. The optimization problem is solved by a novel alternating-direction minimization scheme. The MEER-CBCT framework was tested in a simulation study using an NCAT phantom and an experimental study using a Gammex phantom. RESULTS: MEER-CBCT framework was successfully realized on a clinical Varian TrueBeam onboard CBCT platform with three energy channels of 80, 100, and 120 kVp. In the simulation study, the attenuation coefficient image achieved a structural similarity index of 0.98, compared to 0.61 for the image reconstructed by the conventional conjugate gradient least square (CGLS) algorithm, primarily because of reduction in artifacts. In the experimental study, the attenuation image obtained a contrast-to-noise ratio ≥60, much higher than that of CGLS results (~16) because of noise reduction. The median errors in rED and EC were 0.5% and 1.4% in the simulation study and 1.4% and 2.3% in the experimental study. CONCLUSION: We proposed a novel MEER-CBCT framework realized on a clinical CBCT platform. Simulation and experimental studies demonstrated its capability to simultaneously reconstruct x-ray attenuation coefficient, rED, and EC images accurately.
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Tomografía Computarizada de Haz Cónico/métodos , Tomografía Computarizada de Haz Cónico/instrumentación , Procesamiento de Imagen Asistido por Computador , Fantasmas de ImagenRESUMEN
There are increasing applications of dual-energy computed tomography (CT), a type of spectral CT, in neuroradiology and head and neck imaging. In this 2-part review, the fundamental principles underlying spectral CT scanning and the major considerations in implementing this type of scanning in clinical practice are reviewed. In the first part of this 2-part review, the physical principles underlying spectral CT scanning are reviewed, followed by an overview of the different approaches for spectral CT scanning, including a discussion of the strengths and challenges encountered with each approach.
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Tomografía Computarizada por Rayos X , Humanos , Tomografía Computarizada por Rayos X/instrumentación , Tomografía Computarizada por Rayos X/métodosRESUMEN
OBJECTIVE: To assess the agreement between the true non-contrast (TNC) attenuation values of intra-abdominal structures and attenuation values obtained on virtual-unenhanced (VUE) images based on rapid kVp-switching dual-energy CT. The effects of contrast phase and patient characteristics (e.g., BMI, hematocrit, hemoglobin content) on VUE values were also investigated. METHODS: Ninety four patients who underwent triphasic abdominal CT (liver mass protocol, n = 47; pancreas mass protocol, n = 47) between August 2014 and May 2015 were retrospectively reviewed. Unenhanced series was performed using conventional single-energy mode at 120 kVp. Late arterial and venous phase post-contrast series were obtained utilizing rapid kVp-switching dual-energy CT technique. VUE images were processed off of arterial (VUE-art) and venous (VUE-ven) phase series. Attenuation values of liver, pancreas, kidneys, adrenal glands, muscle, subcutaneous fat, aorta, IVC, and main portal vein were recorded on TNC and VUE sets of images. Attenuation values were compared using univariate linear regression and Student two-tailed paired t test. RESULTS: There was excellent correlation between TNC, VUE-art, and VUE-ven attenuation values across all organs (p < 0.0001). Paired Student t test, however, showed significant difference between TNC and VUE-art attenuation of kidneys, right adrenal gland, paraspinal muscle, and aorta. There was also significant difference between TNC and VUE-ven attenuation of left kidney. Percentage of cases which had >10 HU difference between VUE and TNC for an individual was calculated which ranged between 13% (right kidney) and 42% (right adrenal gland). CONCLUSION: Although the correlation between VUE and TNC attenuation values was excellent and mean difference between TNC and VUE attenuation values was negligible (ranging between -5.94 HU for paraspinal muscles to 6.2 HU in aorta), intra-patient analysis showed a considerable number of cases which had >10 HU difference between VUE and TNC. VUE-ven generally offered a better approximation of TNC values. Further optimization of post-processing algorithms might be necessary before complete replacement of TNC with VUE images.
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Radiografía Abdominal/métodos , Imagen Radiográfica por Emisión de Doble Fotón/métodos , Tomografía Computarizada por Rayos X/métodos , Medios de Contraste , Femenino , Humanos , Yopamidol , Masculino , Persona de Mediana Edad , Interpretación de Imagen Radiográfica Asistida por Computador , Estudios RetrospectivosRESUMEN
In medical X-ray Computed Tomography (CT), the use of two distinct X-ray source spectra (energies) allows dose-reduction and material discrimination relative to that achieved with only one source spectrum. Existing dual-energy CT methods include source kVp-switching, double-layer detection, dual-source gantry, and two-pass scanning. Each method suffers either from strong spectral correlation or patient-motion artifacts. To simultaneously address these problems, we propose to improve CT data acquisition with the Grating Oriented Line-wise Filtration (GOLF) method, a novel X-ray filter that is placed between the source and patient. GOLF uses a combination of absorption and filtering gratings that are moved relative to each other and in synchronization with the X-ray tube kVp-switching process and/or the detector view-sampling process. Simulation results show that GOLF can improve the spectral performance of kVp-switching to match that of dual-source CT while avoiding patient motion artifacts and dual imaging chains. Although significant flux is absorbed by this pre-patient filter, the proposed GOLF method is a novel path for cost-effectively extracting dual-energy or multi-energy data and reducing radiation dose with or without kVp switching.
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In X-ray computed tomography (CT), the presence of metallic parts in patients causes serious artifacts and degrades image quality. Many algorithms were published for metal artifact reduction (MAR) over the past decades with various degrees of success but without a perfect solution. Some MAR algorithms are based on the assumption that metal artifacts are due only to strong beam hardening and may fail in the case of serious photon starvation. Iterative methods handle photon starvation by discarding or underweighting corrupted data, but the results are not always stable and they come with high computational cost. In this paper, we propose a high-kVp-assisted CT scan mode combining a standard CT scan with a few projection views at a high-kVp value to obtain critical projection information near the metal parts. This method only requires minor hardware modifications on a modern CT scanner. Two MAR algorithms are proposed: dual-energy normalized MAR (DNMAR) and high-energy embedded MAR (HEMAR), aiming at situations without and with photon starvation respectively. Simulation results obtained with the CT simulator CatSim demonstrate that the proposed DNMAR and HEMAR methods can eliminate metal artifacts effectively.
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There is an increasing body of evidence establishing the advantages of dual-energy CT (DECT) for evaluation of head and neck squamous cell carcinoma (HNSCC). Focusing on a single-source DECT system with fast kVp switching, we will review the principles behind DECT and associated post-processing steps that make this technology especially suitable for HNSCC evaluation and staging. The article will review current applications of DECT for evaluation of HNSCC including use of different reconstructions to improve tumor conspicuity, tumor-normal soft tissue interface, accuracy of invasion of critical structures such as thyroid cartilage, and reduce dental artifact. We will provide a practical approach for DECT implementation into routine clinical use and a multi-parametric approach for scan interpretation based on the experience at our institution. The article will conclude with a brief overview of potential future applications of the technique.